diff --git a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/java_defs.h b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/java_defs.h
index e41dc2dd9df..6028c4ea71d 100644
--- a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/java_defs.h
+++ b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/java_defs.h
@@ -97,9 +97,6 @@ class Type {
   static Type IterableOf(const Type& type) {
     return Interface("Iterable").add_parameter(type);
   }
-  static Type DataTypeOf(const Type& type) {
-    return Class("DataType", "org.tensorflow").add_parameter(type);
-  }
   static Type ForDataType(DataType data_type) {
     switch (data_type) {
       case DataType::DT_BOOL:
diff --git a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_generator.cc b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_generator.cc
index 14d33c58fc7..16744db3799 100644
--- a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_generator.cc
+++ b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_generator.cc
@@ -103,13 +103,22 @@ void CollectOpDependencies(const OpSpec& op, RenderMode mode,
   }
   for (const AttributeSpec& attribute : op.attributes()) {
     out->push_back(attribute.var().type());
-    out->push_back(attribute.jni_type());
+    if (attribute.jni_type().name() == "DataType") {
+      out->push_back(Type::Class("Operands", "org.tensorflow.op"));
+    } else {
+      out->push_back(attribute.jni_type());
+    }
     if (attribute.has_default_value() &&
         attribute.type().kind() == Type::GENERIC) {
       out->push_back(Type::ForDataType(attribute.default_value()->type()));
     }
   }
   for (const AttributeSpec& optional_attribute : op.optional_attributes()) {
+    if (optional_attribute.jni_type().name() == "DataType") {
+      out->push_back(Type::Class("Operands", "org.tensorflow.op"));
+    } else {
+      out->push_back(optional_attribute.jni_type());
+    }
     out->push_back(optional_attribute.var().type());
   }
 }
@@ -117,25 +126,32 @@ void CollectOpDependencies(const OpSpec& op, RenderMode mode,
 void WriteSetAttrDirective(const AttributeSpec& attr, bool optional,
                            SourceWriter* writer) {
   string var_name = optional ? "opts." + attr.var().name() : attr.var().name();
-  if (attr.iterable()) {
-    string array_name = attr.var().name() + "Array";
-    writer->AppendType(attr.jni_type())
-        .Append("[] " + array_name + " = new ")
-        .AppendType(attr.jni_type())
-        .Append("[" + var_name + ".size()];")
-        .EndLine()
-        .BeginBlock("for (int i = 0; i < " + array_name + ".length; ++i)")
-        .Append(array_name + "[i] = ");
-    writer->Append(var_name + ".get(i);");
-    writer->EndLine()
-        .EndBlock()
-        .Append("opBuilder.setAttr(\"" + attr.op_def_name() + "\", ")
-        .Append(array_name + ");")
-        .EndLine();
-  } else {
+  if (attr.jni_type().name() == "DataType") {
     writer->Append("opBuilder.setAttr(\"" + attr.op_def_name() + "\", ")
-        .Append(var_name + ");")
-        .EndLine();
+          .Append(attr.iterable() ? "Operands.toDataTypes(" : "Operands.toDataType(")
+          .Append(attr.var().name() + "));")
+          .EndLine();
+  } else {
+    if (attr.iterable()) {
+      string array_name = attr.var().name() + "Array";
+      writer->AppendType(attr.jni_type())
+          .Append("[] " + array_name + " = new ")
+          .AppendType(attr.jni_type())
+          .Append("[" + var_name + ".size()];")
+          .EndLine()
+          .BeginBlock("for (int i = 0; i < " + array_name + ".length; ++i)")
+          .Append(array_name + "[i] = ");
+      writer->Append(var_name + ".get(i);");
+      writer->EndLine()
+          .EndBlock()
+          .Append("opBuilder.setAttr(\"" + attr.op_def_name() + "\", ")
+          .Append(array_name + ");")
+          .EndLine();
+    } else {
+      writer->Append("opBuilder.setAttr(\"" + attr.op_def_name() + "\", ")
+          .Append(var_name + ");")
+          .EndLine();
+    }
   }
 }
 
@@ -177,7 +193,7 @@ void RenderSecondaryFactoryMethod(const OpSpec& op, const Type& op_class,
     if (attr.type().kind() == Type::GENERIC &&
         default_types.find(attr.type().name()) != default_types.end()) {
       factory_statement << default_types.at(attr.type().name()).name()
-                        << ".DTYPE";
+                        << ".class";
     } else {
       AddArgument(attr.var(), attr.description(), &factory, &factory_doc);
       factory_statement << attr.var().name();
diff --git a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_specs.cc b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_specs.cc
index 7d184bf2a46..56de15d9ab7 100644
--- a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_specs.cc
+++ b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/op_specs.cc
@@ -81,13 +81,19 @@ class TypeResolver {
   std::pair<Type, Type> MakeTypePair(const Type& type) {
     return std::make_pair(type, type);
   }
-  Type NextGeneric() {
+  Type NextGeneric(const OpDef_AttrDef& attr_def) {
     char generic_letter = next_generic_letter_++;
     if (next_generic_letter_ > 'Z') {
       next_generic_letter_ = 'A';
     }
-    return Type::Generic(string(1, generic_letter))
-        .add_supertype(Type::Class("TType", "org.tensorflow.types.family"));
+    return Type::Generic(string(1, generic_letter));
+  }
+  Type TypeFamilyOf(const OpDef_AttrDef& attr_def) {
+    // TODO(karllessard) support more type families
+    if (IsRealNumbers(attr_def.allowed_values())) {
+      return Type::Interface("TNumber", "org.tensorflow.types.family");
+    }
+    return Type::Interface("TType", "org.tensorflow.types.family");
   }
 };
 
@@ -155,11 +161,9 @@ std::pair<Type, Type> TypeResolver::TypesOf(const OpDef_AttrDef& attr_def,
     types = MakeTypePair(Type::Class("Tensor", "org.tensorflow"));
 
   } else if (attr_type == "type") {
-    Type type = *iterable_out ? Type::Wildcard() : NextGeneric();
-    if (IsRealNumbers(attr_def.allowed_values())) {
-      type.add_supertype(Type::Class("TNumber", "org.tensorflow.types.family"));
-    }
-    types = MakeTypePair(type, Type::Enum("DataType", "org.tensorflow"));
+    Type type = *iterable_out ? Type::Wildcard() : NextGeneric(attr_def);
+    type.add_supertype(TypeFamilyOf(attr_def));
+    types = MakeTypePair(type, Type::Enum("DataType", "org.tensorflow.proto.framework"));
 
   } else {
     LOG(FATAL) << "Cannot resolve data type for attribute \"" << attr_type
@@ -305,7 +309,7 @@ AttributeSpec CreateAttribute(const OpDef_AttrDef& attr_def,
   bool iterable = false;
   std::pair<Type, Type> types = type_resolver->TypesOf(attr_def, &iterable);
   Type var_type = types.first.kind() == Type::GENERIC
-                      ? Type::DataTypeOf(types.first)
+                      ? Type::ClassOf(types.first)
                       : types.first;
   if (iterable) {
     var_type = Type::ListOf(var_type);
diff --git a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.cc b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.cc
index 8598b1d945d..37315f0dff3 100644
--- a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.cc
+++ b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.cc
@@ -85,6 +85,7 @@ SourceWriter& SourceWriter::Append(const StringPiece& str) {
 SourceWriter& SourceWriter::AppendType(const Type& type) {
   if (type.wildcard()) {
     Append("?");
+    WriteTypeBounds(type.supertypes());
   } else {
     Append(type.name());
     if (!type.parameters().empty()) {
@@ -321,14 +322,27 @@ SourceWriter& SourceWriter::WriteGenerics(
       Append(", ");
     }
     Append(pt->name());
-    if (!pt->supertypes().empty()) {
-      Append(" extends ").AppendType(pt->supertypes().front());
-    }
+    WriteTypeBounds(pt->supertypes());
     first = false;
   }
   return Append(">");
 }
 
+SourceWriter& SourceWriter::WriteTypeBounds(
+    const std::list<Type>& bounds) {
+  bool first = true;
+  for (const Type& bound : bounds) {
+    if (first) {
+      Append(" extends ");
+      first = false;
+    } else {
+      Append(" & ");
+    }
+    AppendType(bound);
+  }
+  return *this;
+}
+
 SourceWriter::GenericNamespace* SourceWriter::PushGenericNamespace(
     int modifiers) {
   GenericNamespace* generic_namespace;
diff --git a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.h b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.h
index 097887083e7..26b97f7a9c4 100644
--- a/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.h
+++ b/tensorflow-core/tensorflow-core-api/src/bazel/op_generator/source_writer.h
@@ -213,6 +213,7 @@ class SourceWriter {
   SourceWriter& WriteJavadoc(const Javadoc& javadoc);
   SourceWriter& WriteAnnotations(const std::list<Annotation>& annotations);
   SourceWriter& WriteGenerics(const std::list<const Type*>& generics);
+  SourceWriter& WriteTypeBounds(const std::list<Type>& bounds);
   GenericNamespace* PushGenericNamespace(int modifiers);
   void PopGenericNamespace();
 };
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataExperimentalOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataExperimentalOps.java
index f78720827b0..ab4089a045d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataExperimentalOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataExperimentalOps.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.data.experimental.DataServiceDataset;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
+import org.tensorflow.types.family.TType;
 
 /**
  * An API for building {@code data.experimental} operations as {@link Op Op}s
@@ -57,7 +57,7 @@ public final class DataExperimentalOps {
   public DataServiceDataset dataServiceDataset(Operand<TInt64> datasetId,
       Operand<TString> processingMode, Operand<TString> address, Operand<TString> protocol,
       Operand<TString> jobName, Operand<TInt64> maxOutstandingRequests, Operand<?> iterationCounter,
-      List<DataType<?>> outputTypes, List<Shape> outputShapes,
+      List<Class<? extends TType>> outputTypes, List<Shape> outputShapes,
       DataServiceDataset.Options... options) {
     return DataServiceDataset.create(scope, datasetId, processingMode, address, protocol, jobName, maxOutstandingRequests, iterationCounter, outputTypes, outputShapes, options);
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java
index b3207a5d4e7..f5f3e7ebf86 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java
@@ -18,7 +18,6 @@
 package org.tensorflow.op;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.data.AnonymousIterator;
@@ -49,6 +48,7 @@
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
+import org.tensorflow.types.family.TType;
 
 /**
  * An API for building {@code data} operations as {@link Op Op}s
@@ -75,7 +75,7 @@ public final class DataOps {
    * @param outputShapes
    * @return a new instance of AnonymousIterator
    */
-  public AnonymousIterator anonymousIterator(List<DataType<?>> outputTypes,
+  public AnonymousIterator anonymousIterator(List<Class<? extends TType>> outputTypes,
       List<Shape> outputShapes) {
     return AnonymousIterator.create(scope, outputTypes, outputShapes);
   }
@@ -93,8 +93,8 @@ public AnonymousIterator anonymousIterator(List<DataType<?>> outputTypes,
    * @return a new instance of BatchDataset
    */
   public BatchDataset batchDataset(Operand<?> inputDataset, Operand<TInt64> batchSize,
-      Operand<TBool> dropRemainder, List<DataType<?>> outputTypes, List<Shape> outputShapes,
-      BatchDataset.Options... options) {
+      Operand<TBool> dropRemainder, List<Class<? extends TType>> outputTypes,
+      List<Shape> outputShapes, BatchDataset.Options... options) {
     return BatchDataset.create(scope, inputDataset, batchSize, dropRemainder, outputTypes, outputShapes, options);
   }
 
@@ -129,7 +129,7 @@ public CSVDataset cSVDataset(Operand<TString> filenames, Operand<TString> compre
    * @return a new instance of ConcatenateDataset
    */
   public ConcatenateDataset concatenateDataset(Operand<?> inputDataset, Operand<?> anotherDataset,
-      List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+      List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     return ConcatenateDataset.create(scope, inputDataset, anotherDataset, outputTypes, outputShapes);
   }
 
@@ -164,8 +164,8 @@ public DeserializeIterator deserializeIterator(Operand<?> resourceHandle, Operan
    * @param outputShapes
    * @return a new instance of Iterator
    */
-  public Iterator iterator(String sharedName, String container, List<DataType<?>> outputTypes,
-      List<Shape> outputShapes) {
+  public Iterator iterator(String sharedName, String container,
+      List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     return Iterator.create(scope, sharedName, container, outputTypes, outputShapes);
   }
 
@@ -177,8 +177,8 @@ public Iterator iterator(String sharedName, String container, List<DataType<?>>
    * @param outputShapes
    * @return a new instance of IteratorGetNext
    */
-  public IteratorGetNext iteratorGetNext(Operand<?> iterator, List<DataType<?>> outputTypes,
-      List<Shape> outputShapes) {
+  public IteratorGetNext iteratorGetNext(Operand<?> iterator,
+      List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     return IteratorGetNext.create(scope, iterator, outputTypes, outputShapes);
   }
 
@@ -191,7 +191,7 @@ public IteratorGetNext iteratorGetNext(Operand<?> iterator, List<DataType<?>> ou
    * @return a new instance of IteratorGetNextAsOptional
    */
   public IteratorGetNextAsOptional iteratorGetNextAsOptional(Operand<?> iterator,
-      List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+      List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     return IteratorGetNextAsOptional.create(scope, iterator, outputTypes, outputShapes);
   }
 
@@ -208,8 +208,8 @@ public IteratorGetNextAsOptional iteratorGetNextAsOptional(Operand<?> iterator,
    * @param outputShapes
    * @return a new instance of IteratorGetNextSync
    */
-  public IteratorGetNextSync iteratorGetNextSync(Operand<?> iterator, List<DataType<?>> outputTypes,
-      List<Shape> outputShapes) {
+  public IteratorGetNextSync iteratorGetNextSync(Operand<?> iterator,
+      List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     return IteratorGetNextSync.create(scope, iterator, outputTypes, outputShapes);
   }
 
@@ -255,8 +255,8 @@ public OptionalFromValue optionalFromValue(Iterable<Operand<?>> components) {
    * @param outputShapes
    * @return a new instance of OptionalGetValue
    */
-  public OptionalGetValue optionalGetValue(Operand<?> optional, List<DataType<?>> outputTypes,
-      List<Shape> outputShapes) {
+  public OptionalGetValue optionalGetValue(Operand<?> optional,
+      List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     return OptionalGetValue.create(scope, optional, outputTypes, outputShapes);
   }
 
@@ -290,7 +290,7 @@ public OptionalNone optionalNone() {
    * @return a new instance of RangeDataset
    */
   public RangeDataset rangeDataset(Operand<TInt64> start, Operand<TInt64> stop,
-      Operand<TInt64> step, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+      Operand<TInt64> step, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     return RangeDataset.create(scope, start, stop, step, outputTypes, outputShapes);
   }
 
@@ -305,7 +305,7 @@ public RangeDataset rangeDataset(Operand<TInt64> start, Operand<TInt64> stop,
    * @return a new instance of RepeatDataset
    */
   public RepeatDataset repeatDataset(Operand<?> inputDataset, Operand<TInt64> count,
-      List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+      List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     return RepeatDataset.create(scope, inputDataset, count, outputTypes, outputShapes);
   }
 
@@ -332,7 +332,7 @@ public SerializeIterator serializeIterator(Operand<?> resourceHandle,
    * @return a new instance of SkipDataset
    */
   public SkipDataset skipDataset(Operand<?> inputDataset, Operand<TInt64> count,
-      List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+      List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     return SkipDataset.create(scope, inputDataset, count, outputTypes, outputShapes);
   }
 
@@ -348,7 +348,7 @@ public SkipDataset skipDataset(Operand<?> inputDataset, Operand<TInt64> count,
    * @return a new instance of TakeDataset
    */
   public TakeDataset takeDataset(Operand<?> inputDataset, Operand<TInt64> count,
-      List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+      List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     return TakeDataset.create(scope, inputDataset, count, outputTypes, outputShapes);
   }
 
@@ -409,8 +409,8 @@ public TfRecordDataset tfRecordDataset(Operand<TString> filenames,
    * @param outputShapes
    * @return a new instance of ZipDataset
    */
-  public ZipDataset zipDataset(Iterable<Operand<?>> inputDatasets, List<DataType<?>> outputTypes,
-      List<Shape> outputShapes) {
+  public ZipDataset zipDataset(Iterable<Operand<?>> inputDatasets,
+      List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     return ZipDataset.create(scope, inputDatasets, outputTypes, outputShapes);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java
index 1fb69c6637d..acf6a748b70 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java
@@ -17,7 +17,6 @@
 //
 package org.tensorflow.op;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.dtypes.AsString;
 import org.tensorflow.op.dtypes.Cast;
@@ -73,7 +72,7 @@ public <T extends TType> AsString asString(Operand<T> input, AsString.Options...
    * @param options carries optional attributes values
    * @return a new instance of Cast
    */
-  public <U extends TType, T extends TType> Cast<U> cast(Operand<T> x, DataType<U> DstT,
+  public <U extends TType, T extends TType> Cast<U> cast(Operand<T> x, Class<U> DstT,
       Cast.Options... options) {
     return Cast.create(scope, x, DstT, options);
   }
@@ -102,7 +101,7 @@ public <U extends TType, T extends TType> Cast<U> cast(Operand<T> x, DataType<U>
    * @return a new instance of Complex
    */
   public <U extends TType, T extends TNumber> Complex<U> complex(Operand<T> real, Operand<T> imag,
-      DataType<U> Tout) {
+      Class<U> Tout) {
     return Complex.create(scope, real, imag, Tout);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java
index 35791f74ec8..13db1243c8a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java
@@ -18,7 +18,6 @@
 package org.tensorflow.op;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.image.AdjustContrast;
 import org.tensorflow.op.image.AdjustHue;
@@ -272,7 +271,7 @@ public <T extends TNumber> CropAndResizeGradBoxes cropAndResizeGradBoxes(Operand
    */
   public <T extends TNumber> CropAndResizeGradImage<T> cropAndResizeGradImage(
       Operand<TFloat32> grads, Operand<TFloat32> boxes, Operand<TInt32> boxInd,
-      Operand<TInt32> imageSize, DataType<T> T, CropAndResizeGradImage.Options... options) {
+      Operand<TInt32> imageSize, Class<T> T, CropAndResizeGradImage.Options... options) {
     return CropAndResizeGradImage.create(scope, grads, boxes, boxInd, imageSize, T, options);
   }
 
@@ -463,7 +462,7 @@ public DecodePng<TUint8> decodePng(Operand<TString> contents, DecodePng.Options.
    * @param options carries optional attributes values
    * @return a new instance of DecodePng
    */
-  public <T extends TNumber> DecodePng<T> decodePng(Operand<TString> contents, DataType<T> dtype,
+  public <T extends TNumber> DecodePng<T> decodePng(Operand<TString> contents, Class<T> dtype,
       DecodePng.Options... options) {
     return DecodePng.create(scope, contents, dtype, options);
   }
@@ -625,7 +624,7 @@ public ExtractJpegShape<TInt32> extractJpegShape(Operand<TString> contents) {
    * @return a new instance of ExtractJpegShape
    */
   public <T extends TNumber> ExtractJpegShape<T> extractJpegShape(Operand<TString> contents,
-      DataType<T> outputType) {
+      Class<T> outputType) {
     return ExtractJpegShape.create(scope, contents, outputType);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java
index 3cb7569ab38..f8d48de3690 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java
@@ -18,7 +18,6 @@
 package org.tensorflow.op;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.io.DecodeBase64;
@@ -171,7 +170,7 @@ public DecodeJsonExample decodeJsonExample(Operand<TString> jsonExamples) {
    * @return a new instance of DecodePaddedRaw
    */
   public <T extends TNumber> DecodePaddedRaw<T> decodePaddedRaw(Operand<TString> inputBytes,
-      Operand<TInt32> fixedLength, DataType<T> outType, DecodePaddedRaw.Options... options) {
+      Operand<TInt32> fixedLength, Class<T> outType, DecodePaddedRaw.Options... options) {
     return DecodePaddedRaw.create(scope, inputBytes, fixedLength, outType, options);
   }
 
@@ -184,7 +183,7 @@ public <T extends TNumber> DecodePaddedRaw<T> decodePaddedRaw(Operand<TString> i
    * @param options carries optional attributes values
    * @return a new instance of DecodeRaw
    */
-  public <T extends TType> DecodeRaw<T> decodeRaw(Operand<TString> bytes, DataType<T> outType,
+  public <T extends TType> DecodeRaw<T> decodeRaw(Operand<TString> bytes, Class<T> outType,
       DecodeRaw.Options... options) {
     return DecodeRaw.create(scope, bytes, outType, options);
   }
@@ -241,7 +240,7 @@ public <T extends TType> DecodeRaw<T> decodeRaw(Operand<TString> bytes, DataType
    * @return a new instance of DeserializeManySparse
    */
   public <T extends TType> DeserializeManySparse<T> deserializeManySparse(
-      Operand<TString> serializedSparse, DataType<T> dtype) {
+      Operand<TString> serializedSparse, Class<T> dtype) {
     return DeserializeManySparse.create(scope, serializedSparse, dtype);
   }
 
@@ -270,7 +269,8 @@ public EncodeBase64 encodeBase64(Operand<TString> input, EncodeBase64.Options...
    * @param options carries optional attributes values
    * @return a new instance of FifoQueue
    */
-  public FifoQueue fifoQueue(List<DataType<?>> componentTypes, FifoQueue.Options... options) {
+  public FifoQueue fifoQueue(List<Class<? extends TType>> componentTypes,
+      FifoQueue.Options... options) {
     return FifoQueue.create(scope, componentTypes, options);
   }
 
@@ -334,7 +334,7 @@ public MatchingFiles matchingFiles(Operand<TString> pattern) {
    * @param options carries optional attributes values
    * @return a new instance of PaddingFifoQueue
    */
-  public PaddingFifoQueue paddingFifoQueue(List<DataType<?>> componentTypes,
+  public PaddingFifoQueue paddingFifoQueue(List<Class<? extends TType>> componentTypes,
       PaddingFifoQueue.Options... options) {
     return PaddingFifoQueue.create(scope, componentTypes, options);
   }
@@ -396,9 +396,9 @@ public PaddingFifoQueue paddingFifoQueue(List<DataType<?>> componentTypes,
    */
   public ParseExample parseExample(Operand<TString> serialized, Operand<TString> names,
       Operand<TString> sparseKeys, Operand<TString> denseKeys, Operand<TString> raggedKeys,
-      Iterable<Operand<?>> denseDefaults, Long numSparse, List<DataType<?>> sparseTypes,
-      List<DataType<?>> raggedValueTypes, List<DataType<?>> raggedSplitTypes,
-      List<Shape> denseShapes) {
+      Iterable<Operand<?>> denseDefaults, Long numSparse, List<Class<? extends TType>> sparseTypes,
+      List<Class<? extends TType>> raggedValueTypes,
+      List<Class<? extends TNumber>> raggedSplitTypes, List<Shape> denseShapes) {
     return ParseExample.create(scope, serialized, names, sparseKeys, denseKeys, raggedKeys, denseDefaults, numSparse, sparseTypes, raggedValueTypes, raggedSplitTypes, denseShapes);
   }
 
@@ -454,10 +454,13 @@ public ParseSequenceExample parseSequenceExample(Operand<TString> serialized,
       Operand<TString> contextDenseKeys, Operand<TString> contextRaggedKeys,
       Operand<TString> featureListSparseKeys, Operand<TString> featureListDenseKeys,
       Operand<TString> featureListRaggedKeys, Operand<TBool> featureListDenseMissingAssumedEmpty,
-      Iterable<Operand<?>> contextDenseDefaults, List<DataType<?>> contextSparseTypes,
-      List<DataType<?>> contextRaggedValueTypes, List<DataType<?>> contextRaggedSplitTypes,
-      List<DataType<?>> featureListDenseTypes, List<DataType<?>> featureListSparseTypes,
-      List<DataType<?>> featureListRaggedValueTypes, List<DataType<?>> featureListRaggedSplitTypes,
+      Iterable<Operand<?>> contextDenseDefaults, List<Class<? extends TType>> contextSparseTypes,
+      List<Class<? extends TType>> contextRaggedValueTypes,
+      List<Class<? extends TNumber>> contextRaggedSplitTypes,
+      List<Class<? extends TType>> featureListDenseTypes,
+      List<Class<? extends TType>> featureListSparseTypes,
+      List<Class<? extends TType>> featureListRaggedValueTypes,
+      List<Class<? extends TNumber>> featureListRaggedSplitTypes,
       ParseSequenceExample.Options... options) {
     return ParseSequenceExample.create(scope, serialized, debugName, contextSparseKeys, contextDenseKeys, contextRaggedKeys, featureListSparseKeys, featureListDenseKeys, featureListRaggedKeys, featureListDenseMissingAssumedEmpty, contextDenseDefaults, contextSparseTypes, contextRaggedValueTypes, contextRaggedSplitTypes, featureListDenseTypes, featureListSparseTypes, featureListRaggedValueTypes, featureListRaggedSplitTypes, options);
   }
@@ -499,7 +502,7 @@ public ParseSequenceExample parseSequenceExample(Operand<TString> serialized,
    */
   public ParseSingleExample parseSingleExample(Operand<TString> serialized,
       Iterable<Operand<?>> denseDefaults, Long numSparse, List<String> sparseKeys,
-      List<String> denseKeys, List<DataType<?>> sparseTypes, List<Shape> denseShapes) {
+      List<String> denseKeys, List<Class<? extends TType>> sparseTypes, List<Shape> denseShapes) {
     return ParseSingleExample.create(scope, serialized, denseDefaults, numSparse, sparseKeys, denseKeys, sparseTypes, denseShapes);
   }
 
@@ -553,8 +556,9 @@ public ParseSingleSequenceExample parseSingleSequenceExample(Operand<TString> se
       Iterable<Operand<TString>> contextSparseKeys, Iterable<Operand<TString>> contextDenseKeys,
       Iterable<Operand<TString>> featureListSparseKeys,
       Iterable<Operand<TString>> featureListDenseKeys, Iterable<Operand<?>> contextDenseDefaults,
-      Operand<TString> debugName, List<DataType<?>> contextSparseTypes,
-      List<DataType<?>> featureListDenseTypes, List<DataType<?>> featureListSparseTypes,
+      Operand<TString> debugName, List<Class<? extends TType>> contextSparseTypes,
+      List<Class<? extends TType>> featureListDenseTypes,
+      List<Class<? extends TType>> featureListSparseTypes,
       ParseSingleSequenceExample.Options... options) {
     return ParseSingleSequenceExample.create(scope, serialized, featureListDenseMissingAssumedEmpty, contextSparseKeys, contextDenseKeys, featureListSparseKeys, featureListDenseKeys, contextDenseDefaults, debugName, contextSparseTypes, featureListDenseTypes, featureListSparseTypes, options);
   }
@@ -569,7 +573,7 @@ public ParseSingleSequenceExample parseSingleSequenceExample(Operand<TString> se
    * @return a new instance of ParseTensor
    */
   public <T extends TType> ParseTensor<T> parseTensor(Operand<TString> serialized,
-      DataType<T> outType) {
+      Class<T> outType) {
     return ParseTensor.create(scope, serialized, outType);
   }
 
@@ -590,8 +594,8 @@ public <T extends TType> ParseTensor<T> parseTensor(Operand<TString> serialized,
    * @param options carries optional attributes values
    * @return a new instance of PriorityQueue
    */
-  public PriorityQueue priorityQueue(List<DataType<?>> componentTypes, List<Shape> shapes,
-      PriorityQueue.Options... options) {
+  public PriorityQueue priorityQueue(List<Class<? extends TType>> componentTypes,
+      List<Shape> shapes, PriorityQueue.Options... options) {
     return PriorityQueue.create(scope, componentTypes, shapes, options);
   }
 
@@ -627,7 +631,7 @@ public QueueClose queueClose(Operand<?> handle, QueueClose.Options... options) {
    * @param options carries optional attributes values
    * @return a new instance of QueueDequeue
    */
-  public QueueDequeue queueDequeue(Operand<?> handle, List<DataType<?>> componentTypes,
+  public QueueDequeue queueDequeue(Operand<?> handle, List<Class<? extends TType>> componentTypes,
       QueueDequeue.Options... options) {
     return QueueDequeue.create(scope, handle, componentTypes, options);
   }
@@ -656,7 +660,7 @@ public QueueDequeue queueDequeue(Operand<?> handle, List<DataType<?>> componentT
    * @return a new instance of QueueDequeueMany
    */
   public QueueDequeueMany queueDequeueMany(Operand<?> handle, Operand<TInt32> n,
-      List<DataType<?>> componentTypes, QueueDequeueMany.Options... options) {
+      List<Class<? extends TType>> componentTypes, QueueDequeueMany.Options... options) {
     return QueueDequeueMany.create(scope, handle, n, componentTypes, options);
   }
 
@@ -688,7 +692,7 @@ public QueueDequeueMany queueDequeueMany(Operand<?> handle, Operand<TInt32> n,
    * @return a new instance of QueueDequeueUpTo
    */
   public QueueDequeueUpTo queueDequeueUpTo(Operand<?> handle, Operand<TInt32> n,
-      List<DataType<?>> componentTypes, QueueDequeueUpTo.Options... options) {
+      List<Class<? extends TType>> componentTypes, QueueDequeueUpTo.Options... options) {
     return QueueDequeueUpTo.create(scope, handle, n, componentTypes, options);
   }
 
@@ -765,7 +769,7 @@ public QueueSize queueSize(Operand<?> handle) {
    * @param options carries optional attributes values
    * @return a new instance of RandomShuffleQueue
    */
-  public RandomShuffleQueue randomShuffleQueue(List<DataType<?>> componentTypes,
+  public RandomShuffleQueue randomShuffleQueue(List<Class<? extends TType>> componentTypes,
       RandomShuffleQueue.Options... options) {
     return RandomShuffleQueue.create(scope, componentTypes, options);
   }
@@ -917,7 +921,7 @@ public <T extends TType> SerializeManySparse<TString> serializeManySparse(
    */
   public <U extends TType, T extends TType> SerializeManySparse<U> serializeManySparse(
       Operand<TInt64> sparseIndices, Operand<T> sparseValues, Operand<TInt64> sparseShape,
-      DataType<U> outType) {
+      Class<U> outType) {
     return SerializeManySparse.create(scope, sparseIndices, sparseValues, sparseShape, outType);
   }
 
@@ -948,7 +952,7 @@ public <T extends TType> SerializeSparse<TString> serializeSparse(Operand<TInt64
    */
   public <U extends TType, T extends TType> SerializeSparse<U> serializeSparse(
       Operand<TInt64> sparseIndices, Operand<T> sparseValues, Operand<TInt64> sparseShape,
-      DataType<U> outType) {
+      Class<U> outType) {
     return SerializeSparse.create(scope, sparseIndices, sparseValues, sparseShape, outType);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java
index 6d63d9ddd89..f15c50fe691 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java
@@ -17,7 +17,6 @@
 //
 package org.tensorflow.op;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.linalg.BandPart;
 import org.tensorflow.op.linalg.BatchCholesky;
@@ -399,7 +398,7 @@ public <T extends TType> Det<T> det(Operand<T> input) {
    * @param options carries optional attributes values
    * @return a new instance of Eig
    */
-  public <U extends TType, T extends TType> Eig<U> eig(Operand<T> input, DataType<U> Tout,
+  public <U extends TType, T extends TType> Eig<U> eig(Operand<T> input, Class<U> Tout,
       Eig.Options... options) {
     return Eig.create(scope, input, Tout, options);
   }
@@ -685,7 +684,7 @@ public <T extends TType> Lu<T, TInt32> lu(Operand<T> input) {
    * @return a new instance of Lu
    */
   public <T extends TType, U extends TNumber> Lu<T, U> lu(Operand<T> input,
-      DataType<U> outputIdxType) {
+      Class<U> outputIdxType) {
     return Lu.create(scope, input, outputIdxType);
   }
 
@@ -1376,7 +1375,7 @@ public <T extends TType> Qr<T> qr(Operand<T> input, Qr.Options... options) {
    */
   public <V extends TType, T extends TType, U extends TType, W extends TType> QuantizedMatMul<V> quantizedMatMul(
       Operand<T> a, Operand<U> b, Operand<TFloat32> minA, Operand<TFloat32> maxA,
-      Operand<TFloat32> minB, Operand<TFloat32> maxB, DataType<V> Toutput, DataType<W> Tactivation,
+      Operand<TFloat32> minB, Operand<TFloat32> maxB, Class<V> Toutput, Class<W> Tactivation,
       QuantizedMatMul.Options... options) {
     return QuantizedMatMul.create(scope, a, b, minA, maxA, minB, maxB, Toutput, Tactivation, options);
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java
index b193c2e404d..252a84fd745 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java
@@ -17,7 +17,6 @@
 //
 package org.tensorflow.op;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.math.Abs;
@@ -292,7 +291,7 @@ public <T extends TType> Angle<TFloat32> angle(Operand<T> input) {
    * @param Tout
    * @return a new instance of Angle
    */
-  public <U extends TNumber, T extends TType> Angle<U> angle(Operand<T> input, DataType<U> Tout) {
+  public <U extends TNumber, T extends TType> Angle<U> angle(Operand<T> input, Class<U> Tout) {
     return Angle.create(scope, input, Tout);
   }
 
@@ -360,7 +359,7 @@ public <T extends TType, U extends TNumber> ArgMax<TInt64> argMax(Operand<T> inp
    * @return a new instance of ArgMax
    */
   public <V extends TNumber, T extends TType, U extends TNumber> ArgMax<V> argMax(Operand<T> input,
-      Operand<U> dimension, DataType<V> outputType) {
+      Operand<U> dimension, Class<V> outputType) {
     return ArgMax.create(scope, input, dimension, outputType);
   }
 
@@ -415,7 +414,7 @@ public <T extends TType, U extends TNumber> ArgMin<TInt64> argMin(Operand<T> inp
    * @return a new instance of ArgMin
    */
   public <V extends TNumber, T extends TType, U extends TNumber> ArgMin<V> argMin(Operand<T> input,
-      Operand<U> dimension, DataType<V> outputType) {
+      Operand<U> dimension, Class<V> outputType) {
     return ArgMin.create(scope, input, dimension, outputType);
   }
 
@@ -654,7 +653,7 @@ public <T extends TType> ComplexAbs<TFloat32> complexAbs(Operand<T> x) {
    * @return a new instance of ComplexAbs
    */
   public <U extends TNumber, T extends TType> ComplexAbs<U> complexAbs(Operand<T> x,
-      DataType<U> Tout) {
+      Class<U> Tout) {
     return ComplexAbs.create(scope, x, Tout);
   }
 
@@ -1181,7 +1180,7 @@ public <T extends TType> Imag<TFloat32> imag(Operand<T> input) {
    * @param Tout
    * @return a new instance of Imag
    */
-  public <U extends TNumber, T extends TType> Imag<U> imag(Operand<T> input, DataType<U> Tout) {
+  public <U extends TNumber, T extends TType> Imag<U> imag(Operand<T> input, Class<U> Tout) {
     return Imag.create(scope, input, Tout);
   }
 
@@ -1638,7 +1637,7 @@ public <T extends TType> Pow<T> pow(Operand<T> x, Operand<T> y) {
    */
   public <V extends TType, T extends TType, U extends TType> QuantizedAdd<V> quantizedAdd(
       Operand<T> x, Operand<U> y, Operand<TFloat32> minX, Operand<TFloat32> maxX,
-      Operand<TFloat32> minY, Operand<TFloat32> maxY, DataType<V> Toutput) {
+      Operand<TFloat32> minY, Operand<TFloat32> maxY, Class<V> Toutput) {
     return QuantizedAdd.create(scope, x, y, minX, maxX, minY, maxY, Toutput);
   }
 
@@ -1657,7 +1656,7 @@ public <V extends TType, T extends TType, U extends TType> QuantizedAdd<V> quant
    */
   public <V extends TType, T extends TType, U extends TType> QuantizedMul<V> quantizedMul(
       Operand<T> x, Operand<U> y, Operand<TFloat32> minX, Operand<TFloat32> maxX,
-      Operand<TFloat32> minY, Operand<TFloat32> maxY, DataType<V> Toutput) {
+      Operand<TFloat32> minY, Operand<TFloat32> maxY, Class<V> Toutput) {
     return QuantizedMul.create(scope, x, y, minX, maxX, minY, maxY, Toutput);
   }
 
@@ -1702,7 +1701,7 @@ public <T extends TType> Real<TFloat32> real(Operand<T> input) {
    * @param Tout
    * @return a new instance of Real
    */
-  public <U extends TNumber, T extends TType> Real<U> real(Operand<T> input, DataType<U> Tout) {
+  public <U extends TNumber, T extends TType> Real<U> real(Operand<T> input, Class<U> Tout) {
     return Real.create(scope, input, Tout);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java
index 0992cc606ba..8b5b01fac32 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java
@@ -18,7 +18,6 @@
 package org.tensorflow.op;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.nn.AvgPool;
 import org.tensorflow.op.nn.AvgPool3d;
@@ -645,8 +644,8 @@ public <T extends TNumber> CudnnRNNParamsToCanonical<T> cudnnRNNParamsToCanonica
    * @return a new instance of CudnnRnnParamsSize
    */
   public <U extends TNumber, T extends TNumber> CudnnRnnParamsSize<U> cudnnRnnParamsSize(
-      Operand<TInt32> numLayers, Operand<TInt32> numUnits, Operand<TInt32> inputSize, DataType<T> T,
-      DataType<U> S, CudnnRnnParamsSize.Options... options) {
+      Operand<TInt32> numLayers, Operand<TInt32> numUnits, Operand<TInt32> inputSize, Class<T> T,
+      Class<U> S, CudnnRnnParamsSize.Options... options) {
     return CudnnRnnParamsSize.create(scope, numLayers, numUnits, inputSize, T, S, options);
   }
 
@@ -1504,7 +1503,7 @@ public <T extends TNumber> MaxPoolWithArgmax<T, TInt64> maxPoolWithArgmax(Operan
    * @return a new instance of MaxPoolWithArgmax
    */
   public <T extends TNumber, U extends TNumber> MaxPoolWithArgmax<T, U> maxPoolWithArgmax(
-      Operand<T> input, List<Long> ksize, List<Long> strides, DataType<U> Targmax, String padding,
+      Operand<T> input, List<Long> ksize, List<Long> strides, Class<U> Targmax, String padding,
       MaxPoolWithArgmax.Options... options) {
     return MaxPoolWithArgmax.create(scope, input, ksize, strides, Targmax, padding, options);
   }
@@ -1591,7 +1590,7 @@ public <U extends TType, T extends TType> QuantizedBatchNormWithGlobalNormalizat
       Operand<T> t, Operand<TFloat32> tMin, Operand<TFloat32> tMax, Operand<T> m,
       Operand<TFloat32> mMin, Operand<TFloat32> mMax, Operand<T> v, Operand<TFloat32> vMin,
       Operand<TFloat32> vMax, Operand<T> beta, Operand<TFloat32> betaMin, Operand<TFloat32> betaMax,
-      Operand<T> gamma, Operand<TFloat32> gammaMin, Operand<TFloat32> gammaMax, DataType<U> outType,
+      Operand<T> gamma, Operand<TFloat32> gammaMin, Operand<TFloat32> gammaMax, Class<U> outType,
       Float varianceEpsilon, Boolean scaleAfterNormalization) {
     return QuantizedBatchNormWithGlobalNormalization.create(scope, t, tMin, tMax, m, mMin, mMax, v, vMin, vMax, beta, betaMin, betaMax, gamma, gammaMin, gammaMax, outType, varianceEpsilon, scaleAfterNormalization);
   }
@@ -1613,7 +1612,7 @@ public <U extends TType, T extends TType> QuantizedBatchNormWithGlobalNormalizat
    */
   public <V extends TType, T extends TType, U extends TType> QuantizedBiasAdd<V> quantizedBiasAdd(
       Operand<T> input, Operand<U> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput,
-      Operand<TFloat32> minBias, Operand<TFloat32> maxBias, DataType<V> outType) {
+      Operand<TFloat32> minBias, Operand<TFloat32> maxBias, Class<V> outType) {
     return QuantizedBiasAdd.create(scope, input, bias, minInput, maxInput, minBias, maxBias, outType);
   }
 
@@ -1641,7 +1640,7 @@ public <V extends TType, T extends TType, U extends TType> QuantizedBiasAdd<V> q
    */
   public <V extends TType, T extends TType, U extends TType> QuantizedConv2d<V> quantizedConv2d(
       Operand<T> input, Operand<U> filter, Operand<TFloat32> minInput, Operand<TFloat32> maxInput,
-      Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, DataType<V> outType,
+      Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Class<V> outType,
       List<Long> strides, String padding, QuantizedConv2d.Options... options) {
     return QuantizedConv2d.create(scope, input, filter, minInput, maxInput, minFilter, maxFilter, outType, strides, padding, options);
   }
@@ -1692,7 +1691,7 @@ public <T extends TType> QuantizedMaxPool<T> quantizedMaxPool(Operand<T> input,
    * @return a new instance of QuantizedRelu
    */
   public <U extends TType, T extends TType> QuantizedRelu<U> quantizedRelu(Operand<T> features,
-      Operand<TFloat32> minFeatures, Operand<TFloat32> maxFeatures, DataType<U> outType) {
+      Operand<TFloat32> minFeatures, Operand<TFloat32> maxFeatures, Class<U> outType) {
     return QuantizedRelu.create(scope, features, minFeatures, maxFeatures, outType);
   }
 
@@ -1707,7 +1706,7 @@ public <U extends TType, T extends TType> QuantizedRelu<U> quantizedRelu(Operand
    * @return a new instance of QuantizedRelu6
    */
   public <U extends TType, T extends TType> QuantizedRelu6<U> quantizedRelu6(Operand<T> features,
-      Operand<TFloat32> minFeatures, Operand<TFloat32> maxFeatures, DataType<U> outType) {
+      Operand<TFloat32> minFeatures, Operand<TFloat32> maxFeatures, Class<U> outType) {
     return QuantizedRelu6.create(scope, features, minFeatures, maxFeatures, outType);
   }
 
@@ -1724,7 +1723,7 @@ public <U extends TType, T extends TType> QuantizedRelu6<U> quantizedRelu6(Opera
    */
   public <U extends TType, T extends TType> QuantizedReluX<U> quantizedReluX(Operand<T> features,
       Operand<TFloat32> maxValue, Operand<TFloat32> minFeatures, Operand<TFloat32> maxFeatures,
-      DataType<U> outType) {
+      Class<U> outType) {
     return QuantizedReluX.create(scope, features, maxValue, minFeatures, maxFeatures, outType);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java
index 06908c41d6a..d6e69085324 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java
@@ -19,7 +19,6 @@
 
 import java.nio.charset.Charset;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.DeviceSpec;
 import org.tensorflow.EagerSession;
 import org.tensorflow.ExecutionEnvironment;
@@ -648,7 +647,7 @@ public <T extends TType> AssignVariableOp assignVariableOp(Operand<?> resource,
    * @param options carries optional attributes values
    * @return a new instance of Barrier
    */
-  public Barrier barrier(List<DataType<?>> componentTypes, Barrier.Options... options) {
+  public Barrier barrier(List<Class<? extends TType>> componentTypes, Barrier.Options... options) {
     return Barrier.create(scope, componentTypes, options);
   }
 
@@ -729,7 +728,7 @@ public BarrierReadySize barrierReadySize(Operand<TString> handle) {
    * @return a new instance of BarrierTakeMany
    */
   public BarrierTakeMany barrierTakeMany(Operand<TString> handle, Operand<TInt32> numElements,
-      List<DataType<?>> componentTypes, BarrierTakeMany.Options... options) {
+      List<Class<? extends TType>> componentTypes, BarrierTakeMany.Options... options) {
     return BarrierTakeMany.create(scope, handle, numElements, componentTypes, options);
   }
 
@@ -989,7 +988,7 @@ public <T extends TType, U extends TNumber, V extends TNumber> BatchToSpaceNd<T>
    * @param type
    * @return a new instance of Bitcast
    */
-  public <U extends TType, T extends TType> Bitcast<U> bitcast(Operand<T> input, DataType<U> type) {
+  public <U extends TType, T extends TType> Bitcast<U> bitcast(Operand<T> input, Class<U> type) {
     return Bitcast.create(scope, input, type);
   }
 
@@ -1854,16 +1853,16 @@ public Constant<TString> constant(Charset charset, Shape shape, DataBuffer<Strin
   /**
    * Create a constant with data from the given buffer.
    *
+   * @param <T> the tensor type
    * @param scope is a scope used to add the underlying operation.
-   * @param type the tensor datatype.
+   * @param type the tensor type class
    * @param shape the tensor shape.
    * @param data a buffer containing the tensor data.
    * @return a constant of type `type`
    * @throws IllegalArgumentException If the tensor datatype or shape is not compatible with the
    *      buffer
    */
-  public <T extends TType> Constant<T> constant(DataType<T> type, Shape shape,
-      ByteDataBuffer data) {
+  public <T extends TType> Constant<T> constant(Class<T> type, Shape shape, ByteDataBuffer data) {
     return Constant.tensorOf(scope, type, shape, data);
   }
 
@@ -2138,7 +2137,7 @@ public <T extends TType> EditDistance editDistance(Operand<TInt64> hypothesisInd
    * @param options carries optional attributes values
    * @return a new instance of Empty
    */
-  public <T extends TType> Empty<T> empty(Operand<TInt32> shape, DataType<T> dtype,
+  public <T extends TType> Empty<T> empty(Operand<TInt32> shape, Class<T> dtype,
       Empty.Options... options) {
     return Empty.create(scope, shape, dtype, options);
   }
@@ -2159,7 +2158,7 @@ public <T extends TType> Empty<T> empty(Operand<TInt32> shape, DataType<T> dtype
    * @return a new instance of EmptyTensorList
    */
   public <T extends TNumber, U extends TType> EmptyTensorList emptyTensorList(
-      Operand<T> elementShape, Operand<TInt32> maxNumElements, DataType<U> elementDtype) {
+      Operand<T> elementShape, Operand<TInt32> maxNumElements, Class<U> elementDtype) {
     return EmptyTensorList.create(scope, elementShape, maxNumElements, elementDtype);
   }
 
@@ -2491,7 +2490,7 @@ public <T extends TType> GetSessionHandle getSessionHandle(Operand<T> value) {
    * @return a new instance of GetSessionTensor
    */
   public <T extends TType> GetSessionTensor<T> getSessionTensor(Operand<TString> handle,
-      DataType<T> dtype) {
+      Class<T> dtype) {
     return GetSessionTensor.create(scope, handle, dtype);
   }
 
@@ -2571,8 +2570,8 @@ public <T extends TType> GuaranteeConst<T> guaranteeConst(Operand<T> input) {
    * @param options carries optional attributes values
    * @return a new instance of HashTable
    */
-  public <T extends TType, U extends TType> HashTable hashTable(DataType<T> keyDtype,
-      DataType<U> valueDtype, HashTable.Options... options) {
+  public <T extends TType, U extends TType> HashTable hashTable(Class<T> keyDtype,
+      Class<U> valueDtype, HashTable.Options... options) {
     return HashTable.create(scope, keyDtype, valueDtype, options);
   }
 
@@ -2635,7 +2634,7 @@ public <T extends TNumber> HistogramFixedWidth<TInt32> histogramFixedWidth(Opera
    * @return a new instance of HistogramFixedWidth
    */
   public <U extends TNumber, T extends TNumber> HistogramFixedWidth<U> histogramFixedWidth(
-      Operand<T> values, Operand<T> valueRange, Operand<TInt32> nbins, DataType<U> dtype) {
+      Operand<T> values, Operand<T> valueRange, Operand<TInt32> nbins, Class<U> dtype) {
     return HistogramFixedWidth.create(scope, values, valueRange, nbins, dtype);
   }
 
@@ -2685,7 +2684,7 @@ public IdentityN identityN(Iterable<Operand<?>> input) {
    *  NewReadOnlyMemoryRegionFromFile in tensorflow::Env.
    * @return a new instance of ImmutableConst
    */
-  public <T extends TType> ImmutableConst<T> immutableConst(DataType<T> dtype, Shape shape,
+  public <T extends TType> ImmutableConst<T> immutableConst(Class<T> dtype, Shape shape,
       String memoryRegionName) {
     return ImmutableConst.create(scope, dtype, shape, memoryRegionName);
   }
@@ -2710,7 +2709,7 @@ public <T extends TType> ImmutableConst<T> immutableConst(DataType<T> dtype, Sha
    *    try (Session s = new Session(g)) {
    *      s.run(tf.init());  // initialize all variables
    *
-   *      try (Tensor<TInt32> t = s.runner().fetch(z).run().get(0).expect(TInt32.DTYPE)) {
+   *      try (TInt32 t = (TInt32)s.runner().fetch(z).run().get(0)) {
    *        assertEquals(30, t.data().getInt());
    *      }
    *    }
@@ -2737,7 +2736,7 @@ public <T extends TType> ImmutableConst<T> immutableConst(DataType<T> dtype, Sha
    *  try (SavedModelBundle model = SavedModelBundle.load("/path/to/model", "train")) {
    *    model.session().run(Init.DEFAULT_NAME);
    *
-   *    try (Tensor<TInt32> t = s.runner().fetch("z").run().get(0).expect(TInt32.DTYPE)) {
+   *    try (TInt32 t = (TInt32)s.runner().fetch("z").run().get(0)) {
    *      assertEquals(30, t.data().getInt());
    *    }
    *  }
@@ -2880,7 +2879,7 @@ public <T extends TType> IsVariableInitialized isVariableInitialized(Operand<T>
    * @return a new instance of LookupTableExport
    */
   public <T extends TType, U extends TType> LookupTableExport<T, U> lookupTableExport(
-      Operand<?> tableHandle, DataType<T> Tkeys, DataType<U> Tvalues) {
+      Operand<?> tableHandle, Class<T> Tkeys, Class<U> Tvalues) {
     return LookupTableExport.create(scope, tableHandle, Tkeys, Tvalues);
   }
 
@@ -2966,7 +2965,7 @@ public LoopCond loopCond(Operand<TBool> input) {
    * @param options carries optional attributes values
    * @return a new instance of MapClear
    */
-  public MapClear mapClear(List<DataType<?>> dtypes, MapClear.Options... options) {
+  public MapClear mapClear(List<Class<? extends TType>> dtypes, MapClear.Options... options) {
     return MapClear.create(scope, dtypes, options);
   }
 
@@ -2977,7 +2976,7 @@ public MapClear mapClear(List<DataType<?>> dtypes, MapClear.Options... options)
    * @param options carries optional attributes values
    * @return a new instance of MapIncompleteSize
    */
-  public MapIncompleteSize mapIncompleteSize(List<DataType<?>> dtypes,
+  public MapIncompleteSize mapIncompleteSize(List<Class<? extends TType>> dtypes,
       MapIncompleteSize.Options... options) {
     return MapIncompleteSize.create(scope, dtypes, options);
   }
@@ -2994,8 +2993,8 @@ public MapIncompleteSize mapIncompleteSize(List<DataType<?>> dtypes,
    * @param options carries optional attributes values
    * @return a new instance of MapPeek
    */
-  public MapPeek mapPeek(Operand<TInt64> key, Operand<TInt32> indices, List<DataType<?>> dtypes,
-      MapPeek.Options... options) {
+  public MapPeek mapPeek(Operand<TInt64> key, Operand<TInt32> indices,
+      List<Class<? extends TType>> dtypes, MapPeek.Options... options) {
     return MapPeek.create(scope, key, indices, dtypes, options);
   }
 
@@ -3006,7 +3005,7 @@ public MapPeek mapPeek(Operand<TInt64> key, Operand<TInt32> indices, List<DataTy
    * @param options carries optional attributes values
    * @return a new instance of MapSize
    */
-  public MapSize mapSize(List<DataType<?>> dtypes, MapSize.Options... options) {
+  public MapSize mapSize(List<Class<? extends TType>> dtypes, MapSize.Options... options) {
     return MapSize.create(scope, dtypes, options);
   }
 
@@ -3022,7 +3021,8 @@ public MapSize mapSize(List<DataType<?>> dtypes, MapSize.Options... options) {
    * @return a new instance of MapStage
    */
   public MapStage mapStage(Operand<TInt64> key, Operand<TInt32> indices,
-      Iterable<Operand<?>> values, List<DataType<?>> dtypes, MapStage.Options... options) {
+      Iterable<Operand<?>> values, List<Class<? extends TType>> dtypes,
+      MapStage.Options... options) {
     return MapStage.create(scope, key, indices, values, dtypes, options);
   }
 
@@ -3039,7 +3039,7 @@ public MapStage mapStage(Operand<TInt64> key, Operand<TInt32> indices,
    * @return a new instance of MapUnstage
    */
   public MapUnstage mapUnstage(Operand<TInt64> key, Operand<TInt32> indices,
-      List<DataType<?>> dtypes, MapUnstage.Options... options) {
+      List<Class<? extends TType>> dtypes, MapUnstage.Options... options) {
     return MapUnstage.create(scope, key, indices, dtypes, options);
   }
 
@@ -3054,8 +3054,8 @@ public MapUnstage mapUnstage(Operand<TInt64> key, Operand<TInt32> indices,
    * @param options carries optional attributes values
    * @return a new instance of MapUnstageNoKey
    */
-  public MapUnstageNoKey mapUnstageNoKey(Operand<TInt32> indices, List<DataType<?>> dtypes,
-      MapUnstageNoKey.Options... options) {
+  public MapUnstageNoKey mapUnstageNoKey(Operand<TInt32> indices,
+      List<Class<? extends TType>> dtypes, MapUnstageNoKey.Options... options) {
     return MapUnstageNoKey.create(scope, indices, dtypes, options);
   }
 
@@ -3196,7 +3196,7 @@ public <T extends TType, U extends TNumber> MirrorPad<T> mirrorPad(Operand<T> in
    * @return a new instance of MlirPassthroughOp
    */
   public MlirPassthroughOp mlirPassthroughOp(Iterable<Operand<?>> inputs, String mlirModule,
-      List<DataType<?>> Toutputs) {
+      List<Class<? extends TType>> Toutputs) {
     return MlirPassthroughOp.create(scope, inputs, mlirModule, Toutputs);
   }
 
@@ -3218,7 +3218,7 @@ public MlirPassthroughOp mlirPassthroughOp(Iterable<Operand<?>> inputs, String m
    * @return a new instance of MutableDenseHashTable
    */
   public <T extends TType, U extends TType> MutableDenseHashTable mutableDenseHashTable(
-      Operand<T> emptyKey, Operand<T> deletedKey, DataType<U> valueDtype,
+      Operand<T> emptyKey, Operand<T> deletedKey, Class<U> valueDtype,
       MutableDenseHashTable.Options... options) {
     return MutableDenseHashTable.create(scope, emptyKey, deletedKey, valueDtype, options);
   }
@@ -3235,8 +3235,8 @@ public <T extends TType, U extends TType> MutableDenseHashTable mutableDenseHash
    * @param options carries optional attributes values
    * @return a new instance of MutableHashTable
    */
-  public <T extends TType, U extends TType> MutableHashTable mutableHashTable(DataType<T> keyDtype,
-      DataType<U> valueDtype, MutableHashTable.Options... options) {
+  public <T extends TType, U extends TType> MutableHashTable mutableHashTable(Class<T> keyDtype,
+      Class<U> valueDtype, MutableHashTable.Options... options) {
     return MutableHashTable.create(scope, keyDtype, valueDtype, options);
   }
 
@@ -3253,7 +3253,7 @@ public <T extends TType, U extends TType> MutableHashTable mutableHashTable(Data
    * @return a new instance of MutableHashTableOfTensors
    */
   public <T extends TType, U extends TType> MutableHashTableOfTensors mutableHashTableOfTensors(
-      DataType<T> keyDtype, DataType<U> valueDtype, MutableHashTableOfTensors.Options... options) {
+      Class<T> keyDtype, Class<U> valueDtype, MutableHashTableOfTensors.Options... options) {
     return MutableHashTableOfTensors.create(scope, keyDtype, valueDtype, options);
   }
 
@@ -3434,11 +3434,11 @@ public <U extends TType, T extends TNumber> OneHot<U> oneHot(Operand<T> indices,
    *
    * @param scope is a scope used to add the underlying operation
    * @param dims a 1-D operand that represents the shape of the output tensor
-   * @param type the output tensor datatype. Can not be TString.
+   * @param type the output tensor type class. Can not be TString.
    * @return a constant tensor initialized with ones
    * @throws IllegalArgumentException if the tensor type or shape cannot be initialized with ones.
    */
-  public <T extends TType, U extends TNumber> Ones<T> ones(Operand<U> dims, DataType<T> type) {
+  public <T extends TType, U extends TNumber> Ones<T> ones(Operand<U> dims, Class<T> type) {
     return Ones.create(scope, dims, type);
   }
 
@@ -3460,7 +3460,7 @@ public <T extends TType> OnesLike<T> onesLike(Operand<T> x) {
    * @param options carries optional attributes values
    * @return a new instance of OrderedMapClear
    */
-  public OrderedMapClear orderedMapClear(List<DataType<?>> dtypes,
+  public OrderedMapClear orderedMapClear(List<Class<? extends TType>> dtypes,
       OrderedMapClear.Options... options) {
     return OrderedMapClear.create(scope, dtypes, options);
   }
@@ -3472,7 +3472,7 @@ public OrderedMapClear orderedMapClear(List<DataType<?>> dtypes,
    * @param options carries optional attributes values
    * @return a new instance of OrderedMapIncompleteSize
    */
-  public OrderedMapIncompleteSize orderedMapIncompleteSize(List<DataType<?>> dtypes,
+  public OrderedMapIncompleteSize orderedMapIncompleteSize(List<Class<? extends TType>> dtypes,
       OrderedMapIncompleteSize.Options... options) {
     return OrderedMapIncompleteSize.create(scope, dtypes, options);
   }
@@ -3491,7 +3491,7 @@ public OrderedMapIncompleteSize orderedMapIncompleteSize(List<DataType<?>> dtype
    * @return a new instance of OrderedMapPeek
    */
   public OrderedMapPeek orderedMapPeek(Operand<TInt64> key, Operand<TInt32> indices,
-      List<DataType<?>> dtypes, OrderedMapPeek.Options... options) {
+      List<Class<? extends TType>> dtypes, OrderedMapPeek.Options... options) {
     return OrderedMapPeek.create(scope, key, indices, dtypes, options);
   }
 
@@ -3502,7 +3502,7 @@ public OrderedMapPeek orderedMapPeek(Operand<TInt64> key, Operand<TInt32> indice
    * @param options carries optional attributes values
    * @return a new instance of OrderedMapSize
    */
-  public OrderedMapSize orderedMapSize(List<DataType<?>> dtypes,
+  public OrderedMapSize orderedMapSize(List<Class<? extends TType>> dtypes,
       OrderedMapSize.Options... options) {
     return OrderedMapSize.create(scope, dtypes, options);
   }
@@ -3521,7 +3521,8 @@ public OrderedMapSize orderedMapSize(List<DataType<?>> dtypes,
    * @return a new instance of OrderedMapStage
    */
   public OrderedMapStage orderedMapStage(Operand<TInt64> key, Operand<TInt32> indices,
-      Iterable<Operand<?>> values, List<DataType<?>> dtypes, OrderedMapStage.Options... options) {
+      Iterable<Operand<?>> values, List<Class<? extends TType>> dtypes,
+      OrderedMapStage.Options... options) {
     return OrderedMapStage.create(scope, key, indices, values, dtypes, options);
   }
 
@@ -3538,7 +3539,7 @@ public OrderedMapStage orderedMapStage(Operand<TInt64> key, Operand<TInt32> indi
    * @return a new instance of OrderedMapUnstage
    */
   public OrderedMapUnstage orderedMapUnstage(Operand<TInt64> key, Operand<TInt32> indices,
-      List<DataType<?>> dtypes, OrderedMapUnstage.Options... options) {
+      List<Class<? extends TType>> dtypes, OrderedMapUnstage.Options... options) {
     return OrderedMapUnstage.create(scope, key, indices, dtypes, options);
   }
 
@@ -3554,7 +3555,7 @@ public OrderedMapUnstage orderedMapUnstage(Operand<TInt64> key, Operand<TInt32>
    * @return a new instance of OrderedMapUnstageNoKey
    */
   public OrderedMapUnstageNoKey orderedMapUnstageNoKey(Operand<TInt32> indices,
-      List<DataType<?>> dtypes, OrderedMapUnstageNoKey.Options... options) {
+      List<Class<? extends TType>> dtypes, OrderedMapUnstageNoKey.Options... options) {
     return OrderedMapUnstageNoKey.create(scope, indices, dtypes, options);
   }
 
@@ -3705,7 +3706,7 @@ public <T extends TType> ParallelDynamicStitch<T> parallelDynamicStitch(
    * @param options carries optional attributes values
    * @return a new instance of Placeholder
    */
-  public <T extends TType> Placeholder<T> placeholder(DataType<T> dtype,
+  public <T extends TType> Placeholder<T> placeholder(Class<T> dtype,
       Placeholder.Options... options) {
     return Placeholder.create(scope, dtype, options);
   }
@@ -3834,8 +3835,7 @@ public <T extends TType> Rank rank(Operand<T> input) {
    * @param dtype the dtype of the value.
    * @return a new instance of ReadVariableOp
    */
-  public <T extends TType> ReadVariableOp<T> readVariableOp(Operand<?> resource,
-      DataType<T> dtype) {
+  public <T extends TType> ReadVariableOp<T> readVariableOp(Operand<?> resource, Class<T> dtype) {
     return ReadVariableOp.create(scope, resource, dtype);
   }
 
@@ -4016,7 +4016,7 @@ public <T extends TType> RefSwitch<T> refSwitch(Operand<T> data, Operand<TBool>
    * @return a new instance of RemoteFusedGraphExecute
    */
   public RemoteFusedGraphExecute remoteFusedGraphExecute(Iterable<Operand<?>> inputs,
-      List<DataType<?>> Toutputs, String serializedRemoteFusedGraphExecuteInfo) {
+      List<Class<? extends TType>> Toutputs, String serializedRemoteFusedGraphExecuteInfo) {
     return RemoteFusedGraphExecute.create(scope, inputs, Toutputs, serializedRemoteFusedGraphExecuteInfo);
   }
 
@@ -4103,7 +4103,7 @@ public <T extends TType, U extends TNumber> Reshape<T> reshape(Operand<T> tensor
    * @return a new instance of ResourceCountUpTo
    */
   public <T extends TNumber> ResourceCountUpTo<T> resourceCountUpTo(Operand<?> resource, Long limit,
-      DataType<T> T) {
+      Class<T> T) {
     return ResourceCountUpTo.create(scope, resource, limit, T);
   }
 
@@ -4131,7 +4131,7 @@ public <T extends TNumber> ResourceCountUpTo<T> resourceCountUpTo(Operand<?> res
    * @return a new instance of ResourceGather
    */
   public <U extends TType, T extends TNumber> ResourceGather<U> resourceGather(Operand<?> resource,
-      Operand<T> indices, DataType<U> dtype, ResourceGather.Options... options) {
+      Operand<T> indices, Class<U> dtype, ResourceGather.Options... options) {
     return ResourceGather.create(scope, resource, indices, dtype, options);
   }
 
@@ -4144,7 +4144,7 @@ public <U extends TType, T extends TNumber> ResourceGather<U> resourceGather(Ope
    * @return a new instance of ResourceGatherNd
    */
   public <U extends TType, T extends TNumber> ResourceGatherNd<U> resourceGatherNd(
-      Operand<?> resource, Operand<T> indices, DataType<U> dtype) {
+      Operand<?> resource, Operand<T> indices, Class<U> dtype) {
     return ResourceGatherNd.create(scope, resource, indices, dtype);
   }
 
@@ -5423,7 +5423,7 @@ public <T extends TType> SetDiff1d<T, TInt32> setDiff1d(Operand<T> x, Operand<T>
    * @return a new instance of SetDiff1d
    */
   public <T extends TType, U extends TNumber> SetDiff1d<T, U> setDiff1d(Operand<T> x, Operand<T> y,
-      DataType<U> outIdx) {
+      Class<U> outIdx) {
     return SetDiff1d.create(scope, x, y, outIdx);
   }
 
@@ -5484,7 +5484,7 @@ public <T extends TType> org.tensorflow.op.core.Shape<TInt32> shape(Operand<T> i
    * @return a new instance of Shape
    */
   public <U extends TNumber, T extends TType> org.tensorflow.op.core.Shape<U> shape(
-      Operand<T> input, DataType<U> outType) {
+      Operand<T> input, Class<U> outType) {
     return org.tensorflow.op.core.Shape.create(scope, input, outType);
   }
 
@@ -5512,7 +5512,7 @@ public <T extends TType> ShapeN<TInt32> shapeN(Iterable<Operand<T>> input) {
    * @return a new instance of ShapeN
    */
   public <U extends TNumber, T extends TType> ShapeN<U> shapeN(Iterable<Operand<T>> input,
-      DataType<U> outType) {
+      Class<U> outType) {
     return ShapeN.create(scope, input, outType);
   }
 
@@ -5553,7 +5553,7 @@ public <T extends TType> Size<TInt32> size(Operand<T> input) {
    * @param outType
    * @return a new instance of Size
    */
-  public <U extends TNumber, T extends TType> Size<U> size(Operand<T> input, DataType<U> outType) {
+  public <U extends TNumber, T extends TType> Size<U> size(Operand<T> input, Class<U> outType) {
     return Size.create(scope, input, outType);
   }
 
@@ -5833,7 +5833,7 @@ public Stage stage(Iterable<Operand<?>> values, Stage.Options... options) {
    * @param options carries optional attributes values
    * @return a new instance of StageClear
    */
-  public StageClear stageClear(List<DataType<?>> dtypes, StageClear.Options... options) {
+  public StageClear stageClear(List<Class<? extends TType>> dtypes, StageClear.Options... options) {
     return StageClear.create(scope, dtypes, options);
   }
 
@@ -5849,7 +5849,7 @@ public StageClear stageClear(List<DataType<?>> dtypes, StageClear.Options... opt
    * @param options carries optional attributes values
    * @return a new instance of StagePeek
    */
-  public StagePeek stagePeek(Operand<TInt32> index, List<DataType<?>> dtypes,
+  public StagePeek stagePeek(Operand<TInt32> index, List<Class<? extends TType>> dtypes,
       StagePeek.Options... options) {
     return StagePeek.create(scope, index, dtypes, options);
   }
@@ -5861,7 +5861,7 @@ public StagePeek stagePeek(Operand<TInt32> index, List<DataType<?>> dtypes,
    * @param options carries optional attributes values
    * @return a new instance of StageSize
    */
-  public StageSize stageSize(List<DataType<?>> dtypes, StageSize.Options... options) {
+  public StageSize stageSize(List<Class<? extends TType>> dtypes, StageSize.Options... options) {
     return StageSize.create(scope, dtypes, options);
   }
 
@@ -6126,7 +6126,7 @@ public <T extends TType> SwitchCond<T> switchCond(Operand<T> data, Operand<TBool
    * @param options carries optional attributes values
    * @return a new instance of TemporaryVariable
    */
-  public <T extends TType> TemporaryVariable<T> temporaryVariable(Shape shape, DataType<T> dtype,
+  public <T extends TType> TemporaryVariable<T> temporaryVariable(Shape shape, Class<T> dtype,
       TemporaryVariable.Options... options) {
     return TemporaryVariable.create(scope, shape, dtype, options);
   }
@@ -6141,7 +6141,7 @@ public <T extends TType> TemporaryVariable<T> temporaryVariable(Shape shape, Dat
    * @param options carries optional attributes values
    * @return a new instance of TensorArray
    */
-  public <T extends TType> TensorArray tensorArray(Operand<TInt32> size, DataType<T> dtype,
+  public <T extends TType> TensorArray tensorArray(Operand<TInt32> size, Class<T> dtype,
       TensorArray.Options... options) {
     return TensorArray.create(scope, size, dtype, options);
   }
@@ -6181,7 +6181,7 @@ public TensorArrayClose tensorArrayClose(Operand<?> handle) {
    * @return a new instance of TensorArrayConcat
    */
   public <T extends TType> TensorArrayConcat<T> tensorArrayConcat(Operand<?> handle,
-      Operand<TFloat32> flowIn, DataType<T> dtype, TensorArrayConcat.Options... options) {
+      Operand<TFloat32> flowIn, Class<T> dtype, TensorArrayConcat.Options... options) {
     return TensorArrayConcat.create(scope, handle, flowIn, dtype, options);
   }
 
@@ -6199,7 +6199,7 @@ public <T extends TType> TensorArrayConcat<T> tensorArrayConcat(Operand<?> handl
    * @return a new instance of TensorArrayGather
    */
   public <T extends TType> TensorArrayGather<T> tensorArrayGather(Operand<?> handle,
-      Operand<TInt32> indices, Operand<TFloat32> flowIn, DataType<T> dtype,
+      Operand<TInt32> indices, Operand<TFloat32> flowIn, Class<T> dtype,
       TensorArrayGather.Options... options) {
     return TensorArrayGather.create(scope, handle, indices, flowIn, dtype, options);
   }
@@ -6287,7 +6287,7 @@ public TensorArrayGradWithShape tensorArrayGradWithShape(Operand<?> handle,
    * @return a new instance of TensorArrayPack
    */
   public <T extends TType> TensorArrayPack<T> tensorArrayPack(Operand<TString> handle,
-      Operand<TFloat32> flowIn, DataType<T> dtype, TensorArrayPack.Options... options) {
+      Operand<TFloat32> flowIn, Class<T> dtype, TensorArrayPack.Options... options) {
     return TensorArrayPack.create(scope, handle, flowIn, dtype, options);
   }
 
@@ -6302,7 +6302,7 @@ public <T extends TType> TensorArrayPack<T> tensorArrayPack(Operand<TString> han
    * @return a new instance of TensorArrayRead
    */
   public <T extends TType> TensorArrayRead<T> tensorArrayRead(Operand<?> handle,
-      Operand<TInt32> index, Operand<TFloat32> flowIn, DataType<T> dtype) {
+      Operand<TInt32> index, Operand<TFloat32> flowIn, Class<T> dtype) {
     return TensorArrayRead.create(scope, handle, index, flowIn, dtype);
   }
 
@@ -6419,7 +6419,7 @@ public <T extends TType> TensorArrayWrite tensorArrayWrite(Operand<?> handle,
    */
   public <U extends TType, T extends TNumber> TensorListConcat<U> tensorListConcat(
       Operand<?> inputHandle, Operand<T> elementShape, Operand<TInt64> leadingDims,
-      DataType<U> elementDtype) {
+      Class<U> elementDtype) {
     return TensorListConcat.create(scope, inputHandle, elementShape, leadingDims, elementDtype);
   }
 
@@ -6431,7 +6431,7 @@ public <U extends TType, T extends TNumber> TensorListConcat<U> tensorListConcat
    * @return a new instance of TensorListConcatLists
    */
   public <T extends TType> TensorListConcatLists tensorListConcatLists(Operand<?> inputA,
-      Operand<?> inputB, DataType<T> elementDtype) {
+      Operand<?> inputB, Class<T> elementDtype) {
     return TensorListConcatLists.create(scope, inputA, inputB, elementDtype);
   }
 
@@ -6447,7 +6447,7 @@ public <T extends TType> TensorListConcatLists tensorListConcatLists(Operand<?>
    * @return a new instance of TensorListElementShape
    */
   public <T extends TNumber> TensorListElementShape<T> tensorListElementShape(
-      Operand<?> inputHandle, DataType<T> shapeType) {
+      Operand<?> inputHandle, Class<T> shapeType) {
     return TensorListElementShape.create(scope, inputHandle, shapeType);
   }
 
@@ -6486,7 +6486,7 @@ public <T extends TType, U extends TNumber> TensorListFromTensor tensorListFromT
    * @return a new instance of TensorListGather
    */
   public <T extends TType> TensorListGather<T> tensorListGather(Operand<?> inputHandle,
-      Operand<TInt32> indices, Operand<TInt32> elementShape, DataType<T> elementDtype) {
+      Operand<TInt32> indices, Operand<TInt32> elementShape, Class<T> elementDtype) {
     return TensorListGather.create(scope, inputHandle, indices, elementShape, elementDtype);
   }
 
@@ -6500,7 +6500,7 @@ public <T extends TType> TensorListGather<T> tensorListGather(Operand<?> inputHa
    * @return a new instance of TensorListGetItem
    */
   public <T extends TType> TensorListGetItem<T> tensorListGetItem(Operand<?> inputHandle,
-      Operand<TInt32> index, Operand<TInt32> elementShape, DataType<T> elementDtype) {
+      Operand<TInt32> index, Operand<TInt32> elementShape, Class<T> elementDtype) {
     return TensorListGetItem.create(scope, inputHandle, index, elementShape, elementDtype);
   }
 
@@ -6534,7 +6534,7 @@ public TensorListLength tensorListLength(Operand<?> inputHandle) {
    * @return a new instance of TensorListPopBack
    */
   public <T extends TType> TensorListPopBack<T> tensorListPopBack(Operand<?> inputHandle,
-      Operand<TInt32> elementShape, DataType<T> elementDtype) {
+      Operand<TInt32> elementShape, Class<T> elementDtype) {
     return TensorListPopBack.create(scope, inputHandle, elementShape, elementDtype);
   }
 
@@ -6581,7 +6581,7 @@ public <T extends TType> TensorListPushBackBatch tensorListPushBackBatch(Operand
    * @return a new instance of TensorListReserve
    */
   public <T extends TNumber, U extends TType> TensorListReserve tensorListReserve(
-      Operand<T> elementShape, Operand<TInt32> numElements, DataType<U> elementDtype) {
+      Operand<T> elementShape, Operand<TInt32> numElements, Class<U> elementDtype) {
     return TensorListReserve.create(scope, elementShape, numElements, elementDtype);
   }
 
@@ -6697,7 +6697,7 @@ public <T extends TType, U extends TNumber> TensorListSplit tensorListSplit(Oper
    * @return a new instance of TensorListStack
    */
   public <T extends TType> TensorListStack<T> tensorListStack(Operand<?> inputHandle,
-      Operand<TInt32> elementShape, DataType<T> elementDtype, TensorListStack.Options... options) {
+      Operand<TInt32> elementShape, Class<T> elementDtype, TensorListStack.Options... options) {
     return TensorListStack.create(scope, inputHandle, elementShape, elementDtype, options);
   }
 
@@ -7304,7 +7304,7 @@ public <T extends TType, U extends TNumber> Unique<T, TInt32> unique(Operand<T>
    * @return a new instance of Unique
    */
   public <T extends TType, V extends TNumber, U extends TNumber> Unique<T, V> unique(Operand<T> x,
-      Operand<U> axis, DataType<V> outIdx) {
+      Operand<U> axis, Class<V> outIdx) {
     return Unique.create(scope, x, axis, outIdx);
   }
 
@@ -7421,7 +7421,7 @@ public <T extends TType, U extends TNumber> UniqueWithCounts<T, TInt32> uniqueWi
    * @return a new instance of UniqueWithCounts
    */
   public <T extends TType, V extends TNumber, U extends TNumber> UniqueWithCounts<T, V> uniqueWithCounts(
-      Operand<T> x, Operand<U> axis, DataType<V> outIdx) {
+      Operand<T> x, Operand<U> axis, Class<V> outIdx) {
     return UniqueWithCounts.create(scope, x, axis, outIdx);
   }
 
@@ -7494,7 +7494,7 @@ public <T extends TType> Unstack<T> unstack(Operand<T> value, Long num,
    * @param options carries optional attributes values
    * @return a new instance of Unstage
    */
-  public Unstage unstage(List<DataType<?>> dtypes, Unstage.Options... options) {
+  public Unstage unstage(List<Class<? extends TType>> dtypes, Unstage.Options... options) {
     return Unstage.create(scope, dtypes, options);
   }
 
@@ -7507,7 +7507,7 @@ public Unstage unstage(List<DataType<?>> dtypes, Unstage.Options... options) {
    * @param options carries optional attributes values
    * @return a new instance of VarHandleOp
    */
-  public <T extends TType> VarHandleOp varHandleOp(DataType<T> dtype, Shape shape,
+  public <T extends TType> VarHandleOp varHandleOp(Class<T> dtype, Shape shape,
       VarHandleOp.Options... options) {
     return VarHandleOp.create(scope, dtype, shape, options);
   }
@@ -7550,7 +7550,7 @@ public <T extends TType> Variable<T> variable(Operand<T> init, Variable.Options.
    * @param options carries optional attributes values
    * @return a new instance of Variable
    */
-  public <T extends TType> Variable<T> variable(Shape shape, DataType<T> dtype,
+  public <T extends TType> Variable<T> variable(Shape shape, Class<T> dtype,
       Variable.Options... options) {
     return Variable.create(scope, shape, dtype, options);
   }
@@ -7590,7 +7590,7 @@ public VariableShape<TInt32> variableShape(Operand<?> input) {
    * @param outType
    * @return a new instance of VariableShape
    */
-  public <T extends TNumber> VariableShape<T> variableShape(Operand<?> input, DataType<T> outType) {
+  public <T extends TNumber> VariableShape<T> variableShape(Operand<?> input, Class<T> outType) {
     return VariableShape.create(scope, input, outType);
   }
 
@@ -7708,7 +7708,7 @@ public <T extends TType> XlaSpmdShardToFullShape<T> xlaSpmdShardToFullShape(Oper
    * @return a constant tensor initialized with zeros
    * @throws IllegalArgumentException if the tensor type or shape cannot be initialized with zeros.
    */
-  public <T extends TType, U extends TNumber> Zeros<T> zeros(Operand<U> dims, DataType<T> type) {
+  public <T extends TType, U extends TNumber> Zeros<T> zeros(Operand<U> dims, Class<T> type) {
     return Zeros.create(scope, dims, type);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java
index 0a0703a8f5b..bcca8f36505 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java
@@ -17,7 +17,6 @@
 //
 package org.tensorflow.op;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.quantization.Dequantize;
 import org.tensorflow.op.quantization.FakeQuantWithMinMaxArgs;
@@ -176,7 +175,7 @@ public <T extends TType> Dequantize<TFloat32> dequantize(Operand<T> input,
    * @return a new instance of Dequantize
    */
   public <U extends TNumber, T extends TType> Dequantize<U> dequantize(Operand<T> input,
-      Operand<TFloat32> minRange, Operand<TFloat32> maxRange, DataType<U> dtype,
+      Operand<TFloat32> minRange, Operand<TFloat32> maxRange, Class<U> dtype,
       Dequantize.Options... options) {
     return Dequantize.create(scope, input, minRange, maxRange, dtype, options);
   }
@@ -507,7 +506,7 @@ public FakeQuantWithMinMaxVarsPerChannelGradient fakeQuantWithMinMaxVarsPerChann
    * @return a new instance of Quantize
    */
   public <T extends TType> Quantize<T> quantize(Operand<TFloat32> input, Operand<TFloat32> minRange,
-      Operand<TFloat32> maxRange, DataType<T> T, Quantize.Options... options) {
+      Operand<TFloat32> maxRange, Class<T> T, Quantize.Options... options) {
     return Quantize.create(scope, input, minRange, maxRange, T, options);
   }
 
@@ -565,8 +564,7 @@ public <T extends TNumber> QuantizeAndDequantize<T> quantizeAndDequantize(Operan
    * @return a new instance of QuantizeDownAndShrinkRange
    */
   public <U extends TType, T extends TType> QuantizeDownAndShrinkRange<U> quantizeDownAndShrinkRange(
-      Operand<T> input, Operand<TFloat32> inputMin, Operand<TFloat32> inputMax,
-      DataType<U> outType) {
+      Operand<T> input, Operand<TFloat32> inputMin, Operand<TFloat32> inputMax, Class<U> outType) {
     return QuantizeDownAndShrinkRange.create(scope, input, inputMin, inputMax, outType);
   }
 
@@ -628,7 +626,7 @@ public <T extends TType> RequantizationRange requantizationRange(Operand<T> inpu
    */
   public <U extends TType, T extends TType> Requantize<U> requantize(Operand<T> input,
       Operand<TFloat32> inputMin, Operand<TFloat32> inputMax, Operand<TFloat32> requestedOutputMin,
-      Operand<TFloat32> requestedOutputMax, DataType<U> outType) {
+      Operand<TFloat32> requestedOutputMax, Class<U> outType) {
     return Requantize.create(scope, input, inputMin, inputMax, requestedOutputMin, requestedOutputMax, outType);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java
index 1dde01b96b1..f0c3b8c660c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java
@@ -17,7 +17,6 @@
 //
 package org.tensorflow.op;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.random.AllCandidateSampler;
 import org.tensorflow.op.random.LogUniformCandidateSampler;
@@ -144,7 +143,7 @@ public <T extends TNumber> Multinomial<TInt64> multinomial(Operand<T> logits,
    * @return a new instance of Multinomial
    */
   public <U extends TNumber, T extends TNumber> Multinomial<U> multinomial(Operand<T> logits,
-      Operand<TInt32> numSamples, DataType<U> outputDtype, Multinomial.Options... options) {
+      Operand<TInt32> numSamples, Class<U> outputDtype, Multinomial.Options... options) {
     return Multinomial.create(scope, logits, numSamples, outputDtype, options);
   }
 
@@ -239,7 +238,7 @@ public <T extends TNumber, U extends TNumber> RandomPoisson<TInt64> randomPoisso
    * @return a new instance of RandomPoisson
    */
   public <V extends TNumber, T extends TNumber, U extends TNumber> RandomPoisson<V> randomPoisson(
-      Operand<T> shape, Operand<U> rate, DataType<V> dtype, RandomPoisson.Options... options) {
+      Operand<T> shape, Operand<U> rate, Class<V> dtype, RandomPoisson.Options... options) {
     return RandomPoisson.create(scope, shape, rate, dtype, options);
   }
 
@@ -277,7 +276,7 @@ public <T extends TType> RandomShuffle<T> randomShuffle(Operand<T> value,
    * @return a new instance of RandomStandardNormal
    */
   public <U extends TNumber, T extends TNumber> RandomStandardNormal<U> randomStandardNormal(
-      Operand<T> shape, DataType<U> dtype, RandomStandardNormal.Options... options) {
+      Operand<T> shape, Class<U> dtype, RandomStandardNormal.Options... options) {
     return RandomStandardNormal.create(scope, shape, dtype, options);
   }
 
@@ -294,7 +293,7 @@ public <U extends TNumber, T extends TNumber> RandomStandardNormal<U> randomStan
    * @return a new instance of RandomUniform
    */
   public <U extends TNumber, T extends TNumber> RandomUniform<U> randomUniform(Operand<T> shape,
-      DataType<U> dtype, RandomUniform.Options... options) {
+      Class<U> dtype, RandomUniform.Options... options) {
     return RandomUniform.create(scope, shape, dtype, options);
   }
 
@@ -361,7 +360,7 @@ public <T extends TNumber, U extends TNumber> StatefulRandomBinomial<TInt64> sta
    */
   public <V extends TNumber, T extends TNumber, U extends TNumber> StatefulRandomBinomial<V> statefulRandomBinomial(
       Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape, Operand<U> counts,
-      Operand<U> probs, DataType<V> dtype) {
+      Operand<U> probs, Class<V> dtype) {
     return StatefulRandomBinomial.create(scope, resource, algorithm, shape, counts, probs, dtype);
   }
 
@@ -394,7 +393,7 @@ public <T extends TType> StatefulStandardNormal<TFloat32> statefulStandardNormal
    * @return a new instance of StatefulStandardNormal
    */
   public <U extends TType, T extends TType> StatefulStandardNormal<U> statefulStandardNormal(
-      Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape, DataType<U> dtype) {
+      Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape, Class<U> dtype) {
     return StatefulStandardNormal.create(scope, resource, algorithm, shape, dtype);
   }
 
@@ -425,7 +424,7 @@ public <T extends TNumber, U extends TNumber> StatelessMultinomial<TInt64> state
    * @return a new instance of StatelessMultinomial
    */
   public <V extends TNumber, T extends TNumber, U extends TNumber> StatelessMultinomial<V> statelessMultinomial(
-      Operand<T> logits, Operand<TInt32> numSamples, Operand<U> seed, DataType<V> outputDtype) {
+      Operand<T> logits, Operand<TInt32> numSamples, Operand<U> seed, Class<V> outputDtype) {
     return StatelessMultinomial.create(scope, logits, numSamples, seed, outputDtype);
   }
 
@@ -460,7 +459,7 @@ public <T extends TNumber, U extends TNumber> StatelessRandomNormal<TFloat32> st
    * @return a new instance of StatelessRandomNormal
    */
   public <V extends TNumber, T extends TNumber, U extends TNumber> StatelessRandomNormal<V> statelessRandomNormal(
-      Operand<T> shape, Operand<U> seed, DataType<V> dtype) {
+      Operand<T> shape, Operand<U> seed, Class<V> dtype) {
     return StatelessRandomNormal.create(scope, shape, seed, dtype);
   }
 
@@ -497,7 +496,7 @@ public <T extends TNumber, U extends TNumber> StatelessRandomUniform<TFloat32> s
    * @return a new instance of StatelessRandomUniform
    */
   public <V extends TNumber, T extends TNumber, U extends TNumber> StatelessRandomUniform<V> statelessRandomUniform(
-      Operand<T> shape, Operand<U> seed, DataType<V> dtype) {
+      Operand<T> shape, Operand<U> seed, Class<V> dtype) {
     return StatelessRandomUniform.create(scope, shape, seed, dtype);
   }
 
@@ -536,7 +535,7 @@ public <T extends TNumber, U extends TNumber> StatelessTruncatedNormal<TFloat32>
    * @return a new instance of StatelessTruncatedNormal
    */
   public <V extends TNumber, T extends TNumber, U extends TNumber> StatelessTruncatedNormal<V> statelessTruncatedNormal(
-      Operand<T> shape, Operand<U> seed, DataType<V> dtype) {
+      Operand<T> shape, Operand<U> seed, Class<V> dtype) {
     return StatelessTruncatedNormal.create(scope, shape, seed, dtype);
   }
 
@@ -554,7 +553,7 @@ public <V extends TNumber, T extends TNumber, U extends TNumber> StatelessTrunca
    * @return a new instance of TruncatedNormal
    */
   public <U extends TNumber, T extends TNumber> TruncatedNormal<U> truncatedNormal(Operand<T> shape,
-      DataType<U> dtype, TruncatedNormal.Options... options) {
+      Class<U> dtype, TruncatedNormal.Options... options) {
     return TruncatedNormal.create(scope, shape, dtype, options);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ShapeOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ShapeOps.java
index 5ed7ab60999..ac5ec77a7fb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ShapeOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ShapeOps.java
@@ -17,7 +17,6 @@
 //
 package org.tensorflow.op;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.core.Shape;
 import org.tensorflow.op.core.Shapes;
@@ -115,12 +114,12 @@ public Operand<TInt32> flatten(Shape<TInt32> shape) {
    * @param <U> the shape datatype
    * @param scope current scope
    * @param operand the operand to flatten
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the reshaped operand
    */
   public <T extends TType, U extends TNumber> Operand<T> flatten(Operand<T> operand,
-      DataType<U> dType) {
-    return Shapes.flatten(scope, operand, dType);
+      Class<U> type) {
+    return Shapes.flatten(scope, operand, type);
   }
 
   /**
@@ -129,11 +128,11 @@ public <T extends TType, U extends TNumber> Operand<T> flatten(Operand<T> operan
    * @param <U> the shape datatype
    * @param scope current scope
    * @param shape the TensorFlow shape
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the flattened shape
    */
-  public <U extends TNumber> Operand<U> flatten(Shape<U> shape, DataType<U> dType) {
-    return Shapes.flatten(scope, shape, dType);
+  public <U extends TNumber> Operand<U> flatten(Shape<U> shape, Class<U> type) {
+    return Shapes.flatten(scope, shape, type);
   }
 
   /**
@@ -152,12 +151,12 @@ public Operand<TInt32> head(Shape<TInt32> shape) {
    *
    * @param scope current scope
    * @param shape the TensorFlow shape
-   * @param dType the shape datatype.
+   * @param type the shape datatype.
    * @param <U> the shape datatype.
    * @return a 1-dimensional Operand containing the Shape's first dimension
    */
-  public <U extends TNumber> Operand<U> head(Shape<U> shape, DataType<U> dType) {
-    return Shapes.head(scope, shape, dType);
+  public <U extends TNumber> Operand<U> head(Shape<U> shape, Class<U> type) {
+    return Shapes.head(scope, shape, type);
   }
 
   /**
@@ -177,11 +176,11 @@ public Operand<TInt32> numDimensions(Shape<TInt32> shape) {
    * @param <U> the shape datatype
    * @param scope the curren scope
    * @param shape the shape
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the number of dimensions
    */
-  public <U extends TNumber> Operand<U> numDimensions(Shape<U> shape, DataType<U> dType) {
-    return Shapes.numDimensions(scope, shape, dType);
+  public <U extends TNumber> Operand<U> numDimensions(Shape<U> shape, Class<U> type) {
+    return Shapes.numDimensions(scope, shape, type);
   }
 
   /**
@@ -261,12 +260,12 @@ public Operand<TInt32> reduceDims(Shape<TInt32> shape, Operand<TInt32> axis) {
    * @param scope current scope
    * @param operand the operand
    * @param axis the axis
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the reshaped operand
    */
   public <T extends TType, U extends TNumber> Operand<T> reduceDims(Operand<T> operand,
-      Operand<U> axis, DataType<U> dType) {
-    return Shapes.reduceDims(scope, operand, axis, dType);
+      Operand<U> axis, Class<U> type) {
+    return Shapes.reduceDims(scope, operand, axis, type);
   }
 
   /**
@@ -276,12 +275,11 @@ public <T extends TType, U extends TNumber> Operand<T> reduceDims(Operand<T> ope
    * @param scope current scope
    * @param shape the TensorFlow shape
    * @param axis the axis
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the reduced shape
    */
-  public <U extends TNumber> Operand<U> reduceDims(Shape<U> shape, Operand<U> axis,
-      DataType<U> dType) {
-    return Shapes.reduceDims(scope, shape, axis, dType);
+  public <U extends TNumber> Operand<U> reduceDims(Shape<U> shape, Operand<U> axis, Class<U> type) {
+    return Shapes.reduceDims(scope, shape, axis, type);
   }
 
   /**
@@ -308,28 +306,28 @@ public <T extends TType> Operand<TInt32> size(Operand<T> input, Operand<TInt32>
   }
 
   /**
-   * Get the size represented by the TensorFlow shape.
+   * Get the size of the specified dimension in the shape.
    *
-   * @param <U> the type of the shape
    * @param scope current scope
    * @param shape the TensorFlow shape
-   * @param dType the shape datatype
-   * @return the size
+   * @param dim the dimension
+   * @return the size of the specified dimension
    */
-  public <U extends TNumber> Operand<U> size(Shape<U> shape, DataType<U> dType) {
-    return Shapes.size(scope, shape, dType);
+  public Operand<TInt32> size(Shape<TInt32> shape, Operand<TInt32> dim) {
+    return Shapes.size(scope, shape, dim);
   }
 
   /**
-   * Get the size of the specified dimension in the shape.
+   * Get the size represented by the TensorFlow shape.
    *
+   * @param <U> the type of the shape
    * @param scope current scope
    * @param shape the TensorFlow shape
-   * @param dim the dimension
-   * @return the size of the specified dimension
+   * @param type the shape datatype
+   * @return the size
    */
-  public Operand<TInt32> size(Shape<TInt32> shape, Operand<TInt32> dim) {
-    return Shapes.size(scope, shape, dim);
+  public <U extends TNumber> Operand<U> size(Shape<U> shape, Class<U> type) {
+    return Shapes.size(scope, shape, type);
   }
 
   /**
@@ -339,12 +337,12 @@ public Operand<TInt32> size(Shape<TInt32> shape, Operand<TInt32> dim) {
    * @param scope current scope
    * @param input the operand
    * @param dim the dimension
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the size of the specified dimension
    */
   public <T extends TType, U extends TNumber> Operand<U> size(Operand<T> input, Operand<U> dim,
-      DataType<U> dType) {
-    return Shapes.size(scope, input, dim, dType);
+      Class<U> type) {
+    return Shapes.size(scope, input, dim, type);
   }
 
   /**
@@ -354,11 +352,11 @@ public <T extends TType, U extends TNumber> Operand<U> size(Operand<T> input, Op
    * @param scope current scope
    * @param shape the TensorFlow shape
    * @param dim the dimension
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the size of the specified dimension
    */
-  public <U extends TNumber> Operand<U> size(Shape<U> shape, Operand<U> dim, DataType<U> dType) {
-    return Shapes.size(scope, shape, dim, dType);
+  public <U extends TNumber> Operand<U> size(Shape<U> shape, Operand<U> dim, Class<U> type) {
+    return Shapes.size(scope, shape, dim, type);
   }
 
   /**
@@ -378,11 +376,11 @@ public Operand<TInt32> squeeze(Shape<TInt32> shape) {
    * @param <U> the shape datatype.
    * @param scope current scope
    * @param shape the TensorFlow shape
-   * @param dType the shape datatype.
+   * @param type the shape datatype.
    * @return the squeezed shape
    */
-  public <U extends TNumber> Operand<U> squeeze(Shape<U> shape, DataType<U> dType) {
-    return Shapes.squeeze(scope, shape, dType);
+  public <U extends TNumber> Operand<U> squeeze(Shape<U> shape, Class<U> type) {
+    return Shapes.squeeze(scope, shape, type);
   }
 
   /**
@@ -404,13 +402,13 @@ public Operand<TInt32> tail(Shape<TInt32> shape) {
    *
    * @param scope current scope
    * @param shape the TensorFlow shape
-   * @param dType the shape datatype.
+   * @param type the shape datatype.
    * @param <U> the shape datatype.
    * @return a 1-dimensional Operand that contains the dimension matching the last dimension of the
    *      Shape
    */
-  public <U extends TNumber> Operand<U> tail(Shape<U> shape, DataType<U> dType) {
-    return Shapes.tail(scope, shape, dType);
+  public <U extends TNumber> Operand<U> tail(Shape<U> shape, Class<U> type) {
+    return Shapes.tail(scope, shape, type);
   }
 
   /**
@@ -434,13 +432,13 @@ public Operand<TInt32> take(Shape<TInt32> shape, Operand<TInt32> n) {
    * @param scope current scope
    * @param shape the TensorFlow shape
    * @param n the number of leading dimensions to get, must be <= than the shape's numDimensions()
-   * @param dType the shape datatype.
+   * @param type the shape datatype.
    * @param <U> the shape datatype.
    * @return a 1-dimensional operand with the dimensions matching * the first n dimensions of the
    *      shape
    */
-  public <U extends TNumber> Operand<U> take(Shape<U> shape, Operand<U> n, DataType<U> dType) {
-    return Shapes.take(scope, shape, n, dType);
+  public <U extends TNumber> Operand<U> take(Shape<U> shape, Operand<U> n, Class<U> type) {
+    return Shapes.take(scope, shape, n, type);
   }
 
   /**
@@ -464,13 +462,13 @@ public <U extends TNumber> Operand<TInt32> takeLast(Shape<TInt32> shape, Operand
    * @param scope current scope
    * @param shape the TensorFlow shape
    * @param n the number of leading dimensions to get, must be <= than the shape's numDimensions()
-   * @param dType the shape datatype.
+   * @param type the shape datatype.
    * @param <U> the shape datatype.
    * @return a 1-dimensional operand containing the dimensions matching the last n dimensions of the
    *      shape
    */
-  public <U extends TNumber> Operand<U> takeLast(Shape<U> shape, Operand<U> n, DataType<U> dType) {
-    return Shapes.takeLast(scope, shape, n, dType);
+  public <U extends TNumber> Operand<U> takeLast(Shape<U> shape, Operand<U> n, Class<U> type) {
+    return Shapes.takeLast(scope, shape, n, type);
   }
 
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java
index b71fb5cce13..e8ac9a0e53b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java
@@ -17,7 +17,6 @@
 //
 package org.tensorflow.op;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.signal.BatchFft;
 import org.tensorflow.op.signal.BatchFft2d;
@@ -245,7 +244,7 @@ public <T extends TType> Irfft<TFloat32> irfft(Operand<T> input, Operand<TInt32>
    * @return a new instance of Irfft
    */
   public <U extends TNumber, T extends TType> Irfft<U> irfft(Operand<T> input,
-      Operand<TInt32> fftLength, DataType<U> Treal) {
+      Operand<TInt32> fftLength, Class<U> Treal) {
     return Irfft.create(scope, input, fftLength, Treal);
   }
 
@@ -301,7 +300,7 @@ public <T extends TType> Irfft2d<TFloat32> irfft2d(Operand<T> input, Operand<TIn
    * @return a new instance of Irfft2d
    */
   public <U extends TNumber, T extends TType> Irfft2d<U> irfft2d(Operand<T> input,
-      Operand<TInt32> fftLength, DataType<U> Treal) {
+      Operand<TInt32> fftLength, Class<U> Treal) {
     return Irfft2d.create(scope, input, fftLength, Treal);
   }
 
@@ -357,7 +356,7 @@ public <T extends TType> Irfft3d<TFloat32> irfft3d(Operand<T> input, Operand<TIn
    * @return a new instance of Irfft3d
    */
   public <U extends TNumber, T extends TType> Irfft3d<U> irfft3d(Operand<T> input,
-      Operand<TInt32> fftLength, DataType<U> Treal) {
+      Operand<TInt32> fftLength, Class<U> Treal) {
     return Irfft3d.create(scope, input, fftLength, Treal);
   }
 
@@ -382,7 +381,7 @@ public <U extends TNumber, T extends TType> Irfft3d<U> irfft3d(Operand<T> input,
    * @return a new instance of Rfft
    */
   public <U extends TType, T extends TNumber> Rfft<U> rfft(Operand<T> input,
-      Operand<TInt32> fftLength, DataType<U> Tcomplex) {
+      Operand<TInt32> fftLength, Class<U> Tcomplex) {
     return Rfft.create(scope, input, fftLength, Tcomplex);
   }
 
@@ -408,7 +407,7 @@ public <U extends TType, T extends TNumber> Rfft<U> rfft(Operand<T> input,
    * @return a new instance of Rfft2d
    */
   public <U extends TType, T extends TNumber> Rfft2d<U> rfft2d(Operand<T> input,
-      Operand<TInt32> fftLength, DataType<U> Tcomplex) {
+      Operand<TInt32> fftLength, Class<U> Tcomplex) {
     return Rfft2d.create(scope, input, fftLength, Tcomplex);
   }
 
@@ -434,7 +433,7 @@ public <U extends TType, T extends TNumber> Rfft2d<U> rfft2d(Operand<T> input,
    * @return a new instance of Rfft3d
    */
   public <U extends TType, T extends TNumber> Rfft3d<U> rfft3d(Operand<T> input,
-      Operand<TInt32> fftLength, DataType<U> Tcomplex) {
+      Operand<TInt32> fftLength, Class<U> Tcomplex) {
     return Rfft3d.create(scope, input, fftLength, Tcomplex);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java
index 4bd61718ecc..3971fc6fc06 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java
@@ -17,7 +17,6 @@
 //
 package org.tensorflow.op;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.sparse.AddManySparseToTensorsMap;
@@ -272,7 +271,7 @@ public <T extends TType> DenseToSparseSetOperation<T> denseToSparseSetOperation(
    * @return a new instance of DeserializeSparse
    */
   public <U extends TType, T extends TType> DeserializeSparse<U> deserializeSparse(
-      Operand<T> serializedSparse, DataType<U> dtype) {
+      Operand<T> serializedSparse, Class<U> dtype) {
     return DeserializeSparse.create(scope, serializedSparse, dtype);
   }
 
@@ -318,7 +317,7 @@ public <T extends TType> SparseAccumulatorApplyGradient sparseAccumulatorApplyGr
    * @return a new instance of SparseAccumulatorTakeGradient
    */
   public <T extends TType> SparseAccumulatorTakeGradient<T> sparseAccumulatorTakeGradient(
-      Operand<TString> handle, Operand<TInt32> numRequired, DataType<T> dtype) {
+      Operand<TString> handle, Operand<TInt32> numRequired, Class<T> dtype) {
     return SparseAccumulatorTakeGradient.create(scope, handle, numRequired, dtype);
   }
 
@@ -479,8 +478,8 @@ public <T extends TType> SparseConcat<T> sparseConcat(Iterable<Operand<TInt64>>
    * @param options carries optional attributes values
    * @return a new instance of SparseConditionalAccumulator
    */
-  public <T extends TType> SparseConditionalAccumulator sparseConditionalAccumulator(
-      DataType<T> dtype, Shape shape, SparseConditionalAccumulator.Options... options) {
+  public <T extends TType> SparseConditionalAccumulator sparseConditionalAccumulator(Class<T> dtype,
+      Shape shape, SparseConditionalAccumulator.Options... options) {
     return SparseConditionalAccumulator.create(scope, dtype, shape, options);
   }
 
@@ -1496,7 +1495,7 @@ public <T extends TType> SparseToSparseSetOperation<T> sparseToSparseSetOperatio
    * @return a new instance of TakeManySparseFromTensorsMap
    */
   public <T extends TType> TakeManySparseFromTensorsMap<T> takeManySparseFromTensorsMap(
-      Operand<TInt64> sparseHandles, DataType<T> dtype,
+      Operand<TInt64> sparseHandles, Class<T> dtype,
       TakeManySparseFromTensorsMap.Options... options) {
     return TakeManySparseFromTensorsMap.create(scope, sparseHandles, dtype, options);
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java
index d1f2940bfa2..6d380c31bc6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java
@@ -18,7 +18,6 @@
 package org.tensorflow.op;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.strings.Join;
 import org.tensorflow.op.strings.Lower;
@@ -486,8 +485,7 @@ public ToNumber<TFloat32> toNumber(Operand<TString> stringTensor) {
    * @param outType The numeric type to interpret each string in `string_tensor` as.
    * @return a new instance of ToNumber
    */
-  public <T extends TNumber> ToNumber<T> toNumber(Operand<TString> stringTensor,
-      DataType<T> outType) {
+  public <T extends TNumber> ToNumber<T> toNumber(Operand<TString> stringTensor, Class<T> outType) {
     return ToNumber.create(scope, stringTensor, outType);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java
index d45e2c85425..d21b5e037d3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java
@@ -18,7 +18,6 @@
 package org.tensorflow.op;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.train.AccumulatorApplyGradient;
@@ -162,7 +161,7 @@ public AccumulatorSetGlobalStep accumulatorSetGlobalStep(Operand<TString> handle
    * @return a new instance of AccumulatorTakeGradient
    */
   public <T extends TType> AccumulatorTakeGradient<T> accumulatorTakeGradient(
-      Operand<TString> handle, Operand<TInt32> numRequired, DataType<T> dtype) {
+      Operand<TString> handle, Operand<TInt32> numRequired, Class<T> dtype) {
     return AccumulatorTakeGradient.create(scope, handle, numRequired, dtype);
   }
 
@@ -545,7 +544,7 @@ public <T extends TType> BatchMatMul<T> batchMatMul(Operand<T> x, Operand<T> y,
    * @param options carries optional attributes values
    * @return a new instance of ConditionalAccumulator
    */
-  public <T extends TType> ConditionalAccumulator conditionalAccumulator(DataType<T> dtype,
+  public <T extends TType> ConditionalAccumulator conditionalAccumulator(Class<T> dtype,
       Shape shape, ConditionalAccumulator.Options... options) {
     return ConditionalAccumulator.create(scope, dtype, shape, options);
   }
@@ -1298,7 +1297,7 @@ public <T extends TType, U extends TNumber> ResourceSparseApplyRmsProp resourceS
    * @return a new instance of Restore
    */
   public Restore restore(Operand<TString> prefix, Operand<TString> tensorNames,
-      Operand<TString> shapeAndSlices, List<DataType<?>> dtypes) {
+      Operand<TString> shapeAndSlices, List<Class<? extends TType>> dtypes) {
     return Restore.create(scope, prefix, tensorNames, shapeAndSlices, dtypes);
   }
 
@@ -1324,7 +1323,7 @@ public Restore restore(Operand<TString> prefix, Operand<TString> tensorNames,
    * @return a new instance of RestoreSlice
    */
   public <T extends TType> RestoreSlice<T> restoreSlice(Operand<TString> filePattern,
-      Operand<TString> tensorName, Operand<TString> shapeAndSlice, DataType<T> dt,
+      Operand<TString> tensorName, Operand<TString> shapeAndSlice, Class<T> dt,
       RestoreSlice.Options... options) {
     return RestoreSlice.create(scope, filePattern, tensorName, shapeAndSlice, dt, options);
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java
index 585e721733a..4c8df665739 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java
@@ -17,7 +17,6 @@
 //
 package org.tensorflow.op;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.xla.BroadcastHelper;
@@ -281,7 +280,7 @@ public <T extends TType, U extends TNumber> Pad<T> pad(Operand<T> input, Operand
    * @param shape The shape of the tensor.
    * @return a new instance of Recv
    */
-  public <T extends TType> Recv<T> recv(DataType<T> dtype, String tensorName, Shape shape) {
+  public <T extends TType> Recv<T> recv(Class<T> dtype, String tensorName, Shape shape) {
     return Recv.create(scope, dtype, tensorName, shape);
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java
index 692eaa591aa..86fad697878 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Elementwise computes the bitwise AND of `x` and `y`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java
index 3d7837ec98a..cea0b766cfe 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Elementwise computes the bitwise OR of `x` and `y`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java
index af7de8fc140..f209732bb5c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Elementwise computes the bitwise XOR of `x` and `y`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java
index fe92038487b..4f4e063ed50 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Invert (flip) each bit of supported types; for example, type `uint8` value 01010101 becomes 10101010.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java
index c85fa62863a..98ca43ae889 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Elementwise computes the bitwise left-shift of `x` and `y`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java
index 80bb7418680..4d08a05bf1a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Elementwise computes the bitwise right-shift of `x` and `y`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/AllReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/AllReduce.java
index 3301d27fcd8..adaafc5fc90 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/AllReduce.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/AllReduce.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Mutually reduces multiple tensors of identical type and shape.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/BroadcastRecv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/BroadcastRecv.java
index 4b22670cb9d..bce981a1f6f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/BroadcastRecv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/BroadcastRecv.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.collective;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -77,10 +77,10 @@ private Options() {
    * @return a new instance of BroadcastRecv
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> BroadcastRecv<T> create(Scope scope, DataType<T> T, Long groupSize, Long groupKey, Long instanceKey, Shape shape, Options... options) {
+  public static <T extends TType> BroadcastRecv<T> create(Scope scope, Class<T> T, Long groupSize, Long groupKey, Long instanceKey, Shape shape, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("CollectiveBcastRecv", scope.makeOpName("BroadcastRecv"));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("T", T);
+    opBuilder.setAttr("T", Operands.toDataType(T));
     opBuilder.setAttr("group_size", groupSize);
     opBuilder.setAttr("group_key", groupKey);
     opBuilder.setAttr("instance_key", instanceKey);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/All.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/All.java
index 231336110a5..17b3a3bf0c3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/All.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/All.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the "logical and" of elements across dimensions of a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Any.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Any.java
index 031cfdb03b3..85a60f6b2e0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Any.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Any.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the "logical or" of elements across dimensions of a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Barrier.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Barrier.java
index 6bdda78f84d..b429cce3084 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Barrier.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Barrier.java
@@ -18,17 +18,18 @@
 package org.tensorflow.op.core;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TString;
+import org.tensorflow.types.family.TType;
 
 /**
  * Defines a barrier that persists across different graph executions.
@@ -105,14 +106,10 @@ private Options() {
    * @return a new instance of Barrier
    */
   @Endpoint(describeByClass = true)
-  public static Barrier create(Scope scope, List<DataType<?>> componentTypes, Options... options) {
+  public static Barrier create(Scope scope, List<Class<? extends TType>> componentTypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("Barrier", scope.makeOpName("Barrier"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] componentTypesArray = new DataType[componentTypes.size()];
-    for (int i = 0; i < componentTypesArray.length; ++i) {
-      componentTypesArray[i] = componentTypes.get(i);
-    }
-    opBuilder.setAttr("component_types", componentTypesArray);
+    opBuilder.setAttr("component_types", Operands.toDataTypes(componentTypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.shapes != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierTakeMany.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierTakeMany.java
index 1473dce90b6..4bf16ef62e0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierTakeMany.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BarrierTakeMany.java
@@ -19,11 +19,11 @@
 
 import java.util.Arrays;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -31,6 +31,7 @@
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
+import org.tensorflow.types.family.TType;
 
 /**
  * Takes the given number of completed elements from a barrier.
@@ -98,16 +99,12 @@ private Options() {
    * @return a new instance of BarrierTakeMany
    */
   @Endpoint(describeByClass = true)
-  public static BarrierTakeMany create(Scope scope, Operand<TString> handle, Operand<TInt32> numElements, List<DataType<?>> componentTypes, Options... options) {
+  public static BarrierTakeMany create(Scope scope, Operand<TString> handle, Operand<TInt32> numElements, List<Class<? extends TType>> componentTypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("BarrierTakeMany", scope.makeOpName("BarrierTakeMany"));
     opBuilder.addInput(handle.asOutput());
     opBuilder.addInput(numElements.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] componentTypesArray = new DataType[componentTypes.size()];
-    for (int i = 0; i < componentTypesArray.length; ++i) {
-      componentTypesArray[i] = componentTypes.get(i);
-    }
-    opBuilder.setAttr("component_types", componentTypesArray);
+    opBuilder.setAttr("component_types", Operands.toDataTypes(componentTypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.allowSmallBatch != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java
index f4f74845369..04ea83cf3be 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -96,11 +96,11 @@ public final class Bitcast<U extends TType> extends RawOp implements Operand<U>
    * @return a new instance of Bitcast
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> Bitcast<U> create(Scope scope, Operand<T> input, DataType<U> type) {
+  public static <U extends TType, T extends TType> Bitcast<U> create(Scope scope, Operand<T> input, Class<U> type) {
     OperationBuilder opBuilder = scope.env().opBuilder("Bitcast", scope.makeOpName("Bitcast"));
     opBuilder.addInput(input.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("type", type);
+    opBuilder.setAttr("type", Operands.toDataType(type));
     return new Bitcast<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java
index 346ff14c7ec..91611ab6888 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Return the shape of s0 op s1 with broadcast.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java
index ca291872f8d..8aa19f97259 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Return the reduction indices for computing gradients of s0 op s1 with broadcast.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bucketize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bucketize.java
index ce79347d467..87197f19c3d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bucketize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bucketize.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Bucketizes 'input' based on 'boundaries'.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CollectiveGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CollectiveGather.java
index b84c8833780..2e1de3898fa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CollectiveGather.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CollectiveGather.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Mutually accumulates multiple tensors of identical type and shape.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java
index c3f2dd9870f..5d518629b78 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Increments 'ref' until it reaches 'limit'.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DecodeProto.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DecodeProto.java
index 127a5bffe8c..1b8373c8e6b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DecodeProto.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DecodeProto.java
@@ -19,17 +19,18 @@
 
 import java.util.Arrays;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TString;
+import org.tensorflow.types.family.TType;
 
 /**
  * The op extracts fields from a serialized protocol buffers message into tensors.
@@ -135,7 +136,7 @@ private Options() {
    * @return a new instance of DecodeProto
    */
   @Endpoint(describeByClass = true)
-  public static DecodeProto create(Scope scope, Operand<TString> bytes, String messageType, List<String> fieldNames, List<DataType<?>> outputTypes, Options... options) {
+  public static DecodeProto create(Scope scope, Operand<TString> bytes, String messageType, List<String> fieldNames, List<Class<? extends TType>> outputTypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("DecodeProtoV2", scope.makeOpName("DecodeProto"));
     opBuilder.addInput(bytes.asOutput());
     opBuilder = scope.apply(opBuilder);
@@ -145,11 +146,7 @@ public static DecodeProto create(Scope scope, Operand<TString> bytes, String mes
       fieldNamesArray[i] = fieldNames.get(i);
     }
     opBuilder.setAttr("field_names", fieldNamesArray);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.descriptorSource != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java
index 64e18b3e566..7e7140b9015 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -68,11 +68,11 @@ private Options() {
    * @return a new instance of Empty
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> Empty<T> create(Scope scope, Operand<TInt32> shape, DataType<T> dtype, Options... options) {
+  public static <T extends TType> Empty<T> create(Scope scope, Operand<TInt32> shape, Class<T> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("Empty", scope.makeOpName("Empty"));
     opBuilder.addInput(shape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.init != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EmptyTensorList.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EmptyTensorList.java
index 37fcfd5cd93..e5ec261e5b8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EmptyTensorList.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EmptyTensorList.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -53,12 +53,12 @@ public final class EmptyTensorList extends RawOp implements Operand<TType> {
    * @return a new instance of EmptyTensorList
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber, U extends TType> EmptyTensorList create(Scope scope, Operand<T> elementShape, Operand<TInt32> maxNumElements, DataType<U> elementDtype) {
+  public static <T extends TNumber, U extends TType> EmptyTensorList create(Scope scope, Operand<T> elementShape, Operand<TInt32> maxNumElements, Class<U> elementDtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("EmptyTensorList", scope.makeOpName("EmptyTensorList"));
     opBuilder.addInput(elementShape.asOutput());
     opBuilder.addInput(maxNumElements.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("element_dtype", elementDtype);
+    opBuilder.setAttr("element_dtype", Operands.toDataType(elementDtype));
     return new EmptyTensorList(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java
index f90febe4c1d..b52cc4b3a77 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Extract `patches` from `input` and put them in the "depth" output dimension. 3D extension of `extract_image_patches`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java
index ba2e22c337d..8a04f173ef8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -46,11 +46,11 @@ public final class GetSessionTensor<T extends TType> extends RawOp implements Op
    * @return a new instance of GetSessionTensor
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> GetSessionTensor<T> create(Scope scope, Operand<TString> handle, DataType<T> dtype) {
+  public static <T extends TType> GetSessionTensor<T> create(Scope scope, Operand<TString> handle, Class<T> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("GetSessionTensor", scope.makeOpName("GetSessionTensor"));
     opBuilder.addInput(handle.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new GetSessionTensor<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HashTable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HashTable.java
index 7ecb8439cd2..75f53539f84 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HashTable.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HashTable.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -88,11 +88,11 @@ private Options() {
    * @return a new instance of HashTable
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType, U extends TType> HashTable create(Scope scope, DataType<T> keyDtype, DataType<U> valueDtype, Options... options) {
+  public static <T extends TType, U extends TType> HashTable create(Scope scope, Class<T> keyDtype, Class<U> valueDtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("HashTableV2", scope.makeOpName("HashTable"));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("key_dtype", keyDtype);
-    opBuilder.setAttr("value_dtype", valueDtype);
+    opBuilder.setAttr("key_dtype", Operands.toDataType(keyDtype));
+    opBuilder.setAttr("value_dtype", Operands.toDataType(valueDtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.container != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java
index fbdedfb8d5c..86e6cce541a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java
@@ -17,18 +17,17 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Return histogram of values.
@@ -67,13 +66,13 @@ public final class HistogramFixedWidth<U extends TNumber> extends RawOp implemen
    * @return a new instance of HistogramFixedWidth
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TNumber> HistogramFixedWidth<U> create(Scope scope, Operand<T> values, Operand<T> valueRange, Operand<TInt32> nbins, DataType<U> dtype) {
+  public static <U extends TNumber, T extends TNumber> HistogramFixedWidth<U> create(Scope scope, Operand<T> values, Operand<T> valueRange, Operand<TInt32> nbins, Class<U> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("HistogramFixedWidth", scope.makeOpName("HistogramFixedWidth"));
     opBuilder.addInput(values.asOutput());
     opBuilder.addInput(valueRange.asOutput());
     opBuilder.addInput(nbins.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new HistogramFixedWidth<U>(opBuilder.build());
   }
   
@@ -90,7 +89,7 @@ public static <U extends TNumber, T extends TNumber> HistogramFixedWidth<U> crea
    */
   @Endpoint(describeByClass = true)
   public static <T extends TNumber> HistogramFixedWidth<TInt32> create(Scope scope, Operand<T> values, Operand<T> valueRange, Operand<TInt32> nbins) {
-    return create(scope, values, valueRange, nbins, TInt32.DTYPE);
+    return create(scope, values, valueRange, nbins, TInt32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java
index 404c4672776..319304aff8b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -50,10 +50,10 @@ public final class ImmutableConst<T extends TType> extends RawOp implements Oper
    * @return a new instance of ImmutableConst
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> ImmutableConst<T> create(Scope scope, DataType<T> dtype, Shape shape, String memoryRegionName) {
+  public static <T extends TType> ImmutableConst<T> create(Scope scope, Class<T> dtype, Shape shape, String memoryRegionName) {
     OperationBuilder opBuilder = scope.env().opBuilder("ImmutableConst", scope.makeOpName("ImmutableConst"));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     opBuilder.setAttr("shape", shape);
     opBuilder.setAttr("memory_region_name", memoryRegionName);
     return new ImmutableConst<T>(opBuilder.build());
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java
index c0694e4165a..29662e643f8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Generates values in an interval.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java
index 952bf8e9994..7685fa5e7b4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,12 +47,12 @@ public final class LookupTableExport<T extends TType, U extends TType> extends R
    * @return a new instance of LookupTableExport
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType, U extends TType> LookupTableExport<T, U> create(Scope scope, Operand<?> tableHandle, DataType<T> Tkeys, DataType<U> Tvalues) {
+  public static <T extends TType, U extends TType> LookupTableExport<T, U> create(Scope scope, Operand<?> tableHandle, Class<T> Tkeys, Class<U> Tvalues) {
     OperationBuilder opBuilder = scope.env().opBuilder("LookupTableExportV2", scope.makeOpName("LookupTableExport"));
     opBuilder.addInput(tableHandle.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Tkeys", Tkeys);
-    opBuilder.setAttr("Tvalues", Tvalues);
+    opBuilder.setAttr("Tkeys", Operands.toDataType(Tkeys));
+    opBuilder.setAttr("Tvalues", Operands.toDataType(Tvalues));
     return new LookupTableExport<T, U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java
index f2671d23aae..1aa8badb5a1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -66,12 +66,12 @@ public final class LowerBound<U extends TNumber> extends RawOp implements Operan
    * @return a new instance of LowerBound
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> LowerBound<U> create(Scope scope, Operand<T> sortedInputs, Operand<T> values, DataType<U> outType) {
+  public static <U extends TNumber, T extends TType> LowerBound<U> create(Scope scope, Operand<T> sortedInputs, Operand<T> values, Class<U> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("LowerBound", scope.makeOpName("LowerBound"));
     opBuilder.addInput(sortedInputs.asOutput());
     opBuilder.addInput(values.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new LowerBound<U>(opBuilder.build());
   }
   
@@ -86,7 +86,7 @@ public static <U extends TNumber, T extends TType> LowerBound<U> create(Scope sc
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> LowerBound<TInt32> create(Scope scope, Operand<T> sortedInputs, Operand<T> values) {
-    return create(scope, sortedInputs, values, TInt32.DTYPE);
+    return create(scope, sortedInputs, values, TInt32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapClear.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapClear.java
index 5b3c43ee0d8..e680e7db08a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapClear.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapClear.java
@@ -18,13 +18,14 @@
 package org.tensorflow.op.core;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.types.family.TType;
 
 /**
  * Op removes all elements in the underlying container.
@@ -87,14 +88,10 @@ private Options() {
    * @return a new instance of MapClear
    */
   @Endpoint(describeByClass = true)
-  public static MapClear create(Scope scope, List<DataType<?>> dtypes, Options... options) {
+  public static MapClear create(Scope scope, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("MapClear", scope.makeOpName("MapClear"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapIncompleteSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapIncompleteSize.java
index 016ec0f023c..6fa921bb408 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapIncompleteSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapIncompleteSize.java
@@ -18,16 +18,17 @@
 package org.tensorflow.op.core;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
+import org.tensorflow.types.family.TType;
 
 /**
  * Op returns the number of incomplete elements in the underlying container.
@@ -90,14 +91,10 @@ private Options() {
    * @return a new instance of MapIncompleteSize
    */
   @Endpoint(describeByClass = true)
-  public static MapIncompleteSize create(Scope scope, List<DataType<?>> dtypes, Options... options) {
+  public static MapIncompleteSize create(Scope scope, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("MapIncompleteSize", scope.makeOpName("MapIncompleteSize"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapPeek.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapPeek.java
index 15e941ec891..316bc08c64c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapPeek.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapPeek.java
@@ -20,11 +20,11 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -99,16 +99,12 @@ private Options() {
    * @return a new instance of MapPeek
    */
   @Endpoint(describeByClass = true)
-  public static MapPeek create(Scope scope, Operand<TInt64> key, Operand<TInt32> indices, List<DataType<?>> dtypes, Options... options) {
+  public static MapPeek create(Scope scope, Operand<TInt64> key, Operand<TInt32> indices, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("MapPeek", scope.makeOpName("MapPeek"));
     opBuilder.addInput(key.asOutput());
     opBuilder.addInput(indices.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapSize.java
index f6e99dc5ee4..0cd9510a8f7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapSize.java
@@ -18,16 +18,17 @@
 package org.tensorflow.op.core;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
+import org.tensorflow.types.family.TType;
 
 /**
  * Op returns the number of elements in the underlying container.
@@ -90,14 +91,10 @@ private Options() {
    * @return a new instance of MapSize
    */
   @Endpoint(describeByClass = true)
-  public static MapSize create(Scope scope, List<DataType<?>> dtypes, Options... options) {
+  public static MapSize create(Scope scope, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("MapSize", scope.makeOpName("MapSize"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapStage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapStage.java
index 2e5c7d0ea4f..76f9086f46e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapStage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapStage.java
@@ -18,7 +18,6 @@
 package org.tensorflow.op.core;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -29,6 +28,7 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
+import org.tensorflow.types.family.TType;
 
 /**
  * Stage (key, values) in the underlying container which behaves like a hashtable.
@@ -97,17 +97,13 @@ private Options() {
    * @return a new instance of MapStage
    */
   @Endpoint(describeByClass = true)
-  public static MapStage create(Scope scope, Operand<TInt64> key, Operand<TInt32> indices, Iterable<Operand<?>> values, List<DataType<?>> dtypes, Options... options) {
+  public static MapStage create(Scope scope, Operand<TInt64> key, Operand<TInt32> indices, Iterable<Operand<?>> values, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("MapStage", scope.makeOpName("MapStage"));
     opBuilder.addInput(key.asOutput());
     opBuilder.addInput(indices.asOutput());
     opBuilder.addInputList(Operands.asOutputs(values));
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstage.java
index e6cab844ab0..6d189a50d7b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstage.java
@@ -20,11 +20,11 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -99,16 +99,12 @@ private Options() {
    * @return a new instance of MapUnstage
    */
   @Endpoint(describeByClass = true)
-  public static MapUnstage create(Scope scope, Operand<TInt64> key, Operand<TInt32> indices, List<DataType<?>> dtypes, Options... options) {
+  public static MapUnstage create(Scope scope, Operand<TInt64> key, Operand<TInt32> indices, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("MapUnstage", scope.makeOpName("MapUnstage"));
     opBuilder.addInput(key.asOutput());
     opBuilder.addInput(indices.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstageNoKey.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstageNoKey.java
index a523400c34e..9848ab2d845 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstageNoKey.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapUnstageNoKey.java
@@ -19,17 +19,18 @@
 
 import java.util.Arrays;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
+import org.tensorflow.types.family.TType;
 
 /**
  * Op removes and returns a random (key, value)
@@ -96,15 +97,11 @@ private Options() {
    * @return a new instance of MapUnstageNoKey
    */
   @Endpoint(describeByClass = true)
-  public static MapUnstageNoKey create(Scope scope, Operand<TInt32> indices, List<DataType<?>> dtypes, Options... options) {
+  public static MapUnstageNoKey create(Scope scope, Operand<TInt32> indices, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("MapUnstageNoKey", scope.makeOpName("MapUnstageNoKey"));
     opBuilder.addInput(indices.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MlirPassthroughOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MlirPassthroughOp.java
index 1596cf10e84..e80af4ecee8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MlirPassthroughOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MlirPassthroughOp.java
@@ -20,7 +20,6 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -78,16 +77,12 @@ public final class MlirPassthroughOp extends RawOp implements Iterable<Operand<T
    * @return a new instance of MlirPassthroughOp
    */
   @Endpoint(describeByClass = true)
-  public static MlirPassthroughOp create(Scope scope, Iterable<Operand<?>> inputs, String mlirModule, List<DataType<?>> Toutputs) {
+  public static MlirPassthroughOp create(Scope scope, Iterable<Operand<?>> inputs, String mlirModule, List<Class<? extends TType>> Toutputs) {
     OperationBuilder opBuilder = scope.env().opBuilder("MlirPassthroughOp", scope.makeOpName("MlirPassthroughOp"));
     opBuilder.addInputList(Operands.asOutputs(inputs));
     opBuilder = scope.apply(opBuilder);
     opBuilder.setAttr("mlir_module", mlirModule);
-    DataType[] ToutputsArray = new DataType[Toutputs.size()];
-    for (int i = 0; i < ToutputsArray.length; ++i) {
-      ToutputsArray[i] = Toutputs.get(i);
-    }
-    opBuilder.setAttr("Toutputs", ToutputsArray);
+    opBuilder.setAttr("Toutputs", Operands.toDataTypes(Toutputs));
     return new MlirPassthroughOp(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableDenseHashTable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableDenseHashTable.java
index dc73ae16585..28a85dc0082 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableDenseHashTable.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableDenseHashTable.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -122,12 +122,12 @@ private Options() {
    * @return a new instance of MutableDenseHashTable
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType, U extends TType> MutableDenseHashTable create(Scope scope, Operand<T> emptyKey, Operand<T> deletedKey, DataType<U> valueDtype, Options... options) {
+  public static <T extends TType, U extends TType> MutableDenseHashTable create(Scope scope, Operand<T> emptyKey, Operand<T> deletedKey, Class<U> valueDtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("MutableDenseHashTableV2", scope.makeOpName("MutableDenseHashTable"));
     opBuilder.addInput(emptyKey.asOutput());
     opBuilder.addInput(deletedKey.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("value_dtype", valueDtype);
+    opBuilder.setAttr("value_dtype", Operands.toDataType(valueDtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.container != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTable.java
index 469742f61fa..1a551a3d77f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTable.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTable.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -88,11 +88,11 @@ private Options() {
    * @return a new instance of MutableHashTable
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType, U extends TType> MutableHashTable create(Scope scope, DataType<T> keyDtype, DataType<U> valueDtype, Options... options) {
+  public static <T extends TType, U extends TType> MutableHashTable create(Scope scope, Class<T> keyDtype, Class<U> valueDtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("MutableHashTableV2", scope.makeOpName("MutableHashTable"));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("key_dtype", keyDtype);
-    opBuilder.setAttr("value_dtype", valueDtype);
+    opBuilder.setAttr("key_dtype", Operands.toDataType(keyDtype));
+    opBuilder.setAttr("value_dtype", Operands.toDataType(valueDtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.container != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTableOfTensors.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTableOfTensors.java
index d15b924f034..c054b60ad0b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTableOfTensors.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MutableHashTableOfTensors.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -97,11 +97,11 @@ private Options() {
    * @return a new instance of MutableHashTableOfTensors
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType, U extends TType> MutableHashTableOfTensors create(Scope scope, DataType<T> keyDtype, DataType<U> valueDtype, Options... options) {
+  public static <T extends TType, U extends TType> MutableHashTableOfTensors create(Scope scope, Class<T> keyDtype, Class<U> valueDtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("MutableHashTableOfTensorsV2", scope.makeOpName("MutableHashTableOfTensors"));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("key_dtype", keyDtype);
-    opBuilder.setAttr("value_dtype", valueDtype);
+    opBuilder.setAttr("key_dtype", Operands.toDataType(keyDtype));
+    opBuilder.setAttr("value_dtype", Operands.toDataType(valueDtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.container != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java
index 1e2e0b440ff..8d891145adb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs a tensor containing the reduction across all input tensors.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java
index 7b5dd9d98b7..8febd22137b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Sends `input` to all devices that are connected to the output.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java
index a88f18ebe5f..ceb8480274c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Reduces `input` from `num_devices` using `reduction` to a single device.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapClear.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapClear.java
index 14c7aef5aac..dd789bcec82 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapClear.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapClear.java
@@ -18,13 +18,14 @@
 package org.tensorflow.op.core;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.types.family.TType;
 
 /**
  * Op removes all elements in the underlying container.
@@ -87,14 +88,10 @@ private Options() {
    * @return a new instance of OrderedMapClear
    */
   @Endpoint(describeByClass = true)
-  public static OrderedMapClear create(Scope scope, List<DataType<?>> dtypes, Options... options) {
+  public static OrderedMapClear create(Scope scope, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("OrderedMapClear", scope.makeOpName("OrderedMapClear"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapIncompleteSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapIncompleteSize.java
index 06c0e20af69..56d520b02ff 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapIncompleteSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapIncompleteSize.java
@@ -18,16 +18,17 @@
 package org.tensorflow.op.core;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
+import org.tensorflow.types.family.TType;
 
 /**
  * Op returns the number of incomplete elements in the underlying container.
@@ -90,14 +91,10 @@ private Options() {
    * @return a new instance of OrderedMapIncompleteSize
    */
   @Endpoint(describeByClass = true)
-  public static OrderedMapIncompleteSize create(Scope scope, List<DataType<?>> dtypes, Options... options) {
+  public static OrderedMapIncompleteSize create(Scope scope, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("OrderedMapIncompleteSize", scope.makeOpName("OrderedMapIncompleteSize"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapPeek.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapPeek.java
index 91af29049bf..893be796c79 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapPeek.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapPeek.java
@@ -20,11 +20,11 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -100,16 +100,12 @@ private Options() {
    * @return a new instance of OrderedMapPeek
    */
   @Endpoint(describeByClass = true)
-  public static OrderedMapPeek create(Scope scope, Operand<TInt64> key, Operand<TInt32> indices, List<DataType<?>> dtypes, Options... options) {
+  public static OrderedMapPeek create(Scope scope, Operand<TInt64> key, Operand<TInt32> indices, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("OrderedMapPeek", scope.makeOpName("OrderedMapPeek"));
     opBuilder.addInput(key.asOutput());
     opBuilder.addInput(indices.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapSize.java
index 1a995fbd947..3c561660900 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapSize.java
@@ -18,16 +18,17 @@
 package org.tensorflow.op.core;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
+import org.tensorflow.types.family.TType;
 
 /**
  * Op returns the number of elements in the underlying container.
@@ -90,14 +91,10 @@ private Options() {
    * @return a new instance of OrderedMapSize
    */
   @Endpoint(describeByClass = true)
-  public static OrderedMapSize create(Scope scope, List<DataType<?>> dtypes, Options... options) {
+  public static OrderedMapSize create(Scope scope, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("OrderedMapSize", scope.makeOpName("OrderedMapSize"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapStage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapStage.java
index aee7309dbd4..a78c20a9623 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapStage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapStage.java
@@ -18,7 +18,6 @@
 package org.tensorflow.op.core;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -29,6 +28,7 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
+import org.tensorflow.types.family.TType;
 
 /**
  * Stage (key, values) in the underlying container which behaves like a ordered
@@ -99,17 +99,13 @@ private Options() {
    * @return a new instance of OrderedMapStage
    */
   @Endpoint(describeByClass = true)
-  public static OrderedMapStage create(Scope scope, Operand<TInt64> key, Operand<TInt32> indices, Iterable<Operand<?>> values, List<DataType<?>> dtypes, Options... options) {
+  public static OrderedMapStage create(Scope scope, Operand<TInt64> key, Operand<TInt32> indices, Iterable<Operand<?>> values, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("OrderedMapStage", scope.makeOpName("OrderedMapStage"));
     opBuilder.addInput(key.asOutput());
     opBuilder.addInput(indices.asOutput());
     opBuilder.addInputList(Operands.asOutputs(values));
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstage.java
index 5666b321065..667f0f198fb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstage.java
@@ -20,11 +20,11 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -99,16 +99,12 @@ private Options() {
    * @return a new instance of OrderedMapUnstage
    */
   @Endpoint(describeByClass = true)
-  public static OrderedMapUnstage create(Scope scope, Operand<TInt64> key, Operand<TInt32> indices, List<DataType<?>> dtypes, Options... options) {
+  public static OrderedMapUnstage create(Scope scope, Operand<TInt64> key, Operand<TInt32> indices, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("OrderedMapUnstage", scope.makeOpName("OrderedMapUnstage"));
     opBuilder.addInput(key.asOutput());
     opBuilder.addInput(indices.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstageNoKey.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstageNoKey.java
index 4f28b783451..fb0d239d6a2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstageNoKey.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapUnstageNoKey.java
@@ -19,17 +19,18 @@
 
 import java.util.Arrays;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
+import org.tensorflow.types.family.TType;
 
 /**
  * Op removes and returns the (key, value) element with the smallest
@@ -96,15 +97,11 @@ private Options() {
    * @return a new instance of OrderedMapUnstageNoKey
    */
   @Endpoint(describeByClass = true)
-  public static OrderedMapUnstageNoKey create(Scope scope, Operand<TInt32> indices, List<DataType<?>> dtypes, Options... options) {
+  public static OrderedMapUnstageNoKey create(Scope scope, Operand<TInt32> indices, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("OrderedMapUnstageNoKey", scope.makeOpName("OrderedMapUnstageNoKey"));
     opBuilder.addInput(indices.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java
index f173c27a36c..a510d2d5cb7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -70,10 +70,10 @@ private Options() {
    * @return a new instance of Placeholder
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> Placeholder<T> create(Scope scope, DataType<T> dtype, Options... options) {
+  public static <T extends TType> Placeholder<T> create(Scope scope, Class<T> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("Placeholder", scope.makeOpName("Placeholder"));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.shape != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Range.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Range.java
index 05e58a15da0..7f30e607c86 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Range.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Range.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Creates a sequence of numbers.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java
index ee6624f4fc8..1e73225cc89 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -52,11 +52,11 @@ public final class ReadVariableOp<T extends TType> extends RawOp implements Oper
    * @return a new instance of ReadVariableOp
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> ReadVariableOp<T> create(Scope scope, Operand<?> resource, DataType<T> dtype) {
+  public static <T extends TType> ReadVariableOp<T> create(Scope scope, Operand<?> resource, Class<T> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("ReadVariableOp", scope.makeOpName("ReadVariableOp"));
     opBuilder.addInput(resource.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new ReadVariableOp<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java
index 148c8a5d1ce..ccae187f1ec 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -70,10 +70,10 @@ private Options() {
    * @return a new instance of Recv
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> Recv<T> create(Scope scope, DataType<T> tensorType, String tensorName, String sendDevice, Long sendDeviceIncarnation, String recvDevice, Options... options) {
+  public static <T extends TType> Recv<T> create(Scope scope, Class<T> tensorType, String tensorName, String sendDevice, Long sendDeviceIncarnation, String recvDevice, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("Recv", scope.makeOpName("Recv"));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("tensor_type", tensorType);
+    opBuilder.setAttr("tensor_type", Operands.toDataType(tensorType));
     opBuilder.setAttr("tensor_name", tensorName);
     opBuilder.setAttr("send_device", sendDevice);
     opBuilder.setAttr("send_device_incarnation", sendDeviceIncarnation);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAll.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAll.java
index 0766d3a0cf6..9c731309c44 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAll.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAll.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the "logical and" of elements across dimensions of a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAny.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAny.java
index b853c9c3df4..ce57bd4911b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAny.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceAny.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the "logical or" of elements across dimensions of a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RemoteFusedGraphExecute.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RemoteFusedGraphExecute.java
index dd7cbdad550..b0dcdfc5398 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RemoteFusedGraphExecute.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RemoteFusedGraphExecute.java
@@ -20,7 +20,6 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -57,15 +56,11 @@ public final class RemoteFusedGraphExecute extends RawOp implements Iterable<Ope
    * @return a new instance of RemoteFusedGraphExecute
    */
   @Endpoint(describeByClass = true)
-  public static RemoteFusedGraphExecute create(Scope scope, Iterable<Operand<?>> inputs, List<DataType<?>> Toutputs, String serializedRemoteFusedGraphExecuteInfo) {
+  public static RemoteFusedGraphExecute create(Scope scope, Iterable<Operand<?>> inputs, List<Class<? extends TType>> Toutputs, String serializedRemoteFusedGraphExecuteInfo) {
     OperationBuilder opBuilder = scope.env().opBuilder("RemoteFusedGraphExecute", scope.makeOpName("RemoteFusedGraphExecute"));
     opBuilder.addInputList(Operands.asOutputs(inputs));
     opBuilder = scope.apply(opBuilder);
-    DataType[] ToutputsArray = new DataType[Toutputs.size()];
-    for (int i = 0; i < ToutputsArray.length; ++i) {
-      ToutputsArray[i] = Toutputs.get(i);
-    }
-    opBuilder.setAttr("Toutputs", ToutputsArray);
+    opBuilder.setAttr("Toutputs", Operands.toDataTypes(Toutputs));
     opBuilder.setAttr("serialized_remote_fused_graph_execute_info", serializedRemoteFusedGraphExecuteInfo);
     return new RemoteFusedGraphExecute(opBuilder.build());
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java
index 7600321885f..cbfb7ea15d2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java
@@ -17,17 +17,16 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Increments variable pointed to by 'resource' until it reaches 'limit'.
@@ -48,12 +47,12 @@ public final class ResourceCountUpTo<T extends TNumber> extends RawOp implements
    * @return a new instance of ResourceCountUpTo
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber> ResourceCountUpTo<T> create(Scope scope, Operand<?> resource, Long limit, DataType<T> T) {
+  public static <T extends TNumber> ResourceCountUpTo<T> create(Scope scope, Operand<?> resource, Long limit, Class<T> T) {
     OperationBuilder opBuilder = scope.env().opBuilder("ResourceCountUpTo", scope.makeOpName("ResourceCountUpTo"));
     opBuilder.addInput(resource.asOutput());
     opBuilder = scope.apply(opBuilder);
     opBuilder.setAttr("limit", limit);
-    opBuilder.setAttr("T", T);
+    opBuilder.setAttr("T", Operands.toDataType(T));
     return new ResourceCountUpTo<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java
index 8d29d6f9a6f..4830d44d3ba 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -90,12 +90,12 @@ private Options() {
    * @return a new instance of ResourceGather
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TNumber> ResourceGather<U> create(Scope scope, Operand<?> resource, Operand<T> indices, DataType<U> dtype, Options... options) {
+  public static <U extends TType, T extends TNumber> ResourceGather<U> create(Scope scope, Operand<?> resource, Operand<T> indices, Class<U> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("ResourceGather", scope.makeOpName("ResourceGather"));
     opBuilder.addInput(resource.asOutput());
     opBuilder.addInput(indices.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.batchDims != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java
index ed90a270f83..d78b649a997 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -45,12 +45,12 @@ public final class ResourceGatherNd<U extends TType> extends RawOp implements Op
    * @return a new instance of ResourceGatherNd
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TNumber> ResourceGatherNd<U> create(Scope scope, Operand<?> resource, Operand<T> indices, DataType<U> dtype) {
+  public static <U extends TType, T extends TNumber> ResourceGatherNd<U> create(Scope scope, Operand<?> resource, Operand<T> indices, Class<U> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("ResourceGatherNd", scope.makeOpName("ResourceGatherNd"));
     opBuilder.addInput(resource.asOutput());
     opBuilder.addInput(indices.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new ResourceGatherNd<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java
index e96cd9db5fd..746a6d30a35 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Reduces sparse updates into a variable reference using the `max` operation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java
index 596ae2b1882..4f854496bf3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Reduces sparse updates into a variable reference using the `min` operation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java
index 4c5a51af3f4..515f413fca9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -69,12 +69,12 @@ public final class SetDiff1d<T extends TType, U extends TNumber> extends RawOp {
    * @return a new instance of SetDiff1d
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType, U extends TNumber> SetDiff1d<T, U> create(Scope scope, Operand<T> x, Operand<T> y, DataType<U> outIdx) {
+  public static <T extends TType, U extends TNumber> SetDiff1d<T, U> create(Scope scope, Operand<T> x, Operand<T> y, Class<U> outIdx) {
     OperationBuilder opBuilder = scope.env().opBuilder("ListDiff", scope.makeOpName("SetDiff1d"));
     opBuilder.addInput(x.asOutput());
     opBuilder.addInput(y.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_idx", outIdx);
+    opBuilder.setAttr("out_idx", Operands.toDataType(outIdx));
     return new SetDiff1d<T, U>(opBuilder.build());
   }
   
@@ -88,7 +88,7 @@ public static <T extends TType, U extends TNumber> SetDiff1d<T, U> create(Scope
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> SetDiff1d<T, TInt32> create(Scope scope, Operand<T> x, Operand<T> y) {
-    return create(scope, x, y, TInt32.DTYPE);
+    return create(scope, x, y, TInt32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java
index 4fdefdae3a7..a2d8a43a496 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -56,11 +56,11 @@ public final class Shape<U extends TNumber> extends RawOp implements Operand<U>
    * @return a new instance of Shape
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> Shape<U> create(Scope scope, Operand<T> input, DataType<U> outType) {
+  public static <U extends TNumber, T extends TType> Shape<U> create(Scope scope, Operand<T> input, Class<U> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("Shape", scope.makeOpName("Shape"));
     opBuilder.addInput(input.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new Shape<U>(opBuilder.build());
   }
   
@@ -73,7 +73,7 @@ public static <U extends TNumber, T extends TType> Shape<U> create(Scope scope,
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> Shape<TInt32> create(Scope scope, Operand<T> input) {
-    return create(scope, input, TInt32.DTYPE);
+    return create(scope, input, TInt32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java
index c295cf810e2..b196e321962 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java
@@ -20,7 +20,6 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -53,11 +52,11 @@ public final class ShapeN<U extends TNumber> extends RawOp implements Iterable<O
    * @return a new instance of ShapeN
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> ShapeN<U> create(Scope scope, Iterable<Operand<T>> input, DataType<U> outType) {
+  public static <U extends TNumber, T extends TType> ShapeN<U> create(Scope scope, Iterable<Operand<T>> input, Class<U> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("ShapeN", scope.makeOpName("ShapeN"));
     opBuilder.addInputList(Operands.asOutputs(input));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new ShapeN<U>(opBuilder.build());
   }
   
@@ -70,7 +69,7 @@ public static <U extends TNumber, T extends TType> ShapeN<U> create(Scope scope,
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> ShapeN<TInt32> create(Scope scope, Iterable<Operand<T>> input) {
-    return create(scope, input, TInt32.DTYPE);
+    return create(scope, input, TInt32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java
index fbc3f2928a8..127608e1fac 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -57,11 +57,11 @@ public final class Size<U extends TNumber> extends RawOp implements Operand<U> {
    * @return a new instance of Size
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> Size<U> create(Scope scope, Operand<T> input, DataType<U> outType) {
+  public static <U extends TNumber, T extends TType> Size<U> create(Scope scope, Operand<T> input, Class<U> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("Size", scope.makeOpName("Size"));
     opBuilder.addInput(input.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new Size<U>(opBuilder.build());
   }
   
@@ -74,7 +74,7 @@ public static <U extends TNumber, T extends TType> Size<U> create(Scope scope, O
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> Size<TInt32> create(Scope scope, Operand<T> input) {
-    return create(scope, input, TInt32.DTYPE);
+    return create(scope, input, TInt32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageClear.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageClear.java
index 5bcf715d7a6..7be90432f6b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageClear.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageClear.java
@@ -18,13 +18,14 @@
 package org.tensorflow.op.core;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.types.family.TType;
 
 /**
  * Op removes all elements in the underlying container.
@@ -87,14 +88,10 @@ private Options() {
    * @return a new instance of StageClear
    */
   @Endpoint(describeByClass = true)
-  public static StageClear create(Scope scope, List<DataType<?>> dtypes, Options... options) {
+  public static StageClear create(Scope scope, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("StageClear", scope.makeOpName("StageClear"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StagePeek.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StagePeek.java
index f200a074545..eb6e6dde91c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StagePeek.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StagePeek.java
@@ -20,11 +20,11 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -98,15 +98,11 @@ private Options() {
    * @return a new instance of StagePeek
    */
   @Endpoint(describeByClass = true)
-  public static StagePeek create(Scope scope, Operand<TInt32> index, List<DataType<?>> dtypes, Options... options) {
+  public static StagePeek create(Scope scope, Operand<TInt32> index, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("StagePeek", scope.makeOpName("StagePeek"));
     opBuilder.addInput(index.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageSize.java
index 09791a6332f..c70660c2071 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StageSize.java
@@ -18,16 +18,17 @@
 package org.tensorflow.op.core;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
+import org.tensorflow.types.family.TType;
 
 /**
  * Op returns the number of elements in the underlying container.
@@ -90,14 +91,10 @@ private Options() {
    * @return a new instance of StageSize
    */
   @Endpoint(describeByClass = true)
-  public static StageSize create(Scope scope, List<DataType<?>> dtypes, Options... options) {
+  public static StageSize create(Scope scope, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("StageSize", scope.makeOpName("StageSize"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java
index fad59c7168a..15f54863824 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -82,11 +82,11 @@ private Options() {
    * @return a new instance of TemporaryVariable
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> TemporaryVariable<T> create(Scope scope, Shape shape, DataType<T> dtype, Options... options) {
+  public static <T extends TType> TemporaryVariable<T> create(Scope scope, Shape shape, Class<T> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("TemporaryVariable", scope.makeOpName("TemporaryVariable"));
     opBuilder = scope.apply(opBuilder);
     opBuilder.setAttr("shape", shape);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.varName != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArray.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArray.java
index f8ab8d68d64..c162f3110f6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArray.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArray.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -116,11 +116,11 @@ private Options() {
    * @return a new instance of TensorArray
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> TensorArray create(Scope scope, Operand<TInt32> size, DataType<T> dtype, Options... options) {
+  public static <T extends TType> TensorArray create(Scope scope, Operand<TInt32> size, Class<T> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("TensorArrayV3", scope.makeOpName("TensorArray"));
     opBuilder.addInput(size.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.elementShape != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java
index 64c24bd69d4..a861b19400e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -83,12 +83,12 @@ private Options() {
    * @return a new instance of TensorArrayConcat
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> TensorArrayConcat<T> create(Scope scope, Operand<?> handle, Operand<TFloat32> flowIn, DataType<T> dtype, Options... options) {
+  public static <T extends TType> TensorArrayConcat<T> create(Scope scope, Operand<?> handle, Operand<TFloat32> flowIn, Class<T> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("TensorArrayConcatV3", scope.makeOpName("TensorArrayConcat"));
     opBuilder.addInput(handle.asOutput());
     opBuilder.addInput(flowIn.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.elementShapeExcept0 != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java
index 76f577f4e01..8f4bcea319e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -74,13 +74,13 @@ private Options() {
    * @return a new instance of TensorArrayGather
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> TensorArrayGather<T> create(Scope scope, Operand<?> handle, Operand<TInt32> indices, Operand<TFloat32> flowIn, DataType<T> dtype, Options... options) {
+  public static <T extends TType> TensorArrayGather<T> create(Scope scope, Operand<?> handle, Operand<TInt32> indices, Operand<TFloat32> flowIn, Class<T> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("TensorArrayGatherV3", scope.makeOpName("TensorArrayGather"));
     opBuilder.addInput(handle.asOutput());
     opBuilder.addInput(indices.asOutput());
     opBuilder.addInput(flowIn.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.elementShape != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java
index d9505d5c4a2..aa45df4b937 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -67,12 +67,12 @@ private Options() {
    * @return a new instance of TensorArrayPack
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> TensorArrayPack<T> create(Scope scope, Operand<TString> handle, Operand<TFloat32> flowIn, DataType<T> dtype, Options... options) {
+  public static <T extends TType> TensorArrayPack<T> create(Scope scope, Operand<TString> handle, Operand<TFloat32> flowIn, Class<T> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("TensorArrayPack", scope.makeOpName("TensorArrayPack"));
     opBuilder.addInput(handle.asOutput());
     opBuilder.addInput(flowIn.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.elementShape != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java
index 3e299a0c5d5..c076510e393 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -49,13 +49,13 @@ public final class TensorArrayRead<T extends TType> extends RawOp implements Ope
    * @return a new instance of TensorArrayRead
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> TensorArrayRead<T> create(Scope scope, Operand<?> handle, Operand<TInt32> index, Operand<TFloat32> flowIn, DataType<T> dtype) {
+  public static <T extends TType> TensorArrayRead<T> create(Scope scope, Operand<?> handle, Operand<TInt32> index, Operand<TFloat32> flowIn, Class<T> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("TensorArrayReadV3", scope.makeOpName("TensorArrayRead"));
     opBuilder.addInput(handle.asOutput());
     opBuilder.addInput(index.asOutput());
     opBuilder.addInput(flowIn.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new TensorArrayRead<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java
index 1e1941053ac..685c9c1d900 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -62,13 +62,13 @@ public final class TensorListConcat<U extends TType> extends RawOp {
    * @return a new instance of TensorListConcat
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TNumber> TensorListConcat<U> create(Scope scope, Operand<?> inputHandle, Operand<T> elementShape, Operand<TInt64> leadingDims, DataType<U> elementDtype) {
+  public static <U extends TType, T extends TNumber> TensorListConcat<U> create(Scope scope, Operand<?> inputHandle, Operand<T> elementShape, Operand<TInt64> leadingDims, Class<U> elementDtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("TensorListConcatV2", scope.makeOpName("TensorListConcat"));
     opBuilder.addInput(inputHandle.asOutput());
     opBuilder.addInput(elementShape.asOutput());
     opBuilder.addInput(leadingDims.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("element_dtype", elementDtype);
+    opBuilder.setAttr("element_dtype", Operands.toDataType(elementDtype));
     return new TensorListConcat<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcatLists.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcatLists.java
index 7554a301d16..25b2e06df84 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcatLists.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcatLists.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -43,12 +43,12 @@ public final class TensorListConcatLists extends RawOp implements Operand<TType>
    * @return a new instance of TensorListConcatLists
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> TensorListConcatLists create(Scope scope, Operand<?> inputA, Operand<?> inputB, DataType<T> elementDtype) {
+  public static <T extends TType> TensorListConcatLists create(Scope scope, Operand<?> inputA, Operand<?> inputB, Class<T> elementDtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("TensorListConcatLists", scope.makeOpName("TensorListConcatLists"));
     opBuilder.addInput(inputA.asOutput());
     opBuilder.addInput(inputB.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("element_dtype", elementDtype);
+    opBuilder.setAttr("element_dtype", Operands.toDataType(elementDtype));
     return new TensorListConcatLists(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java
index d0511f3b96a..a985213de4e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java
@@ -17,17 +17,16 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * The shape of the elements of the given list, as a tensor.
@@ -49,11 +48,11 @@ public final class TensorListElementShape<T extends TNumber> extends RawOp imple
    * @return a new instance of TensorListElementShape
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber> TensorListElementShape<T> create(Scope scope, Operand<?> inputHandle, DataType<T> shapeType) {
+  public static <T extends TNumber> TensorListElementShape<T> create(Scope scope, Operand<?> inputHandle, Class<T> shapeType) {
     OperationBuilder opBuilder = scope.env().opBuilder("TensorListElementShape", scope.makeOpName("TensorListElementShape"));
     opBuilder.addInput(inputHandle.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("shape_type", shapeType);
+    opBuilder.setAttr("shape_type", Operands.toDataType(shapeType));
     return new TensorListElementShape<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java
index 2acb7aea4ae..90cacdd0435 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -55,13 +55,13 @@ public final class TensorListGather<T extends TType> extends RawOp implements Op
    * @return a new instance of TensorListGather
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> TensorListGather<T> create(Scope scope, Operand<?> inputHandle, Operand<TInt32> indices, Operand<TInt32> elementShape, DataType<T> elementDtype) {
+  public static <T extends TType> TensorListGather<T> create(Scope scope, Operand<?> inputHandle, Operand<TInt32> indices, Operand<TInt32> elementShape, Class<T> elementDtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("TensorListGather", scope.makeOpName("TensorListGather"));
     opBuilder.addInput(inputHandle.asOutput());
     opBuilder.addInput(indices.asOutput());
     opBuilder.addInput(elementShape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("element_dtype", elementDtype);
+    opBuilder.setAttr("element_dtype", Operands.toDataType(elementDtype));
     return new TensorListGather<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java
index af86e14fa92..7f96f897242 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -46,13 +46,13 @@ public final class TensorListGetItem<T extends TType> extends RawOp implements O
    * @return a new instance of TensorListGetItem
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> TensorListGetItem<T> create(Scope scope, Operand<?> inputHandle, Operand<TInt32> index, Operand<TInt32> elementShape, DataType<T> elementDtype) {
+  public static <T extends TType> TensorListGetItem<T> create(Scope scope, Operand<?> inputHandle, Operand<TInt32> index, Operand<TInt32> elementShape, Class<T> elementDtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("TensorListGetItem", scope.makeOpName("TensorListGetItem"));
     opBuilder.addInput(inputHandle.asOutput());
     opBuilder.addInput(index.asOutput());
     opBuilder.addInput(elementShape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("element_dtype", elementDtype);
+    opBuilder.setAttr("element_dtype", Operands.toDataType(elementDtype));
     return new TensorListGetItem<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java
index 9e601b5733b..5600bf69778 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -54,12 +54,12 @@ public final class TensorListPopBack<T extends TType> extends RawOp {
    * @return a new instance of TensorListPopBack
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> TensorListPopBack<T> create(Scope scope, Operand<?> inputHandle, Operand<TInt32> elementShape, DataType<T> elementDtype) {
+  public static <T extends TType> TensorListPopBack<T> create(Scope scope, Operand<?> inputHandle, Operand<TInt32> elementShape, Class<T> elementDtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("TensorListPopBack", scope.makeOpName("TensorListPopBack"));
     opBuilder.addInput(inputHandle.asOutput());
     opBuilder.addInput(elementShape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("element_dtype", elementDtype);
+    opBuilder.setAttr("element_dtype", Operands.toDataType(elementDtype));
     return new TensorListPopBack<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListReserve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListReserve.java
index 439bfe69886..71e4c2b2f06 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListReserve.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListReserve.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -51,12 +51,12 @@ public final class TensorListReserve extends RawOp implements Operand<TType> {
    * @return a new instance of TensorListReserve
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber, U extends TType> TensorListReserve create(Scope scope, Operand<T> elementShape, Operand<TInt32> numElements, DataType<U> elementDtype) {
+  public static <T extends TNumber, U extends TType> TensorListReserve create(Scope scope, Operand<T> elementShape, Operand<TInt32> numElements, Class<U> elementDtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("TensorListReserve", scope.makeOpName("TensorListReserve"));
     opBuilder.addInput(elementShape.asOutput());
     opBuilder.addInput(numElements.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("element_dtype", elementDtype);
+    opBuilder.setAttr("element_dtype", Operands.toDataType(elementDtype));
     return new TensorListReserve(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java
index 5ce4e4242ea..20284f1e76e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -74,12 +74,12 @@ private Options() {
    * @return a new instance of TensorListStack
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> TensorListStack<T> create(Scope scope, Operand<?> inputHandle, Operand<TInt32> elementShape, DataType<T> elementDtype, Options... options) {
+  public static <T extends TType> TensorListStack<T> create(Scope scope, Operand<?> inputHandle, Operand<TInt32> elementShape, Class<T> elementDtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("TensorListStack", scope.makeOpName("TensorListStack"));
     opBuilder.addInput(inputHandle.asOutput());
     opBuilder.addInput(elementShape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("element_dtype", elementDtype);
+    opBuilder.setAttr("element_dtype", Operands.toDataType(elementDtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.numElements != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java
index 29703554467..40b303e2a05 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -90,12 +90,12 @@ public final class Unique<T extends TType, V extends TNumber> extends RawOp {
    * @return a new instance of Unique
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType, V extends TNumber, U extends TNumber> Unique<T, V> create(Scope scope, Operand<T> x, Operand<U> axis, DataType<V> outIdx) {
+  public static <T extends TType, V extends TNumber, U extends TNumber> Unique<T, V> create(Scope scope, Operand<T> x, Operand<U> axis, Class<V> outIdx) {
     OperationBuilder opBuilder = scope.env().opBuilder("UniqueV2", scope.makeOpName("Unique"));
     opBuilder.addInput(x.asOutput());
     opBuilder.addInput(axis.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_idx", outIdx);
+    opBuilder.setAttr("out_idx", Operands.toDataType(outIdx));
     return new Unique<T, V>(opBuilder.build());
   }
   
@@ -110,7 +110,7 @@ public static <T extends TType, V extends TNumber, U extends TNumber> Unique<T,
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType, U extends TNumber> Unique<T, TInt32> create(Scope scope, Operand<T> x, Operand<U> axis) {
-    return create(scope, x, axis, TInt32.DTYPE);
+    return create(scope, x, axis, TInt32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java
index 1c0b63c6444..cf2ae7566cc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -94,12 +94,12 @@ public final class UniqueWithCounts<T extends TType, V extends TNumber> extends
    * @return a new instance of UniqueWithCounts
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType, V extends TNumber, U extends TNumber> UniqueWithCounts<T, V> create(Scope scope, Operand<T> x, Operand<U> axis, DataType<V> outIdx) {
+  public static <T extends TType, V extends TNumber, U extends TNumber> UniqueWithCounts<T, V> create(Scope scope, Operand<T> x, Operand<U> axis, Class<V> outIdx) {
     OperationBuilder opBuilder = scope.env().opBuilder("UniqueWithCountsV2", scope.makeOpName("UniqueWithCounts"));
     opBuilder.addInput(x.asOutput());
     opBuilder.addInput(axis.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_idx", outIdx);
+    opBuilder.setAttr("out_idx", Operands.toDataType(outIdx));
     return new UniqueWithCounts<T, V>(opBuilder.build());
   }
   
@@ -114,7 +114,7 @@ public static <T extends TType, V extends TNumber, U extends TNumber> UniqueWith
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType, U extends TNumber> UniqueWithCounts<T, TInt32> create(Scope scope, Operand<T> x, Operand<U> axis) {
-    return create(scope, x, axis, TInt32.DTYPE);
+    return create(scope, x, axis, TInt32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java
index 18ff27b22f4..0ce98a63884 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Converts an array of flat indices into a tuple of coordinate arrays.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstage.java
index e765d849117..2997b5eaa57 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstage.java
@@ -20,11 +20,11 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -95,14 +95,10 @@ private Options() {
    * @return a new instance of Unstage
    */
   @Endpoint(describeByClass = true)
-  public static Unstage create(Scope scope, List<DataType<?>> dtypes, Options... options) {
+  public static Unstage create(Scope scope, List<Class<? extends TType>> dtypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("Unstage", scope.makeOpName("Unstage"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.capacity != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java
index c8f83e5bbb0..6bc9d8034fd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -66,12 +66,12 @@ public final class UpperBound<U extends TNumber> extends RawOp implements Operan
    * @return a new instance of UpperBound
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> UpperBound<U> create(Scope scope, Operand<T> sortedInputs, Operand<T> values, DataType<U> outType) {
+  public static <U extends TNumber, T extends TType> UpperBound<U> create(Scope scope, Operand<T> sortedInputs, Operand<T> values, Class<U> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("UpperBound", scope.makeOpName("UpperBound"));
     opBuilder.addInput(sortedInputs.asOutput());
     opBuilder.addInput(values.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new UpperBound<U>(opBuilder.build());
   }
   
@@ -86,7 +86,7 @@ public static <U extends TNumber, T extends TType> UpperBound<U> create(Scope sc
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> UpperBound<TInt32> create(Scope scope, Operand<T> sortedInputs, Operand<T> values) {
-    return create(scope, sortedInputs, values, TInt32.DTYPE);
+    return create(scope, sortedInputs, values, TInt32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VarHandleOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VarHandleOp.java
index 1d5c519c417..41d962d4381 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VarHandleOp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VarHandleOp.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.core;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -85,10 +85,10 @@ private Options() {
    * @return a new instance of VarHandleOp
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> VarHandleOp create(Scope scope, DataType<T> dtype, Shape shape, Options... options) {
+  public static <T extends TType> VarHandleOp create(Scope scope, Class<T> dtype, Shape shape, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("VarHandleOp", scope.makeOpName("VarHandleOp"));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     opBuilder.setAttr("shape", shape);
     if (options != null) {
       for (Options opts : options) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java
index 38b66d3deca..98e545d7b76 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -81,11 +81,11 @@ private Options() {
    * @return a new instance of Variable
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> Variable<T> create(Scope scope, Shape shape, DataType<T> dtype, Options... options) {
+  public static <T extends TType> Variable<T> create(Scope scope, Shape shape, Class<T> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("VariableV2", scope.makeOpName("Variable"));
     opBuilder = scope.apply(opBuilder);
     opBuilder.setAttr("shape", shape);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.container != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java
index 3f7a30bc2f4..ab37a6c4d08 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java
@@ -17,18 +17,17 @@
 
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns the shape of the variable pointed to by `resource`.
@@ -56,11 +55,11 @@ public final class VariableShape<T extends TNumber> extends RawOp implements Ope
    * @return a new instance of VariableShape
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber> VariableShape<T> create(Scope scope, Operand<?> input, DataType<T> outType) {
+  public static <T extends TNumber> VariableShape<T> create(Scope scope, Operand<?> input, Class<T> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("VariableShape", scope.makeOpName("VariableShape"));
     opBuilder.addInput(input.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new VariableShape<T>(opBuilder.build());
   }
   
@@ -73,7 +72,7 @@ public static <T extends TNumber> VariableShape<T> create(Scope scope, Operand<?
    */
   @Endpoint(describeByClass = true)
   public static VariableShape<TInt32> create(Scope scope, Operand<?> input) {
-    return create(scope, input, TInt32.DTYPE);
+    return create(scope, input, TInt32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousIterator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousIterator.java
index 3e9325f8ffc..3be3e0be3eb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousIterator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousIterator.java
@@ -18,15 +18,16 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.types.family.TType;
 
 /**
  * A container for an iterator resource.
@@ -43,14 +44,10 @@ public final class AnonymousIterator extends RawOp {
    * @return a new instance of AnonymousIterator
    */
   @Endpoint(describeByClass = true)
-  public static AnonymousIterator create(Scope scope, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static AnonymousIterator create(Scope scope, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("AnonymousIteratorV2", scope.makeOpName("AnonymousIterator"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousMultiDeviceIterator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousMultiDeviceIterator.java
index c88b52dac89..d02a1f37cf3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousMultiDeviceIterator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AnonymousMultiDeviceIterator.java
@@ -18,15 +18,16 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
+import org.tensorflow.types.family.TType;
 
 /**
  * A container for a multi device iterator resource.
@@ -43,7 +44,7 @@ public final class AnonymousMultiDeviceIterator extends RawOp {
    * @return a new instance of AnonymousMultiDeviceIterator
    */
   @Endpoint(describeByClass = true)
-  public static AnonymousMultiDeviceIterator create(Scope scope, List<String> devices, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static AnonymousMultiDeviceIterator create(Scope scope, List<String> devices, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("AnonymousMultiDeviceIterator", scope.makeOpName("AnonymousMultiDeviceIterator"));
     opBuilder = scope.apply(opBuilder);
     String[] devicesArray = new String[devices.size()];
@@ -51,11 +52,7 @@ public static AnonymousMultiDeviceIterator create(Scope scope, List<String> devi
       devicesArray[i] = devices.get(i);
     }
     opBuilder.setAttr("devices", devicesArray);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AssertNextDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AssertNextDataset.java
index 56c48d9093c..ee9da65be4d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AssertNextDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AssertNextDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -58,16 +58,12 @@ public final class AssertNextDataset extends RawOp implements Operand<TType> {
    * @return a new instance of AssertNextDataset
    */
   @Endpoint(describeByClass = true)
-  public static AssertNextDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> transformations, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static AssertNextDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> transformations, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("AssertNextDataset", scope.makeOpName("AssertNextDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(transformations.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AutoShardDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AutoShardDataset.java
index 92b73b6603e..1e18bf6be11 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AutoShardDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/AutoShardDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -76,17 +76,13 @@ private Options() {
    * @return a new instance of AutoShardDataset
    */
   @Endpoint(describeByClass = true)
-  public static AutoShardDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numWorkers, Operand<TInt64> index, List<DataType<?>> outputTypes, List<Shape> outputShapes, Options... options) {
+  public static AutoShardDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numWorkers, Operand<TInt64> index, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("AutoShardDataset", scope.makeOpName("AutoShardDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(numWorkers.asOutput());
     opBuilder.addInput(index.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BatchDataset.java
index a37b4eb3169..ee03bac2b95 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BatchDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -71,17 +71,13 @@ private Options() {
    * @return a new instance of BatchDataset
    */
   @Endpoint(describeByClass = true)
-  public static BatchDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> batchSize, Operand<TBool> dropRemainder, List<DataType<?>> outputTypes, List<Shape> outputShapes, Options... options) {
+  public static BatchDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> batchSize, Operand<TBool> dropRemainder, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("BatchDatasetV2", scope.makeOpName("BatchDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(batchSize.asOutput());
     opBuilder.addInput(dropRemainder.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BytesProducedStatsDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BytesProducedStatsDataset.java
index 4e5dbab1143..b9cea475727 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BytesProducedStatsDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/BytesProducedStatsDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,16 +47,12 @@ public final class BytesProducedStatsDataset extends RawOp implements Operand<TT
    * @return a new instance of BytesProducedStatsDataset
    */
   @Endpoint(describeByClass = true)
-  public static BytesProducedStatsDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> tag, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static BytesProducedStatsDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> tag, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("BytesProducedStatsDataset", scope.makeOpName("BytesProducedStatsDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(tag.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDataset.java
index 4df9c69bc61..25431c48ec6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -53,16 +53,12 @@ public final class CacheDataset extends RawOp implements Operand<TType> {
    * @return a new instance of CacheDataset
    */
   @Endpoint(describeByClass = true)
-  public static CacheDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> filename, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static CacheDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> filename, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("CacheDataset", scope.makeOpName("CacheDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(filename.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDatasetV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDatasetV2.java
index ed5f087c039..c5cd457be55 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDatasetV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/CacheDatasetV2.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,17 +47,13 @@ public final class CacheDatasetV2 extends RawOp implements Operand<TType> {
    * @return a new instance of CacheDatasetV2
    */
   @Endpoint(describeByClass = true)
-  public static CacheDatasetV2 create(Scope scope, Operand<?> inputDataset, Operand<TString> filename, Operand<?> cache, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static CacheDatasetV2 create(Scope scope, Operand<?> inputDataset, Operand<TString> filename, Operand<?> cache, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("CacheDatasetV2", scope.makeOpName("CacheDatasetV2"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(filename.asOutput());
     opBuilder.addInput(cache.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ChooseFastestDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ChooseFastestDataset.java
index c10cf4d1660..e29e27f73f4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ChooseFastestDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ChooseFastestDataset.java
@@ -18,7 +18,6 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -46,16 +45,12 @@ public final class ChooseFastestDataset extends RawOp implements Operand<TType>
    * @return a new instance of ChooseFastestDataset
    */
   @Endpoint(describeByClass = true)
-  public static ChooseFastestDataset create(Scope scope, Iterable<Operand<?>> inputDatasets, Long numExperiments, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static ChooseFastestDataset create(Scope scope, Iterable<Operand<?>> inputDatasets, Long numExperiments, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ChooseFastestDataset", scope.makeOpName("ChooseFastestDataset"));
     opBuilder.addInputList(Operands.asOutputs(inputDatasets));
     opBuilder = scope.apply(opBuilder);
     opBuilder.setAttr("num_experiments", numExperiments);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ConcatenateDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ConcatenateDataset.java
index 9806530cd4b..bd32060b138 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ConcatenateDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ConcatenateDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,16 +47,12 @@ public final class ConcatenateDataset extends RawOp implements Operand<TType> {
    * @return a new instance of ConcatenateDataset
    */
   @Endpoint(describeByClass = true)
-  public static ConcatenateDataset create(Scope scope, Operand<?> inputDataset, Operand<?> anotherDataset, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static ConcatenateDataset create(Scope scope, Operand<?> inputDataset, Operand<?> anotherDataset, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ConcatenateDataset", scope.makeOpName("ConcatenateDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(anotherDataset.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToSingleElement.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToSingleElement.java
index 5df75adc3f4..a74413e1935 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToSingleElement.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DatasetToSingleElement.java
@@ -20,12 +20,12 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,15 +47,11 @@ public final class DatasetToSingleElement extends RawOp implements Iterable<Oper
    * @return a new instance of DatasetToSingleElement
    */
   @Endpoint(describeByClass = true)
-  public static DatasetToSingleElement create(Scope scope, Operand<?> dataset, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static DatasetToSingleElement create(Scope scope, Operand<?> dataset, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("DatasetToSingleElement", scope.makeOpName("DatasetToSingleElement"));
     opBuilder.addInput(dataset.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DenseToSparseBatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DenseToSparseBatchDataset.java
index 87c843cb06c..1b5c9ec6ceb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DenseToSparseBatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DenseToSparseBatchDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -51,17 +51,13 @@ public final class DenseToSparseBatchDataset extends RawOp implements Operand<TT
    * @return a new instance of DenseToSparseBatchDataset
    */
   @Endpoint(describeByClass = true)
-  public static DenseToSparseBatchDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> batchSize, Operand<TInt64> rowShape, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static DenseToSparseBatchDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> batchSize, Operand<TInt64> rowShape, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("DenseToSparseBatchDataset", scope.makeOpName("DenseToSparseBatchDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(batchSize.asOutput());
     opBuilder.addInput(rowShape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DirectedInterleaveDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DirectedInterleaveDataset.java
index 654fec6185c..0e543dc351a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DirectedInterleaveDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/DirectedInterleaveDataset.java
@@ -18,7 +18,6 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -49,16 +48,12 @@ public final class DirectedInterleaveDataset extends RawOp implements Operand<TT
    * @return a new instance of DirectedInterleaveDataset
    */
   @Endpoint(describeByClass = true)
-  public static DirectedInterleaveDataset create(Scope scope, Operand<?> selectorInputDataset, Iterable<Operand<?>> dataInputDatasets, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static DirectedInterleaveDataset create(Scope scope, Operand<?> selectorInputDataset, Iterable<Operand<?>> dataInputDatasets, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("DirectedInterleaveDataset", scope.makeOpName("DirectedInterleaveDataset"));
     opBuilder.addInput(selectorInputDataset.asOutput());
     opBuilder.addInputList(Operands.asOutputs(dataInputDatasets));
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FilterByLastComponentDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FilterByLastComponentDataset.java
index 9119d082346..d1d1c55e08f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FilterByLastComponentDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/FilterByLastComponentDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -45,15 +45,11 @@ public final class FilterByLastComponentDataset extends RawOp implements Operand
    * @return a new instance of FilterByLastComponentDataset
    */
   @Endpoint(describeByClass = true)
-  public static FilterByLastComponentDataset create(Scope scope, Operand<?> inputDataset, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static FilterByLastComponentDataset create(Scope scope, Operand<?> inputDataset, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("FilterByLastComponentDataset", scope.makeOpName("FilterByLastComponentDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IgnoreErrorsDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IgnoreErrorsDataset.java
index 2d0822d06a2..0b4bec924b2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IgnoreErrorsDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IgnoreErrorsDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -45,15 +45,11 @@ public final class IgnoreErrorsDataset extends RawOp implements Operand<TType> {
    * @return a new instance of IgnoreErrorsDataset
    */
   @Endpoint(describeByClass = true)
-  public static IgnoreErrorsDataset create(Scope scope, Operand<?> inputDataset, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static IgnoreErrorsDataset create(Scope scope, Operand<?> inputDataset, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("IgnoreErrorsDataset", scope.makeOpName("IgnoreErrorsDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/Iterator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/Iterator.java
index c1c3804bdbe..d20e98d5c9b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/Iterator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/Iterator.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -46,16 +46,12 @@ public final class Iterator extends RawOp implements Operand<TType> {
    * @return a new instance of Iterator
    */
   @Endpoint(describeByClass = true)
-  public static Iterator create(Scope scope, String sharedName, String container, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static Iterator create(Scope scope, String sharedName, String container, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("IteratorV2", scope.makeOpName("Iterator"));
     opBuilder = scope.apply(opBuilder);
     opBuilder.setAttr("shared_name", sharedName);
     opBuilder.setAttr("container", container);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorFromStringHandle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorFromStringHandle.java
index b65e2c57225..4de1a9f1e9e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorFromStringHandle.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorFromStringHandle.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -64,15 +64,11 @@ private Options() {
    * @return a new instance of IteratorFromStringHandle
    */
   @Endpoint(describeByClass = true)
-  public static IteratorFromStringHandle create(Scope scope, Operand<TString> stringHandle, List<DataType<?>> outputTypes, Options... options) {
+  public static IteratorFromStringHandle create(Scope scope, Operand<TString> stringHandle, List<Class<? extends TType>> outputTypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("IteratorFromStringHandleV2", scope.makeOpName("IteratorFromStringHandle"));
     opBuilder.addInput(stringHandle.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.outputShapes != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNext.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNext.java
index 33c7d435baa..a41f441f650 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNext.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNext.java
@@ -20,12 +20,12 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -48,15 +48,11 @@ public final class IteratorGetNext extends RawOp implements Iterable<Operand<TTy
    * @return a new instance of IteratorGetNext
    */
   @Endpoint(describeByClass = true)
-  public static IteratorGetNext create(Scope scope, Operand<?> iterator, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static IteratorGetNext create(Scope scope, Operand<?> iterator, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("IteratorGetNext", scope.makeOpName("IteratorGetNext"));
     opBuilder.addInput(iterator.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextAsOptional.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextAsOptional.java
index 2ab688f371e..7d4f441eb83 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextAsOptional.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextAsOptional.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -46,15 +46,11 @@ public final class IteratorGetNextAsOptional extends RawOp implements Operand<TT
    * @return a new instance of IteratorGetNextAsOptional
    */
   @Endpoint(describeByClass = true)
-  public static IteratorGetNextAsOptional create(Scope scope, Operand<?> iterator, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static IteratorGetNextAsOptional create(Scope scope, Operand<?> iterator, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("IteratorGetNextAsOptional", scope.makeOpName("IteratorGetNextAsOptional"));
     opBuilder.addInput(iterator.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextSync.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextSync.java
index 4b7114fb0c7..bdce447dd0a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextSync.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/IteratorGetNextSync.java
@@ -20,12 +20,12 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -53,15 +53,11 @@ public final class IteratorGetNextSync extends RawOp implements Iterable<Operand
    * @return a new instance of IteratorGetNextSync
    */
   @Endpoint(describeByClass = true)
-  public static IteratorGetNextSync create(Scope scope, Operand<?> iterator, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static IteratorGetNextSync create(Scope scope, Operand<?> iterator, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("IteratorGetNextSync", scope.makeOpName("IteratorGetNextSync"));
     opBuilder.addInput(iterator.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LMDBDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LMDBDataset.java
index bca9d0b50cf..c67912ec018 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LMDBDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LMDBDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -58,15 +58,11 @@ public final class LMDBDataset extends RawOp implements Operand<TType> {
    * @return a new instance of LMDBDataset
    */
   @Endpoint(describeByClass = true)
-  public static LMDBDataset create(Scope scope, Operand<TString> filenames, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static LMDBDataset create(Scope scope, Operand<TString> filenames, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("LMDBDataset", scope.makeOpName("LMDBDataset"));
     opBuilder.addInput(filenames.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LatencyStatsDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LatencyStatsDataset.java
index e9a9425f891..047057a1c25 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LatencyStatsDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LatencyStatsDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,16 +47,12 @@ public final class LatencyStatsDataset extends RawOp implements Operand<TType> {
    * @return a new instance of LatencyStatsDataset
    */
   @Endpoint(describeByClass = true)
-  public static LatencyStatsDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> tag, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static LatencyStatsDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> tag, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("LatencyStatsDataset", scope.makeOpName("LatencyStatsDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(tag.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java
index 8ac38a713ea..3b41dd2e918 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes rectified linear gradients for a LeakyRelu operation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MaxIntraOpParallelismDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MaxIntraOpParallelismDataset.java
index 3f3b43038c2..14a35d14d07 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MaxIntraOpParallelismDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MaxIntraOpParallelismDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,16 +47,12 @@ public final class MaxIntraOpParallelismDataset extends RawOp implements Operand
    * @return a new instance of MaxIntraOpParallelismDataset
    */
   @Endpoint(describeByClass = true)
-  public static MaxIntraOpParallelismDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> maxIntraOpParallelism, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static MaxIntraOpParallelismDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> maxIntraOpParallelism, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("MaxIntraOpParallelismDataset", scope.makeOpName("MaxIntraOpParallelismDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(maxIntraOpParallelism.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ModelDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ModelDataset.java
index 9cb6913b9d6..f62be66854b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ModelDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ModelDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -76,15 +76,11 @@ private Options() {
    * @return a new instance of ModelDataset
    */
   @Endpoint(describeByClass = true)
-  public static ModelDataset create(Scope scope, Operand<?> inputDataset, List<DataType<?>> outputTypes, List<Shape> outputShapes, Options... options) {
+  public static ModelDataset create(Scope scope, Operand<?> inputDataset, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("ModelDataset", scope.makeOpName("ModelDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIterator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIterator.java
index 5db1b83475f..e6ee9d12c02 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIterator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIterator.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -49,7 +49,7 @@ public final class MultiDeviceIterator extends RawOp implements Operand<TType> {
    * @return a new instance of MultiDeviceIterator
    */
   @Endpoint(describeByClass = true)
-  public static MultiDeviceIterator create(Scope scope, List<String> devices, String sharedName, String container, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static MultiDeviceIterator create(Scope scope, List<String> devices, String sharedName, String container, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("MultiDeviceIterator", scope.makeOpName("MultiDeviceIterator"));
     opBuilder = scope.apply(opBuilder);
     String[] devicesArray = new String[devices.size()];
@@ -59,11 +59,7 @@ public static MultiDeviceIterator create(Scope scope, List<String> devices, Stri
     opBuilder.setAttr("devices", devicesArray);
     opBuilder.setAttr("shared_name", sharedName);
     opBuilder.setAttr("container", container);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorFromStringHandle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorFromStringHandle.java
index 3a4113e10b5..5e6fdb1c640 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorFromStringHandle.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorFromStringHandle.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -65,15 +65,11 @@ private Options() {
    * @return a new instance of MultiDeviceIteratorFromStringHandle
    */
   @Endpoint(describeByClass = true)
-  public static MultiDeviceIteratorFromStringHandle create(Scope scope, Operand<TString> stringHandle, List<DataType<?>> outputTypes, Options... options) {
+  public static MultiDeviceIteratorFromStringHandle create(Scope scope, Operand<TString> stringHandle, List<Class<? extends TType>> outputTypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("MultiDeviceIteratorFromStringHandle", scope.makeOpName("MultiDeviceIteratorFromStringHandle"));
     opBuilder.addInput(stringHandle.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.outputShapes != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorGetNextFromShard.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorGetNextFromShard.java
index c7313076e26..578bf00fe78 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorGetNextFromShard.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/MultiDeviceIteratorGetNextFromShard.java
@@ -20,12 +20,12 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -51,17 +51,13 @@ public final class MultiDeviceIteratorGetNextFromShard extends RawOp implements
    * @return a new instance of MultiDeviceIteratorGetNextFromShard
    */
   @Endpoint(describeByClass = true)
-  public static MultiDeviceIteratorGetNextFromShard create(Scope scope, Operand<?> multiDeviceIterator, Operand<TInt32> shardNum, Operand<TInt64> incarnationId, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static MultiDeviceIteratorGetNextFromShard create(Scope scope, Operand<?> multiDeviceIterator, Operand<TInt32> shardNum, Operand<TInt64> incarnationId, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("MultiDeviceIteratorGetNextFromShard", scope.makeOpName("MultiDeviceIteratorGetNextFromShard"));
     opBuilder.addInput(multiDeviceIterator.asOutput());
     opBuilder.addInput(shardNum.asOutput());
     opBuilder.addInput(incarnationId.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/NonSerializableDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/NonSerializableDataset.java
index c5b887812ef..49fece5850f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/NonSerializableDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/NonSerializableDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -44,15 +44,11 @@ public final class NonSerializableDataset extends RawOp implements Operand<TType
    * @return a new instance of NonSerializableDataset
    */
   @Endpoint(describeByClass = true)
-  public static NonSerializableDataset create(Scope scope, Operand<?> inputDataset, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static NonSerializableDataset create(Scope scope, Operand<?> inputDataset, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("NonSerializableDataset", scope.makeOpName("NonSerializableDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptimizeDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptimizeDataset.java
index d08521d3d54..c9bd55a0320 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptimizeDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptimizeDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -69,16 +69,12 @@ private Options() {
    * @return a new instance of OptimizeDataset
    */
   @Endpoint(describeByClass = true)
-  public static OptimizeDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> optimizations, List<DataType<?>> outputTypes, List<Shape> outputShapes, Options... options) {
+  public static OptimizeDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> optimizations, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("OptimizeDataset", scope.makeOpName("OptimizeDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(optimizations.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalGetValue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalGetValue.java
index 5218e9e64e7..eeaa8d61642 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalGetValue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionalGetValue.java
@@ -20,12 +20,12 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -48,15 +48,11 @@ public final class OptionalGetValue extends RawOp implements Iterable<Operand<TT
    * @return a new instance of OptionalGetValue
    */
   @Endpoint(describeByClass = true)
-  public static OptionalGetValue create(Scope scope, Operand<?> optional, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static OptionalGetValue create(Scope scope, Operand<?> optional, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("OptionalGetValue", scope.makeOpName("OptionalGetValue"));
     opBuilder.addInput(optional.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrefetchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrefetchDataset.java
index 65dcbf4806d..7e86b47bfe1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrefetchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrefetchDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -77,16 +77,12 @@ private Options() {
    * @return a new instance of PrefetchDataset
    */
   @Endpoint(describeByClass = true)
-  public static PrefetchDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> bufferSize, List<DataType<?>> outputTypes, List<Shape> outputShapes, Options... options) {
+  public static PrefetchDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> bufferSize, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("PrefetchDataset", scope.makeOpName("PrefetchDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(bufferSize.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrivateThreadPoolDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrivateThreadPoolDataset.java
index 63f8045f2e3..92d7753b54a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrivateThreadPoolDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/PrivateThreadPoolDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,16 +47,12 @@ public final class PrivateThreadPoolDataset extends RawOp implements Operand<TTy
    * @return a new instance of PrivateThreadPoolDataset
    */
   @Endpoint(describeByClass = true)
-  public static PrivateThreadPoolDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numThreads, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static PrivateThreadPoolDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numThreads, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("PrivateThreadPoolDataset", scope.makeOpName("PrivateThreadPoolDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(numThreads.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RandomDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RandomDataset.java
index 431e2244118..5108bec6d0d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RandomDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RandomDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -60,16 +60,12 @@ public final class RandomDataset extends RawOp implements Operand<TType> {
    * @return a new instance of RandomDataset
    */
   @Endpoint(describeByClass = true)
-  public static RandomDataset create(Scope scope, Operand<TInt64> seed, Operand<TInt64> seed2, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static RandomDataset create(Scope scope, Operand<TInt64> seed, Operand<TInt64> seed2, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("RandomDataset", scope.makeOpName("RandomDataset"));
     opBuilder.addInput(seed.asOutput());
     opBuilder.addInput(seed2.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RangeDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RangeDataset.java
index 8fdcdfad0e6..0acede3a72b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RangeDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RangeDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -49,17 +49,13 @@ public final class RangeDataset extends RawOp implements Operand<TType> {
    * @return a new instance of RangeDataset
    */
   @Endpoint(describeByClass = true)
-  public static RangeDataset create(Scope scope, Operand<TInt64> start, Operand<TInt64> stop, Operand<TInt64> step, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static RangeDataset create(Scope scope, Operand<TInt64> start, Operand<TInt64> stop, Operand<TInt64> step, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("RangeDataset", scope.makeOpName("RangeDataset"));
     opBuilder.addInput(start.asOutput());
     opBuilder.addInput(stop.asOutput());
     opBuilder.addInput(step.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RebatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RebatchDataset.java
index 050e765ecf6..4d73b0dbbcf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RebatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RebatchDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -72,16 +72,12 @@ private Options() {
    * @return a new instance of RebatchDataset
    */
   @Endpoint(describeByClass = true)
-  public static RebatchDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numReplicas, List<DataType<?>> outputTypes, List<Shape> outputShapes, Options... options) {
+  public static RebatchDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numReplicas, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("RebatchDataset", scope.makeOpName("RebatchDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(numReplicas.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RepeatDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RepeatDataset.java
index 33a598eb33c..ad327527c06 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RepeatDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/RepeatDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -49,16 +49,12 @@ public final class RepeatDataset extends RawOp implements Operand<TType> {
    * @return a new instance of RepeatDataset
    */
   @Endpoint(describeByClass = true)
-  public static RepeatDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> count, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static RepeatDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> count, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("RepeatDataset", scope.makeOpName("RepeatDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(count.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SamplingDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SamplingDataset.java
index ec75a203366..7f67f238136 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SamplingDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SamplingDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -57,18 +57,14 @@ public final class SamplingDataset extends RawOp implements Operand<TType> {
    * @return a new instance of SamplingDataset
    */
   @Endpoint(describeByClass = true)
-  public static SamplingDataset create(Scope scope, Operand<?> inputDataset, Operand<TFloat32> rate, Operand<TInt64> seed, Operand<TInt64> seed2, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static SamplingDataset create(Scope scope, Operand<?> inputDataset, Operand<TFloat32> rate, Operand<TInt64> seed, Operand<TInt64> seed2, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("SamplingDataset", scope.makeOpName("SamplingDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(rate.asOutput());
     opBuilder.addInput(seed.asOutput());
     opBuilder.addInput(seed2.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SetStatsAggregatorDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SetStatsAggregatorDataset.java
index 247856790af..7e774e3a103 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SetStatsAggregatorDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SetStatsAggregatorDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -48,18 +48,14 @@ public final class SetStatsAggregatorDataset extends RawOp implements Operand<TT
    * @return a new instance of SetStatsAggregatorDataset
    */
   @Endpoint(describeByClass = true)
-  public static SetStatsAggregatorDataset create(Scope scope, Operand<?> inputDataset, Operand<?> statsAggregator, Operand<TString> tag, Operand<TString> counterPrefix, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static SetStatsAggregatorDataset create(Scope scope, Operand<?> inputDataset, Operand<?> statsAggregator, Operand<TString> tag, Operand<TString> counterPrefix, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("SetStatsAggregatorDataset", scope.makeOpName("SetStatsAggregatorDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(statsAggregator.asOutput());
     opBuilder.addInput(tag.asOutput());
     opBuilder.addInput(counterPrefix.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShardDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShardDataset.java
index 1255fe5e4b4..53b184949e7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShardDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShardDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -68,17 +68,13 @@ private Options() {
    * @return a new instance of ShardDataset
    */
   @Endpoint(describeByClass = true)
-  public static ShardDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numShards, Operand<TInt64> index, List<DataType<?>> outputTypes, List<Shape> outputShapes, Options... options) {
+  public static ShardDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numShards, Operand<TInt64> index, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("ShardDataset", scope.makeOpName("ShardDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(numShards.asOutput());
     opBuilder.addInput(index.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleAndRepeatDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleAndRepeatDataset.java
index 063b9d7352a..bc486a3777c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleAndRepeatDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleAndRepeatDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -70,7 +70,7 @@ private Options() {
    * @return a new instance of ShuffleAndRepeatDataset
    */
   @Endpoint(describeByClass = true)
-  public static ShuffleAndRepeatDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> bufferSize, Operand<TInt64> seed, Operand<TInt64> seed2, Operand<TInt64> count, Operand<?> seedGenerator, List<DataType<?>> outputTypes, List<Shape> outputShapes, Options... options) {
+  public static ShuffleAndRepeatDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> bufferSize, Operand<TInt64> seed, Operand<TInt64> seed2, Operand<TInt64> count, Operand<?> seedGenerator, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("ShuffleAndRepeatDatasetV2", scope.makeOpName("ShuffleAndRepeatDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(bufferSize.asOutput());
@@ -79,11 +79,7 @@ public static ShuffleAndRepeatDataset create(Scope scope, Operand<?> inputDatase
     opBuilder.addInput(count.asOutput());
     opBuilder.addInput(seedGenerator.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleDataset.java
index 27e4982773f..d458c12b68c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ShuffleDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -69,7 +69,7 @@ private Options() {
    * @return a new instance of ShuffleDataset
    */
   @Endpoint(describeByClass = true)
-  public static ShuffleDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> bufferSize, Operand<TInt64> seed, Operand<TInt64> seed2, Operand<?> seedGenerator, List<DataType<?>> outputTypes, List<Shape> outputShapes, Options... options) {
+  public static ShuffleDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> bufferSize, Operand<TInt64> seed, Operand<TInt64> seed2, Operand<?> seedGenerator, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("ShuffleDatasetV3", scope.makeOpName("ShuffleDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(bufferSize.asOutput());
@@ -77,11 +77,7 @@ public static ShuffleDataset create(Scope scope, Operand<?> inputDataset, Operan
     opBuilder.addInput(seed2.asOutput());
     opBuilder.addInput(seedGenerator.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SkipDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SkipDataset.java
index b4f77efda63..dea92ac046b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SkipDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SkipDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -49,16 +49,12 @@ public final class SkipDataset extends RawOp implements Operand<TType> {
    * @return a new instance of SkipDataset
    */
   @Endpoint(describeByClass = true)
-  public static SkipDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> count, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static SkipDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> count, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("SkipDataset", scope.makeOpName("SkipDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(count.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SleepDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SleepDataset.java
index 4d338ac51b6..926cc93fe89 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SleepDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SleepDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -46,16 +46,12 @@ public final class SleepDataset extends RawOp implements Operand<TType> {
    * @return a new instance of SleepDataset
    */
   @Endpoint(describeByClass = true)
-  public static SleepDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> sleepMicroseconds, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static SleepDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> sleepMicroseconds, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("SleepDataset", scope.makeOpName("SleepDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(sleepMicroseconds.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SlidingWindowDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SlidingWindowDataset.java
index 2ce91cfa3ec..2c10ea43cd9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SlidingWindowDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SlidingWindowDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -52,18 +52,14 @@ public final class SlidingWindowDataset extends RawOp implements Operand<TType>
    * @return a new instance of SlidingWindowDataset
    */
   @Endpoint(describeByClass = true)
-  public static SlidingWindowDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> windowSize, Operand<TInt64> windowShift, Operand<TInt64> windowStride, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static SlidingWindowDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> windowSize, Operand<TInt64> windowShift, Operand<TInt64> windowStride, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("SlidingWindowDataset", scope.makeOpName("SlidingWindowDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(windowSize.asOutput());
     opBuilder.addInput(windowShift.asOutput());
     opBuilder.addInput(windowStride.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotDataset.java
deleted file mode 100644
index dd9afe060dc..00000000000
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SnapshotDataset.java
+++ /dev/null
@@ -1,375 +0,0 @@
-/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-=======================================================================*/
-
-// This class has been generated, DO NOT EDIT!
-
-package org.tensorflow.op.data;
-
-import java.util.List;
-import org.tensorflow.DataType;
-import org.tensorflow.Operand;
-import org.tensorflow.Operation;
-import org.tensorflow.OperationBuilder;
-import org.tensorflow.Output;
-import org.tensorflow.ndarray.Shape;
-import org.tensorflow.op.RawOp;
-import org.tensorflow.op.Scope;
-import org.tensorflow.op.annotation.Endpoint;
-import org.tensorflow.types.TString;
-import org.tensorflow.types.family.TType;
-
-/**
- * Creates a dataset that will write to / read from a snapshot.
- * <p>
- * This dataset attempts to determine whether a valid snapshot exists at the
- * `snapshot_path`, and reads from the snapshot in lieu of using `input_dataset`.
- * If not, it will run the preprocessing pipeline as usual, and write out a
- * snapshot of the data processed for future use.
- */
-public final class SnapshotDataset extends RawOp implements Operand<TType> {
-  
-  /**
-   * Optional attributes for {@link org.tensorflow.op.data.SnapshotDataset}
-   */
-  public static class Options {
-    
-    /**
-     * @param compression 
-     */
-    public Options compression(String compression) {
-      this.compression = compression;
-      return this;
-    }
-    
-    /**
-     * @param readerPathPrefix 
-     */
-    public Options readerPathPrefix(String readerPathPrefix) {
-      this.readerPathPrefix = readerPathPrefix;
-      return this;
-    }
-    
-    /**
-     * @param writerPathPrefix 
-     */
-    public Options writerPathPrefix(String writerPathPrefix) {
-      this.writerPathPrefix = writerPathPrefix;
-      return this;
-    }
-    
-    /**
-     * @param shardSizeBytes 
-     */
-    public Options shardSizeBytes(Long shardSizeBytes) {
-      this.shardSizeBytes = shardSizeBytes;
-      return this;
-    }
-    
-    /**
-     * @param pendingSnapshotExpirySeconds 
-     */
-    public Options pendingSnapshotExpirySeconds(Long pendingSnapshotExpirySeconds) {
-      this.pendingSnapshotExpirySeconds = pendingSnapshotExpirySeconds;
-      return this;
-    }
-    
-    /**
-     * @param numReaderThreads 
-     */
-    public Options numReaderThreads(Long numReaderThreads) {
-      this.numReaderThreads = numReaderThreads;
-      return this;
-    }
-    
-    /**
-     * @param readerBufferSize 
-     */
-    public Options readerBufferSize(Long readerBufferSize) {
-      this.readerBufferSize = readerBufferSize;
-      return this;
-    }
-    
-    /**
-     * @param numWriterThreads 
-     */
-    public Options numWriterThreads(Long numWriterThreads) {
-      this.numWriterThreads = numWriterThreads;
-      return this;
-    }
-    
-    /**
-     * @param writerBufferSize 
-     */
-    public Options writerBufferSize(Long writerBufferSize) {
-      this.writerBufferSize = writerBufferSize;
-      return this;
-    }
-    
-    /**
-     * @param shuffleOnRead 
-     */
-    public Options shuffleOnRead(Boolean shuffleOnRead) {
-      this.shuffleOnRead = shuffleOnRead;
-      return this;
-    }
-    
-    /**
-     * @param seed 
-     */
-    public Options seed(Long seed) {
-      this.seed = seed;
-      return this;
-    }
-    
-    /**
-     * @param seed2 
-     */
-    public Options seed2(Long seed2) {
-      this.seed2 = seed2;
-      return this;
-    }
-    
-    /**
-     * @param mode 
-     */
-    public Options mode(String mode) {
-      this.mode = mode;
-      return this;
-    }
-    
-    /**
-     * @param snapshotName 
-     */
-    public Options snapshotName(String snapshotName) {
-      this.snapshotName = snapshotName;
-      return this;
-    }
-    
-    private String compression;
-    private String readerPathPrefix;
-    private String writerPathPrefix;
-    private Long shardSizeBytes;
-    private Long pendingSnapshotExpirySeconds;
-    private Long numReaderThreads;
-    private Long readerBufferSize;
-    private Long numWriterThreads;
-    private Long writerBufferSize;
-    private Boolean shuffleOnRead;
-    private Long seed;
-    private Long seed2;
-    private String mode;
-    private String snapshotName;
-    
-    private Options() {
-    }
-  }
-  
-  /**
-   * Factory method to create a class wrapping a new SnapshotDataset operation.
-   * 
-   * @param scope current scope
-   * @param inputDataset A variant tensor representing the input dataset.
-   * @param path The path we should write snapshots to / read snapshots from.
-   * @param outputTypes 
-   * @param outputShapes 
-   * @param options carries optional attributes values
-   * @return a new instance of SnapshotDataset
-   */
-  @Endpoint(describeByClass = true)
-  public static SnapshotDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> path, List<DataType<?>> outputTypes, List<Shape> outputShapes, Options... options) {
-    OperationBuilder opBuilder = scope.env().opBuilder("SnapshotDataset", scope.makeOpName("SnapshotDataset"));
-    opBuilder.addInput(inputDataset.asOutput());
-    opBuilder.addInput(path.asOutput());
-    opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
-    Shape[] outputShapesArray = new Shape[outputShapes.size()];
-    for (int i = 0; i < outputShapesArray.length; ++i) {
-      outputShapesArray[i] = outputShapes.get(i);
-    }
-    opBuilder.setAttr("output_shapes", outputShapesArray);
-    if (options != null) {
-      for (Options opts : options) {
-        if (opts.compression != null) {
-          opBuilder.setAttr("compression", opts.compression);
-        }
-        if (opts.readerPathPrefix != null) {
-          opBuilder.setAttr("reader_path_prefix", opts.readerPathPrefix);
-        }
-        if (opts.writerPathPrefix != null) {
-          opBuilder.setAttr("writer_path_prefix", opts.writerPathPrefix);
-        }
-        if (opts.shardSizeBytes != null) {
-          opBuilder.setAttr("shard_size_bytes", opts.shardSizeBytes);
-        }
-        if (opts.pendingSnapshotExpirySeconds != null) {
-          opBuilder.setAttr("pending_snapshot_expiry_seconds", opts.pendingSnapshotExpirySeconds);
-        }
-        if (opts.numReaderThreads != null) {
-          opBuilder.setAttr("num_reader_threads", opts.numReaderThreads);
-        }
-        if (opts.readerBufferSize != null) {
-          opBuilder.setAttr("reader_buffer_size", opts.readerBufferSize);
-        }
-        if (opts.numWriterThreads != null) {
-          opBuilder.setAttr("num_writer_threads", opts.numWriterThreads);
-        }
-        if (opts.writerBufferSize != null) {
-          opBuilder.setAttr("writer_buffer_size", opts.writerBufferSize);
-        }
-        if (opts.shuffleOnRead != null) {
-          opBuilder.setAttr("shuffle_on_read", opts.shuffleOnRead);
-        }
-        if (opts.seed != null) {
-          opBuilder.setAttr("seed", opts.seed);
-        }
-        if (opts.seed2 != null) {
-          opBuilder.setAttr("seed2", opts.seed2);
-        }
-        if (opts.mode != null) {
-          opBuilder.setAttr("mode", opts.mode);
-        }
-        if (opts.snapshotName != null) {
-          opBuilder.setAttr("snapshot_name", opts.snapshotName);
-        }
-      }
-    }
-    return new SnapshotDataset(opBuilder.build());
-  }
-  
-  /**
-   * @param compression 
-   */
-  public static Options compression(String compression) {
-    return new Options().compression(compression);
-  }
-  
-  /**
-   * @param readerPathPrefix 
-   */
-  public static Options readerPathPrefix(String readerPathPrefix) {
-    return new Options().readerPathPrefix(readerPathPrefix);
-  }
-  
-  /**
-   * @param writerPathPrefix 
-   */
-  public static Options writerPathPrefix(String writerPathPrefix) {
-    return new Options().writerPathPrefix(writerPathPrefix);
-  }
-  
-  /**
-   * @param shardSizeBytes 
-   */
-  public static Options shardSizeBytes(Long shardSizeBytes) {
-    return new Options().shardSizeBytes(shardSizeBytes);
-  }
-  
-  /**
-   * @param pendingSnapshotExpirySeconds 
-   */
-  public static Options pendingSnapshotExpirySeconds(Long pendingSnapshotExpirySeconds) {
-    return new Options().pendingSnapshotExpirySeconds(pendingSnapshotExpirySeconds);
-  }
-  
-  /**
-   * @param numReaderThreads 
-   */
-  public static Options numReaderThreads(Long numReaderThreads) {
-    return new Options().numReaderThreads(numReaderThreads);
-  }
-  
-  /**
-   * @param readerBufferSize 
-   */
-  public static Options readerBufferSize(Long readerBufferSize) {
-    return new Options().readerBufferSize(readerBufferSize);
-  }
-  
-  /**
-   * @param numWriterThreads 
-   */
-  public static Options numWriterThreads(Long numWriterThreads) {
-    return new Options().numWriterThreads(numWriterThreads);
-  }
-  
-  /**
-   * @param writerBufferSize 
-   */
-  public static Options writerBufferSize(Long writerBufferSize) {
-    return new Options().writerBufferSize(writerBufferSize);
-  }
-  
-  /**
-   * @param shuffleOnRead 
-   */
-  public static Options shuffleOnRead(Boolean shuffleOnRead) {
-    return new Options().shuffleOnRead(shuffleOnRead);
-  }
-  
-  /**
-   * @param seed 
-   */
-  public static Options seed(Long seed) {
-    return new Options().seed(seed);
-  }
-  
-  /**
-   * @param seed2 
-   */
-  public static Options seed2(Long seed2) {
-    return new Options().seed2(seed2);
-  }
-  
-  /**
-   * @param mode 
-   */
-  public static Options mode(String mode) {
-    return new Options().mode(mode);
-  }
-  
-  /**
-   * @param snapshotName 
-   */
-  public static Options snapshotName(String snapshotName) {
-    return new Options().snapshotName(snapshotName);
-  }
-  
-  /**
-   */
-  public Output<?> handle() {
-    return handle;
-  }
-  
-  @Override
-  @SuppressWarnings("unchecked")
-  public Output<TType> asOutput() {
-    return (Output<TType>) handle;
-  }
-  
-  /** The name of this op, as known by TensorFlow core engine */
-  public static final String OP_NAME = "SnapshotDataset";
-  
-  private Output<?> handle;
-  
-  private SnapshotDataset(Operation operation) {
-    super(operation);
-    int outputIdx = 0;
-    handle = operation.output(outputIdx++);
-  }
-}
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SqlDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SqlDataset.java
index 5fa54ddc199..e22c4f13bb1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SqlDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/SqlDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -48,17 +48,13 @@ public final class SqlDataset extends RawOp implements Operand<TType> {
    * @return a new instance of SqlDataset
    */
   @Endpoint(describeByClass = true)
-  public static SqlDataset create(Scope scope, Operand<TString> driverName, Operand<TString> dataSourceName, Operand<TString> query, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static SqlDataset create(Scope scope, Operand<TString> driverName, Operand<TString> dataSourceName, Operand<TString> query, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("SqlDataset", scope.makeOpName("SqlDataset"));
     opBuilder.addInput(driverName.asOutput());
     opBuilder.addInput(dataSourceName.asOutput());
     opBuilder.addInput(query.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TakeDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TakeDataset.java
index ea531147a0e..61d3ebc7916 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TakeDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/TakeDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -50,16 +50,12 @@ public final class TakeDataset extends RawOp implements Operand<TType> {
    * @return a new instance of TakeDataset
    */
   @Endpoint(describeByClass = true)
-  public static TakeDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> count, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static TakeDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> count, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("TakeDataset", scope.makeOpName("TakeDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(count.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ThreadPoolDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ThreadPoolDataset.java
index 1c8886b81f5..fe1f7d9f859 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ThreadPoolDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ThreadPoolDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -46,16 +46,12 @@ public final class ThreadPoolDataset extends RawOp implements Operand<TType> {
    * @return a new instance of ThreadPoolDataset
    */
   @Endpoint(describeByClass = true)
-  public static ThreadPoolDataset create(Scope scope, Operand<?> inputDataset, Operand<?> threadPool, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static ThreadPoolDataset create(Scope scope, Operand<?> inputDataset, Operand<?> threadPool, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ThreadPoolDataset", scope.makeOpName("ThreadPoolDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(threadPool.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UnbatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UnbatchDataset.java
index e573884c4c4..1e8cc5cd305 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UnbatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UnbatchDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -45,15 +45,11 @@ public final class UnbatchDataset extends RawOp implements Operand<TType> {
    * @return a new instance of UnbatchDataset
    */
   @Endpoint(describeByClass = true)
-  public static UnbatchDataset create(Scope scope, Operand<?> inputDataset, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static UnbatchDataset create(Scope scope, Operand<?> inputDataset, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("UnbatchDataset", scope.makeOpName("UnbatchDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UniqueDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UniqueDataset.java
index 375a80da417..6bd918a3db0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UniqueDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/UniqueDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -45,15 +45,11 @@ public final class UniqueDataset extends RawOp implements Operand<TType> {
    * @return a new instance of UniqueDataset
    */
   @Endpoint(describeByClass = true)
-  public static UniqueDataset create(Scope scope, Operand<?> inputDataset, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static UniqueDataset create(Scope scope, Operand<?> inputDataset, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("UniqueDataset", scope.makeOpName("UniqueDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WindowDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WindowDataset.java
index 89ada3cfb40..a44807564c1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WindowDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/WindowDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -98,7 +98,7 @@ public final class WindowDataset extends RawOp implements Operand<TType> {
    * @return a new instance of WindowDataset
    */
   @Endpoint(describeByClass = true)
-  public static WindowDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> size, Operand<TInt64> shift, Operand<TInt64> stride, Operand<TBool> dropRemainder, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static WindowDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> size, Operand<TInt64> shift, Operand<TInt64> stride, Operand<TBool> dropRemainder, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("WindowDataset", scope.makeOpName("WindowDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(size.asOutput());
@@ -106,11 +106,7 @@ public static WindowDataset create(Scope scope, Operand<?> inputDataset, Operand
     opBuilder.addInput(stride.asOutput());
     opBuilder.addInput(dropRemainder.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ZipDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ZipDataset.java
index 133ef39430c..47dd0be0775 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ZipDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ZipDataset.java
@@ -18,7 +18,6 @@
 package org.tensorflow.op.data;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -53,15 +52,11 @@ public final class ZipDataset extends RawOp implements Operand<TType> {
    * @return a new instance of ZipDataset
    */
   @Endpoint(describeByClass = true)
-  public static ZipDataset create(Scope scope, Iterable<Operand<?>> inputDatasets, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static ZipDataset create(Scope scope, Iterable<Operand<?>> inputDatasets, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ZipDataset", scope.makeOpName("ZipDataset"));
     opBuilder.addInputList(Operands.asOutputs(inputDatasets));
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertCardinalityDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertCardinalityDataset.java
index 09ade444b05..8ab5989b44b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertCardinalityDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertCardinalityDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -46,16 +46,12 @@ public final class AssertCardinalityDataset extends RawOp implements Operand<TTy
    * @return a new instance of AssertCardinalityDataset
    */
   @Endpoint(describeByClass = true)
-  public static AssertCardinalityDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> cardinality, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static AssertCardinalityDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> cardinality, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("AssertCardinalityDataset", scope.makeOpName("AssertCardinalityDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(cardinality.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertNextDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertNextDataset.java
index ac3227bda10..2483e971723 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertNextDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AssertNextDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -46,16 +46,12 @@ public final class AssertNextDataset extends RawOp implements Operand<TType> {
    * @return a new instance of AssertNextDataset
    */
   @Endpoint(describeByClass = true)
-  public static AssertNextDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> transformations, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static AssertNextDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> transformations, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalAssertNextDataset", scope.makeOpName("AssertNextDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(transformations.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AutoShardDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AutoShardDataset.java
index 556b7acd89a..fc630d53919 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AutoShardDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/AutoShardDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -76,17 +76,13 @@ private Options() {
    * @return a new instance of AutoShardDataset
    */
   @Endpoint(describeByClass = true)
-  public static AutoShardDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numWorkers, Operand<TInt64> index, List<DataType<?>> outputTypes, List<Shape> outputShapes, Options... options) {
+  public static AutoShardDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numWorkers, Operand<TInt64> index, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalAutoShardDataset", scope.makeOpName("AutoShardDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(numWorkers.asOutput());
     opBuilder.addInput(index.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/BytesProducedStatsDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/BytesProducedStatsDataset.java
index ca545d5e89b..76a5a96f895 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/BytesProducedStatsDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/BytesProducedStatsDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,16 +47,12 @@ public final class BytesProducedStatsDataset extends RawOp implements Operand<TT
    * @return a new instance of BytesProducedStatsDataset
    */
   @Endpoint(describeByClass = true)
-  public static BytesProducedStatsDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> tag, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static BytesProducedStatsDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> tag, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalBytesProducedStatsDataset", scope.makeOpName("BytesProducedStatsDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(tag.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ChooseFastestDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ChooseFastestDataset.java
index b3551d4f38d..b735a535c48 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ChooseFastestDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ChooseFastestDataset.java
@@ -18,7 +18,6 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -46,16 +45,12 @@ public final class ChooseFastestDataset extends RawOp implements Operand<TType>
    * @return a new instance of ChooseFastestDataset
    */
   @Endpoint(describeByClass = true)
-  public static ChooseFastestDataset create(Scope scope, Iterable<Operand<?>> inputDatasets, Long numExperiments, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static ChooseFastestDataset create(Scope scope, Iterable<Operand<?>> inputDatasets, Long numExperiments, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalChooseFastestDataset", scope.makeOpName("ChooseFastestDataset"));
     opBuilder.addInputList(Operands.asOutputs(inputDatasets));
     opBuilder = scope.apply(opBuilder);
     opBuilder.setAttr("num_experiments", numExperiments);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DataServiceDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DataServiceDataset.java
index 56037ab9963..6307dddf9dc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DataServiceDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DataServiceDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -73,7 +73,7 @@ private Options() {
    * @return a new instance of DataServiceDataset
    */
   @Endpoint(describeByClass = true)
-  public static DataServiceDataset create(Scope scope, Operand<TInt64> datasetId, Operand<TString> processingMode, Operand<TString> address, Operand<TString> protocol, Operand<TString> jobName, Operand<TInt64> maxOutstandingRequests, Operand<?> iterationCounter, List<DataType<?>> outputTypes, List<Shape> outputShapes, Options... options) {
+  public static DataServiceDataset create(Scope scope, Operand<TInt64> datasetId, Operand<TString> processingMode, Operand<TString> address, Operand<TString> protocol, Operand<TString> jobName, Operand<TInt64> maxOutstandingRequests, Operand<?> iterationCounter, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("DataServiceDataset", scope.makeOpName("DataServiceDataset"));
     opBuilder.addInput(datasetId.asOutput());
     opBuilder.addInput(processingMode.asOutput());
@@ -83,11 +83,7 @@ public static DataServiceDataset create(Scope scope, Operand<TInt64> datasetId,
     opBuilder.addInput(maxOutstandingRequests.asOutput());
     opBuilder.addInput(iterationCounter.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DenseToSparseBatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DenseToSparseBatchDataset.java
index 1edc739575f..fd19c2fc45c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DenseToSparseBatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DenseToSparseBatchDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -51,17 +51,13 @@ public final class DenseToSparseBatchDataset extends RawOp implements Operand<TT
    * @return a new instance of DenseToSparseBatchDataset
    */
   @Endpoint(describeByClass = true)
-  public static DenseToSparseBatchDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> batchSize, Operand<TInt64> rowShape, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static DenseToSparseBatchDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> batchSize, Operand<TInt64> rowShape, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalDenseToSparseBatchDataset", scope.makeOpName("DenseToSparseBatchDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(batchSize.asOutput());
     opBuilder.addInput(rowShape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DirectedInterleaveDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DirectedInterleaveDataset.java
index 076f7220fc0..c1bdefa37dc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DirectedInterleaveDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/DirectedInterleaveDataset.java
@@ -18,7 +18,6 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -49,16 +48,12 @@ public final class DirectedInterleaveDataset extends RawOp implements Operand<TT
    * @return a new instance of DirectedInterleaveDataset
    */
   @Endpoint(describeByClass = true)
-  public static DirectedInterleaveDataset create(Scope scope, Operand<?> selectorInputDataset, Iterable<Operand<?>> dataInputDatasets, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static DirectedInterleaveDataset create(Scope scope, Operand<?> selectorInputDataset, Iterable<Operand<?>> dataInputDatasets, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalDirectedInterleaveDataset", scope.makeOpName("DirectedInterleaveDataset"));
     opBuilder.addInput(selectorInputDataset.asOutput());
     opBuilder.addInputList(Operands.asOutputs(dataInputDatasets));
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/IgnoreErrorsDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/IgnoreErrorsDataset.java
index 8390d3d672f..419baa98adf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/IgnoreErrorsDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/IgnoreErrorsDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -45,15 +45,11 @@ public final class IgnoreErrorsDataset extends RawOp implements Operand<TType> {
    * @return a new instance of IgnoreErrorsDataset
    */
   @Endpoint(describeByClass = true)
-  public static IgnoreErrorsDataset create(Scope scope, Operand<?> inputDataset, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static IgnoreErrorsDataset create(Scope scope, Operand<?> inputDataset, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalIgnoreErrorsDataset", scope.makeOpName("IgnoreErrorsDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LatencyStatsDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LatencyStatsDataset.java
index f20c55f6c82..1c333d77ac5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LatencyStatsDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LatencyStatsDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,16 +47,12 @@ public final class LatencyStatsDataset extends RawOp implements Operand<TType> {
    * @return a new instance of LatencyStatsDataset
    */
   @Endpoint(describeByClass = true)
-  public static LatencyStatsDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> tag, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static LatencyStatsDataset create(Scope scope, Operand<?> inputDataset, Operand<TString> tag, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalLatencyStatsDataset", scope.makeOpName("LatencyStatsDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(tag.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LmdbDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LmdbDataset.java
index 339154d5c31..4cdb41cc8e3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LmdbDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/LmdbDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -45,15 +45,11 @@ public final class LmdbDataset extends RawOp implements Operand<TType> {
    * @return a new instance of LmdbDataset
    */
   @Endpoint(describeByClass = true)
-  public static LmdbDataset create(Scope scope, Operand<TString> filenames, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static LmdbDataset create(Scope scope, Operand<TString> filenames, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalLMDBDataset", scope.makeOpName("LmdbDataset"));
     opBuilder.addInput(filenames.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MaxIntraOpParallelismDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MaxIntraOpParallelismDataset.java
index cb22b4e910d..37d6f3915cc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MaxIntraOpParallelismDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/MaxIntraOpParallelismDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,16 +47,12 @@ public final class MaxIntraOpParallelismDataset extends RawOp implements Operand
    * @return a new instance of MaxIntraOpParallelismDataset
    */
   @Endpoint(describeByClass = true)
-  public static MaxIntraOpParallelismDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> maxIntraOpParallelism, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static MaxIntraOpParallelismDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> maxIntraOpParallelism, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalMaxIntraOpParallelismDataset", scope.makeOpName("MaxIntraOpParallelismDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(maxIntraOpParallelism.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/NonSerializableDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/NonSerializableDataset.java
index 06543121f3a..ef096a1b19f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/NonSerializableDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/NonSerializableDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -44,15 +44,11 @@ public final class NonSerializableDataset extends RawOp implements Operand<TType
    * @return a new instance of NonSerializableDataset
    */
   @Endpoint(describeByClass = true)
-  public static NonSerializableDataset create(Scope scope, Operand<?> inputDataset, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static NonSerializableDataset create(Scope scope, Operand<?> inputDataset, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalNonSerializableDataset", scope.makeOpName("NonSerializableDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParseExampleDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParseExampleDataset.java
index c1465ff7082..eb9aceba455 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParseExampleDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParseExampleDataset.java
@@ -18,7 +18,6 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -102,7 +101,7 @@ private Options() {
    * @return a new instance of ParseExampleDataset
    */
   @Endpoint(describeByClass = true)
-  public static ParseExampleDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numParallelCalls, Iterable<Operand<?>> denseDefaults, List<String> sparseKeys, List<String> denseKeys, List<DataType<?>> sparseTypes, List<Shape> denseShapes, List<DataType<?>> outputTypes, List<Shape> outputShapes, List<DataType<?>> raggedValueTypes, List<DataType<?>> raggedSplitTypes, Options... options) {
+  public static ParseExampleDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numParallelCalls, Iterable<Operand<?>> denseDefaults, List<String> sparseKeys, List<String> denseKeys, List<Class<? extends TType>> sparseTypes, List<Shape> denseShapes, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes, List<Class<? extends TType>> raggedValueTypes, List<Class<? extends TNumber>> raggedSplitTypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("ParseExampleDatasetV2", scope.makeOpName("ParseExampleDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(numParallelCalls.asOutput());
@@ -118,36 +117,20 @@ public static ParseExampleDataset create(Scope scope, Operand<?> inputDataset, O
       denseKeysArray[i] = denseKeys.get(i);
     }
     opBuilder.setAttr("dense_keys", denseKeysArray);
-    DataType[] sparseTypesArray = new DataType[sparseTypes.size()];
-    for (int i = 0; i < sparseTypesArray.length; ++i) {
-      sparseTypesArray[i] = sparseTypes.get(i);
-    }
-    opBuilder.setAttr("sparse_types", sparseTypesArray);
+    opBuilder.setAttr("sparse_types", Operands.toDataTypes(sparseTypes));
     Shape[] denseShapesArray = new Shape[denseShapes.size()];
     for (int i = 0; i < denseShapesArray.length; ++i) {
       denseShapesArray[i] = denseShapes.get(i);
     }
     opBuilder.setAttr("dense_shapes", denseShapesArray);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
     }
     opBuilder.setAttr("output_shapes", outputShapesArray);
-    DataType[] raggedValueTypesArray = new DataType[raggedValueTypes.size()];
-    for (int i = 0; i < raggedValueTypesArray.length; ++i) {
-      raggedValueTypesArray[i] = raggedValueTypes.get(i);
-    }
-    opBuilder.setAttr("ragged_value_types", raggedValueTypesArray);
-    DataType[] raggedSplitTypesArray = new DataType[raggedSplitTypes.size()];
-    for (int i = 0; i < raggedSplitTypesArray.length; ++i) {
-      raggedSplitTypesArray[i] = raggedSplitTypes.get(i);
-    }
-    opBuilder.setAttr("ragged_split_types", raggedSplitTypesArray);
+    opBuilder.setAttr("ragged_value_types", Operands.toDataTypes(raggedValueTypes));
+    opBuilder.setAttr("ragged_split_types", Operands.toDataTypes(raggedSplitTypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.deterministic != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/PrivateThreadPoolDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/PrivateThreadPoolDataset.java
index d987b21f0bd..bc0a4750675 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/PrivateThreadPoolDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/PrivateThreadPoolDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,16 +47,12 @@ public final class PrivateThreadPoolDataset extends RawOp implements Operand<TTy
    * @return a new instance of PrivateThreadPoolDataset
    */
   @Endpoint(describeByClass = true)
-  public static PrivateThreadPoolDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numThreads, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static PrivateThreadPoolDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numThreads, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalPrivateThreadPoolDataset", scope.makeOpName("PrivateThreadPoolDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(numThreads.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RandomDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RandomDataset.java
index 239e8531c03..435d331f68e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RandomDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RandomDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -49,16 +49,12 @@ public final class RandomDataset extends RawOp implements Operand<TType> {
    * @return a new instance of RandomDataset
    */
   @Endpoint(describeByClass = true)
-  public static RandomDataset create(Scope scope, Operand<TInt64> seed, Operand<TInt64> seed2, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static RandomDataset create(Scope scope, Operand<TInt64> seed, Operand<TInt64> seed2, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalRandomDataset", scope.makeOpName("RandomDataset"));
     opBuilder.addInput(seed.asOutput());
     opBuilder.addInput(seed2.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RebatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RebatchDataset.java
index d970139989a..219f9bd44b4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RebatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/RebatchDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -72,16 +72,12 @@ private Options() {
    * @return a new instance of RebatchDataset
    */
   @Endpoint(describeByClass = true)
-  public static RebatchDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numReplicas, List<DataType<?>> outputTypes, List<Shape> outputShapes, Options... options) {
+  public static RebatchDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> numReplicas, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalRebatchDataset", scope.makeOpName("RebatchDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(numReplicas.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SetStatsAggregatorDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SetStatsAggregatorDataset.java
index 66e9be0e7e9..b87aa6597ea 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SetStatsAggregatorDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SetStatsAggregatorDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -48,18 +48,14 @@ public final class SetStatsAggregatorDataset extends RawOp implements Operand<TT
    * @return a new instance of SetStatsAggregatorDataset
    */
   @Endpoint(describeByClass = true)
-  public static SetStatsAggregatorDataset create(Scope scope, Operand<?> inputDataset, Operand<?> statsAggregator, Operand<TString> tag, Operand<TString> counterPrefix, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static SetStatsAggregatorDataset create(Scope scope, Operand<?> inputDataset, Operand<?> statsAggregator, Operand<TString> tag, Operand<TString> counterPrefix, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalSetStatsAggregatorDataset", scope.makeOpName("SetStatsAggregatorDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(statsAggregator.asOutput());
     opBuilder.addInput(tag.asOutput());
     opBuilder.addInput(counterPrefix.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SleepDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SleepDataset.java
index 8377ac20bdf..4fac4cfc637 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SleepDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SleepDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -46,16 +46,12 @@ public final class SleepDataset extends RawOp implements Operand<TType> {
    * @return a new instance of SleepDataset
    */
   @Endpoint(describeByClass = true)
-  public static SleepDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> sleepMicroseconds, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static SleepDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> sleepMicroseconds, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalSleepDataset", scope.makeOpName("SleepDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(sleepMicroseconds.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SlidingWindowDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SlidingWindowDataset.java
index a68f34c069d..85dde0defb6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SlidingWindowDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SlidingWindowDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -52,18 +52,14 @@ public final class SlidingWindowDataset extends RawOp implements Operand<TType>
    * @return a new instance of SlidingWindowDataset
    */
   @Endpoint(describeByClass = true)
-  public static SlidingWindowDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> windowSize, Operand<TInt64> windowShift, Operand<TInt64> windowStride, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static SlidingWindowDataset create(Scope scope, Operand<?> inputDataset, Operand<TInt64> windowSize, Operand<TInt64> windowShift, Operand<TInt64> windowStride, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalSlidingWindowDataset", scope.makeOpName("SlidingWindowDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(windowSize.asOutput());
     opBuilder.addInput(windowShift.asOutput());
     opBuilder.addInput(windowStride.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SqlDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SqlDataset.java
index 126818001ab..6964f134918 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SqlDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/SqlDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -48,17 +48,13 @@ public final class SqlDataset extends RawOp implements Operand<TType> {
    * @return a new instance of SqlDataset
    */
   @Endpoint(describeByClass = true)
-  public static SqlDataset create(Scope scope, Operand<TString> driverName, Operand<TString> dataSourceName, Operand<TString> query, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static SqlDataset create(Scope scope, Operand<TString> driverName, Operand<TString> dataSourceName, Operand<TString> query, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalSqlDataset", scope.makeOpName("SqlDataset"));
     opBuilder.addInput(driverName.asOutput());
     opBuilder.addInput(dataSourceName.asOutput());
     opBuilder.addInput(query.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ThreadPoolDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ThreadPoolDataset.java
index c8c7d309f69..fb2af7e60a7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ThreadPoolDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ThreadPoolDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -46,16 +46,12 @@ public final class ThreadPoolDataset extends RawOp implements Operand<TType> {
    * @return a new instance of ThreadPoolDataset
    */
   @Endpoint(describeByClass = true)
-  public static ThreadPoolDataset create(Scope scope, Operand<?> inputDataset, Operand<?> threadPool, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static ThreadPoolDataset create(Scope scope, Operand<?> inputDataset, Operand<?> threadPool, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalThreadPoolDataset", scope.makeOpName("ThreadPoolDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder.addInput(threadPool.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UnbatchDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UnbatchDataset.java
index 5e0750da3c6..c00d3fe5470 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UnbatchDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UnbatchDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -45,15 +45,11 @@ public final class UnbatchDataset extends RawOp implements Operand<TType> {
    * @return a new instance of UnbatchDataset
    */
   @Endpoint(describeByClass = true)
-  public static UnbatchDataset create(Scope scope, Operand<?> inputDataset, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static UnbatchDataset create(Scope scope, Operand<?> inputDataset, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalUnbatchDataset", scope.makeOpName("UnbatchDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UncompressElement.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UncompressElement.java
index 486a71b0f9f..36e07fe069c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UncompressElement.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UncompressElement.java
@@ -20,12 +20,12 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,15 +47,11 @@ public final class UncompressElement extends RawOp implements Iterable<Operand<T
    * @return a new instance of UncompressElement
    */
   @Endpoint(describeByClass = true)
-  public static UncompressElement create(Scope scope, Operand<?> compressed, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static UncompressElement create(Scope scope, Operand<?> compressed, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("UncompressElement", scope.makeOpName("UncompressElement"));
     opBuilder.addInput(compressed.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UniqueDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UniqueDataset.java
index dde6d8a9552..6461c5afafa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UniqueDataset.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/UniqueDataset.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.data.experimental;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -45,15 +45,11 @@ public final class UniqueDataset extends RawOp implements Operand<TType> {
    * @return a new instance of UniqueDataset
    */
   @Endpoint(describeByClass = true)
-  public static UniqueDataset create(Scope scope, Operand<?> inputDataset, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+  public static UniqueDataset create(Scope scope, Operand<?> inputDataset, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExperimentalUniqueDataset", scope.makeOpName("UniqueDataset"));
     opBuilder.addInput(inputDataset.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] outputTypesArray = new DataType[outputTypes.size()];
-    for (int i = 0; i < outputTypesArray.length; ++i) {
-      outputTypesArray[i] = outputTypes.get(i);
-    }
-    opBuilder.setAttr("output_types", outputTypesArray);
+    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
     Shape[] outputShapesArray = new Shape[outputShapes.size()];
     for (int i = 0; i < outputShapesArray.length; ++i) {
       outputShapesArray[i] = outputShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java
index 2f24bf16a5c..a24bde53102 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Checks a tensor for NaN, -Inf and +Inf values.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java
index 4b37bd511ed..281d59d21c8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.debugging;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -132,11 +132,11 @@ private Options() {
    * @return a new instance of DebugNumericsSummary
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> DebugNumericsSummary<U> create(Scope scope, Operand<T> input, DataType<U> outputDtype, Options... options) {
+  public static <U extends TNumber, T extends TType> DebugNumericsSummary<U> create(Scope scope, Operand<T> input, Class<U> outputDtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("DebugNumericSummaryV2", scope.makeOpName("DebugNumericsSummary"));
     opBuilder.addInput(input.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("output_dtype", outputDtype);
+    opBuilder.setAttr("output_dtype", Operands.toDataType(outputDtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.tensorDebugMode != null) {
@@ -160,7 +160,7 @@ public static <U extends TNumber, T extends TType> DebugNumericsSummary<U> creat
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> DebugNumericsSummary<TFloat32> create(Scope scope, Operand<T> input, Options... options) {
-    return create(scope, input, TFloat32.DTYPE, options);
+    return create(scope, input, TFloat32.class, options);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java
index 0731c5112ae..502d0e564e3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.dtypes;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -65,11 +65,11 @@ private Options() {
    * @return a new instance of Cast
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> Cast<U> create(Scope scope, Operand<T> x, DataType<U> DstT, Options... options) {
+  public static <U extends TType, T extends TType> Cast<U> create(Scope scope, Operand<T> x, Class<U> DstT, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("Cast", scope.makeOpName("Cast"));
     opBuilder.addInput(x.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("DstT", DstT);
+    opBuilder.setAttr("DstT", Operands.toDataType(DstT));
     if (options != null) {
       for (Options opts : options) {
         if (opts.Truncate != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java
index aeed73b547c..126d26f5945 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.dtypes;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -62,12 +62,12 @@ public final class Complex<U extends TType> extends RawOp implements Operand<U>
    * @return a new instance of Complex
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TNumber> Complex<U> create(Scope scope, Operand<T> real, Operand<T> imag, DataType<U> Tout) {
+  public static <U extends TType, T extends TNumber> Complex<U> create(Scope scope, Operand<T> real, Operand<T> imag, Class<U> Tout) {
     OperationBuilder opBuilder = scope.env().opBuilder("Complex", scope.makeOpName("Complex"));
     opBuilder.addInput(real.asOutput());
     opBuilder.addInput(imag.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Tout", Tout);
+    opBuilder.setAttr("Tout", Operands.toDataType(Tout));
     return new Complex<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java
index 8e53fc204ce..1c3eb4b86bc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Adjust the contrast of one or more images.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java
index e76cf4cc056..fa9d0e9a50c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Adjust the hue of one or more images.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java
index f8f62572e43..5c023d89c6b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Adjust the saturation of one or more images.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResize.java
index a02c0afc7e1..7724191d9ef 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResize.java
@@ -28,7 +28,6 @@
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Extracts crops from the input image tensor and resizes them.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradBoxes.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradBoxes.java
index e86c413c8d9..82dae7df1e0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradBoxes.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradBoxes.java
@@ -28,7 +28,6 @@
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the gradient of the crop_and_resize op wrt the input boxes tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java
index 0d2221348d7..97cd59a6db6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.image;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -29,7 +29,6 @@
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the gradient of the crop_and_resize op wrt the input image tensor.
@@ -84,14 +83,14 @@ private Options() {
    * @return a new instance of CropAndResizeGradImage
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber> CropAndResizeGradImage<T> create(Scope scope, Operand<TFloat32> grads, Operand<TFloat32> boxes, Operand<TInt32> boxInd, Operand<TInt32> imageSize, DataType<T> T, Options... options) {
+  public static <T extends TNumber> CropAndResizeGradImage<T> create(Scope scope, Operand<TFloat32> grads, Operand<TFloat32> boxes, Operand<TInt32> boxInd, Operand<TInt32> imageSize, Class<T> T, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("CropAndResizeGradImage", scope.makeOpName("CropAndResizeGradImage"));
     opBuilder.addInput(grads.asOutput());
     opBuilder.addInput(boxes.asOutput());
     opBuilder.addInput(boxInd.asOutput());
     opBuilder.addInput(imageSize.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("T", T);
+    opBuilder.setAttr("T", Operands.toDataType(T));
     if (options != null) {
       for (Options opts : options) {
         if (opts.method != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java
index 2130da508dd..c2eb543f629 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.image;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -29,7 +29,6 @@
 import org.tensorflow.types.TString;
 import org.tensorflow.types.TUint8;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Decode a PNG-encoded image to a uint8 or uint16 tensor.
@@ -92,11 +91,11 @@ private Options() {
    * @return a new instance of DecodePng
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber> DecodePng<T> create(Scope scope, Operand<TString> contents, DataType<T> dtype, Options... options) {
+  public static <T extends TNumber> DecodePng<T> create(Scope scope, Operand<TString> contents, Class<T> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("DecodePng", scope.makeOpName("DecodePng"));
     opBuilder.addInput(contents.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.channels != null) {
@@ -117,7 +116,7 @@ public static <T extends TNumber> DecodePng<T> create(Scope scope, Operand<TStri
    */
   @Endpoint(describeByClass = true)
   public static DecodePng<TUint8> create(Scope scope, Operand<TString> contents, Options... options) {
-    return create(scope, contents, TUint8.DTYPE, options);
+    return create(scope, contents, TUint8.class, options);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java
index 3edef6b3b4a..5204c603b31 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Draw bounding boxes on a batch of images.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodePng.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodePng.java
index df2579b94d1..cd0e8b89f7b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodePng.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodePng.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * PNG-encode an image.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java
index 1e56198a4b8..bb12cb5cb1a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.image;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -29,7 +29,6 @@
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Extract the shape information of a JPEG-encoded image.
@@ -51,11 +50,11 @@ public final class ExtractJpegShape<T extends TNumber> extends RawOp implements
    * @return a new instance of ExtractJpegShape
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber> ExtractJpegShape<T> create(Scope scope, Operand<TString> contents, DataType<T> outputType) {
+  public static <T extends TNumber> ExtractJpegShape<T> create(Scope scope, Operand<TString> contents, Class<T> outputType) {
     OperationBuilder opBuilder = scope.env().opBuilder("ExtractJpegShape", scope.makeOpName("ExtractJpegShape"));
     opBuilder.addInput(contents.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("output_type", outputType);
+    opBuilder.setAttr("output_type", Operands.toDataType(outputType));
     return new ExtractJpegShape<T>(opBuilder.build());
   }
   
@@ -68,7 +67,7 @@ public static <T extends TNumber> ExtractJpegShape<T> create(Scope scope, Operan
    */
   @Endpoint(describeByClass = true)
   public static ExtractJpegShape<TInt32> create(Scope scope, Operand<TString> contents) {
-    return create(scope, contents, TInt32.DTYPE);
+    return create(scope, contents, TInt32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java
index f51027d884b..7934480bad9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Convert one or more images from HSV to RGB.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java
index fc72745c500..5fd57e44754 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java
@@ -28,7 +28,6 @@
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Applies the given transform to each of the images.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppression.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppression.java
index da5681b0bd3..0f2e983f786 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppression.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/NonMaxSuppression.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Greedily selects a subset of bounding boxes in descending order of score,
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java
index 355b2bf37ed..133c38eaaa3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Randomly crop `image`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeArea.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeArea.java
index 2ad69becce8..4d998f6cf1b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeArea.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeArea.java
@@ -28,7 +28,6 @@
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Resize `images` to `size` using area interpolation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubic.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubic.java
index b6adb9242d4..ecc156ed9d8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubic.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubic.java
@@ -28,7 +28,6 @@
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Resize `images` to `size` using bicubic interpolation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java
index 4f59a26a025..e5526a769f3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the gradient of bicubic interpolation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinear.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinear.java
index fa02d5b9ec7..0c96019b54d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinear.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinear.java
@@ -28,7 +28,6 @@
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Resize `images` to `size` using bilinear interpolation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java
index 18dc81aa7ec..38c20992da0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the gradient of bilinear interpolation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java
index 72fca1f45fe..3e4763c692c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Resize `images` to `size` using nearest neighbor interpolation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java
index 56f33a63e05..c3d2dd10e2a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the gradient of nearest neighbor interpolation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java
index 1b7a0c33d3c..2746052a7b0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Converts one or more images from RGB to HSV.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java
index 4fec1955f54..78a37b37dc2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Generate a single randomly distorted bounding box for an image.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslate.java
index 45bb5c00961..41d49fd75f2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslate.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslate.java
@@ -28,7 +28,6 @@
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  */
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslateGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslateGrad.java
index 680351d79a4..b6f55d1d159 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslateGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ScaleAndTranslateGrad.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code output()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java
index 2a37c8e0bad..ca41464e1b3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.io;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -29,7 +29,6 @@
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Reinterpret the bytes of a string as a vector of numbers.
@@ -71,12 +70,12 @@ private Options() {
    * @return a new instance of DecodePaddedRaw
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber> DecodePaddedRaw<T> create(Scope scope, Operand<TString> inputBytes, Operand<TInt32> fixedLength, DataType<T> outType, Options... options) {
+  public static <T extends TNumber> DecodePaddedRaw<T> create(Scope scope, Operand<TString> inputBytes, Operand<TInt32> fixedLength, Class<T> outType, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("DecodePaddedRaw", scope.makeOpName("DecodePaddedRaw"));
     opBuilder.addInput(inputBytes.asOutput());
     opBuilder.addInput(fixedLength.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     if (options != null) {
       for (Options opts : options) {
         if (opts.littleEndian != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java
index fac97605459..5ef7da94d51 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.io;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -68,11 +68,11 @@ private Options() {
    * @return a new instance of DecodeRaw
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> DecodeRaw<T> create(Scope scope, Operand<TString> bytes, DataType<T> outType, Options... options) {
+  public static <T extends TType> DecodeRaw<T> create(Scope scope, Operand<TString> bytes, Class<T> outType, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("DecodeRaw", scope.makeOpName("DecodeRaw"));
     opBuilder.addInput(bytes.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     if (options != null) {
       for (Options opts : options) {
         if (opts.littleEndian != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java
index b1006d65daa..9d2e496e50e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.io;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -90,11 +90,11 @@ public final class DeserializeManySparse<T extends TType> extends RawOp {
    * @return a new instance of DeserializeManySparse
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> DeserializeManySparse<T> create(Scope scope, Operand<TString> serializedSparse, DataType<T> dtype) {
+  public static <T extends TType> DeserializeManySparse<T> create(Scope scope, Operand<TString> serializedSparse, Class<T> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("DeserializeManySparse", scope.makeOpName("DeserializeManySparse"));
     opBuilder.addInput(serializedSparse.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new DeserializeManySparse<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/FifoQueue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/FifoQueue.java
index 8ea087d91f9..0559fbddbf1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/FifoQueue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/FifoQueue.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.io;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -97,14 +97,10 @@ private Options() {
    * @return a new instance of FifoQueue
    */
   @Endpoint(describeByClass = true)
-  public static FifoQueue create(Scope scope, List<DataType<?>> componentTypes, Options... options) {
+  public static FifoQueue create(Scope scope, List<Class<? extends TType>> componentTypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("FIFOQueueV2", scope.makeOpName("FifoQueue"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] componentTypesArray = new DataType[componentTypes.size()];
-    for (int i = 0; i < componentTypesArray.length; ++i) {
-      componentTypesArray[i] = componentTypes.get(i);
-    }
-    opBuilder.setAttr("component_types", componentTypesArray);
+    opBuilder.setAttr("component_types", Operands.toDataTypes(componentTypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.shapes != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PaddingFifoQueue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PaddingFifoQueue.java
index 615e5749f28..691e35140ca 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PaddingFifoQueue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PaddingFifoQueue.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.io;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -105,14 +105,10 @@ private Options() {
    * @return a new instance of PaddingFifoQueue
    */
   @Endpoint(describeByClass = true)
-  public static PaddingFifoQueue create(Scope scope, List<DataType<?>> componentTypes, Options... options) {
+  public static PaddingFifoQueue create(Scope scope, List<Class<? extends TType>> componentTypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("PaddingFIFOQueueV2", scope.makeOpName("PaddingFifoQueue"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] componentTypesArray = new DataType[componentTypes.size()];
-    for (int i = 0; i < componentTypesArray.length; ++i) {
-      componentTypesArray[i] = componentTypes.get(i);
-    }
-    opBuilder.setAttr("component_types", componentTypesArray);
+    opBuilder.setAttr("component_types", Operands.toDataTypes(componentTypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.shapes != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseExample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseExample.java
index 512e6d6f1ee..bdd66a0a62a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseExample.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseExample.java
@@ -19,7 +19,6 @@
 
 import java.util.Arrays;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -33,6 +32,7 @@
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
+import org.tensorflow.types.family.TType;
 
 /**
  * Transforms a vector of tf.Example protos (as strings) into typed tensors.
@@ -97,7 +97,7 @@ public final class ParseExample extends RawOp {
    * @return a new instance of ParseExample
    */
   @Endpoint(describeByClass = true)
-  public static ParseExample create(Scope scope, Operand<TString> serialized, Operand<TString> names, Operand<TString> sparseKeys, Operand<TString> denseKeys, Operand<TString> raggedKeys, Iterable<Operand<?>> denseDefaults, Long numSparse, List<DataType<?>> sparseTypes, List<DataType<?>> raggedValueTypes, List<DataType<?>> raggedSplitTypes, List<Shape> denseShapes) {
+  public static ParseExample create(Scope scope, Operand<TString> serialized, Operand<TString> names, Operand<TString> sparseKeys, Operand<TString> denseKeys, Operand<TString> raggedKeys, Iterable<Operand<?>> denseDefaults, Long numSparse, List<Class<? extends TType>> sparseTypes, List<Class<? extends TType>> raggedValueTypes, List<Class<? extends TNumber>> raggedSplitTypes, List<Shape> denseShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ParseExampleV2", scope.makeOpName("ParseExample"));
     opBuilder.addInput(serialized.asOutput());
     opBuilder.addInput(names.asOutput());
@@ -107,21 +107,9 @@ public static ParseExample create(Scope scope, Operand<TString> serialized, Oper
     opBuilder.addInputList(Operands.asOutputs(denseDefaults));
     opBuilder = scope.apply(opBuilder);
     opBuilder.setAttr("num_sparse", numSparse);
-    DataType[] sparseTypesArray = new DataType[sparseTypes.size()];
-    for (int i = 0; i < sparseTypesArray.length; ++i) {
-      sparseTypesArray[i] = sparseTypes.get(i);
-    }
-    opBuilder.setAttr("sparse_types", sparseTypesArray);
-    DataType[] raggedValueTypesArray = new DataType[raggedValueTypes.size()];
-    for (int i = 0; i < raggedValueTypesArray.length; ++i) {
-      raggedValueTypesArray[i] = raggedValueTypes.get(i);
-    }
-    opBuilder.setAttr("ragged_value_types", raggedValueTypesArray);
-    DataType[] raggedSplitTypesArray = new DataType[raggedSplitTypes.size()];
-    for (int i = 0; i < raggedSplitTypesArray.length; ++i) {
-      raggedSplitTypesArray[i] = raggedSplitTypes.get(i);
-    }
-    opBuilder.setAttr("ragged_split_types", raggedSplitTypesArray);
+    opBuilder.setAttr("sparse_types", Operands.toDataTypes(sparseTypes));
+    opBuilder.setAttr("ragged_value_types", Operands.toDataTypes(raggedValueTypes));
+    opBuilder.setAttr("ragged_split_types", Operands.toDataTypes(raggedSplitTypes));
     Shape[] denseShapesArray = new Shape[denseShapes.size()];
     for (int i = 0; i < denseShapesArray.length; ++i) {
       denseShapesArray[i] = denseShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSequenceExample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSequenceExample.java
index cb798f6ada0..b4c9479d7c7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSequenceExample.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSequenceExample.java
@@ -19,7 +19,6 @@
 
 import java.util.Arrays;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -34,6 +33,7 @@
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
+import org.tensorflow.types.family.TType;
 
 /**
  * Transforms a vector of tf.io.SequenceExample protos (as strings) into
@@ -153,7 +153,7 @@ private Options() {
    * @return a new instance of ParseSequenceExample
    */
   @Endpoint(describeByClass = true)
-  public static ParseSequenceExample create(Scope scope, Operand<TString> serialized, Operand<TString> debugName, Operand<TString> contextSparseKeys, Operand<TString> contextDenseKeys, Operand<TString> contextRaggedKeys, Operand<TString> featureListSparseKeys, Operand<TString> featureListDenseKeys, Operand<TString> featureListRaggedKeys, Operand<TBool> featureListDenseMissingAssumedEmpty, Iterable<Operand<?>> contextDenseDefaults, List<DataType<?>> contextSparseTypes, List<DataType<?>> contextRaggedValueTypes, List<DataType<?>> contextRaggedSplitTypes, List<DataType<?>> featureListDenseTypes, List<DataType<?>> featureListSparseTypes, List<DataType<?>> featureListRaggedValueTypes, List<DataType<?>> featureListRaggedSplitTypes, Options... options) {
+  public static ParseSequenceExample create(Scope scope, Operand<TString> serialized, Operand<TString> debugName, Operand<TString> contextSparseKeys, Operand<TString> contextDenseKeys, Operand<TString> contextRaggedKeys, Operand<TString> featureListSparseKeys, Operand<TString> featureListDenseKeys, Operand<TString> featureListRaggedKeys, Operand<TBool> featureListDenseMissingAssumedEmpty, Iterable<Operand<?>> contextDenseDefaults, List<Class<? extends TType>> contextSparseTypes, List<Class<? extends TType>> contextRaggedValueTypes, List<Class<? extends TNumber>> contextRaggedSplitTypes, List<Class<? extends TType>> featureListDenseTypes, List<Class<? extends TType>> featureListSparseTypes, List<Class<? extends TType>> featureListRaggedValueTypes, List<Class<? extends TNumber>> featureListRaggedSplitTypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("ParseSequenceExampleV2", scope.makeOpName("ParseSequenceExample"));
     opBuilder.addInput(serialized.asOutput());
     opBuilder.addInput(debugName.asOutput());
@@ -166,41 +166,13 @@ public static ParseSequenceExample create(Scope scope, Operand<TString> serializ
     opBuilder.addInput(featureListDenseMissingAssumedEmpty.asOutput());
     opBuilder.addInputList(Operands.asOutputs(contextDenseDefaults));
     opBuilder = scope.apply(opBuilder);
-    DataType[] contextSparseTypesArray = new DataType[contextSparseTypes.size()];
-    for (int i = 0; i < contextSparseTypesArray.length; ++i) {
-      contextSparseTypesArray[i] = contextSparseTypes.get(i);
-    }
-    opBuilder.setAttr("context_sparse_types", contextSparseTypesArray);
-    DataType[] contextRaggedValueTypesArray = new DataType[contextRaggedValueTypes.size()];
-    for (int i = 0; i < contextRaggedValueTypesArray.length; ++i) {
-      contextRaggedValueTypesArray[i] = contextRaggedValueTypes.get(i);
-    }
-    opBuilder.setAttr("context_ragged_value_types", contextRaggedValueTypesArray);
-    DataType[] contextRaggedSplitTypesArray = new DataType[contextRaggedSplitTypes.size()];
-    for (int i = 0; i < contextRaggedSplitTypesArray.length; ++i) {
-      contextRaggedSplitTypesArray[i] = contextRaggedSplitTypes.get(i);
-    }
-    opBuilder.setAttr("context_ragged_split_types", contextRaggedSplitTypesArray);
-    DataType[] featureListDenseTypesArray = new DataType[featureListDenseTypes.size()];
-    for (int i = 0; i < featureListDenseTypesArray.length; ++i) {
-      featureListDenseTypesArray[i] = featureListDenseTypes.get(i);
-    }
-    opBuilder.setAttr("feature_list_dense_types", featureListDenseTypesArray);
-    DataType[] featureListSparseTypesArray = new DataType[featureListSparseTypes.size()];
-    for (int i = 0; i < featureListSparseTypesArray.length; ++i) {
-      featureListSparseTypesArray[i] = featureListSparseTypes.get(i);
-    }
-    opBuilder.setAttr("feature_list_sparse_types", featureListSparseTypesArray);
-    DataType[] featureListRaggedValueTypesArray = new DataType[featureListRaggedValueTypes.size()];
-    for (int i = 0; i < featureListRaggedValueTypesArray.length; ++i) {
-      featureListRaggedValueTypesArray[i] = featureListRaggedValueTypes.get(i);
-    }
-    opBuilder.setAttr("feature_list_ragged_value_types", featureListRaggedValueTypesArray);
-    DataType[] featureListRaggedSplitTypesArray = new DataType[featureListRaggedSplitTypes.size()];
-    for (int i = 0; i < featureListRaggedSplitTypesArray.length; ++i) {
-      featureListRaggedSplitTypesArray[i] = featureListRaggedSplitTypes.get(i);
-    }
-    opBuilder.setAttr("feature_list_ragged_split_types", featureListRaggedSplitTypesArray);
+    opBuilder.setAttr("context_sparse_types", Operands.toDataTypes(contextSparseTypes));
+    opBuilder.setAttr("context_ragged_value_types", Operands.toDataTypes(contextRaggedValueTypes));
+    opBuilder.setAttr("context_ragged_split_types", Operands.toDataTypes(contextRaggedSplitTypes));
+    opBuilder.setAttr("feature_list_dense_types", Operands.toDataTypes(featureListDenseTypes));
+    opBuilder.setAttr("feature_list_sparse_types", Operands.toDataTypes(featureListSparseTypes));
+    opBuilder.setAttr("feature_list_ragged_value_types", Operands.toDataTypes(featureListRaggedValueTypes));
+    opBuilder.setAttr("feature_list_ragged_split_types", Operands.toDataTypes(featureListRaggedSplitTypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.NcontextSparse != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleExample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleExample.java
index a18f4d69e32..f860fec4dc4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleExample.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleExample.java
@@ -19,7 +19,6 @@
 
 import java.util.Arrays;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -32,6 +31,7 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
+import org.tensorflow.types.family.TType;
 
 /**
  * Transforms a tf.Example proto (as a string) into typed tensors.
@@ -76,7 +76,7 @@ public final class ParseSingleExample extends RawOp {
    * @return a new instance of ParseSingleExample
    */
   @Endpoint(describeByClass = true)
-  public static ParseSingleExample create(Scope scope, Operand<TString> serialized, Iterable<Operand<?>> denseDefaults, Long numSparse, List<String> sparseKeys, List<String> denseKeys, List<DataType<?>> sparseTypes, List<Shape> denseShapes) {
+  public static ParseSingleExample create(Scope scope, Operand<TString> serialized, Iterable<Operand<?>> denseDefaults, Long numSparse, List<String> sparseKeys, List<String> denseKeys, List<Class<? extends TType>> sparseTypes, List<Shape> denseShapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("ParseSingleExample", scope.makeOpName("ParseSingleExample"));
     opBuilder.addInput(serialized.asOutput());
     opBuilder.addInputList(Operands.asOutputs(denseDefaults));
@@ -92,11 +92,7 @@ public static ParseSingleExample create(Scope scope, Operand<TString> serialized
       denseKeysArray[i] = denseKeys.get(i);
     }
     opBuilder.setAttr("dense_keys", denseKeysArray);
-    DataType[] sparseTypesArray = new DataType[sparseTypes.size()];
-    for (int i = 0; i < sparseTypesArray.length; ++i) {
-      sparseTypesArray[i] = sparseTypes.get(i);
-    }
-    opBuilder.setAttr("sparse_types", sparseTypesArray);
+    opBuilder.setAttr("sparse_types", Operands.toDataTypes(sparseTypes));
     Shape[] denseShapesArray = new Shape[denseShapes.size()];
     for (int i = 0; i < denseShapesArray.length; ++i) {
       denseShapesArray[i] = denseShapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleSequenceExample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleSequenceExample.java
index 67c6ea97ac1..b54be0324b9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleSequenceExample.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleSequenceExample.java
@@ -19,7 +19,6 @@
 
 import java.util.Arrays;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -32,6 +31,7 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
+import org.tensorflow.types.family.TType;
 
 /**
  * Transforms a scalar brain.SequenceExample proto (as strings) into typed tensors.
@@ -122,7 +122,7 @@ private Options() {
    * @return a new instance of ParseSingleSequenceExample
    */
   @Endpoint(describeByClass = true)
-  public static ParseSingleSequenceExample create(Scope scope, Operand<TString> serialized, Operand<TString> featureListDenseMissingAssumedEmpty, Iterable<Operand<TString>> contextSparseKeys, Iterable<Operand<TString>> contextDenseKeys, Iterable<Operand<TString>> featureListSparseKeys, Iterable<Operand<TString>> featureListDenseKeys, Iterable<Operand<?>> contextDenseDefaults, Operand<TString> debugName, List<DataType<?>> contextSparseTypes, List<DataType<?>> featureListDenseTypes, List<DataType<?>> featureListSparseTypes, Options... options) {
+  public static ParseSingleSequenceExample create(Scope scope, Operand<TString> serialized, Operand<TString> featureListDenseMissingAssumedEmpty, Iterable<Operand<TString>> contextSparseKeys, Iterable<Operand<TString>> contextDenseKeys, Iterable<Operand<TString>> featureListSparseKeys, Iterable<Operand<TString>> featureListDenseKeys, Iterable<Operand<?>> contextDenseDefaults, Operand<TString> debugName, List<Class<? extends TType>> contextSparseTypes, List<Class<? extends TType>> featureListDenseTypes, List<Class<? extends TType>> featureListSparseTypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("ParseSingleSequenceExample", scope.makeOpName("ParseSingleSequenceExample"));
     opBuilder.addInput(serialized.asOutput());
     opBuilder.addInput(featureListDenseMissingAssumedEmpty.asOutput());
@@ -133,21 +133,9 @@ public static ParseSingleSequenceExample create(Scope scope, Operand<TString> se
     opBuilder.addInputList(Operands.asOutputs(contextDenseDefaults));
     opBuilder.addInput(debugName.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] contextSparseTypesArray = new DataType[contextSparseTypes.size()];
-    for (int i = 0; i < contextSparseTypesArray.length; ++i) {
-      contextSparseTypesArray[i] = contextSparseTypes.get(i);
-    }
-    opBuilder.setAttr("context_sparse_types", contextSparseTypesArray);
-    DataType[] featureListDenseTypesArray = new DataType[featureListDenseTypes.size()];
-    for (int i = 0; i < featureListDenseTypesArray.length; ++i) {
-      featureListDenseTypesArray[i] = featureListDenseTypes.get(i);
-    }
-    opBuilder.setAttr("feature_list_dense_types", featureListDenseTypesArray);
-    DataType[] featureListSparseTypesArray = new DataType[featureListSparseTypes.size()];
-    for (int i = 0; i < featureListSparseTypesArray.length; ++i) {
-      featureListSparseTypesArray[i] = featureListSparseTypes.get(i);
-    }
-    opBuilder.setAttr("feature_list_sparse_types", featureListSparseTypesArray);
+    opBuilder.setAttr("context_sparse_types", Operands.toDataTypes(contextSparseTypes));
+    opBuilder.setAttr("feature_list_dense_types", Operands.toDataTypes(featureListDenseTypes));
+    opBuilder.setAttr("feature_list_sparse_types", Operands.toDataTypes(featureListSparseTypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.contextDenseShapes != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java
index 993141554a6..9af89bdcd2d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.io;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,11 +47,11 @@ public final class ParseTensor<T extends TType> extends RawOp implements Operand
    * @return a new instance of ParseTensor
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> ParseTensor<T> create(Scope scope, Operand<TString> serialized, DataType<T> outType) {
+  public static <T extends TType> ParseTensor<T> create(Scope scope, Operand<TString> serialized, Class<T> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("ParseTensor", scope.makeOpName("ParseTensor"));
     opBuilder.addInput(serialized.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new ParseTensor<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PriorityQueue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PriorityQueue.java
index b49a498fb0e..9decf07b572 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PriorityQueue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/PriorityQueue.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.io;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -95,14 +95,10 @@ private Options() {
    * @return a new instance of PriorityQueue
    */
   @Endpoint(describeByClass = true)
-  public static PriorityQueue create(Scope scope, List<DataType<?>> componentTypes, List<Shape> shapes, Options... options) {
+  public static PriorityQueue create(Scope scope, List<Class<? extends TType>> componentTypes, List<Shape> shapes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("PriorityQueueV2", scope.makeOpName("PriorityQueue"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] componentTypesArray = new DataType[componentTypes.size()];
-    for (int i = 0; i < componentTypesArray.length; ++i) {
-      componentTypesArray[i] = componentTypes.get(i);
-    }
-    opBuilder.setAttr("component_types", componentTypesArray);
+    opBuilder.setAttr("component_types", Operands.toDataTypes(componentTypes));
     Shape[] shapesArray = new Shape[shapes.size()];
     for (int i = 0; i < shapesArray.length; ++i) {
       shapesArray[i] = shapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeue.java
index 273ff1c91a5..b4d4bb71aaf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeue.java
@@ -20,11 +20,11 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -75,15 +75,11 @@ private Options() {
    * @return a new instance of QueueDequeue
    */
   @Endpoint(describeByClass = true)
-  public static QueueDequeue create(Scope scope, Operand<?> handle, List<DataType<?>> componentTypes, Options... options) {
+  public static QueueDequeue create(Scope scope, Operand<?> handle, List<Class<? extends TType>> componentTypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QueueDequeueV2", scope.makeOpName("QueueDequeue"));
     opBuilder.addInput(handle.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] componentTypesArray = new DataType[componentTypes.size()];
-    for (int i = 0; i < componentTypesArray.length; ++i) {
-      componentTypesArray[i] = componentTypes.get(i);
-    }
-    opBuilder.setAttr("component_types", componentTypesArray);
+    opBuilder.setAttr("component_types", Operands.toDataTypes(componentTypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.timeoutMs != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueMany.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueMany.java
index 229c544e139..1ef3426f354 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueMany.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueMany.java
@@ -20,11 +20,11 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -84,16 +84,12 @@ private Options() {
    * @return a new instance of QueueDequeueMany
    */
   @Endpoint(describeByClass = true)
-  public static QueueDequeueMany create(Scope scope, Operand<?> handle, Operand<TInt32> n, List<DataType<?>> componentTypes, Options... options) {
+  public static QueueDequeueMany create(Scope scope, Operand<?> handle, Operand<TInt32> n, List<Class<? extends TType>> componentTypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QueueDequeueManyV2", scope.makeOpName("QueueDequeueMany"));
     opBuilder.addInput(handle.asOutput());
     opBuilder.addInput(n.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] componentTypesArray = new DataType[componentTypes.size()];
-    for (int i = 0; i < componentTypesArray.length; ++i) {
-      componentTypesArray[i] = componentTypes.get(i);
-    }
-    opBuilder.setAttr("component_types", componentTypesArray);
+    opBuilder.setAttr("component_types", Operands.toDataTypes(componentTypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.timeoutMs != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueUpTo.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueUpTo.java
index 332eefb5096..53516d87ed5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueUpTo.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/QueueDequeueUpTo.java
@@ -20,11 +20,11 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -88,16 +88,12 @@ private Options() {
    * @return a new instance of QueueDequeueUpTo
    */
   @Endpoint(describeByClass = true)
-  public static QueueDequeueUpTo create(Scope scope, Operand<?> handle, Operand<TInt32> n, List<DataType<?>> componentTypes, Options... options) {
+  public static QueueDequeueUpTo create(Scope scope, Operand<?> handle, Operand<TInt32> n, List<Class<? extends TType>> componentTypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QueueDequeueUpToV2", scope.makeOpName("QueueDequeueUpTo"));
     opBuilder.addInput(handle.asOutput());
     opBuilder.addInput(n.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] componentTypesArray = new DataType[componentTypes.size()];
-    for (int i = 0; i < componentTypesArray.length; ++i) {
-      componentTypesArray[i] = componentTypes.get(i);
-    }
-    opBuilder.setAttr("component_types", componentTypesArray);
+    opBuilder.setAttr("component_types", Operands.toDataTypes(componentTypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.timeoutMs != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/RandomShuffleQueue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/RandomShuffleQueue.java
index da168c4f8a8..9ce330cb960 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/RandomShuffleQueue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/RandomShuffleQueue.java
@@ -18,12 +18,12 @@
 package org.tensorflow.op.io;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -127,14 +127,10 @@ private Options() {
    * @return a new instance of RandomShuffleQueue
    */
   @Endpoint(describeByClass = true)
-  public static RandomShuffleQueue create(Scope scope, List<DataType<?>> componentTypes, Options... options) {
+  public static RandomShuffleQueue create(Scope scope, List<Class<? extends TType>> componentTypes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("RandomShuffleQueueV2", scope.makeOpName("RandomShuffleQueue"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] componentTypesArray = new DataType[componentTypes.size()];
-    for (int i = 0; i < componentTypesArray.length; ++i) {
-      componentTypesArray[i] = componentTypes.get(i);
-    }
-    opBuilder.setAttr("component_types", componentTypesArray);
+    opBuilder.setAttr("component_types", Operands.toDataTypes(componentTypes));
     if (options != null) {
       for (Options opts : options) {
         if (opts.shapes != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java
index a513c0b8846..8a712e7278b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.io;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -58,13 +58,13 @@ public final class SerializeManySparse<U extends TType> extends RawOp implements
    * @return a new instance of SerializeManySparse
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> SerializeManySparse<U> create(Scope scope, Operand<TInt64> sparseIndices, Operand<T> sparseValues, Operand<TInt64> sparseShape, DataType<U> outType) {
+  public static <U extends TType, T extends TType> SerializeManySparse<U> create(Scope scope, Operand<TInt64> sparseIndices, Operand<T> sparseValues, Operand<TInt64> sparseShape, Class<U> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("SerializeManySparse", scope.makeOpName("SerializeManySparse"));
     opBuilder.addInput(sparseIndices.asOutput());
     opBuilder.addInput(sparseValues.asOutput());
     opBuilder.addInput(sparseShape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new SerializeManySparse<U>(opBuilder.build());
   }
   
@@ -79,7 +79,7 @@ public static <U extends TType, T extends TType> SerializeManySparse<U> create(S
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> SerializeManySparse<TString> create(Scope scope, Operand<TInt64> sparseIndices, Operand<T> sparseValues, Operand<TInt64> sparseShape) {
-    return create(scope, sparseIndices, sparseValues, sparseShape, TString.DTYPE);
+    return create(scope, sparseIndices, sparseValues, sparseShape, TString.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java
index a817d2f6cd8..611feb50188 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.io;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -50,13 +50,13 @@ public final class SerializeSparse<U extends TType> extends RawOp implements Ope
    * @return a new instance of SerializeSparse
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> SerializeSparse<U> create(Scope scope, Operand<TInt64> sparseIndices, Operand<T> sparseValues, Operand<TInt64> sparseShape, DataType<U> outType) {
+  public static <U extends TType, T extends TType> SerializeSparse<U> create(Scope scope, Operand<TInt64> sparseIndices, Operand<T> sparseValues, Operand<TInt64> sparseShape, Class<U> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("SerializeSparse", scope.makeOpName("SerializeSparse"));
     opBuilder.addInput(sparseIndices.asOutput());
     opBuilder.addInput(sparseValues.asOutput());
     opBuilder.addInput(sparseShape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new SerializeSparse<U>(opBuilder.build());
   }
   
@@ -71,7 +71,7 @@ public static <U extends TType, T extends TType> SerializeSparse<U> create(Scope
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> SerializeSparse<TString> create(Scope scope, Operand<TInt64> sparseIndices, Operand<T> sparseValues, Operand<TInt64> sparseShape) {
-    return create(scope, sparseIndices, sparseValues, sparseShape, TString.DTYPE);
+    return create(scope, sparseIndices, sparseValues, sparseShape, TString.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java
index e5399fa96ef..a7ba5c36639 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code output()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java
index a71729b2b02..515e582f254 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code output()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java
index d9012f7615a..709a59404b9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code output()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java
index 0c5cfddf80c..64559a23676 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code output()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java
index 7c4b17062b1..71490a6b153 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TFloat64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code output()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java
index 5e4a64c943d..7bccee674a9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code output()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java
index 5f060b01f47..450a7ee419d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code e()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java
index 062178ecd74..5a623ebd876 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the reverse mode backpropagated gradient of the Cholesky algorithm.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java
index 3b02aa71ba7..b62fcbf512c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Compute the pairwise cross product.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java
index e595bc9ec4a..ac976cc929e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -78,11 +78,11 @@ private Options() {
    * @return a new instance of Eig
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> Eig<U> create(Scope scope, Operand<T> input, DataType<U> Tout, Options... options) {
+  public static <U extends TType, T extends TType> Eig<U> create(Scope scope, Operand<T> input, Class<U> Tout, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("Eig", scope.makeOpName("Eig"));
     opBuilder.addInput(input.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Tout", Tout);
+    opBuilder.setAttr("Tout", Operands.toDataType(Tout));
     if (options != null) {
       for (Options opts : options) {
         if (opts.computeV != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java
index 412fa76ba75..3edb62f927a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -67,11 +67,11 @@ public final class Lu<T extends TType, U extends TNumber> extends RawOp {
    * @return a new instance of Lu
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType, U extends TNumber> Lu<T, U> create(Scope scope, Operand<T> input, DataType<U> outputIdxType) {
+  public static <T extends TType, U extends TNumber> Lu<T, U> create(Scope scope, Operand<T> input, Class<U> outputIdxType) {
     OperationBuilder opBuilder = scope.env().opBuilder("Lu", scope.makeOpName("Lu"));
     opBuilder.addInput(input.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("output_idx_type", outputIdxType);
+    opBuilder.setAttr("output_idx_type", Operands.toDataType(outputIdxType));
     return new Lu<T, U>(opBuilder.build());
   }
   
@@ -85,7 +85,7 @@ public static <T extends TType, U extends TNumber> Lu<T, U> create(Scope scope,
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> Lu<T, TInt32> create(Scope scope, Operand<T> input) {
-    return create(scope, input, TInt32.DTYPE);
+    return create(scope, input, TInt32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java
index 7f29bb51c6d..517578fe83e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -87,7 +87,7 @@ private Options() {
    * @return a new instance of QuantizedMatMul
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType, W extends TType> QuantizedMatMul<V> create(Scope scope, Operand<T> a, Operand<U> b, Operand<TFloat32> minA, Operand<TFloat32> maxA, Operand<TFloat32> minB, Operand<TFloat32> maxB, DataType<V> Toutput, DataType<W> Tactivation, Options... options) {
+  public static <V extends TType, T extends TType, U extends TType, W extends TType> QuantizedMatMul<V> create(Scope scope, Operand<T> a, Operand<U> b, Operand<TFloat32> minA, Operand<TFloat32> maxA, Operand<TFloat32> minB, Operand<TFloat32> maxB, Class<V> Toutput, Class<W> Tactivation, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedMatMul", scope.makeOpName("QuantizedMatMul"));
     opBuilder.addInput(a.asOutput());
     opBuilder.addInput(b.asOutput());
@@ -96,8 +96,8 @@ public static <V extends TType, T extends TType, U extends TType, W extends TTyp
     opBuilder.addInput(minB.asOutput());
     opBuilder.addInput(maxB.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Toutput", Toutput);
-    opBuilder.setAttr("Tactivation", Tactivation);
+    opBuilder.setAttr("Toutput", Operands.toDataType(Toutput));
+    opBuilder.setAttr("Tactivation", Operands.toDataType(Tactivation));
     if (options != null) {
       for (Options opts : options) {
         if (opts.transposeA != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java
index 17e75ce0ff4..26ebb08a09e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -97,7 +97,7 @@ private Options() {
    * @return a new instance of QuantizedMatMulWithBias
    */
   @Endpoint(describeByClass = true)
-  public static <W extends TType, T extends TType, U extends TType, V extends TType> QuantizedMatMulWithBias<W> create(Scope scope, Operand<T> a, Operand<U> b, Operand<V> bias, Operand<TFloat32> minA, Operand<TFloat32> maxA, Operand<TFloat32> minB, Operand<TFloat32> maxB, DataType<W> Toutput, Options... options) {
+  public static <W extends TType, T extends TType, U extends TType, V extends TType> QuantizedMatMulWithBias<W> create(Scope scope, Operand<T> a, Operand<U> b, Operand<V> bias, Operand<TFloat32> minA, Operand<TFloat32> maxA, Operand<TFloat32> minB, Operand<TFloat32> maxB, Class<W> Toutput, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedMatMulWithBias", scope.makeOpName("QuantizedMatMulWithBias"));
     opBuilder.addInput(a.asOutput());
     opBuilder.addInput(b.asOutput());
@@ -107,7 +107,7 @@ public static <W extends TType, T extends TType, U extends TType, V extends TTyp
     opBuilder.addInput(minB.asOutput());
     opBuilder.addInput(maxB.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Toutput", Toutput);
+    opBuilder.setAttr("Toutput", Operands.toDataType(Toutput));
     if (options != null) {
       for (Options opts : options) {
         if (opts.transposeA != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java
index fa4fe22b8fd..12208c96a14 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -98,7 +98,7 @@ private Options() {
    * @return a new instance of QuantizedMatMulWithBiasAndRelu
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedMatMulWithBiasAndRelu<V> create(Scope scope, Operand<T> a, Operand<U> b, Operand<TFloat32> bias, Operand<TFloat32> minA, Operand<TFloat32> maxA, Operand<TFloat32> minB, Operand<TFloat32> maxB, DataType<V> Toutput, Options... options) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedMatMulWithBiasAndRelu<V> create(Scope scope, Operand<T> a, Operand<U> b, Operand<TFloat32> bias, Operand<TFloat32> minA, Operand<TFloat32> maxA, Operand<TFloat32> minB, Operand<TFloat32> maxB, Class<V> Toutput, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedMatMulWithBiasAndRelu", scope.makeOpName("QuantizedMatMulWithBiasAndRelu"));
     opBuilder.addInput(a.asOutput());
     opBuilder.addInput(b.asOutput());
@@ -108,7 +108,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedMatMu
     opBuilder.addInput(minB.asOutput());
     opBuilder.addInput(maxB.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Toutput", Toutput);
+    opBuilder.setAttr("Toutput", Operands.toDataType(Toutput));
     if (options != null) {
       for (Options opts : options) {
         if (opts.transposeA != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java
index a7a02d36bc5..a20287446c7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -101,7 +101,7 @@ private Options() {
    * @return a new instance of QuantizedMatMulWithBiasAndReluAndRequantize
    */
   @Endpoint(describeByClass = true)
-  public static <W extends TType, T extends TType, U extends TType, V extends TType> QuantizedMatMulWithBiasAndReluAndRequantize<W> create(Scope scope, Operand<T> a, Operand<U> b, Operand<V> bias, Operand<TFloat32> minA, Operand<TFloat32> maxA, Operand<TFloat32> minB, Operand<TFloat32> maxB, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, DataType<W> Toutput, Options... options) {
+  public static <W extends TType, T extends TType, U extends TType, V extends TType> QuantizedMatMulWithBiasAndReluAndRequantize<W> create(Scope scope, Operand<T> a, Operand<U> b, Operand<V> bias, Operand<TFloat32> minA, Operand<TFloat32> maxA, Operand<TFloat32> minB, Operand<TFloat32> maxB, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, Class<W> Toutput, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedMatMulWithBiasAndReluAndRequantize", scope.makeOpName("QuantizedMatMulWithBiasAndReluAndRequantize"));
     opBuilder.addInput(a.asOutput());
     opBuilder.addInput(b.asOutput());
@@ -113,7 +113,7 @@ public static <W extends TType, T extends TType, U extends TType, V extends TTyp
     opBuilder.addInput(minFreezedOutput.asOutput());
     opBuilder.addInput(maxFreezedOutput.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Toutput", Toutput);
+    opBuilder.setAttr("Toutput", Operands.toDataType(Toutput));
     if (options != null) {
       for (Options opts : options) {
         if (opts.transposeA != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java
index bf663d42fcf..5f215d1e8b1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg.sparse;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -49,12 +49,12 @@ public final class CSRSparseMatrixComponents<T extends TType> extends RawOp {
    * @return a new instance of CSRSparseMatrixComponents
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> CSRSparseMatrixComponents<T> create(Scope scope, Operand<?> csrSparseMatrix, Operand<TInt32> index, DataType<T> type) {
+  public static <T extends TType> CSRSparseMatrixComponents<T> create(Scope scope, Operand<?> csrSparseMatrix, Operand<TInt32> index, Class<T> type) {
     OperationBuilder opBuilder = scope.env().opBuilder("CSRSparseMatrixComponents", scope.makeOpName("CSRSparseMatrixComponents"));
     opBuilder.addInput(csrSparseMatrix.asOutput());
     opBuilder.addInput(index.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("type", type);
+    opBuilder.setAttr("type", Operands.toDataType(type));
     return new CSRSparseMatrixComponents<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java
index 456464df341..2c42786fb53 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg.sparse;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -44,11 +44,11 @@ public final class CSRSparseMatrixToDense<T extends TType> extends RawOp impleme
    * @return a new instance of CSRSparseMatrixToDense
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> CSRSparseMatrixToDense<T> create(Scope scope, Operand<?> sparseInput, DataType<T> type) {
+  public static <T extends TType> CSRSparseMatrixToDense<T> create(Scope scope, Operand<?> sparseInput, Class<T> type) {
     OperationBuilder opBuilder = scope.env().opBuilder("CSRSparseMatrixToDense", scope.makeOpName("CSRSparseMatrixToDense"));
     opBuilder.addInput(sparseInput.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("type", type);
+    opBuilder.setAttr("type", Operands.toDataType(type));
     return new CSRSparseMatrixToDense<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java
index 8ac5ccfdf0b..3b88662432f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg.sparse;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -45,11 +45,11 @@ public final class CSRSparseMatrixToSparseTensor<T extends TType> extends RawOp
    * @return a new instance of CSRSparseMatrixToSparseTensor
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> CSRSparseMatrixToSparseTensor<T> create(Scope scope, Operand<?> sparseMatrix, DataType<T> type) {
+  public static <T extends TType> CSRSparseMatrixToSparseTensor<T> create(Scope scope, Operand<?> sparseMatrix, Class<T> type) {
     OperationBuilder opBuilder = scope.env().opBuilder("CSRSparseMatrixToSparseTensor", scope.makeOpName("CSRSparseMatrixToSparseTensor"));
     opBuilder.addInput(sparseMatrix.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("type", type);
+    opBuilder.setAttr("type", Operands.toDataType(type));
     return new CSRSparseMatrixToSparseTensor<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmax.java
index ae1f276fff8..973a63ade9d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmax.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg.sparse;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -49,11 +49,11 @@ public final class SparseMatrixSoftmax extends RawOp implements Operand<TType> {
    * @return a new instance of SparseMatrixSoftmax
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber> SparseMatrixSoftmax create(Scope scope, Operand<?> logits, DataType<T> type) {
+  public static <T extends TNumber> SparseMatrixSoftmax create(Scope scope, Operand<?> logits, Class<T> type) {
     OperationBuilder opBuilder = scope.env().opBuilder("SparseMatrixSoftmax", scope.makeOpName("SparseMatrixSoftmax"));
     opBuilder.addInput(logits.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("type", type);
+    opBuilder.setAttr("type", Operands.toDataType(type));
     return new SparseMatrixSoftmax(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmaxGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmaxGrad.java
index 14d3900cf9d..3de1b6edc1b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmaxGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSoftmaxGrad.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg.sparse;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -44,12 +44,12 @@ public final class SparseMatrixSoftmaxGrad extends RawOp implements Operand<TTyp
    * @return a new instance of SparseMatrixSoftmaxGrad
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber> SparseMatrixSoftmaxGrad create(Scope scope, Operand<?> softmax, Operand<?> gradSoftmax, DataType<T> type) {
+  public static <T extends TNumber> SparseMatrixSoftmaxGrad create(Scope scope, Operand<?> softmax, Operand<?> gradSoftmax, Class<T> type) {
     OperationBuilder opBuilder = scope.env().opBuilder("SparseMatrixSoftmaxGrad", scope.makeOpName("SparseMatrixSoftmaxGrad"));
     opBuilder.addInput(softmax.asOutput());
     opBuilder.addInput(gradSoftmax.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("type", type);
+    opBuilder.setAttr("type", Operands.toDataType(type));
     return new SparseMatrixSoftmaxGrad(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseCholesky.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseCholesky.java
index 1fc8703ac5c..91ec5e652a4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseCholesky.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseCholesky.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg.sparse;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -115,12 +115,12 @@ public final class SparseMatrixSparseCholesky extends RawOp implements Operand<T
    * @return a new instance of SparseMatrixSparseCholesky
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> SparseMatrixSparseCholesky create(Scope scope, Operand<?> input, Operand<TInt32> permutation, DataType<T> type) {
+  public static <T extends TType> SparseMatrixSparseCholesky create(Scope scope, Operand<?> input, Operand<TInt32> permutation, Class<T> type) {
     OperationBuilder opBuilder = scope.env().opBuilder("SparseMatrixSparseCholesky", scope.makeOpName("SparseMatrixSparseCholesky"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(permutation.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("type", type);
+    opBuilder.setAttr("type", Operands.toDataType(type));
     return new SparseMatrixSparseCholesky(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseMatMul.java
index c8d48b4269c..2e47c1ca6ab 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseMatMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixSparseMatMul.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg.sparse;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -163,12 +163,12 @@ private Options() {
    * @return a new instance of SparseMatrixSparseMatMul
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> SparseMatrixSparseMatMul create(Scope scope, Operand<?> a, Operand<?> b, DataType<T> type, Options... options) {
+  public static <T extends TType> SparseMatrixSparseMatMul create(Scope scope, Operand<?> a, Operand<?> b, Class<T> type, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("SparseMatrixSparseMatMul", scope.makeOpName("SparseMatrixSparseMatMul"));
     opBuilder.addInput(a.asOutput());
     opBuilder.addInput(b.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("type", type);
+    opBuilder.setAttr("type", Operands.toDataType(type));
     if (options != null) {
       for (Options opts : options) {
         if (opts.transposeA != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixTranspose.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixTranspose.java
index e4149a7195b..f1f71b33b4f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixTranspose.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixTranspose.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg.sparse;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -65,11 +65,11 @@ private Options() {
    * @return a new instance of SparseMatrixTranspose
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> SparseMatrixTranspose create(Scope scope, Operand<?> input, DataType<T> type, Options... options) {
+  public static <T extends TType> SparseMatrixTranspose create(Scope scope, Operand<?> input, Class<T> type, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("SparseMatrixTranspose", scope.makeOpName("SparseMatrixTranspose"));
     opBuilder.addInput(input.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("type", type);
+    opBuilder.setAttr("type", Operands.toDataType(type));
     if (options != null) {
       for (Options opts : options) {
         if (opts.conjugate != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixZeros.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixZeros.java
index c51571e054b..eea60f2298a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixZeros.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixZeros.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.linalg.sparse;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -43,11 +43,11 @@ public final class SparseMatrixZeros extends RawOp implements Operand<TType> {
    * @return a new instance of SparseMatrixZeros
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> SparseMatrixZeros create(Scope scope, Operand<TInt64> denseShape, DataType<T> type) {
+  public static <T extends TType> SparseMatrixZeros create(Scope scope, Operand<TInt64> denseShape, Class<T> type) {
     OperationBuilder opBuilder = scope.env().opBuilder("SparseMatrixZeros", scope.makeOpName("SparseMatrixZeros"));
     opBuilder.addInput(denseShape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("type", type);
+    opBuilder.setAttr("type", Operands.toDataType(type));
     return new SparseMatrixZeros(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java
index 32f68df69cc..dd31fbdc711 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the absolute value of a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java
index ed03e60c54c..9187006ac28 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.math;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -63,11 +63,11 @@ public final class Angle<U extends TNumber> extends RawOp implements Operand<U>
    * @return a new instance of Angle
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> Angle<U> create(Scope scope, Operand<T> input, DataType<U> Tout) {
+  public static <U extends TNumber, T extends TType> Angle<U> create(Scope scope, Operand<T> input, Class<U> Tout) {
     OperationBuilder opBuilder = scope.env().opBuilder("Angle", scope.makeOpName("Angle"));
     opBuilder.addInput(input.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Tout", Tout);
+    opBuilder.setAttr("Tout", Operands.toDataType(Tout));
     return new Angle<U>(opBuilder.build());
   }
   
@@ -80,7 +80,7 @@ public static <U extends TNumber, T extends TType> Angle<U> create(Scope scope,
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> Angle<TFloat32> create(Scope scope, Operand<T> input) {
-    return create(scope, input, TFloat32.DTYPE);
+    return create(scope, input, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java
index f21885ef002..2672a53fc83 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.math;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -63,12 +63,12 @@ public final class ArgMax<V extends TNumber> extends RawOp implements Operand<V>
    * @return a new instance of ArgMax
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TNumber, T extends TType, U extends TNumber> ArgMax<V> create(Scope scope, Operand<T> input, Operand<U> dimension, DataType<V> outputType) {
+  public static <V extends TNumber, T extends TType, U extends TNumber> ArgMax<V> create(Scope scope, Operand<T> input, Operand<U> dimension, Class<V> outputType) {
     OperationBuilder opBuilder = scope.env().opBuilder("ArgMax", scope.makeOpName("ArgMax"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(dimension.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("output_type", outputType);
+    opBuilder.setAttr("output_type", Operands.toDataType(outputType));
     return new ArgMax<V>(opBuilder.build());
   }
   
@@ -84,7 +84,7 @@ public static <V extends TNumber, T extends TType, U extends TNumber> ArgMax<V>
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType, U extends TNumber> ArgMax<TInt64> create(Scope scope, Operand<T> input, Operand<U> dimension) {
-    return create(scope, input, dimension, TInt64.DTYPE);
+    return create(scope, input, dimension, TInt64.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java
index 4df20c59ca9..be484929189 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.math;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -63,12 +63,12 @@ public final class ArgMin<V extends TNumber> extends RawOp implements Operand<V>
    * @return a new instance of ArgMin
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TNumber, T extends TType, U extends TNumber> ArgMin<V> create(Scope scope, Operand<T> input, Operand<U> dimension, DataType<V> outputType) {
+  public static <V extends TNumber, T extends TType, U extends TNumber> ArgMin<V> create(Scope scope, Operand<T> input, Operand<U> dimension, Class<V> outputType) {
     OperationBuilder opBuilder = scope.env().opBuilder("ArgMin", scope.makeOpName("ArgMin"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(dimension.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("output_type", outputType);
+    opBuilder.setAttr("output_type", Operands.toDataType(outputType));
     return new ArgMin<V>(opBuilder.build());
   }
   
@@ -84,7 +84,7 @@ public static <V extends TNumber, T extends TType, U extends TNumber> ArgMin<V>
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType, U extends TNumber> ArgMin<TInt64> create(Scope scope, Operand<T> input, Operand<U> dimension) {
-    return create(scope, input, dimension, TInt64.DTYPE);
+    return create(scope, input, dimension, TInt64.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java
index 1f6912eeaf0..e8ad73ca897 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes arctangent of `y/x` element-wise, respecting signs of the arguments.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java
index 1569151d185..ec9c56c199e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java
index 7d28d75e7be..26cfa68f377 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java
index 38d6c2bf2d2..4eb2b0d38da 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java
index 083ab146ff4..8eed4770299 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java
index f917f35ec86..86caad140d5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Compute the regularized incomplete beta integral \\(I_x(a, b)\\).
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java
index 6d666696e56..9e8f03af4cc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Counts the number of occurrences of each value in an integer array.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java
index cc1138a827a..ab36643898b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns element-wise smallest integer not less than x.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java
index dfbef1e184e..ce3c3607215 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.math;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -52,11 +52,11 @@ public final class ComplexAbs<U extends TNumber> extends RawOp implements Operan
    * @return a new instance of ComplexAbs
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> ComplexAbs<U> create(Scope scope, Operand<T> x, DataType<U> Tout) {
+  public static <U extends TNumber, T extends TType> ComplexAbs<U> create(Scope scope, Operand<T> x, Class<U> Tout) {
     OperationBuilder opBuilder = scope.env().opBuilder("ComplexAbs", scope.makeOpName("ComplexAbs"));
     opBuilder.addInput(x.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Tout", Tout);
+    opBuilder.setAttr("Tout", Operands.toDataType(Tout));
     return new ComplexAbs<U>(opBuilder.build());
   }
   
@@ -69,7 +69,7 @@ public static <U extends TNumber, T extends TType> ComplexAbs<U> create(Scope sc
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> ComplexAbs<TFloat32> create(Scope scope, Operand<T> x) {
-    return create(scope, x, TFloat32.DTYPE);
+    return create(scope, x, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java
index d0e285db1eb..4e53bb981c0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Compute the cumulative product of the tensor `x` along `axis`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java
index 786a0c93f6f..d6a9d95e4d8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Counts the number of occurrences of each value in an integer array.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java
index f26827cde84..c64f3b40f6d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes Psi, the derivative of Lgamma (the log of the absolute value of
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java
index 0df38217ffd..eb723c89f2a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the Gauss error function of `x` element-wise.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java
index 1e61da00dad..123ce651d03 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the complementary error function of `x` element-wise.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java
index d6664846c30..2fa22d7a60c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns element-wise largest integer not greater than x.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java
index 9c8706740fc..18c6c4fd34d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns element-wise remainder of division. When `x < 0` xor `y < 0` is
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Greater.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Greater.java
index 25d7249a489..3db7896647a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Greater.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Greater.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns the truth value of (x > y) element-wise.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/GreaterEqual.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/GreaterEqual.java
index 84905869eae..abeb67c3e66 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/GreaterEqual.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/GreaterEqual.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns the truth value of (x >= y) element-wise.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java
index ab0b7406aa9..7cb4c526e14 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Compute the lower regularized incomplete Gamma function `P(a, x)`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java
index 2be04b3b61f..e81622a3391 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the gradient of `igamma(a, x)` wrt `a`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java
index 24203335180..ab67c74b7b5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Compute the upper regularized incomplete Gamma function `Q(a, x)`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java
index ce2f523a282..a983a950dff 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.math;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -59,11 +59,11 @@ public final class Imag<U extends TNumber> extends RawOp implements Operand<U> {
    * @return a new instance of Imag
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> Imag<U> create(Scope scope, Operand<T> input, DataType<U> Tout) {
+  public static <U extends TNumber, T extends TType> Imag<U> create(Scope scope, Operand<T> input, Class<U> Tout) {
     OperationBuilder opBuilder = scope.env().opBuilder("Imag", scope.makeOpName("Imag"));
     opBuilder.addInput(input.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Tout", Tout);
+    opBuilder.setAttr("Tout", Operands.toDataType(Tout));
     return new Imag<U>(opBuilder.build());
   }
   
@@ -76,7 +76,7 @@ public static <U extends TNumber, T extends TType> Imag<U> create(Scope scope, O
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> Imag<TFloat32> create(Scope scope, Operand<T> input) {
-    return create(scope, input, TFloat32.DTYPE);
+    return create(scope, input, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java
index e24943d7b8f..04373176367 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the inverse permutation of a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsFinite.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsFinite.java
index 4d1abb1e31b..516f2330b39 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsFinite.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsFinite.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns which elements of x are finite.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsInf.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsInf.java
index a8638f0642a..ac1cf7946cc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsInf.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsInf.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns which elements of x are Inf.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsNan.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsNan.java
index e31e8ddf29e..f58f6a4aa38 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsNan.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IsNan.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns which elements of x are NaN.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Less.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Less.java
index 186a9b2b61e..9564f1b84ff 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Less.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Less.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns the truth value of (x < y) element-wise.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LessEqual.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LessEqual.java
index ae724a8c853..10c0b7647cb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LessEqual.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/LessEqual.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns the truth value of (x <= y) element-wise.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java
index 176eb94ede4..817993ef5c5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the log of the absolute value of `Gamma(x)` element-wise.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java
index 3f472f50956..e592e34e500 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns the max of x and y (i.e. x > y ? x : y) element-wise.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java
index 0e64109ed02..1c3ab3bb724 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns the min of x and y (i.e. x < y ? x : y) element-wise.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java
index de961916821..e8ead53a30d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns element-wise remainder of division. This emulates C semantics in that
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java
index 4c9af64e439..5e5f9d8b326 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java
index 96657da0c5e..ec8a0231618 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns the next representable value of `x1` in the direction of `x2`, element-wise.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java
index 5f236686689..f17bc4958b1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Compute the polygamma function \\(\psi^{(n)}(x)\\).
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/PopulationCount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/PopulationCount.java
index a9e7e157c5d..c3dfd8c23c9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/PopulationCount.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/PopulationCount.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TUint8;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes element-wise population count (a.k.a. popcount, bitsum, bitcount).
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java
index 3b0e3b7851e..ad4a7435e16 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.math;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -51,7 +51,7 @@ public final class QuantizedAdd<V extends TType> extends RawOp {
    * @return a new instance of QuantizedAdd
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedAdd<V> create(Scope scope, Operand<T> x, Operand<U> y, Operand<TFloat32> minX, Operand<TFloat32> maxX, Operand<TFloat32> minY, Operand<TFloat32> maxY, DataType<V> Toutput) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedAdd<V> create(Scope scope, Operand<T> x, Operand<U> y, Operand<TFloat32> minX, Operand<TFloat32> maxX, Operand<TFloat32> minY, Operand<TFloat32> maxY, Class<V> Toutput) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedAdd", scope.makeOpName("QuantizedAdd"));
     opBuilder.addInput(x.asOutput());
     opBuilder.addInput(y.asOutput());
@@ -60,7 +60,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedAdd<V
     opBuilder.addInput(minY.asOutput());
     opBuilder.addInput(maxY.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Toutput", Toutput);
+    opBuilder.setAttr("Toutput", Operands.toDataType(Toutput));
     return new QuantizedAdd<V>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java
index 47ea14523df..cc0a23b4a3c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.math;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -51,7 +51,7 @@ public final class QuantizedMul<V extends TType> extends RawOp {
    * @return a new instance of QuantizedMul
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedMul<V> create(Scope scope, Operand<T> x, Operand<U> y, Operand<TFloat32> minX, Operand<TFloat32> maxX, Operand<TFloat32> minY, Operand<TFloat32> maxY, DataType<V> Toutput) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedMul<V> create(Scope scope, Operand<T> x, Operand<U> y, Operand<TFloat32> minX, Operand<TFloat32> maxX, Operand<TFloat32> minY, Operand<TFloat32> maxY, Class<V> Toutput) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedMul", scope.makeOpName("QuantizedMul"));
     opBuilder.addInput(x.asOutput());
     opBuilder.addInput(y.asOutput());
@@ -60,7 +60,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedMul<V
     opBuilder.addInput(minY.asOutput());
     opBuilder.addInput(maxY.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Toutput", Toutput);
+    opBuilder.setAttr("Toutput", Operands.toDataType(Toutput));
     return new QuantizedMul<V>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java
index 44a4330129d..eba116d98f2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.math;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -59,11 +59,11 @@ public final class Real<U extends TNumber> extends RawOp implements Operand<U> {
    * @return a new instance of Real
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> Real<U> create(Scope scope, Operand<T> input, DataType<U> Tout) {
+  public static <U extends TNumber, T extends TType> Real<U> create(Scope scope, Operand<T> input, Class<U> Tout) {
     OperationBuilder opBuilder = scope.env().opBuilder("Real", scope.makeOpName("Real"));
     opBuilder.addInput(input.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Tout", Tout);
+    opBuilder.setAttr("Tout", Operands.toDataType(Tout));
     return new Real<U>(opBuilder.build());
   }
   
@@ -76,7 +76,7 @@ public static <U extends TNumber, T extends TType> Real<U> create(Scope scope, O
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> Real<TFloat32> create(Scope scope, Operand<T> input) {
-    return create(scope, input, TFloat32.DTYPE);
+    return create(scope, input, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java
index 092787d2300..d1263d29d2e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.math;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -49,7 +49,7 @@ public final class RequantizePerChannel<U extends TType> extends RawOp {
    * @return a new instance of RequantizePerChannel
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> RequantizePerChannel<U> create(Scope scope, Operand<T> input, Operand<TFloat32> inputMin, Operand<TFloat32> inputMax, Operand<TFloat32> requestedOutputMin, Operand<TFloat32> requestedOutputMax, DataType<U> outType) {
+  public static <U extends TType, T extends TType> RequantizePerChannel<U> create(Scope scope, Operand<T> input, Operand<TFloat32> inputMin, Operand<TFloat32> inputMax, Operand<TFloat32> requestedOutputMin, Operand<TFloat32> requestedOutputMax, Class<U> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("RequantizePerChannel", scope.makeOpName("RequantizePerChannel"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(inputMin.asOutput());
@@ -57,7 +57,7 @@ public static <U extends TType, T extends TType> RequantizePerChannel<U> create(
     opBuilder.addInput(requestedOutputMin.asOutput());
     opBuilder.addInput(requestedOutputMax.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new RequantizePerChannel<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java
index 000014596d4..1de8f528899 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns element-wise integer closest to x.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java
index 824c509b390..8c0d4238d3f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the maximum along segments of a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java
index ea4df712929..19ab9059871 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the minimum along segments of a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java
index 674448c5325..5424188a9a6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.math;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -29,7 +29,6 @@
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Generates points from the Sobol sequence.
@@ -54,13 +53,13 @@ public final class SobolSample<T extends TNumber> extends RawOp implements Opera
    * @return a new instance of SobolSample
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber> SobolSample<T> create(Scope scope, Operand<TInt32> dim, Operand<TInt32> numResults, Operand<TInt32> skip, DataType<T> dtype) {
+  public static <T extends TNumber> SobolSample<T> create(Scope scope, Operand<TInt32> dim, Operand<TInt32> numResults, Operand<TInt32> skip, Class<T> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("SobolSample", scope.makeOpName("SobolSample"));
     opBuilder.addInput(dim.asOutput());
     opBuilder.addInput(numResults.asOutput());
     opBuilder.addInput(skip.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new SobolSample<T>(opBuilder.build());
   }
   
@@ -77,7 +76,7 @@ public static <T extends TNumber> SobolSample<T> create(Scope scope, Operand<TIn
    */
   @Endpoint(describeByClass = true)
   public static SobolSample<TFloat32> create(Scope scope, Operand<TInt32> dim, Operand<TInt32> numResults, Operand<TInt32> skip) {
-    return create(scope, dim, numResults, skip, TFloat32.DTYPE);
+    return create(scope, dim, numResults, skip, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java
index 1f1d84bb394..1014467d255 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes softplus: `log(exp(features) + 1)`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java
index f46ebfc0c30..e3582acab64 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes softplus gradients for a softplus operation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java
index 9a737a40101..9419e0db0e4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns element-wise remainder of division. This emulates C semantics in that
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMax.java
index 8f6b834fceb..efaaf2dea96 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMax.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the maximum along segments of a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java
index 2f9eadff306..e73ec14aa1b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the minimum along segments of a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java
index b923c8671f6..73c290262c8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Compute the Hurwitz zeta function \\(\zeta(x, q)\\).
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java
index 9d4324aa5c7..cfa2adab329 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java
index 00ea6ba2590..597e82504d0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java
index 6b37411908f..0e05c32334d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java
index fa35c222824..ae0586d549c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java
index f24d8b24126..e4a677d2f1a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java
index 89bf309b636..bcdd407508b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java
index fbd6c2a7aa4..c5824c47cbd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java
index ab10c5bb5c2..03c8c1ade60 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java
index 507a4cadbbe..92a7561ee8a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java
index cded11af606..9e50d639d02 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java
index 2dff32ad8ef..8cff09b15c3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java
index 86a507a30a8..f3d0848f814 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java
index 1e14aa97198..33d738bf9fd 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java
index 14515106925..39a3c134ebb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <T> data type for {@code y()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java
index 2586bc9d248..77fb90557ec 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Performs average pooling on the input.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java
index e1f7341dd14..7b675fc816e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Performs 3D average pooling on the input.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java
index 252be1aafb7..96ad463e8aa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes gradients of average pooling function.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPoolGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPoolGrad.java
index c8bc81a45b5..585f72414e1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPoolGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPoolGrad.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes gradients of the average pooling function.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java
index b290b029683..9b1b33daee8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the LSTM cell forward propagation for all the time steps.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java
index 45bec4954b8..f7f0c2449d4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the LSTM cell backward propagation for the entire time sequence.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java
index 312aa16796d..e3d98fe0882 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes a 2-D convolution given 4-D `input` and `filter` tensors.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java
index 2cfdaa08a6c..bc282d8b349 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the gradients of convolution with respect to the filter.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java
index dafc1789740..3b43fa3301d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the gradients of convolution with respect to the input.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java
index 563958a8710..b778819c0ce 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes a 3-D convolution given 5-D `input` and `filter` tensors.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java
index 2ca19483b4f..6ec7dd5b71a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the gradients of 3-D convolution with respect to the filter.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java
index a7069f560d0..0d6c1792495 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the gradients of 3-D convolution with respect to the input.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java
index 9f21dfce317..6fb3ae265f4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java
@@ -30,7 +30,6 @@
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Performs beam search decoding on the logits given in input.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java
index db0020e6ee4..2e22105a783 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java
@@ -28,7 +28,6 @@
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Performs greedy decoding on the logits given in inputs.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java
index 155881c8034..1ea61f47a0b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java
@@ -28,7 +28,6 @@
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Calculates the CTC Loss (log probability) for each batch entry.  Also calculates
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java
index 418df889760..12e94a102f6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * A RNN backed by cuDNN.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java
index 9d440d46895..78a08d58328 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Backprop step of CudnnRNNV3.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java
index 65382bfe14c..2c5c451fac8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Converts CudnnRNN params from canonical form to usable form. It supports the projection in LSTM.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java
index bf070e2b602..adf30df3312 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java
@@ -29,7 +29,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Retrieves CudnnRNN params in canonical form. It supports the projection in LSTM.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java
index fc6221112d1..14dcc23a10e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java
@@ -17,18 +17,17 @@
 
 package org.tensorflow.op.nn;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes size of weights that can be used by a Cudnn RNN model.
@@ -146,14 +145,14 @@ private Options() {
    * @return a new instance of CudnnRnnParamsSize
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TNumber> CudnnRnnParamsSize<U> create(Scope scope, Operand<TInt32> numLayers, Operand<TInt32> numUnits, Operand<TInt32> inputSize, DataType<T> T, DataType<U> S, Options... options) {
+  public static <U extends TNumber, T extends TNumber> CudnnRnnParamsSize<U> create(Scope scope, Operand<TInt32> numLayers, Operand<TInt32> numUnits, Operand<TInt32> inputSize, Class<T> T, Class<U> S, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("CudnnRNNParamsSize", scope.makeOpName("CudnnRnnParamsSize"));
     opBuilder.addInput(numLayers.asOutput());
     opBuilder.addInput(numUnits.asOutput());
     opBuilder.addInput(inputSize.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("T", T);
-    opBuilder.setAttr("S", S);
+    opBuilder.setAttr("T", Operands.toDataType(T));
+    opBuilder.setAttr("S", Operands.toDataType(S));
     if (options != null) {
       for (Options opts : options) {
         if (opts.rnnMode != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java
index 36e93d0275e..115a5bb12d8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns the dimension index in the destination data format given the one in
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java
index f683175840d..6f8799f0e68 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns the permuted vector/tensor in the destination data format given the
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java
index 4b90f9e2e61..8420a6524dc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes a 2-D depthwise convolution given 4-D `input` and `filter` tensors.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java
index 9fbc1c64cdc..3825826677b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the gradients of depthwise convolution with respect to the filter.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java
index e8bed246669..35f10aaed5d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the gradients of depthwise convolution with respect to the input.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java
index e5ce7139ecb..d87f33ca07f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the grayscale dilation of 4-D `input` and 3-D `filter` tensors.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java
index 327646fbb15..c4e1d45a440 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the gradient of morphological 2-D dilation with respect to the filter.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropInput.java
index a546990717b..3f6bb100bc5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropInput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropInput.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the gradient of morphological 2-D dilation with respect to the input.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Elu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Elu.java
index 2de2a4230fc..86012a4c4ef 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Elu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Elu.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes exponential linear: `exp(features) - 1` if < 0, `features` otherwise.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java
index 80905bdafc0..4771374123e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes gradients for the exponential linear (Elu) operation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java
index 6eef240adab..a9bddf8774c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Performs fractional average pooling on the input.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java
index 8c84128977f..094ce640a09 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes gradient of the FractionalAvgPool function.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java
index c05d2b19f05..86c7e204757 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Performs fractional max pooling on the input.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java
index 939e1cb1d20..e059e233e05 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes gradient of the FractionalMaxPool function.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java
index 7ca906dd6e8..29a6c2bdad3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Batch normalization.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java
index c1e01556128..aa8d3b94b99 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Gradient for batch normalization.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java
index 74d3caeb6f3..db1a7dac897 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Performs a padding as a preprocess during a convolution.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedResizeAndPadConv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedResizeAndPadConv2d.java
index 4694a56caba..1bc106ee063 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedResizeAndPadConv2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedResizeAndPadConv2d.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Performs a resize and padding as a preprocess during a convolution.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCell.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCell.java
index a25a1ccd584..19ee4709eb8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCell.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCell.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the GRU cell forward propagation for 1 time step.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java
index 823658a8df5..16d2efc3dd5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the GRU cell back-propagation for 1 time step.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InTopK.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InTopK.java
index 9df615a2106..bdf5f761d1a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InTopK.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InTopK.java
@@ -28,7 +28,6 @@
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Says whether the targets are in the top `K` predictions.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java
index 8c30f10a3df..45856e6c255 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * L2 Loss.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java
index 666d0645290..ad144fed082 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the LSTM cell forward propagation for 1 time step.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java
index 26df5317669..6bcf274af61 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the LSTM cell backward propagation for 1 timestep.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java
index ba090ab23d7..2016d3a6abb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes rectified linear: `max(features, features * alpha)`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java
index 858201caee2..1e28dd0ee14 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Local Response Normalization.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java
index d83b0e75975..51915dc43a7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Gradients for Local Response Normalization.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java
index 3fe2e55871f..75addd4b6a8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes log softmax activations.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java
index 63ee208be62..bb802045fc4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Performs 3D max pooling on the input.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java
index 213f4fefb03..12966ef1c04 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes gradients of 3D max pooling function.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java
index cddc0186e5d..1153cc1fb68 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes second-order gradients of the maxpooling function.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGrad.java
index 985d6fa1214..58bcd623533 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGrad.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes gradients of the maxpooling function.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java
index 8138cc51206..84ad249f82d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes second-order gradients of the maxpooling function.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGradWithArgmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGradWithArgmax.java
index 59794d0adfb..5b4af53845d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGradWithArgmax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGradWithArgmax.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes second-order gradients of the maxpooling function.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradWithArgmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradWithArgmax.java
index 75c814d293b..ef9af71cb95 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradWithArgmax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradWithArgmax.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes gradients of the maxpooling function.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java
index 29c3a7a627c..f269753c21b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolWithArgmax.java
@@ -18,18 +18,17 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Performs max pooling on the input and outputs both max values and indices.
@@ -83,7 +82,7 @@ private Options() {
    * @return a new instance of MaxPoolWithArgmax
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber, U extends TNumber> MaxPoolWithArgmax<T, U> create(Scope scope, Operand<T> input, List<Long> ksize, List<Long> strides, DataType<U> Targmax, String padding, Options... options) {
+  public static <T extends TNumber, U extends TNumber> MaxPoolWithArgmax<T, U> create(Scope scope, Operand<T> input, List<Long> ksize, List<Long> strides, Class<U> Targmax, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("MaxPoolWithArgmax", scope.makeOpName("MaxPoolWithArgmax"));
     opBuilder.addInput(input.asOutput());
     opBuilder = scope.apply(opBuilder);
@@ -97,7 +96,7 @@ public static <T extends TNumber, U extends TNumber> MaxPoolWithArgmax<T, U> cre
       stridesArray[i] = strides.get(i);
     }
     opBuilder.setAttr("strides", stridesArray);
-    opBuilder.setAttr("Targmax", Targmax);
+    opBuilder.setAttr("Targmax", Operands.toDataType(Targmax));
     opBuilder.setAttr("padding", padding);
     if (options != null) {
       for (Options opts : options) {
@@ -123,7 +122,7 @@ public static <T extends TNumber, U extends TNumber> MaxPoolWithArgmax<T, U> cre
    */
   @Endpoint(describeByClass = true)
   public static <T extends TNumber> MaxPoolWithArgmax<T, TInt64> create(Scope scope, Operand<T> input, List<Long> ksize, List<Long> strides, String padding, Options... options) {
-    return create(scope, input, ksize, strides, TInt64.DTYPE, padding, options);
+    return create(scope, input, ksize, strides, TInt64.class, padding, options);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/NthElement.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/NthElement.java
index 2c787751fff..9ea182bb4e5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/NthElement.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/NthElement.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Finds values of the `n`-th order statistic for the last dimension.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java
index 97d2aced9b7..60f242ef636 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.nn;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -73,7 +73,7 @@ public final class QuantizedBatchNormWithGlobalNormalization<U extends TType> ex
    * @return a new instance of QuantizedBatchNormWithGlobalNormalization
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> QuantizedBatchNormWithGlobalNormalization<U> create(Scope scope, Operand<T> t, Operand<TFloat32> tMin, Operand<TFloat32> tMax, Operand<T> m, Operand<TFloat32> mMin, Operand<TFloat32> mMax, Operand<T> v, Operand<TFloat32> vMin, Operand<TFloat32> vMax, Operand<T> beta, Operand<TFloat32> betaMin, Operand<TFloat32> betaMax, Operand<T> gamma, Operand<TFloat32> gammaMin, Operand<TFloat32> gammaMax, DataType<U> outType, Float varianceEpsilon, Boolean scaleAfterNormalization) {
+  public static <U extends TType, T extends TType> QuantizedBatchNormWithGlobalNormalization<U> create(Scope scope, Operand<T> t, Operand<TFloat32> tMin, Operand<TFloat32> tMax, Operand<T> m, Operand<TFloat32> mMin, Operand<TFloat32> mMax, Operand<T> v, Operand<TFloat32> vMin, Operand<TFloat32> vMax, Operand<T> beta, Operand<TFloat32> betaMin, Operand<TFloat32> betaMax, Operand<T> gamma, Operand<TFloat32> gammaMin, Operand<TFloat32> gammaMax, Class<U> outType, Float varianceEpsilon, Boolean scaleAfterNormalization) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedBatchNormWithGlobalNormalization", scope.makeOpName("QuantizedBatchNormWithGlobalNormalization"));
     opBuilder.addInput(t.asOutput());
     opBuilder.addInput(tMin.asOutput());
@@ -91,7 +91,7 @@ public static <U extends TType, T extends TType> QuantizedBatchNormWithGlobalNor
     opBuilder.addInput(gammaMin.asOutput());
     opBuilder.addInput(gammaMax.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     opBuilder.setAttr("variance_epsilon", varianceEpsilon);
     opBuilder.setAttr("scale_after_normalization", scaleAfterNormalization);
     return new QuantizedBatchNormWithGlobalNormalization<U>(opBuilder.build());
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java
index 89171c3bc15..05e2ec67aa5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.nn;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -53,7 +53,7 @@ public final class QuantizedBiasAdd<V extends TType> extends RawOp {
    * @return a new instance of QuantizedBiasAdd
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedBiasAdd<V> create(Scope scope, Operand<T> input, Operand<U> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minBias, Operand<TFloat32> maxBias, DataType<V> outType) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedBiasAdd<V> create(Scope scope, Operand<T> input, Operand<U> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minBias, Operand<TFloat32> maxBias, Class<V> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedBiasAdd", scope.makeOpName("QuantizedBiasAdd"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(bias.asOutput());
@@ -62,7 +62,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedBiasA
     opBuilder.addInput(minBias.asOutput());
     opBuilder.addInput(maxBias.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new QuantizedBiasAdd<V>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java
index 516b4d762f1..89aee4bd5f5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -80,7 +80,7 @@ private Options() {
    * @return a new instance of QuantizedConv2DAndRelu
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2DAndRelu<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, DataType<V> outType, List<Long> strides, String padding, Options... options) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2DAndRelu<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Class<V> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedConv2DAndRelu", scope.makeOpName("QuantizedConv2DAndRelu"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -89,7 +89,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedConv2
     opBuilder.addInput(minFilter.asOutput());
     opBuilder.addInput(maxFilter.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java
index 99f10f69ad4..513a9b240e5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -82,7 +82,7 @@ private Options() {
    * @return a new instance of QuantizedConv2DAndReluAndRequantize
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2DAndReluAndRequantize<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, DataType<V> outType, List<Long> strides, String padding, Options... options) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2DAndReluAndRequantize<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, Class<V> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedConv2DAndReluAndRequantize", scope.makeOpName("QuantizedConv2DAndReluAndRequantize"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -93,7 +93,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedConv2
     opBuilder.addInput(minFreezedOutput.asOutput());
     opBuilder.addInput(maxFreezedOutput.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java
index f1531565cee..80a1ddf146a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -82,7 +82,7 @@ private Options() {
    * @return a new instance of QuantizedConv2DAndRequantize
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2DAndRequantize<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, DataType<V> outType, List<Long> strides, String padding, Options... options) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2DAndRequantize<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, Class<V> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedConv2DAndRequantize", scope.makeOpName("QuantizedConv2DAndRequantize"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -93,7 +93,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedConv2
     opBuilder.addInput(minFreezedOutput.asOutput());
     opBuilder.addInput(maxFreezedOutput.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java
index adb0975e3ef..f51143d15be 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -73,7 +73,7 @@ private Options() {
    * @return a new instance of QuantizedConv2DPerChannel
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2DPerChannel<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, DataType<V> outType, List<Long> strides, String padding, Options... options) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2DPerChannel<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Class<V> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedConv2DPerChannel", scope.makeOpName("QuantizedConv2DPerChannel"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -82,7 +82,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedConv2
     opBuilder.addInput(minFilter.asOutput());
     opBuilder.addInput(maxFilter.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java
index 8411f5e30ec..c579e306102 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -81,7 +81,7 @@ private Options() {
    * @return a new instance of QuantizedConv2DWithBias
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2DWithBias<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, DataType<V> outType, List<Long> strides, String padding, Options... options) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2DWithBias<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Class<V> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedConv2DWithBias", scope.makeOpName("QuantizedConv2DWithBias"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -91,7 +91,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedConv2
     opBuilder.addInput(minFilter.asOutput());
     opBuilder.addInput(maxFilter.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java
index d204bd9e6ec..ac9672e9f94 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -81,7 +81,7 @@ private Options() {
    * @return a new instance of QuantizedConv2DWithBiasAndRelu
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2DWithBiasAndRelu<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, DataType<V> outType, List<Long> strides, String padding, Options... options) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2DWithBiasAndRelu<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Class<V> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedConv2DWithBiasAndRelu", scope.makeOpName("QuantizedConv2DWithBiasAndRelu"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -91,7 +91,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedConv2
     opBuilder.addInput(minFilter.asOutput());
     opBuilder.addInput(maxFilter.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java
index dd3f8d7cd05..084f211be2c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -83,7 +83,7 @@ private Options() {
    * @return a new instance of QuantizedConv2DWithBiasAndReluAndRequantize
    */
   @Endpoint(describeByClass = true)
-  public static <W extends TType, T extends TType, U extends TType, V extends TType> QuantizedConv2DWithBiasAndReluAndRequantize<W> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<V> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, DataType<W> outType, List<Long> strides, String padding, Options... options) {
+  public static <W extends TType, T extends TType, U extends TType, V extends TType> QuantizedConv2DWithBiasAndReluAndRequantize<W> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<V> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, Class<W> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedConv2DWithBiasAndReluAndRequantize", scope.makeOpName("QuantizedConv2DWithBiasAndReluAndRequantize"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -95,7 +95,7 @@ public static <W extends TType, T extends TType, U extends TType, V extends TTyp
     opBuilder.addInput(minFreezedOutput.asOutput());
     opBuilder.addInput(maxFreezedOutput.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java
index 57906b25ba5..9a31f82454b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -83,7 +83,7 @@ private Options() {
    * @return a new instance of QuantizedConv2DWithBiasAndRequantize
    */
   @Endpoint(describeByClass = true)
-  public static <W extends TType, T extends TType, U extends TType, V extends TType> QuantizedConv2DWithBiasAndRequantize<W> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<V> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, DataType<W> outType, List<Long> strides, String padding, Options... options) {
+  public static <W extends TType, T extends TType, U extends TType, V extends TType> QuantizedConv2DWithBiasAndRequantize<W> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<V> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, Class<W> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedConv2DWithBiasAndRequantize", scope.makeOpName("QuantizedConv2DWithBiasAndRequantize"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -95,7 +95,7 @@ public static <W extends TType, T extends TType, U extends TType, V extends TTyp
     opBuilder.addInput(minFreezedOutput.asOutput());
     opBuilder.addInput(maxFreezedOutput.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java
index 307232481ab..5d005ac1f9e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -86,7 +86,7 @@ private Options() {
    * @return a new instance of QuantizedConv2DWithBiasSignedSumAndReluAndRequantize
    */
   @Endpoint(describeByClass = true)
-  public static <X extends TType, T extends TType, U extends TType, V extends TType, W extends TType> QuantizedConv2DWithBiasSignedSumAndReluAndRequantize<X> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<V> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, Operand<W> summand, Operand<TFloat32> minSummand, Operand<TFloat32> maxSummand, DataType<X> outType, List<Long> strides, String padding, Options... options) {
+  public static <X extends TType, T extends TType, U extends TType, V extends TType, W extends TType> QuantizedConv2DWithBiasSignedSumAndReluAndRequantize<X> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<V> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, Operand<W> summand, Operand<TFloat32> minSummand, Operand<TFloat32> maxSummand, Class<X> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedConv2DWithBiasSignedSumAndReluAndRequantize", scope.makeOpName("QuantizedConv2DWithBiasSignedSumAndReluAndRequantize"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -101,7 +101,7 @@ public static <X extends TType, T extends TType, U extends TType, V extends TTyp
     opBuilder.addInput(minSummand.asOutput());
     opBuilder.addInput(maxSummand.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java
index 148909cf77d..dffeac89c25 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -82,7 +82,7 @@ private Options() {
    * @return a new instance of QuantizedConv2DWithBiasSumAndRelu
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2DWithBiasSumAndRelu<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> summand, DataType<V> outType, List<Long> strides, String padding, Options... options) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2DWithBiasSumAndRelu<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> summand, Class<V> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedConv2DWithBiasSumAndRelu", scope.makeOpName("QuantizedConv2DWithBiasSumAndRelu"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -93,7 +93,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedConv2
     opBuilder.addInput(maxFilter.asOutput());
     opBuilder.addInput(summand.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java
index 953cf2cddbe..68052783adb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -86,7 +86,7 @@ private Options() {
    * @return a new instance of QuantizedConv2DWithBiasSumAndReluAndRequantize
    */
   @Endpoint(describeByClass = true)
-  public static <X extends TType, T extends TType, U extends TType, V extends TType, W extends TType> QuantizedConv2DWithBiasSumAndReluAndRequantize<X> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<V> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, Operand<W> summand, Operand<TFloat32> minSummand, Operand<TFloat32> maxSummand, DataType<X> outType, List<Long> strides, String padding, Options... options) {
+  public static <X extends TType, T extends TType, U extends TType, V extends TType, W extends TType> QuantizedConv2DWithBiasSumAndReluAndRequantize<X> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<V> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, Operand<W> summand, Operand<TFloat32> minSummand, Operand<TFloat32> maxSummand, Class<X> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedConv2DWithBiasSumAndReluAndRequantize", scope.makeOpName("QuantizedConv2DWithBiasSumAndReluAndRequantize"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -101,7 +101,7 @@ public static <X extends TType, T extends TType, U extends TType, V extends TTyp
     opBuilder.addInput(minSummand.asOutput());
     opBuilder.addInput(maxSummand.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java
index 2bbcade7f7e..6e6788db7aa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -84,7 +84,7 @@ private Options() {
    * @return a new instance of QuantizedConv2d
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2d<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, DataType<V> outType, List<Long> strides, String padding, Options... options) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedConv2d<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Class<V> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedConv2D", scope.makeOpName("QuantizedConv2d"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -93,7 +93,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedConv2
     opBuilder.addInput(minFilter.asOutput());
     opBuilder.addInput(maxFilter.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java
index ca98dc872ad..7dae76d87bc 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -73,7 +73,7 @@ private Options() {
    * @return a new instance of QuantizedDepthwiseConv2D
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedDepthwiseConv2D<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, DataType<V> outType, List<Long> strides, String padding, Options... options) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedDepthwiseConv2D<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Class<V> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedDepthwiseConv2D", scope.makeOpName("QuantizedDepthwiseConv2D"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -82,7 +82,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedDepth
     opBuilder.addInput(minFilter.asOutput());
     opBuilder.addInput(maxFilter.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java
index bd2fe163ed6..fc7f07525af 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -74,7 +74,7 @@ private Options() {
    * @return a new instance of QuantizedDepthwiseConv2DWithBias
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedDepthwiseConv2DWithBias<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, DataType<V> outType, List<Long> strides, String padding, Options... options) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedDepthwiseConv2DWithBias<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Class<V> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedDepthwiseConv2DWithBias", scope.makeOpName("QuantizedDepthwiseConv2DWithBias"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -84,7 +84,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedDepth
     opBuilder.addInput(minFilter.asOutput());
     opBuilder.addInput(maxFilter.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java
index 5726f9af259..c16b3c91a0e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -83,7 +83,7 @@ private Options() {
    * @return a new instance of QuantizedDepthwiseConv2DWithBiasAndRelu
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TType, T extends TType, U extends TType> QuantizedDepthwiseConv2DWithBiasAndRelu<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, DataType<V> outType, List<Long> strides, String padding, Options... options) {
+  public static <V extends TType, T extends TType, U extends TType> QuantizedDepthwiseConv2DWithBiasAndRelu<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<TFloat32> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Class<V> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedDepthwiseConv2DWithBiasAndRelu", scope.makeOpName("QuantizedDepthwiseConv2DWithBiasAndRelu"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -93,7 +93,7 @@ public static <V extends TType, T extends TType, U extends TType> QuantizedDepth
     opBuilder.addInput(minFilter.asOutput());
     opBuilder.addInput(maxFilter.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java
index 073e4f0305b..02dccc28354 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java
@@ -18,11 +18,11 @@
 package org.tensorflow.op.nn;
 
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -85,7 +85,7 @@ private Options() {
    * @return a new instance of QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize
    */
   @Endpoint(describeByClass = true)
-  public static <W extends TType, T extends TType, U extends TType, V extends TType> QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize<W> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<V> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, DataType<W> outType, List<Long> strides, String padding, Options... options) {
+  public static <W extends TType, T extends TType, U extends TType, V extends TType> QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize<W> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<V> bias, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, Operand<TFloat32> minFilter, Operand<TFloat32> maxFilter, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, Class<W> outType, List<Long> strides, String padding, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize", scope.makeOpName("QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(filter.asOutput());
@@ -97,7 +97,7 @@ public static <W extends TType, T extends TType, U extends TType, V extends TTyp
     opBuilder.addInput(minFreezedOutput.asOutput());
     opBuilder.addInput(maxFreezedOutput.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     long[] stridesArray = new long[strides.size()];
     for (int i = 0; i < stridesArray.length; ++i) {
       stridesArray[i] = strides.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java
index 2ad17aa0ab7..56b755f2a71 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.nn;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -48,13 +48,13 @@ public final class QuantizedRelu<U extends TType> extends RawOp {
    * @return a new instance of QuantizedRelu
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> QuantizedRelu<U> create(Scope scope, Operand<T> features, Operand<TFloat32> minFeatures, Operand<TFloat32> maxFeatures, DataType<U> outType) {
+  public static <U extends TType, T extends TType> QuantizedRelu<U> create(Scope scope, Operand<T> features, Operand<TFloat32> minFeatures, Operand<TFloat32> maxFeatures, Class<U> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedRelu", scope.makeOpName("QuantizedRelu"));
     opBuilder.addInput(features.asOutput());
     opBuilder.addInput(minFeatures.asOutput());
     opBuilder.addInput(maxFeatures.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new QuantizedRelu<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java
index 33276f514b3..2f99d1ab861 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.nn;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -48,13 +48,13 @@ public final class QuantizedRelu6<U extends TType> extends RawOp {
    * @return a new instance of QuantizedRelu6
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> QuantizedRelu6<U> create(Scope scope, Operand<T> features, Operand<TFloat32> minFeatures, Operand<TFloat32> maxFeatures, DataType<U> outType) {
+  public static <U extends TType, T extends TType> QuantizedRelu6<U> create(Scope scope, Operand<T> features, Operand<TFloat32> minFeatures, Operand<TFloat32> maxFeatures, Class<U> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedRelu6", scope.makeOpName("QuantizedRelu6"));
     opBuilder.addInput(features.asOutput());
     opBuilder.addInput(minFeatures.asOutput());
     opBuilder.addInput(maxFeatures.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new QuantizedRelu6<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java
index d20e5cd6934..afd943b7595 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.nn;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -49,14 +49,14 @@ public final class QuantizedReluX<U extends TType> extends RawOp {
    * @return a new instance of QuantizedReluX
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> QuantizedReluX<U> create(Scope scope, Operand<T> features, Operand<TFloat32> maxValue, Operand<TFloat32> minFeatures, Operand<TFloat32> maxFeatures, DataType<U> outType) {
+  public static <U extends TType, T extends TType> QuantizedReluX<U> create(Scope scope, Operand<T> features, Operand<TFloat32> maxValue, Operand<TFloat32> minFeatures, Operand<TFloat32> maxFeatures, Class<U> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedReluX", scope.makeOpName("QuantizedReluX"));
     opBuilder.addInput(features.asOutput());
     opBuilder.addInput(maxValue.asOutput());
     opBuilder.addInput(minFeatures.asOutput());
     opBuilder.addInput(maxFeatures.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new QuantizedReluX<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java
index ca05ffc74c5..efb80c73be6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes rectified linear 6: `min(max(features, 0), 6)`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java
index 6408b81970c..38e042b1635 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes rectified linear 6 gradients for a Relu6 operation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java
index 3ea222907ef..27999096f0e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes rectified linear gradients for a Relu operation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java
index a90097c263c..0e7b45fcd6a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes scaled exponential linear: `scale * alpha * (exp(features) - 1)`
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java
index 8ced5023316..e80b0e7114b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes gradients for the scaled exponential linear (Selu) operation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java
index 549f3f9ad92..d7180ef953f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes softmax activations.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java
index acc3fc20ca8..efd21d04476 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes softsign: `features / (abs(features) + 1)`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java
index 2f9f5a911e6..a8d5669551d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes softsign gradients for a softsign operation.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java
index f0c37766115..d86357aa90d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Finds values and indices of the `k` largest elements for the last dimension.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SoftmaxCrossEntropyWithLogits.java
index c1adf5358d6..8032a4c2512 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SoftmaxCrossEntropyWithLogits.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SoftmaxCrossEntropyWithLogits.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes softmax cross entropy cost and gradients to backpropagate.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SparseSoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SparseSoftmaxCrossEntropyWithLogits.java
index 54ed2d30c95..6cbd4fddeb1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SparseSoftmaxCrossEntropyWithLogits.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/raw/SparseSoftmaxCrossEntropyWithLogits.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes softmax cross entropy cost and gradients to backpropagate.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Dequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Dequantize.java
index 3f53e0b5bc7..19c738bc721 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Dequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Dequantize.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.quantization;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -137,13 +137,13 @@ private Options() {
    * @return a new instance of Dequantize
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> Dequantize<U> create(Scope scope, Operand<T> input, Operand<TFloat32> minRange, Operand<TFloat32> maxRange, DataType<U> dtype, Options... options) {
+  public static <U extends TNumber, T extends TType> Dequantize<U> create(Scope scope, Operand<T> input, Operand<TFloat32> minRange, Operand<TFloat32> maxRange, Class<U> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("Dequantize", scope.makeOpName("Dequantize"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(minRange.asOutput());
     opBuilder.addInput(maxRange.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.mode != null) {
@@ -172,7 +172,7 @@ public static <U extends TNumber, T extends TType> Dequantize<U> create(Scope sc
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> Dequantize<TFloat32> create(Scope scope, Operand<T> input, Operand<TFloat32> minRange, Operand<TFloat32> maxRange, Options... options) {
-    return create(scope, input, minRange, maxRange, TFloat32.DTYPE, options);
+    return create(scope, input, minRange, maxRange, TFloat32.class, options);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java
index a310df7317e..edab6594b2c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.quantization;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -220,13 +220,13 @@ private Options() {
    * @return a new instance of Quantize
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> Quantize<T> create(Scope scope, Operand<TFloat32> input, Operand<TFloat32> minRange, Operand<TFloat32> maxRange, DataType<T> T, Options... options) {
+  public static <T extends TType> Quantize<T> create(Scope scope, Operand<TFloat32> input, Operand<TFloat32> minRange, Operand<TFloat32> maxRange, Class<T> T, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizeV2", scope.makeOpName("Quantize"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(minRange.asOutput());
     opBuilder.addInput(maxRange.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("T", T);
+    opBuilder.setAttr("T", Operands.toDataType(T));
     if (options != null) {
       for (Options opts : options) {
         if (opts.mode != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java
index e587abc87ac..d66ff6c4871 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Quantizes then dequantizes a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java
index 35952c74490..5430dbc69ca 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.quantization;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -71,13 +71,13 @@ public final class QuantizeDownAndShrinkRange<U extends TType> extends RawOp {
    * @return a new instance of QuantizeDownAndShrinkRange
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> QuantizeDownAndShrinkRange<U> create(Scope scope, Operand<T> input, Operand<TFloat32> inputMin, Operand<TFloat32> inputMax, DataType<U> outType) {
+  public static <U extends TType, T extends TType> QuantizeDownAndShrinkRange<U> create(Scope scope, Operand<T> input, Operand<TFloat32> inputMin, Operand<TFloat32> inputMax, Class<U> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizeDownAndShrinkRange", scope.makeOpName("QuantizeDownAndShrinkRange"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(inputMin.asOutput());
     opBuilder.addInput(inputMax.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new QuantizeDownAndShrinkRange<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java
index f47477719f5..e925c15546b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.quantization;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -90,7 +90,7 @@ private Options() {
    * @return a new instance of QuantizedMatMulWithBiasAndDequantize
    */
   @Endpoint(describeByClass = true)
-  public static <W extends TNumber, T extends TType, U extends TType, V extends TType> QuantizedMatMulWithBiasAndDequantize<W> create(Scope scope, Operand<T> a, Operand<U> b, Operand<V> bias, Operand<TFloat32> minA, Operand<TFloat32> maxA, Operand<TFloat32> minB, Operand<TFloat32> maxB, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, DataType<W> Toutput, Options... options) {
+  public static <W extends TNumber, T extends TType, U extends TType, V extends TType> QuantizedMatMulWithBiasAndDequantize<W> create(Scope scope, Operand<T> a, Operand<U> b, Operand<V> bias, Operand<TFloat32> minA, Operand<TFloat32> maxA, Operand<TFloat32> minB, Operand<TFloat32> maxB, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, Class<W> Toutput, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedMatMulWithBiasAndDequantize", scope.makeOpName("QuantizedMatMulWithBiasAndDequantize"));
     opBuilder.addInput(a.asOutput());
     opBuilder.addInput(b.asOutput());
@@ -102,7 +102,7 @@ public static <W extends TNumber, T extends TType, U extends TType, V extends TT
     opBuilder.addInput(minFreezedOutput.asOutput());
     opBuilder.addInput(maxFreezedOutput.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Toutput", Toutput);
+    opBuilder.setAttr("Toutput", Operands.toDataType(Toutput));
     if (options != null) {
       for (Options opts : options) {
         if (opts.transposeA != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java
index dd4fe1c4ffa..d971f1a41cf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.quantization;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -89,7 +89,7 @@ private Options() {
    * @return a new instance of QuantizedMatMulWithBiasAndRequantize
    */
   @Endpoint(describeByClass = true)
-  public static <W extends TType, T extends TType, U extends TType, V extends TType> QuantizedMatMulWithBiasAndRequantize<W> create(Scope scope, Operand<T> a, Operand<U> b, Operand<V> bias, Operand<TFloat32> minA, Operand<TFloat32> maxA, Operand<TFloat32> minB, Operand<TFloat32> maxB, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, DataType<W> Toutput, Options... options) {
+  public static <W extends TType, T extends TType, U extends TType, V extends TType> QuantizedMatMulWithBiasAndRequantize<W> create(Scope scope, Operand<T> a, Operand<U> b, Operand<V> bias, Operand<TFloat32> minA, Operand<TFloat32> maxA, Operand<TFloat32> minB, Operand<TFloat32> maxB, Operand<TFloat32> minFreezedOutput, Operand<TFloat32> maxFreezedOutput, Class<W> Toutput, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("QuantizedMatMulWithBiasAndRequantize", scope.makeOpName("QuantizedMatMulWithBiasAndRequantize"));
     opBuilder.addInput(a.asOutput());
     opBuilder.addInput(b.asOutput());
@@ -101,7 +101,7 @@ public static <W extends TType, T extends TType, U extends TType, V extends TTyp
     opBuilder.addInput(minFreezedOutput.asOutput());
     opBuilder.addInput(maxFreezedOutput.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Toutput", Toutput);
+    opBuilder.setAttr("Toutput", Operands.toDataType(Toutput));
     if (options != null) {
       for (Options opts : options) {
         if (opts.transposeA != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java
index a93f0c85a9b..cec1e8823e4 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.quantization;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -58,7 +58,7 @@ public final class Requantize<U extends TType> extends RawOp {
    * @return a new instance of Requantize
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> Requantize<U> create(Scope scope, Operand<T> input, Operand<TFloat32> inputMin, Operand<TFloat32> inputMax, Operand<TFloat32> requestedOutputMin, Operand<TFloat32> requestedOutputMax, DataType<U> outType) {
+  public static <U extends TType, T extends TType> Requantize<U> create(Scope scope, Operand<T> input, Operand<TFloat32> inputMin, Operand<TFloat32> inputMax, Operand<TFloat32> requestedOutputMin, Operand<TFloat32> requestedOutputMax, Class<U> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("Requantize", scope.makeOpName("Requantize"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(inputMin.asOutput());
@@ -66,7 +66,7 @@ public static <U extends TType, T extends TType> Requantize<U> create(Scope scop
     opBuilder.addInput(requestedOutputMin.asOutput());
     opBuilder.addInput(requestedOutputMax.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new Requantize<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java
index 3b23fa1e5a0..12ca81cf3c6 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Counts the number of occurrences of each value in an integer array.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java
index bc188254edd..857d412129f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Performs sparse-output bin counting for a ragged tensor input.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java
index 308bc5fd3d1..3ad9d57582f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java
@@ -17,7 +17,6 @@
 
 package org.tensorflow.op.ragged;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
@@ -62,7 +61,7 @@ public final class RaggedCross<T extends TType, U extends TNumber> extends RawOp
    * @return a new instance of RaggedCross
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType, U extends TNumber> RaggedCross<T, U> create(Scope scope, Iterable<Operand<?>> raggedValues, Iterable<Operand<?>> raggedRowSplits, Iterable<Operand<TInt64>> sparseIndices, Iterable<Operand<?>> sparseValues, Iterable<Operand<TInt64>> sparseShape, Iterable<Operand<?>> denseInputs, String inputOrder, Boolean hashedOutput, Long numBuckets, Long hashKey, DataType<T> outValuesType, DataType<U> outRowSplitsType) {
+  public static <T extends TType, U extends TNumber> RaggedCross<T, U> create(Scope scope, Iterable<Operand<?>> raggedValues, Iterable<Operand<?>> raggedRowSplits, Iterable<Operand<TInt64>> sparseIndices, Iterable<Operand<?>> sparseValues, Iterable<Operand<TInt64>> sparseShape, Iterable<Operand<?>> denseInputs, String inputOrder, Boolean hashedOutput, Long numBuckets, Long hashKey, Class<T> outValuesType, Class<U> outRowSplitsType) {
     OperationBuilder opBuilder = scope.env().opBuilder("RaggedCross", scope.makeOpName("RaggedCross"));
     opBuilder.addInputList(Operands.asOutputs(raggedValues));
     opBuilder.addInputList(Operands.asOutputs(raggedRowSplits));
@@ -75,8 +74,8 @@ public static <T extends TType, U extends TNumber> RaggedCross<T, U> create(Scop
     opBuilder.setAttr("hashed_output", hashedOutput);
     opBuilder.setAttr("num_buckets", numBuckets);
     opBuilder.setAttr("hash_key", hashKey);
-    opBuilder.setAttr("out_values_type", outValuesType);
-    opBuilder.setAttr("out_row_splits_type", outRowSplitsType);
+    opBuilder.setAttr("out_values_type", Operands.toDataType(outValuesType));
+    opBuilder.setAttr("out_row_splits_type", Operands.toDataType(outRowSplitsType));
     return new RaggedCross<T, U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java
index 8f98601a153..67df6a76a63 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java
@@ -17,18 +17,17 @@
 
 package org.tensorflow.op.ragged;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns a `RaggedTensor` containing the specified sequences of numbers.
@@ -64,13 +63,13 @@ public final class RaggedRange<U extends TNumber, T extends TNumber> extends Raw
    * @return a new instance of RaggedRange
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TNumber> RaggedRange<U, T> create(Scope scope, Operand<T> starts, Operand<T> limits, Operand<T> deltas, DataType<U> Tsplits) {
+  public static <U extends TNumber, T extends TNumber> RaggedRange<U, T> create(Scope scope, Operand<T> starts, Operand<T> limits, Operand<T> deltas, Class<U> Tsplits) {
     OperationBuilder opBuilder = scope.env().opBuilder("RaggedRange", scope.makeOpName("RaggedRange"));
     opBuilder.addInput(starts.asOutput());
     opBuilder.addInput(limits.asOutput());
     opBuilder.addInput(deltas.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Tsplits", Tsplits);
+    opBuilder.setAttr("Tsplits", Operands.toDataType(Tsplits));
     return new RaggedRange<U, T>(opBuilder.build());
   }
   
@@ -85,7 +84,7 @@ public static <U extends TNumber, T extends TNumber> RaggedRange<U, T> create(Sc
    */
   @Endpoint(describeByClass = true)
   public static <T extends TNumber> RaggedRange<TInt64, T> create(Scope scope, Operand<T> starts, Operand<T> limits, Operand<T> deltas) {
-    return create(scope, starts, limits, deltas, TInt64.DTYPE);
+    return create(scope, starts, limits, deltas, TInt64.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java
index 7c82a9bf5e7..f58a5ca64f3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java
@@ -19,11 +19,11 @@
 
 import java.util.Arrays;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -67,14 +67,14 @@ public final class RaggedTensorFromVariant<U extends TNumber, T extends TType> e
    * @return a new instance of RaggedTensorFromVariant
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> RaggedTensorFromVariant<U, T> create(Scope scope, Operand<?> encodedRagged, Long inputRaggedRank, Long outputRaggedRank, DataType<T> Tvalues, DataType<U> Tsplits) {
+  public static <U extends TNumber, T extends TType> RaggedTensorFromVariant<U, T> create(Scope scope, Operand<?> encodedRagged, Long inputRaggedRank, Long outputRaggedRank, Class<T> Tvalues, Class<U> Tsplits) {
     OperationBuilder opBuilder = scope.env().opBuilder("RaggedTensorFromVariant", scope.makeOpName("RaggedTensorFromVariant"));
     opBuilder.addInput(encodedRagged.asOutput());
     opBuilder = scope.apply(opBuilder);
     opBuilder.setAttr("input_ragged_rank", inputRaggedRank);
     opBuilder.setAttr("output_ragged_rank", outputRaggedRank);
-    opBuilder.setAttr("Tvalues", Tvalues);
-    opBuilder.setAttr("Tsplits", Tsplits);
+    opBuilder.setAttr("Tvalues", Operands.toDataType(Tvalues));
+    opBuilder.setAttr("Tsplits", Operands.toDataType(Tsplits));
     return new RaggedTensorFromVariant<U, T>(opBuilder.build());
   }
   
@@ -91,8 +91,8 @@ public static <U extends TNumber, T extends TType> RaggedTensorFromVariant<U, T>
    * @return a new instance of RaggedTensorFromVariant
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> RaggedTensorFromVariant<TInt64, T> create(Scope scope, Operand<?> encodedRagged, Long inputRaggedRank, Long outputRaggedRank, DataType<T> Tvalues) {
-    return create(scope, encodedRagged, inputRaggedRank, outputRaggedRank, Tvalues, TInt64.DTYPE);
+  public static <T extends TType> RaggedTensorFromVariant<TInt64, T> create(Scope scope, Operand<?> encodedRagged, Long inputRaggedRank, Long outputRaggedRank, Class<T> Tvalues) {
+    return create(scope, encodedRagged, inputRaggedRank, outputRaggedRank, Tvalues, TInt64.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java
index 716a076af30..5dc566feb29 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -29,7 +29,6 @@
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Draws samples from a multinomial distribution.
@@ -80,12 +79,12 @@ private Options() {
    * @return a new instance of Multinomial
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TNumber> Multinomial<U> create(Scope scope, Operand<T> logits, Operand<TInt32> numSamples, DataType<U> outputDtype, Options... options) {
+  public static <U extends TNumber, T extends TNumber> Multinomial<U> create(Scope scope, Operand<T> logits, Operand<TInt32> numSamples, Class<U> outputDtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("Multinomial", scope.makeOpName("Multinomial"));
     opBuilder.addInput(logits.asOutput());
     opBuilder.addInput(numSamples.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("output_dtype", outputDtype);
+    opBuilder.setAttr("output_dtype", Operands.toDataType(outputDtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.seed != null) {
@@ -111,7 +110,7 @@ public static <U extends TNumber, T extends TNumber> Multinomial<U> create(Scope
    */
   @Endpoint(describeByClass = true)
   public static <T extends TNumber> Multinomial<TInt64> create(Scope scope, Operand<T> logits, Operand<TInt32> numSamples, Options... options) {
-    return create(scope, logits, numSamples, TInt64.DTYPE, options);
+    return create(scope, logits, numSamples, TInt64.class, options);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java
index 56637c87704..2f9aad878b3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -47,11 +47,11 @@ public final class NonDeterministicInts<U extends TType> extends RawOp implement
    * @return a new instance of NonDeterministicInts
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> NonDeterministicInts<U> create(Scope scope, Operand<T> shape, DataType<U> dtype) {
+  public static <U extends TType, T extends TType> NonDeterministicInts<U> create(Scope scope, Operand<T> shape, Class<U> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("NonDeterministicInts", scope.makeOpName("NonDeterministicInts"));
     opBuilder.addInput(shape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new NonDeterministicInts<U>(opBuilder.build());
   }
   
@@ -64,7 +64,7 @@ public static <U extends TType, T extends TType> NonDeterministicInts<U> create(
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> NonDeterministicInts<TInt64> create(Scope scope, Operand<T> shape) {
-    return create(scope, shape, TInt64.DTYPE);
+    return create(scope, shape, TInt64.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java
index 2e60c56577e..f4300ebaa75 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs random values from a normal distribution. The parameters may each be a
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java
index a7ffc285a5d..ddf132eacb8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs random values from the Gamma distribution(s) described by alpha.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java
index ec330931444..35f9c06d172 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the derivative of a Gamma random sample w.r.t. `alpha`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java
index 02a8494bbc6..8b3c70059e0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java
@@ -17,18 +17,17 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs random values from the Poisson distribution(s) described by rate.
@@ -91,12 +90,12 @@ private Options() {
    * @return a new instance of RandomPoisson
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TNumber, T extends TNumber, U extends TNumber> RandomPoisson<V> create(Scope scope, Operand<T> shape, Operand<U> rate, DataType<V> dtype, Options... options) {
+  public static <V extends TNumber, T extends TNumber, U extends TNumber> RandomPoisson<V> create(Scope scope, Operand<T> shape, Operand<U> rate, Class<V> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("RandomPoissonV2", scope.makeOpName("RandomPoisson"));
     opBuilder.addInput(shape.asOutput());
     opBuilder.addInput(rate.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.seed != null) {
@@ -123,7 +122,7 @@ public static <V extends TNumber, T extends TNumber, U extends TNumber> RandomPo
    */
   @Endpoint(describeByClass = true)
   public static <T extends TNumber, U extends TNumber> RandomPoisson<TInt64> create(Scope scope, Operand<T> shape, Operand<U> rate, Options... options) {
-    return create(scope, shape, rate, TInt64.DTYPE, options);
+    return create(scope, shape, rate, TInt64.class, options);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java
index 8e323c90bed..c699ec4509c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java
@@ -17,17 +17,16 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs random values from a normal distribution.
@@ -79,11 +78,11 @@ private Options() {
    * @return a new instance of RandomStandardNormal
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TNumber> RandomStandardNormal<U> create(Scope scope, Operand<T> shape, DataType<U> dtype, Options... options) {
+  public static <U extends TNumber, T extends TNumber> RandomStandardNormal<U> create(Scope scope, Operand<T> shape, Class<U> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("RandomStandardNormal", scope.makeOpName("RandomStandardNormal"));
     opBuilder.addInput(shape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.seed != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java
index 6f5b8a97caf..d3bbe991d60 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java
@@ -17,17 +17,16 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs random values from a uniform distribution.
@@ -80,11 +79,11 @@ private Options() {
    * @return a new instance of RandomUniform
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TNumber> RandomUniform<U> create(Scope scope, Operand<T> shape, DataType<U> dtype, Options... options) {
+  public static <U extends TNumber, T extends TNumber> RandomUniform<U> create(Scope scope, Operand<T> shape, Class<U> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("RandomUniform", scope.makeOpName("RandomUniform"));
     opBuilder.addInput(shape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.seed != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java
index 72f8ede53a4..f6ab24df811 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs random integers from a uniform distribution.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java
index 33c2b7be4dc..67264028253 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java
@@ -17,18 +17,17 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <V> data type for {@code output()} output
@@ -49,7 +48,7 @@ public final class StatefulRandomBinomial<V extends TNumber> extends RawOp imple
    * @return a new instance of StatefulRandomBinomial
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TNumber, T extends TNumber, U extends TNumber> StatefulRandomBinomial<V> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape, Operand<U> counts, Operand<U> probs, DataType<V> dtype) {
+  public static <V extends TNumber, T extends TNumber, U extends TNumber> StatefulRandomBinomial<V> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape, Operand<U> counts, Operand<U> probs, Class<V> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("StatefulRandomBinomial", scope.makeOpName("StatefulRandomBinomial"));
     opBuilder.addInput(resource.asOutput());
     opBuilder.addInput(algorithm.asOutput());
@@ -57,7 +56,7 @@ public static <V extends TNumber, T extends TNumber, U extends TNumber> Stateful
     opBuilder.addInput(counts.asOutput());
     opBuilder.addInput(probs.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new StatefulRandomBinomial<V>(opBuilder.build());
   }
   
@@ -74,7 +73,7 @@ public static <V extends TNumber, T extends TNumber, U extends TNumber> Stateful
    */
   @Endpoint(describeByClass = true)
   public static <T extends TNumber, U extends TNumber> StatefulRandomBinomial<TInt64> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape, Operand<U> counts, Operand<U> probs) {
-    return create(scope, resource, algorithm, shape, counts, probs, TInt64.DTYPE);
+    return create(scope, resource, algorithm, shape, counts, probs, TInt64.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java
index 581509c7f3b..340703444ef 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -51,13 +51,13 @@ public final class StatefulStandardNormal<U extends TType> extends RawOp impleme
    * @return a new instance of StatefulStandardNormal
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> StatefulStandardNormal<U> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape, DataType<U> dtype) {
+  public static <U extends TType, T extends TType> StatefulStandardNormal<U> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape, Class<U> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("StatefulStandardNormalV2", scope.makeOpName("StatefulStandardNormal"));
     opBuilder.addInput(resource.asOutput());
     opBuilder.addInput(algorithm.asOutput());
     opBuilder.addInput(shape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new StatefulStandardNormal<U>(opBuilder.build());
   }
   
@@ -72,7 +72,7 @@ public static <U extends TType, T extends TType> StatefulStandardNormal<U> creat
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> StatefulStandardNormal<TFloat32> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape) {
-    return create(scope, resource, algorithm, shape, TFloat32.DTYPE);
+    return create(scope, resource, algorithm, shape, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java
index 22b75825390..850473f7662 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -52,13 +52,13 @@ public final class StatefulTruncatedNormal<U extends TType> extends RawOp implem
    * @return a new instance of StatefulTruncatedNormal
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> StatefulTruncatedNormal<U> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape, DataType<U> dtype) {
+  public static <U extends TType, T extends TType> StatefulTruncatedNormal<U> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape, Class<U> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("StatefulTruncatedNormal", scope.makeOpName("StatefulTruncatedNormal"));
     opBuilder.addInput(resource.asOutput());
     opBuilder.addInput(algorithm.asOutput());
     opBuilder.addInput(shape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new StatefulTruncatedNormal<U>(opBuilder.build());
   }
   
@@ -73,7 +73,7 @@ public static <U extends TType, T extends TType> StatefulTruncatedNormal<U> crea
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> StatefulTruncatedNormal<TFloat32> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape) {
-    return create(scope, resource, algorithm, shape, TFloat32.DTYPE);
+    return create(scope, resource, algorithm, shape, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java
index 08eed6f0889..b33ced6beec 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -51,13 +51,13 @@ public final class StatefulUniform<U extends TType> extends RawOp implements Ope
    * @return a new instance of StatefulUniform
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> StatefulUniform<U> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape, DataType<U> dtype) {
+  public static <U extends TType, T extends TType> StatefulUniform<U> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape, Class<U> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("StatefulUniform", scope.makeOpName("StatefulUniform"));
     opBuilder.addInput(resource.asOutput());
     opBuilder.addInput(algorithm.asOutput());
     opBuilder.addInput(shape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new StatefulUniform<U>(opBuilder.build());
   }
   
@@ -72,7 +72,7 @@ public static <U extends TType, T extends TType> StatefulUniform<U> create(Scope
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> StatefulUniform<TFloat32> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape) {
-    return create(scope, resource, algorithm, shape, TFloat32.DTYPE);
+    return create(scope, resource, algorithm, shape, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java
index 4489103a8bf..6a06923808a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -49,13 +49,13 @@ public final class StatefulUniformFullInt<U extends TType> extends RawOp impleme
    * @return a new instance of StatefulUniformFullInt
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> StatefulUniformFullInt<U> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape, DataType<U> dtype) {
+  public static <U extends TType, T extends TType> StatefulUniformFullInt<U> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<T> shape, Class<U> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("StatefulUniformFullInt", scope.makeOpName("StatefulUniformFullInt"));
     opBuilder.addInput(resource.asOutput());
     opBuilder.addInput(algorithm.asOutput());
     opBuilder.addInput(shape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new StatefulUniformFullInt<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java
index 60940410499..93f7a9254de 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -29,7 +29,6 @@
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Draws samples from a multinomial distribution.
@@ -51,13 +50,13 @@ public final class StatelessMultinomial<V extends TNumber> extends RawOp impleme
    * @return a new instance of StatelessMultinomial
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TNumber, T extends TNumber, U extends TNumber> StatelessMultinomial<V> create(Scope scope, Operand<T> logits, Operand<TInt32> numSamples, Operand<U> seed, DataType<V> outputDtype) {
+  public static <V extends TNumber, T extends TNumber, U extends TNumber> StatelessMultinomial<V> create(Scope scope, Operand<T> logits, Operand<TInt32> numSamples, Operand<U> seed, Class<V> outputDtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("StatelessMultinomial", scope.makeOpName("StatelessMultinomial"));
     opBuilder.addInput(logits.asOutput());
     opBuilder.addInput(numSamples.asOutput());
     opBuilder.addInput(seed.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("output_dtype", outputDtype);
+    opBuilder.setAttr("output_dtype", Operands.toDataType(outputDtype));
     return new StatelessMultinomial<V>(opBuilder.build());
   }
   
@@ -73,7 +72,7 @@ public static <V extends TNumber, T extends TNumber, U extends TNumber> Stateles
    */
   @Endpoint(describeByClass = true)
   public static <T extends TNumber, U extends TNumber> StatelessMultinomial<TInt64> create(Scope scope, Operand<T> logits, Operand<TInt32> numSamples, Operand<U> seed) {
-    return create(scope, logits, numSamples, seed, TInt64.DTYPE);
+    return create(scope, logits, numSamples, seed, TInt64.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java
index f179c37e30e..f6d5deadabf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * @param <V> data type for {@code output()} output
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java
index 9c0e3cad0df..6da606468d1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java
@@ -17,18 +17,17 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs deterministic pseudorandom random numbers from a binomial distribution.
@@ -55,14 +54,14 @@ public final class StatelessRandomBinomial<W extends TNumber> extends RawOp impl
    * @return a new instance of StatelessRandomBinomial
    */
   @Endpoint(describeByClass = true)
-  public static <W extends TNumber, T extends TNumber, U extends TNumber, V extends TNumber> StatelessRandomBinomial<W> create(Scope scope, Operand<T> shape, Operand<U> seed, Operand<V> counts, Operand<V> probs, DataType<W> dtype) {
+  public static <W extends TNumber, T extends TNumber, U extends TNumber, V extends TNumber> StatelessRandomBinomial<W> create(Scope scope, Operand<T> shape, Operand<U> seed, Operand<V> counts, Operand<V> probs, Class<W> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("StatelessRandomBinomial", scope.makeOpName("StatelessRandomBinomial"));
     opBuilder.addInput(shape.asOutput());
     opBuilder.addInput(seed.asOutput());
     opBuilder.addInput(counts.asOutput());
     opBuilder.addInput(probs.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new StatelessRandomBinomial<W>(opBuilder.build());
   }
   
@@ -80,7 +79,7 @@ public static <W extends TNumber, T extends TNumber, U extends TNumber, V extend
    */
   @Endpoint(describeByClass = true)
   public static <T extends TNumber, U extends TNumber, V extends TNumber> StatelessRandomBinomial<TInt64> create(Scope scope, Operand<T> shape, Operand<U> seed, Operand<V> counts, Operand<V> probs) {
-    return create(scope, shape, seed, counts, probs, TInt64.DTYPE);
+    return create(scope, shape, seed, counts, probs, TInt64.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java
index faf065bfb5a..2b4ca37dee9 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs deterministic pseudorandom random numbers from a gamma distribution.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java
index 34fc3b313f5..6438b29ec4c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java
@@ -17,18 +17,17 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs deterministic pseudorandom values from a normal distribution.
@@ -52,12 +51,12 @@ public final class StatelessRandomNormal<V extends TNumber> extends RawOp implem
    * @return a new instance of StatelessRandomNormal
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TNumber, T extends TNumber, U extends TNumber> StatelessRandomNormal<V> create(Scope scope, Operand<T> shape, Operand<U> seed, DataType<V> dtype) {
+  public static <V extends TNumber, T extends TNumber, U extends TNumber> StatelessRandomNormal<V> create(Scope scope, Operand<T> shape, Operand<U> seed, Class<V> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("StatelessRandomNormal", scope.makeOpName("StatelessRandomNormal"));
     opBuilder.addInput(shape.asOutput());
     opBuilder.addInput(seed.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new StatelessRandomNormal<V>(opBuilder.build());
   }
   
@@ -71,7 +70,7 @@ public static <V extends TNumber, T extends TNumber, U extends TNumber> Stateles
    */
   @Endpoint(describeByClass = true)
   public static <T extends TNumber, U extends TNumber> StatelessRandomNormal<TFloat32> create(Scope scope, Operand<T> shape, Operand<U> seed) {
-    return create(scope, shape, seed, TFloat32.DTYPE);
+    return create(scope, shape, seed, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java
index 06afdb5eb18..c44af6a5e72 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java
@@ -17,17 +17,16 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs deterministic pseudorandom random numbers from a Poisson distribution.
@@ -52,13 +51,13 @@ public final class StatelessRandomPoisson<W extends TNumber> extends RawOp imple
    * @return a new instance of StatelessRandomPoisson
    */
   @Endpoint(describeByClass = true)
-  public static <W extends TNumber, T extends TNumber, U extends TNumber, V extends TNumber> StatelessRandomPoisson<W> create(Scope scope, Operand<T> shape, Operand<U> seed, Operand<V> lam, DataType<W> dtype) {
+  public static <W extends TNumber, T extends TNumber, U extends TNumber, V extends TNumber> StatelessRandomPoisson<W> create(Scope scope, Operand<T> shape, Operand<U> seed, Operand<V> lam, Class<W> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("StatelessRandomPoisson", scope.makeOpName("StatelessRandomPoisson"));
     opBuilder.addInput(shape.asOutput());
     opBuilder.addInput(seed.asOutput());
     opBuilder.addInput(lam.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new StatelessRandomPoisson<W>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java
index 142c30fbf32..814b89ba69c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java
@@ -17,18 +17,17 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs deterministic pseudorandom random values from a uniform distribution.
@@ -53,12 +52,12 @@ public final class StatelessRandomUniform<V extends TNumber> extends RawOp imple
    * @return a new instance of StatelessRandomUniform
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TNumber, T extends TNumber, U extends TNumber> StatelessRandomUniform<V> create(Scope scope, Operand<T> shape, Operand<U> seed, DataType<V> dtype) {
+  public static <V extends TNumber, T extends TNumber, U extends TNumber> StatelessRandomUniform<V> create(Scope scope, Operand<T> shape, Operand<U> seed, Class<V> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("StatelessRandomUniform", scope.makeOpName("StatelessRandomUniform"));
     opBuilder.addInput(shape.asOutput());
     opBuilder.addInput(seed.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new StatelessRandomUniform<V>(opBuilder.build());
   }
   
@@ -72,7 +71,7 @@ public static <V extends TNumber, T extends TNumber, U extends TNumber> Stateles
    */
   @Endpoint(describeByClass = true)
   public static <T extends TNumber, U extends TNumber> StatelessRandomUniform<TFloat32> create(Scope scope, Operand<T> shape, Operand<U> seed) {
-    return create(scope, shape, seed, TFloat32.DTYPE);
+    return create(scope, shape, seed, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java
index 29b7dc61980..d90112620a5 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java
@@ -17,17 +17,16 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs deterministic pseudorandom random integers from a uniform distribution.
@@ -50,12 +49,12 @@ public final class StatelessRandomUniformFullInt<V extends TNumber> extends RawO
    * @return a new instance of StatelessRandomUniformFullInt
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TNumber, T extends TNumber, U extends TNumber> StatelessRandomUniformFullInt<V> create(Scope scope, Operand<T> shape, Operand<U> seed, DataType<V> dtype) {
+  public static <V extends TNumber, T extends TNumber, U extends TNumber> StatelessRandomUniformFullInt<V> create(Scope scope, Operand<T> shape, Operand<U> seed, Class<V> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("StatelessRandomUniformFullInt", scope.makeOpName("StatelessRandomUniformFullInt"));
     opBuilder.addInput(shape.asOutput());
     opBuilder.addInput(seed.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new StatelessRandomUniformFullInt<V>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java
index 287cbba9e79..fb88cc4f69d 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs deterministic pseudorandom random integers from a uniform distribution.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java
index 41f5c746dfa..e38cd931564 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java
@@ -17,18 +17,17 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs deterministic pseudorandom values from a truncated normal distribution.
@@ -54,12 +53,12 @@ public final class StatelessTruncatedNormal<V extends TNumber> extends RawOp imp
    * @return a new instance of StatelessTruncatedNormal
    */
   @Endpoint(describeByClass = true)
-  public static <V extends TNumber, T extends TNumber, U extends TNumber> StatelessTruncatedNormal<V> create(Scope scope, Operand<T> shape, Operand<U> seed, DataType<V> dtype) {
+  public static <V extends TNumber, T extends TNumber, U extends TNumber> StatelessTruncatedNormal<V> create(Scope scope, Operand<T> shape, Operand<U> seed, Class<V> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("StatelessTruncatedNormal", scope.makeOpName("StatelessTruncatedNormal"));
     opBuilder.addInput(shape.asOutput());
     opBuilder.addInput(seed.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new StatelessTruncatedNormal<V>(opBuilder.build());
   }
   
@@ -73,7 +72,7 @@ public static <V extends TNumber, T extends TNumber, U extends TNumber> Stateles
    */
   @Endpoint(describeByClass = true)
   public static <T extends TNumber, U extends TNumber> StatelessTruncatedNormal<TFloat32> create(Scope scope, Operand<T> shape, Operand<U> seed) {
-    return create(scope, shape, seed, TFloat32.DTYPE);
+    return create(scope, shape, seed, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java
index 1212ddef9e1..ff111c2e8d1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java
@@ -17,17 +17,16 @@
 
 package org.tensorflow.op.random;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs random values from a truncated normal distribution.
@@ -81,11 +80,11 @@ private Options() {
    * @return a new instance of TruncatedNormal
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TNumber> TruncatedNormal<U> create(Scope scope, Operand<T> shape, DataType<U> dtype, Options... options) {
+  public static <U extends TNumber, T extends TNumber> TruncatedNormal<U> create(Scope scope, Operand<T> shape, Class<U> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("TruncatedNormal", scope.makeOpName("TruncatedNormal"));
     opBuilder.addInput(shape.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.seed != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java
index 62ace95189d..bd0d2a330ee 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.signal;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -63,12 +63,12 @@ public final class Irfft<U extends TNumber> extends RawOp implements Operand<U>
    * @return a new instance of Irfft
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> Irfft<U> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength, DataType<U> Treal) {
+  public static <U extends TNumber, T extends TType> Irfft<U> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength, Class<U> Treal) {
     OperationBuilder opBuilder = scope.env().opBuilder("IRFFT", scope.makeOpName("Irfft"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(fftLength.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Treal", Treal);
+    opBuilder.setAttr("Treal", Operands.toDataType(Treal));
     return new Irfft<U>(opBuilder.build());
   }
   
@@ -82,7 +82,7 @@ public static <U extends TNumber, T extends TType> Irfft<U> create(Scope scope,
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> Irfft<TFloat32> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength) {
-    return create(scope, input, fftLength, TFloat32.DTYPE);
+    return create(scope, input, fftLength, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java
index 6c278ed40a0..861e7aaf62e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.signal;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -64,12 +64,12 @@ public final class Irfft2d<U extends TNumber> extends RawOp implements Operand<U
    * @return a new instance of Irfft2d
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> Irfft2d<U> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength, DataType<U> Treal) {
+  public static <U extends TNumber, T extends TType> Irfft2d<U> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength, Class<U> Treal) {
     OperationBuilder opBuilder = scope.env().opBuilder("IRFFT2D", scope.makeOpName("Irfft2d"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(fftLength.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Treal", Treal);
+    opBuilder.setAttr("Treal", Operands.toDataType(Treal));
     return new Irfft2d<U>(opBuilder.build());
   }
   
@@ -83,7 +83,7 @@ public static <U extends TNumber, T extends TType> Irfft2d<U> create(Scope scope
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> Irfft2d<TFloat32> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength) {
-    return create(scope, input, fftLength, TFloat32.DTYPE);
+    return create(scope, input, fftLength, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java
index d57d57566dd..d68a0904eff 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.signal;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -64,12 +64,12 @@ public final class Irfft3d<U extends TNumber> extends RawOp implements Operand<U
    * @return a new instance of Irfft3d
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TNumber, T extends TType> Irfft3d<U> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength, DataType<U> Treal) {
+  public static <U extends TNumber, T extends TType> Irfft3d<U> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength, Class<U> Treal) {
     OperationBuilder opBuilder = scope.env().opBuilder("IRFFT3D", scope.makeOpName("Irfft3d"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(fftLength.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Treal", Treal);
+    opBuilder.setAttr("Treal", Operands.toDataType(Treal));
     return new Irfft3d<U>(opBuilder.build());
   }
   
@@ -83,7 +83,7 @@ public static <U extends TNumber, T extends TType> Irfft3d<U> create(Scope scope
    */
   @Endpoint(describeByClass = true)
   public static <T extends TType> Irfft3d<TFloat32> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength) {
-    return create(scope, input, fftLength, TFloat32.DTYPE);
+    return create(scope, input, fftLength, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java
index 4571349f1db..3b8e54a361e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.signal;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -59,12 +59,12 @@ public final class Rfft<U extends TType> extends RawOp implements Operand<U> {
    * @return a new instance of Rfft
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TNumber> Rfft<U> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength, DataType<U> Tcomplex) {
+  public static <U extends TType, T extends TNumber> Rfft<U> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength, Class<U> Tcomplex) {
     OperationBuilder opBuilder = scope.env().opBuilder("RFFT", scope.makeOpName("Rfft"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(fftLength.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Tcomplex", Tcomplex);
+    opBuilder.setAttr("Tcomplex", Operands.toDataType(Tcomplex));
     return new Rfft<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java
index e3daf88207b..cf00ae1b33b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.signal;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -60,12 +60,12 @@ public final class Rfft2d<U extends TType> extends RawOp implements Operand<U> {
    * @return a new instance of Rfft2d
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TNumber> Rfft2d<U> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength, DataType<U> Tcomplex) {
+  public static <U extends TType, T extends TNumber> Rfft2d<U> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength, Class<U> Tcomplex) {
     OperationBuilder opBuilder = scope.env().opBuilder("RFFT2D", scope.makeOpName("Rfft2d"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(fftLength.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Tcomplex", Tcomplex);
+    opBuilder.setAttr("Tcomplex", Operands.toDataType(Tcomplex));
     return new Rfft2d<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java
index f72996a23cf..c01d979d7cb 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.signal;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -60,12 +60,12 @@ public final class Rfft3d<U extends TType> extends RawOp implements Operand<U> {
    * @return a new instance of Rfft3d
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TNumber> Rfft3d<U> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength, DataType<U> Tcomplex) {
+  public static <U extends TType, T extends TNumber> Rfft3d<U> create(Scope scope, Operand<T> input, Operand<TInt32> fftLength, Class<U> Tcomplex) {
     OperationBuilder opBuilder = scope.env().opBuilder("RFFT3D", scope.makeOpName("Rfft3d"));
     opBuilder.addInput(input.asOutput());
     opBuilder.addInput(fftLength.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("Tcomplex", Tcomplex);
+    opBuilder.setAttr("Tcomplex", Operands.toDataType(Tcomplex));
     return new Rfft3d<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java
index 58e4e8c2ff1..c06191594a3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Performs sparse-output bin counting for a tf.tensor input.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java
index a6873029f69..f229dd2ad98 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.sparse;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -89,11 +89,11 @@ public final class DeserializeSparse<U extends TType> extends RawOp {
    * @return a new instance of DeserializeSparse
    */
   @Endpoint(describeByClass = true)
-  public static <U extends TType, T extends TType> DeserializeSparse<U> create(Scope scope, Operand<T> serializedSparse, DataType<U> dtype) {
+  public static <U extends TType, T extends TType> DeserializeSparse<U> create(Scope scope, Operand<T> serializedSparse, Class<U> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("DeserializeSparse", scope.makeOpName("DeserializeSparse"));
     opBuilder.addInput(serializedSparse.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new DeserializeSparse<U>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java
index bfe138e1589..f7250020c10 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.sparse;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -57,12 +57,12 @@ public final class SparseAccumulatorTakeGradient<T extends TType> extends RawOp
    * @return a new instance of SparseAccumulatorTakeGradient
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> SparseAccumulatorTakeGradient<T> create(Scope scope, Operand<TString> handle, Operand<TInt32> numRequired, DataType<T> dtype) {
+  public static <T extends TType> SparseAccumulatorTakeGradient<T> create(Scope scope, Operand<TString> handle, Operand<TInt32> numRequired, Class<T> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("SparseAccumulatorTakeGradient", scope.makeOpName("SparseAccumulatorTakeGradient"));
     opBuilder.addInput(handle.asOutput());
     opBuilder.addInput(numRequired.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new SparseAccumulatorTakeGradient<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java
index abb959533b6..bea0d8b3c71 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Counts the number of occurrences of each value in an integer array.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConditionalAccumulator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConditionalAccumulator.java
index c428e2286cf..e012cb631c8 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConditionalAccumulator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConditionalAccumulator.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.sparse;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -92,10 +92,10 @@ private Options() {
    * @return a new instance of SparseConditionalAccumulator
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> SparseConditionalAccumulator create(Scope scope, DataType<T> dtype, Shape shape, Options... options) {
+  public static <T extends TType> SparseConditionalAccumulator create(Scope scope, Class<T> dtype, Shape shape, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("SparseConditionalAccumulator", scope.makeOpName("SparseConditionalAccumulator"));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     opBuilder.setAttr("shape", shape);
     if (options != null) {
       for (Options opts : options) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java
index 80f3aa2c352..85e6707f0c0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Performs sparse-output bin counting for a sparse tensor input.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseMatMul.java
index 9c5b6df4b07..d254cb3224c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseMatMul.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseMatMul.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Multiply matrix "a" by matrix "b".
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java
index 863e1112a31..190f06c2dbf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java
@@ -28,7 +28,6 @@
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the max of elements across dimensions of a SparseTensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java
index 1bf33bd9e68..ae36fcb07e3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java
@@ -28,7 +28,6 @@
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the max of elements across dimensions of a SparseTensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java
index 4269fd92830..a373bd33f03 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the mean along sparse segments of a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java
index cb2ba01028b..8e558afbe9e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes gradients for SparseSegmentMean.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java
index 4ea84634502..d62b956b096 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the mean along sparse segments of a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java
index 0ffcbc1a257..50fe5cc8068 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the sum along sparse segments of a tensor divided by the sqrt of N.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java
index 772b5a71f31..9faa31633c0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes gradients for SparseSegmentSqrtN.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java
index 5288004ed14..f962af5be0f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the sum along sparse segments of a tensor divided by the sqrt of N.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java
index 7fd16c2eb43..add00c19798 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the sum along sparse segments of a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java
index e4775c51cf2..b956d005069 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java
@@ -26,7 +26,6 @@
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Computes the sum along sparse segments of a tensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java
index 7e3f66ebc05..252a00e838b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Applies softmax to a batched N-D `SparseTensor`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java
index 9903a494197..8886a6fda12 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Returns the element-wise max of two SparseTensors.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java
index ab0123a2c14..a18674e8c4c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.sparse;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -124,11 +124,11 @@ private Options() {
    * @return a new instance of TakeManySparseFromTensorsMap
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> TakeManySparseFromTensorsMap<T> create(Scope scope, Operand<TInt64> sparseHandles, DataType<T> dtype, Options... options) {
+  public static <T extends TType> TakeManySparseFromTensorsMap<T> create(Scope scope, Operand<TInt64> sparseHandles, Class<T> dtype, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("TakeManySparseFromTensorsMap", scope.makeOpName("TakeManySparseFromTensorsMap"));
     opBuilder.addInput(sparseHandles.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     if (options != null) {
       for (Options opts : options) {
         if (opts.container != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java
index 2c967f3ef62..e504e164c41 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Creates ngrams from ragged string data.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Substr.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Substr.java
index 1848bfc513c..472e30bc98c 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Substr.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Substr.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Return substrings from `Tensor` of strings.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java
index db2bac2cf74..547a4f17b95 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.strings;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -29,7 +29,6 @@
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Converts each string in the input Tensor to the specified numeric type.
@@ -58,11 +57,11 @@ public final class ToNumber<T extends TNumber> extends RawOp implements Operand<
    * @return a new instance of ToNumber
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber> ToNumber<T> create(Scope scope, Operand<TString> stringTensor, DataType<T> outType) {
+  public static <T extends TNumber> ToNumber<T> create(Scope scope, Operand<TString> stringTensor, Class<T> outType) {
     OperationBuilder opBuilder = scope.env().opBuilder("StringToNumber", scope.makeOpName("ToNumber"));
     opBuilder.addInput(stringTensor.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("out_type", outType);
+    opBuilder.setAttr("out_type", Operands.toDataType(outType));
     return new ToNumber<T>(opBuilder.build());
   }
   
@@ -75,7 +74,7 @@ public static <T extends TNumber> ToNumber<T> create(Scope scope, Operand<TStrin
    */
   @Endpoint(describeByClass = true)
   public static ToNumber<TFloat32> create(Scope scope, Operand<TString> stringTensor) {
-    return create(scope, stringTensor, TFloat32.DTYPE);
+    return create(scope, stringTensor, TFloat32.class);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java
index d5532df9e78..65e5e256780 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.strings;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -30,7 +30,6 @@
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Decodes each string in `input` into a sequence of Unicode code points.
@@ -116,12 +115,12 @@ private Options() {
    * @return a new instance of UnicodeDecode
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber> UnicodeDecode<T> create(Scope scope, Operand<TString> input, String inputEncoding, DataType<T> Tsplits, Options... options) {
+  public static <T extends TNumber> UnicodeDecode<T> create(Scope scope, Operand<TString> input, String inputEncoding, Class<T> Tsplits, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("UnicodeDecode", scope.makeOpName("UnicodeDecode"));
     opBuilder.addInput(input.asOutput());
     opBuilder = scope.apply(opBuilder);
     opBuilder.setAttr("input_encoding", inputEncoding);
-    opBuilder.setAttr("Tsplits", Tsplits);
+    opBuilder.setAttr("Tsplits", Operands.toDataType(Tsplits));
     if (options != null) {
       for (Options opts : options) {
         if (opts.errors != null) {
@@ -151,7 +150,7 @@ public static <T extends TNumber> UnicodeDecode<T> create(Scope scope, Operand<T
    */
   @Endpoint(describeByClass = true)
   public static UnicodeDecode<TInt64> create(Scope scope, Operand<TString> input, String inputEncoding, Options... options) {
-    return create(scope, input, inputEncoding, TInt64.DTYPE, options);
+    return create(scope, input, inputEncoding, TInt64.class, options);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java
index 1ab449f34c1..2b10934b37a 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.strings;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -30,7 +30,6 @@
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Decodes each string in `input` into a sequence of Unicode code points.
@@ -122,12 +121,12 @@ private Options() {
    * @return a new instance of UnicodeDecodeWithOffsets
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TNumber> UnicodeDecodeWithOffsets<T> create(Scope scope, Operand<TString> input, String inputEncoding, DataType<T> Tsplits, Options... options) {
+  public static <T extends TNumber> UnicodeDecodeWithOffsets<T> create(Scope scope, Operand<TString> input, String inputEncoding, Class<T> Tsplits, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("UnicodeDecodeWithOffsets", scope.makeOpName("UnicodeDecodeWithOffsets"));
     opBuilder.addInput(input.asOutput());
     opBuilder = scope.apply(opBuilder);
     opBuilder.setAttr("input_encoding", inputEncoding);
-    opBuilder.setAttr("Tsplits", Tsplits);
+    opBuilder.setAttr("Tsplits", Operands.toDataType(Tsplits));
     if (options != null) {
       for (Options opts : options) {
         if (opts.errors != null) {
@@ -157,7 +156,7 @@ public static <T extends TNumber> UnicodeDecodeWithOffsets<T> create(Scope scope
    */
   @Endpoint(describeByClass = true)
   public static UnicodeDecodeWithOffsets<TInt64> create(Scope scope, Operand<TString> input, String inputEncoding, Options... options) {
-    return create(scope, input, inputEncoding, TInt64.DTYPE, options);
+    return create(scope, input, inputEncoding, TInt64.class, options);
   }
   
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeEncode.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeEncode.java
index aa49be53b13..d24d09a67ef 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeEncode.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeEncode.java
@@ -28,7 +28,6 @@
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Encode a tensor of ints into unicode strings.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnsortedSegmentJoin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnsortedSegmentJoin.java
index 44532692d04..075d21d219e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnsortedSegmentJoin.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnsortedSegmentJoin.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Joins the elements of `inputs` based on `segment_ids`.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/HistogramSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/HistogramSummary.java
index a309f20f391..0acfec7cac1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/HistogramSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/HistogramSummary.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs a `Summary` protocol buffer with a histogram.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ImageSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ImageSummary.java
index 796f5e24bfc..7217055142b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ImageSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ImageSummary.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs a `Summary` protocol buffer with images.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ScalarSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ScalarSummary.java
index 48517f8a00e..37740dc7ef3 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ScalarSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/ScalarSummary.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Outputs a `Summary` protocol buffer with scalar values.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteHistogramSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteHistogramSummary.java
index 0c4d1363c35..7daeb5ccbd0 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteHistogramSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteHistogramSummary.java
@@ -27,7 +27,6 @@
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  */
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteImageSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteImageSummary.java
index 7a816e98b6a..70eed3c13a1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteImageSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteImageSummary.java
@@ -28,7 +28,6 @@
 import org.tensorflow.types.TString;
 import org.tensorflow.types.TUint8;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  */
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteScalarSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteScalarSummary.java
index 45dddbda36f..ce5a91db59b 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteScalarSummary.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/summary/WriteScalarSummary.java
@@ -27,7 +27,6 @@
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  */
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java
index dd45b4298b8..ff2cb8390be 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java
@@ -27,7 +27,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * An Op to sum inputs across replicated TPU instances.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingRaggedTensorBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingRaggedTensorBatch.java
index 5b799cc2f89..a6256e829fa 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingRaggedTensorBatch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingRaggedTensorBatch.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Eases the porting of code that uses tf.nn.embedding_lookup().
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseBatch.java
index d724e366c91..f302cf7ad5f 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseBatch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseBatch.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * An op that enqueues TPUEmbedding input indices from a SparseTensor.
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseTensorBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseTensorBatch.java
index e7f0444cbf4..a482e5f5ebf 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseTensorBatch.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseTensorBatch.java
@@ -28,7 +28,6 @@
 import org.tensorflow.op.annotation.Operator;
 import org.tensorflow.types.TString;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Eases the porting of code that uses tf.nn.embedding_lookup_sparse().
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java
index 265a9fa70f8..325db448246 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.tpu;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -45,10 +45,10 @@ public final class InfeedDequeue<T extends TType> extends RawOp implements Opera
    * @return a new instance of InfeedDequeue
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> InfeedDequeue<T> create(Scope scope, DataType<T> dtype, Shape shape) {
+  public static <T extends TType> InfeedDequeue<T> create(Scope scope, Class<T> dtype, Shape shape) {
     OperationBuilder opBuilder = scope.env().opBuilder("InfeedDequeue", scope.makeOpName("InfeedDequeue"));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     opBuilder.setAttr("shape", shape);
     return new InfeedDequeue<T>(opBuilder.build());
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeueTuple.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeueTuple.java
index 941886098b6..4816ea0a306 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeueTuple.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeueTuple.java
@@ -20,12 +20,12 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -46,14 +46,10 @@ public final class InfeedDequeueTuple extends RawOp implements Iterable<Operand<
    * @return a new instance of InfeedDequeueTuple
    */
   @Endpoint(describeByClass = true)
-  public static InfeedDequeueTuple create(Scope scope, List<DataType<?>> dtypes, List<Shape> shapes) {
+  public static InfeedDequeueTuple create(Scope scope, List<Class<? extends TType>> dtypes, List<Shape> shapes) {
     OperationBuilder opBuilder = scope.env().opBuilder("InfeedDequeueTuple", scope.makeOpName("InfeedDequeueTuple"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     Shape[] shapesArray = new Shape[shapes.size()];
     for (int i = 0; i < shapesArray.length; ++i) {
       shapesArray[i] = shapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java
index 29c516c6a57..e5aa5a35ed7 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.tpu;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -69,10 +69,10 @@ private Options() {
    * @return a new instance of OutfeedDequeue
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> OutfeedDequeue<T> create(Scope scope, DataType<T> dtype, Shape shape, Options... options) {
+  public static <T extends TType> OutfeedDequeue<T> create(Scope scope, Class<T> dtype, Shape shape, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("OutfeedDequeue", scope.makeOpName("OutfeedDequeue"));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     opBuilder.setAttr("shape", shape);
     if (options != null) {
       for (Options opts : options) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTuple.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTuple.java
index e86472c77e0..705666e1f02 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTuple.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTuple.java
@@ -20,12 +20,12 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -71,14 +71,10 @@ private Options() {
    * @return a new instance of OutfeedDequeueTuple
    */
   @Endpoint(describeByClass = true)
-  public static OutfeedDequeueTuple create(Scope scope, List<DataType<?>> dtypes, List<Shape> shapes, Options... options) {
+  public static OutfeedDequeueTuple create(Scope scope, List<Class<? extends TType>> dtypes, List<Shape> shapes, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("OutfeedDequeueTuple", scope.makeOpName("OutfeedDequeueTuple"));
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     Shape[] shapesArray = new Shape[shapes.size()];
     for (int i = 0; i < shapesArray.length; ++i) {
       shapesArray[i] = shapes.get(i);
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java
index cb6f79796ff..ed8becceee2 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.train;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -55,12 +55,12 @@ public final class AccumulatorTakeGradient<T extends TType> extends RawOp implem
    * @return a new instance of AccumulatorTakeGradient
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> AccumulatorTakeGradient<T> create(Scope scope, Operand<TString> handle, Operand<TInt32> numRequired, DataType<T> dtype) {
+  public static <T extends TType> AccumulatorTakeGradient<T> create(Scope scope, Operand<TString> handle, Operand<TInt32> numRequired, Class<T> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("AccumulatorTakeGradient", scope.makeOpName("AccumulatorTakeGradient"));
     opBuilder.addInput(handle.asOutput());
     opBuilder.addInput(numRequired.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new AccumulatorTakeGradient<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ConditionalAccumulator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ConditionalAccumulator.java
index 5cc5297559f..684d9e3485e 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ConditionalAccumulator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ConditionalAccumulator.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.train;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -92,10 +92,10 @@ private Options() {
    * @return a new instance of ConditionalAccumulator
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> ConditionalAccumulator create(Scope scope, DataType<T> dtype, Shape shape, Options... options) {
+  public static <T extends TType> ConditionalAccumulator create(Scope scope, Class<T> dtype, Shape shape, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("ConditionalAccumulator", scope.makeOpName("ConditionalAccumulator"));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     opBuilder.setAttr("shape", shape);
     if (options != null) {
       for (Options opts : options) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java
index 5758aec8517..62e33a44749 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.train;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -53,12 +53,12 @@ public final class ResourceAccumulatorTakeGradient<T extends TType> extends RawO
    * @return a new instance of ResourceAccumulatorTakeGradient
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> ResourceAccumulatorTakeGradient<T> create(Scope scope, Operand<?> handle, Operand<TInt32> numRequired, DataType<T> dtype) {
+  public static <T extends TType> ResourceAccumulatorTakeGradient<T> create(Scope scope, Operand<?> handle, Operand<TInt32> numRequired, Class<T> dtype) {
     OperationBuilder opBuilder = scope.env().opBuilder("ResourceAccumulatorTakeGradient", scope.makeOpName("ResourceAccumulatorTakeGradient"));
     opBuilder.addInput(handle.asOutput());
     opBuilder.addInput(numRequired.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     return new ResourceAccumulatorTakeGradient<T>(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceConditionalAccumulator.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceConditionalAccumulator.java
index 5471a48a5e9..d44b93e6ac1 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceConditionalAccumulator.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceConditionalAccumulator.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.train;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -92,10 +92,10 @@ private Options() {
    * @return a new instance of ResourceConditionalAccumulator
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> ResourceConditionalAccumulator create(Scope scope, DataType<T> dtype, Shape shape, Options... options) {
+  public static <T extends TType> ResourceConditionalAccumulator create(Scope scope, Class<T> dtype, Shape shape, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("ResourceConditionalAccumulator", scope.makeOpName("ResourceConditionalAccumulator"));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     opBuilder.setAttr("shape", shape);
     if (options != null) {
       for (Options opts : options) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/Restore.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/Restore.java
index a198182719e..bf19384f360 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/Restore.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/Restore.java
@@ -20,11 +20,11 @@
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -65,17 +65,13 @@ public final class Restore extends RawOp implements Iterable<Operand<TType>> {
    * @return a new instance of Restore
    */
   @Endpoint(describeByClass = true)
-  public static Restore create(Scope scope, Operand<TString> prefix, Operand<TString> tensorNames, Operand<TString> shapeAndSlices, List<DataType<?>> dtypes) {
+  public static Restore create(Scope scope, Operand<TString> prefix, Operand<TString> tensorNames, Operand<TString> shapeAndSlices, List<Class<? extends TType>> dtypes) {
     OperationBuilder opBuilder = scope.env().opBuilder("RestoreV2", scope.makeOpName("Restore"));
     opBuilder.addInput(prefix.asOutput());
     opBuilder.addInput(tensorNames.asOutput());
     opBuilder.addInput(shapeAndSlices.asOutput());
     opBuilder = scope.apply(opBuilder);
-    DataType[] dtypesArray = new DataType[dtypes.size()];
-    for (int i = 0; i < dtypesArray.length; ++i) {
-      dtypesArray[i] = dtypes.get(i);
-    }
-    opBuilder.setAttr("dtypes", dtypesArray);
+    opBuilder.setAttr("dtypes", Operands.toDataTypes(dtypes));
     return new Restore(opBuilder.build());
   }
   
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/RestoreSlice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/RestoreSlice.java
index 55fded1c9ff..579b5b8dbad 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/RestoreSlice.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/RestoreSlice.java
@@ -17,11 +17,11 @@
 
 package org.tensorflow.op.train;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -79,13 +79,13 @@ private Options() {
    * @return a new instance of RestoreSlice
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> RestoreSlice<T> create(Scope scope, Operand<TString> filePattern, Operand<TString> tensorName, Operand<TString> shapeAndSlice, DataType<T> dt, Options... options) {
+  public static <T extends TType> RestoreSlice<T> create(Scope scope, Operand<TString> filePattern, Operand<TString> tensorName, Operand<TString> shapeAndSlice, Class<T> dt, Options... options) {
     OperationBuilder opBuilder = scope.env().opBuilder("RestoreSlice", scope.makeOpName("RestoreSlice"));
     opBuilder.addInput(filePattern.asOutput());
     opBuilder.addInput(tensorName.asOutput());
     opBuilder.addInput(shapeAndSlice.asOutput());
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dt", dt);
+    opBuilder.setAttr("dt", Operands.toDataType(dt));
     if (options != null) {
       for (Options opts : options) {
         if (opts.preferredShard != null) {
diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Recv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Recv.java
index 13a7e85b001..05781f61017 100644
--- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Recv.java
+++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/Recv.java
@@ -17,12 +17,12 @@
 
 package org.tensorflow.op.xla;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Operands;
 import org.tensorflow.op.RawOp;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
@@ -50,10 +50,10 @@ public final class Recv<T extends TType> extends RawOp implements Operand<T> {
    * @return a new instance of Recv
    */
   @Endpoint(describeByClass = true)
-  public static <T extends TType> Recv<T> create(Scope scope, DataType<T> dtype, String tensorName, Shape shape) {
+  public static <T extends TType> Recv<T> create(Scope scope, Class<T> dtype, String tensorName, Shape shape) {
     OperationBuilder opBuilder = scope.env().opBuilder("XlaRecv", scope.makeOpName("Recv"));
     opBuilder = scope.apply(opBuilder);
-    opBuilder.setAttr("dtype", dtype);
+    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
     opBuilder.setAttr("tensor_name", tensorName);
     opBuilder.setAttr("shape", shape);
     return new Recv<T>(opBuilder.build());
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/AbstractOperation.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/AbstractOperation.java
index 18f42d08e82..0ffd6c2205e 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/AbstractOperation.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/AbstractOperation.java
@@ -17,6 +17,7 @@
 
 import org.bytedeco.javacpp.Pointer;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -76,7 +77,7 @@ public String toString() {
    * @param outputIdx index of the output of this operation
    * @return output tensor datatype
    */
-  abstract DataType<?> dtype(int outputIdx);
+  abstract DataType dtype(int outputIdx);
 
   /**
    * Returns the tensor of the {@code outputIdx}th output of this operation.
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/ConcreteFunction.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/ConcreteFunction.java
index 0bb0d20cae3..71dc0f7cefc 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/ConcreteFunction.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/ConcreteFunction.java
@@ -54,7 +54,7 @@ public class ConcreteFunction implements AutoCloseable {
    * public class MyModel {
    *
    *   public static Signature addTwo(Ops tf) {
-   *     Placeholder<TFloat32> input = tf.placeholder(TFloat32.DTYPE);
+   *     Placeholder<TFloat32> input = tf.placeholder(TFloat32.class);
    *     Add<TFloat32> output = tf.math.add(input, tf.constant(2.0f));
    *     return Signature.builder("addTwo").input("x", input).output("y", output).build();
    *   }
@@ -92,7 +92,7 @@ public static ConcreteFunction create(Function<Ops, Signature> functionBuilder)
    *
    * <pre>{@code
    * try (Graph g = new Graph()) {
-   *   Placeholder<TFloat32> input = tf.placeholder(TFloat32.DTYPE);
+   *   Placeholder<TFloat32> input = tf.placeholder(TFloat32.class);
    *   Add<TFloat32> output = tf.math.add(input, tf.constant(2.0f));
    *   Signature signature = Signature.builder().input("x", input).output("y", output).build();
    *
@@ -121,7 +121,7 @@ public static ConcreteFunction create(Signature signature, Graph graph) {
    *
    * <pre>{@code
    * try (Graph g = new Graph()) {
-   *   Placeholder<TFloat32> input = tf.placeholder(TFloat32.DTYPE);
+   *   Placeholder<TFloat32> input = tf.placeholder(TFloat32.class);
    *   Add<TFloat32> output = tf.math.add(input, tf.constant(2.0f));
    *   Signature signature = Signature.builder().input("x", input).output("y", output).build();
    *
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/DataType.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/DataType.java
deleted file mode 100644
index 60657837969..00000000000
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/DataType.java
+++ /dev/null
@@ -1,166 +0,0 @@
-/* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-package org.tensorflow;
-
-import org.tensorflow.types.TBfloat16;
-import org.tensorflow.types.TBool;
-import org.tensorflow.types.TFloat16;
-import org.tensorflow.types.TFloat32;
-import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
-import org.tensorflow.types.TInt64;
-import org.tensorflow.types.TUint8;
-import org.tensorflow.types.TString;
-import org.tensorflow.types.family.TType;
-
-/** Represents a type of elements in a {@link Tensor} */
-public final class DataType<T extends TType> {
-
-  /**
-   * Creates a new datatype
-   *
-   * @param name readable-name for this type
-   * @param value must match the corresponding TF_* value in the TensorFlow C API.
-   * @param byteSize size of an element of this type, in bytes, -1 if unknown
-   * @param <T> a tensor type
-   * @param tensorMapper method for mapping tensor memory to elements of this type
-   */
-  public static <T extends TType> DataType<T> create(
-      String name, int value, int byteSize, TensorMapper<T> tensorMapper) {
-    return new DataType<>(name, value, byteSize, tensorMapper);
-  }
-
-  /**
-   * Gets the DataType associated with the readable-name for the type
-   * <p>The name must match exactly the name used to create the desired DataType</p>
-   *
-   * @param name readable-name for the type
-   * @return the DataType
-   * @throws java.lang.IllegalArgumentException if the name is not a valid data type name
-   * @throws java.lang.NullPointerException if name is null
-   */
-  public static DataType<? extends TType> of(String name) {
-    switch (name) {
-      case TBfloat16.NAME:
-        return TBfloat16.DTYPE;
-      case TFloat16.NAME:
-        return TFloat16.DTYPE;
-      case TFloat32.NAME:
-        return TFloat32.DTYPE;
-      case TFloat64.NAME:
-        return TFloat64.DTYPE;
-      case TUint8.NAME:
-        return TUint8.DTYPE;
-      case TInt32.NAME:
-        return TInt32.DTYPE;
-      case TInt64.NAME:
-        return TInt64.DTYPE;
-      case TBool.NAME:
-        return TBool.DTYPE;
-      case TString.NAME:
-        return TString.DTYPE;
-      default:
-        throw new IllegalArgumentException(String.format("%s is an unknown DataType", name));
-    }
-  }
-
-  /** Returns true if this data type represents a floating point type */
-  public boolean isFloating() {
-    switch (this.name()) {
-      case TBfloat16.NAME:
-      case TFloat16.NAME:
-      case TFloat32.NAME:
-      case TFloat64.NAME:
-        return true;
-      default:
-        return false;
-    }
-  }
-
-  /** Returns true if this data type represents an integer type */
-  public boolean isInteger() {
-    switch (this.name()) {
-      case TInt32.NAME:
-      case TInt64.NAME:
-      case TUint8.NAME:
-        return true;
-      default:
-        return false;
-    }
-  }
-
-  /** Returns true if this data type represents a numeric type */
-  public boolean isNumeric() {
-    return isFloating() || isInteger();
-  }
-
-  /** Returns true if this data type represents a boolean type */
-  public boolean isBoolean() {
-    return this.name().equals(TBool.NAME);
-  }
-
-  /** Returns true if this data type represents a string type */
-  public boolean isString() {
-    return this.name().equals(TString.NAME);
-  }
-
-  /** Returns the size of an element of this type, in bytes, or -1 if element size is variable. */
-  public int byteSize() {
-    return byteSize;
-  }
-
-  /** Returns true if this datatype has elements of variable length */
-  public boolean isVariableLength() {
-    return byteSize == -1;
-  }
-
-  /** Returns a readable name for this type */
-  public String name() {
-    return name;
-  }
-
-  @Override
-  public String toString() {
-    return name + " (" + nativeCode + ")";
-  }
-
-  /** Returns the numeric code for this datatype, as recognized by the native library (C API) */
-  int nativeCode() {
-    return nativeCode;
-  }
-
-  /**
-   * Maps a raw tensor to a typed tensor.
-   *
-   * @param tensor tensor to map
-   * @return data structure of elements of this type
-   */
-  T map(RawTensor tensor) {
-    return tensorMapper.mapDense(tensor);
-  }
-
-  private final int nativeCode;
-  private final int byteSize;
-  private final String name;
-  private final TensorMapper<T> tensorMapper;
-
-  private DataType(String name, int nativeCode, int byteSize, TensorMapper<T> tensorMapper) {
-    this.name = name;
-    this.nativeCode = nativeCode;
-    this.byteSize = byteSize;
-    this.tensorMapper = tensorMapper;
-  }
-}
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/DataTypes.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/DataTypes.java
deleted file mode 100644
index 77c0de0c83f..00000000000
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/DataTypes.java
+++ /dev/null
@@ -1,75 +0,0 @@
-/*
- *  Copyright 2019 The TensorFlow Authors. All Rights Reserved.
- *
- *  Licensed under the Apache License, Version 2.0 (the "License");
- *  you may not use this file except in compliance with the License.
- *  You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- *  Unless required by applicable law or agreed to in writing, software
- *  distributed under the License is distributed on an "AS IS" BASIS,
- *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- *  See the License for the specific language governing permissions and
- *  limitations under the License.
- *  =======================================================================
- */
-
-package org.tensorflow;
-
-import java.util.HashMap;
-import java.util.Map;
-import org.tensorflow.types.TBfloat16;
-import org.tensorflow.types.TBool;
-import org.tensorflow.types.TFloat16;
-import org.tensorflow.types.TFloat32;
-import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
-import org.tensorflow.types.TInt64;
-import org.tensorflow.types.TString;
-import org.tensorflow.types.TUint8;
-
-/**
- * Utility class for working with {@link DataType} objects.
- */
-final class DataTypes {
-
-  /**
-   * Find a data type from the type code returned by the native layer (C API).
-   *
-   * <p>Only data types registered via {@link #register(DataType)} can be resolved.
-   *
-   * @param nativeCode native code
-   * @return data type for this code
-   * @throws IllegalArgumentException if the code matches no registered data type
-   */
-  static DataType<?> fromNativeCode(int nativeCode) {
-    DataType<?> dataType = DATA_TYPE_REGISTRY.get(nativeCode);
-    if (dataType == null) {
-      throw new IllegalArgumentException(
-          "DataType " + nativeCode + " is not recognized in Java (version " + TensorFlow.version() + ")");
-    }
-    return dataType;
-  }
-
-  private static final Map<Integer, DataType<?>> DATA_TYPE_REGISTRY = new HashMap<>();
-
-  static {
-    register(TBool.DTYPE);
-    register(TFloat64.DTYPE);
-    register(TFloat32.DTYPE);
-    register(TFloat16.DTYPE);
-    register(TInt32.DTYPE);
-    register(TInt64.DTYPE);
-    register(TString.DTYPE);
-    register(TUint8.DTYPE);
-    register(TBfloat16.DTYPE);
-  }
-
-  // TODO (karllessard): Right now this method is private but we might want to expose it
-  //      to allow user to register custom data types?
-  private static void register(DataType<?> dataType) {
-    DATA_TYPE_REGISTRY.put(dataType.nativeCode(), dataType);
-    DATA_TYPE_REGISTRY.put(dataType.nativeCode() + 100, dataType);
-  }
-}
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperation.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperation.java
index 30387e390ed..09e5a47f8fd 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperation.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperation.java
@@ -29,6 +29,7 @@
 import org.tensorflow.internal.c_api.TF_Status;
 import org.tensorflow.internal.c_api.TF_Tensor;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.proto.framework.DataType;
 
 /**
  * Implementation of an {@link Operation} executed eagerly.
@@ -83,12 +84,12 @@ public int inputListLength(final String name) {
   }
 
   @Override
-  public TFE_TensorHandle getUnsafeNativeHandle(int outputIndex) {
+  TFE_TensorHandle getUnsafeNativeHandle(int outputIndex) {
     return outputHandles[outputIndex];
   }
 
   @Override
-  public Shape shape(int outputIndex) {
+  Shape shape(int outputIndex) {
     // If the tensor of this output has already been resolved, return its shape.
     // Otherwise, retrieve the tensor shape from the native library.
     Tensor tensor = outputTensors.get(outputIndex);
@@ -104,7 +105,7 @@ public Shape shape(int outputIndex) {
   }
 
   @Override
-  public DataType<?> dtype(int outputIndex) {
+  DataType dtype(int outputIndex) {
     // If the tensor of this output has already been resolved, return its datatype.
     // Otherwise, retrieve the tensor datatype from the native library.
     Tensor tensor = outputTensors.get(outputIndex);
@@ -112,11 +113,11 @@ public DataType<?> dtype(int outputIndex) {
       return tensor.dataType();
     }
     TFE_TensorHandle outputNativeHandle = getUnsafeNativeHandle(outputIndex);
-    return DataTypes.fromNativeCode(dataType(outputNativeHandle));
+    return DataType.forNumber(dataType(outputNativeHandle));
   }
 
   @Override
-  public Tensor tensor(int outputIndex) {
+  Tensor tensor(int outputIndex) {
     Tensor tensor = outputTensors.get(outputIndex);
     if (tensor == null) {
       tensor = resolveTensor(outputIndex);
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperationBuilder.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperationBuilder.java
index 5c975929fee..9df8444a11f 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperationBuilder.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerOperationBuilder.java
@@ -48,6 +48,7 @@
 import org.tensorflow.internal.c_api.TF_Status;
 import org.tensorflow.internal.c_api.TF_Tensor;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.proto.framework.DataType;
 
 /**
  * An {@link OperationBuilder} for building {@link Operation Operations} that are executed eagerly.
@@ -159,16 +160,16 @@ public EagerOperationBuilder setAttr(String name, boolean[] values) {
   }
 
   @Override
-  public EagerOperationBuilder setAttr(String name, DataType<?> value) {
-    setAttrType(opHandle, name, value.nativeCode());
+  public EagerOperationBuilder setAttr(String name, DataType value) {
+    setAttrType(opHandle, name, value.getNumber());
     return this;
   }
 
   @Override
-  public EagerOperationBuilder setAttr(String name, DataType<?>[] values) {
+  public EagerOperationBuilder setAttr(String name, DataType[] values) {
     int[] c = new int[values.length];
     for (int i = 0; i < values.length; ++i) {
-      c[i] = values[i].nativeCode();
+      c[i] = values[i].getNumber();
     }
     setAttrTypeList(opHandle, name, c);
     return this;
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Graph.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Graph.java
index 142d481c04f..d70460ee4ea 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Graph.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Graph.java
@@ -54,6 +54,7 @@
 import org.tensorflow.proto.framework.GraphDef;
 import org.tensorflow.proto.util.SaverDef;
 import org.tensorflow.types.TString;
+import org.tensorflow.types.family.TType;
 
 
 /**
@@ -767,14 +768,14 @@ private static SaverDef addVariableSaver(Graph graph) {
 
     List<String> varNames = new ArrayList<>();
     List<Operand<?>> varOutputs = new ArrayList<>();
-    List<DataType<?>> varTypes = new ArrayList<>();
+    List<Class<? extends TType>> varTypes = new ArrayList<>();
 
     for (Iterator<Operation> iter = graph.operations(); iter.hasNext();) {
       Operation op = iter.next();
       if (op.type().equals("VariableV2")) {
         varNames.add(op.name());
         varOutputs.add(op.output(0));
-        varTypes.add(op.output(0).dataType());
+        varTypes.add(op.output(0).type());
       }
     }
 
@@ -783,7 +784,7 @@ private static SaverDef addVariableSaver(Graph graph) {
     Constant<TString> varNamesTensor = tf.constant(StdArrays.ndCopyOf(varNames.toArray(tmp)));
     Operand<TString> varSlices = tf.zerosLike(varNamesTensor);
 
-    Placeholder<TString> saveFilename = tf.placeholder(TString.DTYPE);
+    Placeholder<TString> saveFilename = tf.placeholder(TString.class);
     Save saveVariables = tf.train.save(
         saveFilename,
         varNamesTensor,
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperation.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperation.java
index d2fbc4e4995..e1255748c3b 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperation.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperation.java
@@ -31,6 +31,7 @@
 import org.tensorflow.internal.c_api.TF_Output;
 import org.tensorflow.internal.c_api.TF_Status;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.proto.framework.DataType;
 
 /**
  * Implementation for an {@link Operation} added as a node to a {@link Graph}.
@@ -148,10 +149,10 @@ Shape shape(int outputIdx) {
   }
 
   @Override
-  DataType<?> dtype(int outputIdx) {
+  DataType dtype(int outputIdx) {
     Graph.Reference r = graph.ref();
     try {
-      return DataTypes.fromNativeCode(dtype(r.nativeHandle(), getUnsafeNativeHandle(), outputIdx));
+      return DataType.forNumber(dtype(r.nativeHandle(), getUnsafeNativeHandle(), outputIdx));
     } finally {
       r.close();
     }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperationBuilder.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperationBuilder.java
index 5fda65480e9..927d9c52dd1 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperationBuilder.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/GraphOperationBuilder.java
@@ -52,6 +52,7 @@
 import org.tensorflow.internal.c_api.TF_Status;
 import org.tensorflow.internal.c_api.TF_Tensor;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.proto.framework.DataType;
 
 /** An {@link OperationBuilder} for adding {@link GraphOperation}s to a {@link Graph}. */
 public final class GraphOperationBuilder implements OperationBuilder {
@@ -224,7 +225,7 @@ public GraphOperationBuilder setAttr(String name, boolean[] value) {
   public GraphOperationBuilder setAttr(String name, DataType value) {
     Graph.Reference r = graph.ref();
     try {
-      setAttrType(unsafeNativeHandle, name, value.nativeCode());
+      setAttrType(unsafeNativeHandle, name, value.getNumber());
     } finally {
       r.close();
     }
@@ -235,7 +236,7 @@ public GraphOperationBuilder setAttr(String name, DataType value) {
   public GraphOperationBuilder setAttr(String name, DataType[] value) {
     int[] ctypes = new int[value.length];
     for (int i = 0; i < value.length; ++i) {
-      ctypes[i] = value[i].nativeCode();
+      ctypes[i] = value[i].getNumber();
     }
     Graph.Reference r = graph.ref();
     try {
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Operand.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Operand.java
index 31a93fb999a..80f62eb5acc 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Operand.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Operand.java
@@ -30,11 +30,11 @@
  *
  * // The "decodeJpeg" operation can be used as an operand to the "cast" operation
  * Operand<TUint8> decodeJpeg = tf.image.decodeJpeg(...);
- * tf.dtypes.cast(decodeJpeg, TFloat32.DTYPE);
+ * tf.dtypes.cast(decodeJpeg, TFloat32.class);
  *
  * // The output "y" of the "unique" operation can be used as an operand to the "cast" operation
  * Output<TInt32> y = tf.unique(...).y();
- * tf.dtypes.cast(y, TFloat32.DTYPE);
+ * tf.dtypes.cast(y, TFloat32.class);
  *
  * // The "split" operation can be used as operand list to the "concat" operation
  * Iterable<? extends Operand<TFloat32>> split = tf.split(...);
@@ -66,10 +66,10 @@ default T asTensor() {
   }
 
   /**
-   * Returns the data type of this operand
+   * Returns the tensor type of this operand
    */
-  default DataType<T> dataType() {
-    return asOutput().dataType();
+  default Class<T> type() {
+    return asOutput().type();
   }
 
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/OperationBuilder.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/OperationBuilder.java
index 79f21c33fb7..a487d8b9237 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/OperationBuilder.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/OperationBuilder.java
@@ -16,6 +16,7 @@
 package org.tensorflow;
 
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.proto.framework.DataType;
 
 /**
  * A builder for {@link Operation}s.
@@ -177,7 +178,7 @@ public interface OperationBuilder {
    * @param value attribute value
    * @return the OperationBuilder instance for chaining.
    */
-   OperationBuilder setAttr(String name, DataType<?> value);
+   OperationBuilder setAttr(String name, DataType value);
 
   /**
    * Set the type values of an attribute of the operation being built.
@@ -186,7 +187,7 @@ public interface OperationBuilder {
    * @param value attribute values
    * @return the OperationBuilder instance for chaining.
    */
-   OperationBuilder setAttr(String name, DataType<?>[] value);
+   OperationBuilder setAttr(String name, DataType[] value);
 
   /**
    * Set the tensor value of an attribute of the operation being built.
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Output.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Output.java
index 5b8337f4d70..9e7dedfdc75 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Output.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Output.java
@@ -17,8 +17,9 @@
 
 import java.util.Objects;
 import org.bytedeco.javacpp.Pointer;
+import org.tensorflow.internal.types.registry.TensorTypeRegistry;
 import org.tensorflow.ndarray.Shape;
-import org.tensorflow.ndarray.Shaped;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -39,23 +40,30 @@ public int index() {
 
   /** Returns the DataType of the tensor referred to by this Output. */
   @SuppressWarnings("unchecked")
-  public DataType<T> dataType() {
-    return (DataType<T>)operation.dtype(index);
+  public DataType dataType() {
+    return operation.dtype(index);
+  }
+
+  /** Returns the type of the tensor referred to by this Output. */
+  @SuppressWarnings("unchecked")
+  @Override
+  public Class<T> type() {
+    return (Class<T>)TensorTypeRegistry.find(dataType()).type();
   }
 
   /**
    * Returns this Output object with the type {@code Output<U>}. This method is useful when given a
    * value of type {@code Output<?>}.
    *
-   * @param dt any supported tensor data type
+   * @param type any supported tensor type
    * @throws IllegalArgumentException if the actual data type of this object does not match the type
    *     {@code U}.
    */
   @SuppressWarnings("unchecked")
-  public <U extends TType> Output<U> expect(DataType<U> dt) {
-    if (!dt.equals(this.dataType())) {
+  public <U extends TType> Output<U> expect(Class<U> type) {
+    if (type != type()) {
       throw new IllegalArgumentException(
-          "Cannot cast from output of " + this.dataType() + " to output of " + dt);
+          "Cannot cast from output of " + this.type().getSimpleName() + " to output of " + type.getSimpleName());
     }
     return ((Output<U>) this);
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/RawTensor.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/RawTensor.java
index 5af44ce73df..c332fd7f1d1 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/RawTensor.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/RawTensor.java
@@ -23,9 +23,11 @@
 import org.bytedeco.javacpp.PointerScope;
 import org.tensorflow.internal.buffer.TensorBuffers;
 import org.tensorflow.internal.c_api.TF_Tensor;
+import org.tensorflow.internal.types.registry.TensorTypeInfo;
+import org.tensorflow.internal.types.registry.TensorTypeRegistry;
 import org.tensorflow.ndarray.Shape;
-import org.tensorflow.ndarray.Shaped;
 import org.tensorflow.ndarray.buffer.ByteDataBuffer;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -42,8 +44,8 @@
 public final class RawTensor implements Tensor {
 
   @Override
-  public DataType<?> dataType() {
-    return dtype;
+  public DataType dataType() {
+    return typeInfo.dataType();
   }
 
   @Override
@@ -84,33 +86,52 @@ public ByteDataBuffer data() {
    */
   @Override
   public String toString() {
-    return String.format("%s tensor with shape %s", dtype.toString(), shape);
+    return String.format("%s tensor with shape %s", typeInfo.dataType(), shape);
   }
 
   /**
    * Allocates a new tensor in native memory of the given type, shape and size.
    *
    * <p>The size of the tensor must be at least large enough to contain all scalars for the
-   * given type and shape, i.e. <code>size >= dtype.byteSize() * shape.size()</code>. More memory
-   * can be allocated to store also metadata within the tensor itself, e.g. a lookup table
-   * in a string tensor.
+   * given type and shape. More memory can also be allocated to store also metadata within the
+   * tensor itself, e.g. a lookup table in a string tensor.
    *
-   * @param dtype data type
+   * @param type tensor type class
    * @param shape shape of the tensor
-   * @param size size of the tensor
+   * @param size size in bytes of the tensor, or -1 to compute the size from the shape
    * @return allocated tensor
+   * @throws IllegalArgumentException if {@code size} is smaller than the minimum space required to
+   *                                  store the tensor data
+   * @throws IllegalArgumentException if {@code size} is set to -1 but elements of the given
+   *                                  {@code type} are of variable length (e.g. strings)
+   * @throws IllegalArgumentException if {@code shape} is totally or partially
+   *                                  {@link Shape#hasUnknownDimension() unknown}
+   * @throws IllegalStateException if tensor failed to be allocated
    */
-  static RawTensor allocate(DataType<?> dtype, Shape shape, long size) {
-    // Minimum requirements for datatypes of variable length cannot be verified in a relevant way so
-    // we only validate them for fixed length datatypes
-    if (!dtype.isVariableLength() && shape.size() * dtype.byteSize() > size) {
-      throw new IllegalArgumentException("Tensor size is not large enough to contain all scalar values");
+  static RawTensor allocate(Class<? extends TType> type, Shape shape, long size) {
+    if (shape.hasUnknownDimension()) {
+      throw new IllegalArgumentException(
+          "Cannot allocate a tensor from a totally or partially unknown shape");
     }
-    TF_Tensor nativeHandle = allocate(dtype.nativeCode(), shape.asArray(), size);
+    TensorTypeInfo<?> typeInfo = TensorTypeRegistry.find(type);
+    long allocatedSize = size;
+    if (allocatedSize < 0) {
+      if (typeInfo.isVariableLength()) {
+        throw new IllegalArgumentException(
+            "Explicit size is required for variable-length tensor types");
+      }
+      allocatedSize = shape.size() * typeInfo.byteSize();
+
+    } else if (!typeInfo.isVariableLength() && shape.size() * typeInfo.byteSize() > allocatedSize) {
+      // Minimum requirements for datatypes of variable length cannot be verified in a relevant way so
+      // we only validate them for fixed length datatypes
+      throw new IllegalArgumentException(
+          "Tensor size is not large enough to contain all scalar values");
+    }
+    TF_Tensor nativeHandle = allocate(typeInfo.dataType().getNumber(), shape.asArray(), allocatedSize);
     try (PointerScope scope = new PointerScope()) {
       scope.attach(nativeHandle);
-
-      RawTensor t = new RawTensor(dtype, shape);
+      RawTensor t = new RawTensor(typeInfo, shape);
       t.tensorHandle = nativeHandle;
       t.tensorScope = scope.extend();
       return t;
@@ -123,7 +144,8 @@ static RawTensor allocate(DataType<?> dtype, Shape shape, long size) {
    * <p>Takes ownership of the handle.
    */
   static RawTensor fromHandle(TF_Tensor handle) {
-    RawTensor t = new RawTensor(DataTypes.fromNativeCode(dtype(handle)), Shape.of(shape(handle)));
+    TensorTypeInfo<?> typeInfo = TensorTypeRegistry.find(DataType.forNumber(dtype(handle)));
+    RawTensor t = new RawTensor(typeInfo, Shape.of(shape(handle)));
     try (PointerScope scope = new PointerScope()) {
         scope.attach(handle);
         t.tensorHandle = handle;
@@ -158,13 +180,10 @@ TF_Tensor nativeHandle() {
    * <p>In some cases, it is more useful to keep a typed reference to a tensor rather than its raw
    * nature to prevent mapping its memory on every access (e.g. when calling {@link Operand#asTensor()}).
    *
-   * @param <T> type of the tensor (must be compatible with the internal representation of this tensor,
-   *            as indicated by {@link #dataType()})
    * @return typed reference to this tensor
-   * @throws ClassCastException if {@code T} is not compatible type with {@link #dataType()}
    */
-  <T extends TType> T asTypedTensor() {
-    return (T)dtype.map(this);
+  TType asTypedTensor() {
+    return typeInfo.mapper().mapDense(this);
   }
 
   private static TF_Tensor requireHandle(TF_Tensor handle) {
@@ -197,14 +216,14 @@ private static long[] shape(TF_Tensor handle) {
     return dims;
   }
 
-  RawTensor(DataType<?> dtype, Shape shape) {
-    this.dtype = dtype;
+  RawTensor(TensorTypeInfo<? extends TType> typeInfo, Shape shape) {
+    this.typeInfo = typeInfo;
     this.shape = shape;
   }
 
   private PointerScope tensorScope;
   private TF_Tensor tensorHandle;
-  private final DataType<?> dtype;
+  private final TensorTypeInfo<? extends TType> typeInfo;
   private final Shape shape;
   private ByteDataBuffer buffer = null;
 
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Signature.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Signature.java
index 376dc9039fc..ea32d1fff13 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Signature.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Signature.java
@@ -18,7 +18,6 @@
 import java.util.Map;
 import java.util.Set;
 import org.tensorflow.ndarray.Shape;
-import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.proto.framework.SignatureDef;
 import org.tensorflow.proto.framework.TensorInfo;
 import org.tensorflow.proto.framework.TensorShapeProto;
@@ -113,7 +112,7 @@ private static TensorInfo toTensorInfo(Output<?> operand) {
         tensorShapeBuilder.addDim(Dim.newBuilder().setSize(shape.size(i)));
       }
       return TensorInfo.newBuilder()
-          .setDtype(DataType.forNumber(operand.dataType().nativeCode()))
+          .setDtype(operand.dataType())
           .setTensorShape(tensorShapeBuilder)
           .setName(operand.op().name() + ":" + operand.index())
           .build();
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Tensor.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Tensor.java
index bccdf698608..fc1275229bf 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Tensor.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Tensor.java
@@ -15,19 +15,11 @@
 
 package org.tensorflow;
 
-import static org.tensorflow.internal.c_api.global.tensorflow.TF_Dim;
-import static org.tensorflow.internal.c_api.global.tensorflow.TF_NumDims;
-import static org.tensorflow.internal.c_api.global.tensorflow.TF_TensorByteSize;
-import static org.tensorflow.internal.c_api.global.tensorflow.TF_TensorType;
-
 import java.util.function.Consumer;
-import org.bytedeco.javacpp.PointerScope;
-import org.tensorflow.internal.buffer.TensorBuffers;
-import org.tensorflow.internal.c_api.TF_Tensor;
-import org.tensorflow.ndarray.NdArray;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.ndarray.Shaped;
 import org.tensorflow.ndarray.buffer.ByteDataBuffer;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -57,37 +49,45 @@ public interface Tensor extends Shaped, AutoCloseable {
    * <p>The amount of memory to allocate is derived from the datatype and the shape of the tensor,
    * and is left uninitialized.
    *
-   * @param <T> the tensor element type
-   * @param dtype datatype of the tensor
+   * @param <T> the tensor type
+   * @param type the tensor type class
    * @param shape shape of the tensor
    * @return an allocated but uninitialized tensor
+   * @throws IllegalArgumentException if elements of the given {@code type} are of variable length
+   *                                  (e.g. strings)
+   * @throws IllegalArgumentException if {@code shape} is totally or partially
+   *                                  {@link Shape#hasUnknownDimension() unknown}
    * @throws IllegalStateException if tensor failed to be allocated
    */
-  static <T extends TType> T of(DataType<T> dtype, Shape shape) {
-    return of(dtype, shape, shape.size() * dtype.byteSize());
+  static <T extends TType> T of(Class<T> type, Shape shape) {
+    return of(type, shape, -1);
   }
 
   /**
    * Allocates a tensor of a given datatype, shape and size.
    *
-   * <p>This method is identical to {@link #of(DataType, Shape)}, except that the final size of the
-   * tensor is explicitly set instead of computing it from the datatype and shape, which could be
+   * <p>This method is identical to {@link #of(Class, Shape)}, except that the final size of the
+   * tensor can be explicitly set instead of computing it from the datatype and shape, which could be
    * larger than the actual space required to store the data but not smaller.
    *
-   * @param <T> the tensor element type
-   * @param dtype datatype of the tensor
+   * @param <T> the tensor type
+   * @param type the tensor type class
    * @param shape shape of the tensor
-   * @param size size, in bytes, of the tensor
+   * @param size size in bytes of the tensor or -1 to compute the size from the shape
    * @return an allocated but uninitialized tensor
-   * @see #of(DataType, Shape)
+   * @see #of(Class, Shape)
    * @throws IllegalArgumentException if {@code size} is smaller than the minimum space required to
    *                                  store the tensor data
+   * @throws IllegalArgumentException if {@code size} is set to -1 but elements of the given
+   *                                  {@code type} are of variable length (e.g. strings)
+   * @throws IllegalArgumentException if {@code shape} is totally or partially
+   *                                  {@link Shape#hasUnknownDimension() unknown}
    * @throws IllegalStateException if tensor failed to be allocated
    */
-  static <T extends TType> T of(DataType<T> dtype, Shape shape, long size) {
-    RawTensor tensor = RawTensor.allocate(dtype, shape, size);
+  static <T extends TType> T of(Class<T> type, Shape shape, long size) {
+    RawTensor tensor = RawTensor.allocate(type, shape, size);
     try {
-      return tensor.asTypedTensor();
+      return (T)tensor.asTypedTensor();
     } catch (Exception e) {
       tensor.close();
       throw e;
@@ -103,7 +103,7 @@ static <T extends TType> T of(DataType<T> dtype, Shape shape, long size) {
    *
    * <pre>{@code
    * FloatNdArray data = ...
-   * try (TFloat32 t = Tensor.of(TFloat32.DTYPE, Shape.of(2, 2), data::copyTo)) {
+   * try (TFloat32 t = Tensor.of(TFloat32.class, Shape.of(2, 2), data::copyTo)) {
    *   ...
    * }
    * }</pre>
@@ -111,39 +111,47 @@ static <T extends TType> T of(DataType<T> dtype, Shape shape, long size) {
    * <p>If {@code dataInitializer} fails and throws an exception, the allocated tensor will be
    * automatically released before rethrowing the same exception.
    *
-   * @param <T> the tensor element type
-   * @param dtype datatype of the tensor
+   * @param <T> the tensor type
+   * @param type the tensor type class
    * @param shape shape of the tensor
    * @param dataInitializer method receiving accessor to the allocated tensor data for initialization
    * @return an allocated and initialized tensor
+   * @throws IllegalArgumentException if elements of the given {@code type} are of variable length
+   *                                  (e.g. strings)
+   * @throws IllegalArgumentException if {@code shape} is totally or partially
+   *                                  {@link Shape#hasUnknownDimension() unknown}
    * @throws IllegalStateException if tensor failed to be allocated
    */
-  static <T extends TType> T of(DataType<T> dtype, Shape shape, Consumer<T> dataInitializer) {
-    return of(dtype, shape, shape.size() * dtype.byteSize(), dataInitializer);
+  static <T extends TType> T of(Class<T> type, Shape shape, Consumer<T> dataInitializer) {
+    return of(type, shape, -1, dataInitializer);
   }
 
   /**
    * Allocates a tensor of a given datatype, shape and size.
    *
-   * <p>This method is identical to {@link #of(DataType, Shape, Consumer)}, except that the final
-   * size for the tensor is explicitly set instead of being computed from the datatype and shape.
+   * <p>This method is identical to {@link #of(Class, Shape, Consumer)}, except that the final
+   * size for the tensor can be explicitly set instead of being computed from the datatype and shape.
    *
    * <p>This could be useful for tensor types that stores data but also metadata in the tensor memory,
    * such as the lookup table in a tensor of strings.
    *
-   * @param <T> the tensor element type
-   * @param dtype datatype of the tensor
+   * @param <T> the tensor type
+   * @param type the tensor type class
    * @param shape shape of the tensor
-   * @param size size, in bytes, of the tensor
+   * @param size size in bytes of the tensor or -1 to compute the size from the shape
    * @param dataInitializer method receiving accessor to the allocated tensor data for initialization
    * @return an allocated and initialized tensor
-   * @see #of(DataType, Shape, long, Consumer)
+   * @see #of(Class, Shape, long, Consumer)
    * @throws IllegalArgumentException if {@code size} is smaller than the minimum space required to
    *                                  store the tensor data
+   * @throws IllegalArgumentException if {@code size} is set to -1 but elements of the given
+   *                                  {@code type} are of variable length (e.g. strings)
+   * @throws IllegalArgumentException if {@code shape} is totally or partially
+   *                                  {@link Shape#hasUnknownDimension() unknown}
    * @throws IllegalStateException if tensor failed to be allocated
    */
-  static <T extends TType> T of(DataType<T> dtype, Shape shape, long size, Consumer<T> dataInitializer) {
-    T tensor = of(dtype, shape, size);
+  static <T extends TType> T of(Class<T> type, Shape shape, long size, Consumer<T> dataInitializer) {
+    T tensor = of(type, shape, size);
     try {
       dataInitializer.accept(tensor);
       return tensor;
@@ -159,21 +167,24 @@ static <T extends TType> T of(DataType<T> dtype, Shape shape, long size, Consume
    * <p>Data must have been encoded into {@code data} as per the specification of the TensorFlow <a
    * href="https://www.tensorflow.org/code/tensorflow/c/c_api.h">C API</a>.
    *
-   * @param <T> the tensor element type
-   * @param dtype the tensor element data type
+   * @param <T> the tensor type
+   * @param type the tensor type class
    * @param shape the tensor shape.
    * @param rawData a buffer containing the tensor raw data.
-   * @throws IllegalArgumentException if {@code rawData} is not large enough to contain the tensor data
+   * @throws IllegalArgumentException if {@code rawData} is not large enough to contain the tensor
+   *                                  data
+   * @throws IllegalArgumentException if {@code shape} is totally or partially
+   *                                  {@link Shape#hasUnknownDimension() unknown}
    * @throws IllegalStateException if tensor failed to be allocated with the given parameters
    */
-  static <T extends TType> T of(DataType<T> dtype, Shape shape, ByteDataBuffer rawData) {
-    return of(dtype, shape, rawData.size(), t -> rawData.copyTo(t.asRawTensor().data(), rawData.size()));
+  static <T extends TType> T of(Class<T> type, Shape shape, ByteDataBuffer rawData) {
+    return of(type, shape, rawData.size(), t -> rawData.copyTo(t.asRawTensor().data(), rawData.size()));
   }
 
   /**
    * Returns the {@link DataType} of elements stored in the tensor.
    */
-  DataType<?> dataType();
+  DataType dataType();
 
   /**
    * Returns the size, in bytes, of the tensor data.
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/buffer/ByteSequenceProvider.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/buffer/ByteSequenceProvider.java
index 0d3d60772be..1a63d551336 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/buffer/ByteSequenceProvider.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/buffer/ByteSequenceProvider.java
@@ -19,7 +19,6 @@
 import java.util.Iterator;
 import java.util.function.Function;
 import org.tensorflow.ndarray.NdArray;
-import org.tensorflow.ndarray.NdArraySequence;
 
 /**
  * Produces sequence of bytes to be stored in a {@link ByteSequenceTensorBuffer}.
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TBfloat16Mapper.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TBfloat16Mapper.java
index 7b3a400ba16..27688e55779 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TBfloat16Mapper.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TBfloat16Mapper.java
@@ -16,9 +16,8 @@
  */
 package org.tensorflow.internal.types;
 
-import org.tensorflow.TensorMapper;
-import org.tensorflow.DataType;
 import org.tensorflow.RawTensor;
+import org.tensorflow.TensorMapper;
 import org.tensorflow.internal.buffer.TensorBuffers;
 import org.tensorflow.ndarray.buffer.FloatDataBuffer;
 import org.tensorflow.ndarray.buffer.layout.DataLayouts;
@@ -40,8 +39,8 @@ protected TBfloat16 mapDense(RawTensor tensor) {
   private static final class DenseTBfloat16 extends FloatDenseNdArray implements TBfloat16 {
 
     @Override
-    public DataType<TBfloat16> dataType() {
-      return TBfloat16.DTYPE;
+    public Class<TBfloat16> type() {
+      return TBfloat16.class;
     }
 
     @Override
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TBoolMapper.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TBoolMapper.java
index 2a9c44330c2..ff4c11a521b 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TBoolMapper.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TBoolMapper.java
@@ -16,7 +16,6 @@
  */
 package org.tensorflow.internal.types;
 
-import org.tensorflow.DataType;
 import org.tensorflow.RawTensor;
 import org.tensorflow.TensorMapper;
 import org.tensorflow.internal.buffer.TensorBuffers;
@@ -39,8 +38,8 @@ protected TBool mapDense(RawTensor tensor) {
   private static final class DenseTBool extends BooleanDenseNdArray implements TBool {
 
     @Override
-    public DataType<TBool> dataType() {
-      return TBool.DTYPE;
+    public Class<TBool> type() {
+      return TBool.class;
     }
 
     @Override
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TFloat16Mapper.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TFloat16Mapper.java
index 02ef883f9bf..fec84843f57 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TFloat16Mapper.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TFloat16Mapper.java
@@ -16,7 +16,6 @@
  */
 package org.tensorflow.internal.types;
 
-import org.tensorflow.DataType;
 import org.tensorflow.RawTensor;
 import org.tensorflow.TensorMapper;
 import org.tensorflow.internal.buffer.TensorBuffers;
@@ -40,8 +39,8 @@ protected TFloat16 mapDense(RawTensor tensor) {
   private static final class DenseTFloat16 extends FloatDenseNdArray implements TFloat16 {
 
     @Override
-    public DataType<?> dataType() {
-      return TFloat16.DTYPE;
+    public Class<TFloat16> type() {
+      return TFloat16.class;
     }
 
     @Override
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TFloat32Mapper.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TFloat32Mapper.java
index 1f446e820a7..62fc0d226ac 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TFloat32Mapper.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TFloat32Mapper.java
@@ -16,7 +16,6 @@
  */
 package org.tensorflow.internal.types;
 
-import org.tensorflow.DataType;
 import org.tensorflow.RawTensor;
 import org.tensorflow.TensorMapper;
 import org.tensorflow.internal.buffer.TensorBuffers;
@@ -39,8 +38,8 @@ protected TFloat32 mapDense(RawTensor tensor) {
   private static final class DenseTFloat32 extends FloatDenseNdArray implements TFloat32 {
 
     @Override
-    public DataType<?> dataType() {
-      return TFloat32.DTYPE;
+    public Class<TFloat32> type() {
+      return TFloat32.class;
     }
 
     @Override
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TFloat64Mapper.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TFloat64Mapper.java
index 9735604ecb2..375a7429950 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TFloat64Mapper.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TFloat64Mapper.java
@@ -16,7 +16,6 @@
  */
 package org.tensorflow.internal.types;
 
-import org.tensorflow.DataType;
 import org.tensorflow.RawTensor;
 import org.tensorflow.TensorMapper;
 import org.tensorflow.internal.buffer.TensorBuffers;
@@ -39,8 +38,8 @@ protected TFloat64 mapDense(RawTensor tensor) {
   private static final class DenseTFloat64 extends DoubleDenseNdArray implements TFloat64 {
 
     @Override
-    public DataType<?> dataType() {
-      return TFloat64.DTYPE;
+    public Class<TFloat64> type() {
+      return TFloat64.class;
     }
 
     @Override
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TInt32Mapper.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TInt32Mapper.java
index e0cf98c4ad8..fa0852a8b09 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TInt32Mapper.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TInt32Mapper.java
@@ -16,7 +16,6 @@
  */
 package org.tensorflow.internal.types;
 
-import org.tensorflow.DataType;
 import org.tensorflow.RawTensor;
 import org.tensorflow.TensorMapper;
 import org.tensorflow.internal.buffer.TensorBuffers;
@@ -39,8 +38,8 @@ protected TInt32 mapDense(RawTensor tensor) {
   private static final class DenseTInt32 extends IntDenseNdArray implements TInt32 {
 
     @Override
-    public DataType<?> dataType() {
-      return TInt32.DTYPE;
+    public Class<TInt32> type() {
+      return TInt32.class;
     }
 
     @Override
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TInt64Mapper.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TInt64Mapper.java
index d8a629e16ef..c5f2325e25a 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TInt64Mapper.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TInt64Mapper.java
@@ -16,7 +16,6 @@
  */
 package org.tensorflow.internal.types;
 
-import org.tensorflow.DataType;
 import org.tensorflow.RawTensor;
 import org.tensorflow.TensorMapper;
 import org.tensorflow.internal.buffer.TensorBuffers;
@@ -39,8 +38,8 @@ protected TInt64 mapDense(RawTensor tensor) {
   private static final class DenseTInt64 extends LongDenseNdArray implements TInt64 {
 
     @Override
-    public DataType<?> dataType() {
-      return TInt64.DTYPE;
+    public Class<TInt64> type() {
+      return TInt64.class;
     }
 
     @Override
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TStringMapper.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TStringMapper.java
index 51f224c8734..de7c6016e0e 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TStringMapper.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TStringMapper.java
@@ -18,11 +18,10 @@
 
 import java.nio.charset.Charset;
 import java.nio.charset.StandardCharsets;
-import org.tensorflow.DataType;
 import org.tensorflow.RawTensor;
 import org.tensorflow.TensorMapper;
-import org.tensorflow.internal.buffer.ByteSequenceTensorBuffer;
 import org.tensorflow.internal.buffer.ByteSequenceProvider;
+import org.tensorflow.internal.buffer.ByteSequenceTensorBuffer;
 import org.tensorflow.internal.buffer.TensorBuffers;
 import org.tensorflow.ndarray.NdArray;
 import org.tensorflow.ndarray.NdArrays;
@@ -79,8 +78,8 @@ public NdArray<byte[]> asBytes() {
     }
 
     @Override
-    public DataType<?> dataType() {
-      return TString.DTYPE;
+    public Class<TString> type() {
+      return TString.class;
     }
 
     @Override
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TUint8Mapper.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TUint8Mapper.java
index 5ef0fcad692..427debd1ac8 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TUint8Mapper.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/TUint8Mapper.java
@@ -16,7 +16,6 @@
  */
 package org.tensorflow.internal.types;
 
-import org.tensorflow.DataType;
 import org.tensorflow.RawTensor;
 import org.tensorflow.TensorMapper;
 import org.tensorflow.internal.buffer.TensorBuffers;
@@ -39,8 +38,8 @@ protected TUint8 mapDense(RawTensor tensor) {
   private static final class DenseTUint8 extends ByteDenseNdArray implements TUint8 {
 
     @Override
-    public DataType<?> dataType() {
-      return TUint8.DTYPE;
+    public Class<TUint8> type() {
+      return TUint8.class;
     }
 
     @Override
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/registry/TensorTypeInfo.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/registry/TensorTypeInfo.java
new file mode 100644
index 00000000000..a4a89a71649
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/registry/TensorTypeInfo.java
@@ -0,0 +1,76 @@
+/*
+ *  Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+ *
+ *  Licensed under the Apache License, Version 2.0 (the "License");
+ *  you may not use this file except in compliance with the License.
+ *  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ *  Unless required by applicable law or agreed to in writing, software
+ *  distributed under the License is distributed on an "AS IS" BASIS,
+ *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ *  See the License for the specific language governing permissions and
+ *  limitations under the License.
+ *  =======================================================================
+ */
+package org.tensorflow.internal.types.registry;
+
+import org.tensorflow.TensorMapper;
+import org.tensorflow.proto.framework.DataType;
+import org.tensorflow.types.family.TType;
+
+/**
+ * Registered information about a tensor type.
+ *
+ * @param <T> the tensor type
+ */
+public final class TensorTypeInfo<T extends TType> {
+
+  /**
+   * Returns the class of this tensor type
+   */
+  public Class<T> type() {
+    return type;
+  }
+
+  /**
+   * Returns the corresponding data type for this tensor type
+   */
+  public DataType dataType() {
+    return dataType;
+  }
+
+  /**
+   * Returns the number of bytes required to store one element of the corresponding data type, -1 if variable.
+   */
+  public int byteSize() {
+    return byteSize;
+  }
+
+  /**
+   * Returns true if elements of the corresponding data type are of variable length (undefined number of bytes)
+   */
+  public boolean isVariableLength() {
+    return byteSize < 0;
+  }
+
+  /**
+   * Returns an object used to map {@link org.tensorflow.RawTensor raw tensors} to a tensor of this type
+   */
+  public TensorMapper<T> mapper() {
+    return mapper;
+  }
+
+  TensorTypeInfo(Class<T> type, DataType dataType, int byteSize, TensorMapper<T> mapper) {
+    this.type = type;
+    this.dataType = dataType;
+    this.byteSize = byteSize;
+    this.mapper = mapper;
+  }
+
+  private final Class<T> type;
+  private final DataType dataType;
+  private final int byteSize;
+  private final TensorMapper<T> mapper;
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/registry/TensorTypeRegistry.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/registry/TensorTypeRegistry.java
new file mode 100644
index 00000000000..a30138e0386
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/internal/types/registry/TensorTypeRegistry.java
@@ -0,0 +1,104 @@
+/*
+ *  Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+ *
+ *  Licensed under the Apache License, Version 2.0 (the "License");
+ *  you may not use this file except in compliance with the License.
+ *  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ *  Unless required by applicable law or agreed to in writing, software
+ *  distributed under the License is distributed on an "AS IS" BASIS,
+ *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ *  See the License for the specific language governing permissions and
+ *  limitations under the License.
+ *  =======================================================================
+ */
+package org.tensorflow.internal.types.registry;
+
+import java.util.HashMap;
+import java.util.Map;
+import org.tensorflow.TensorMapper;
+import org.tensorflow.proto.framework.DataType;
+import org.tensorflow.types.TBfloat16;
+import org.tensorflow.types.TBool;
+import org.tensorflow.types.TFloat16;
+import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.TFloat64;
+import org.tensorflow.types.TInt32;
+import org.tensorflow.types.TInt64;
+import org.tensorflow.types.TString;
+import org.tensorflow.types.TUint8;
+import org.tensorflow.types.annotation.TensorType;
+import org.tensorflow.types.family.TType;
+
+/**
+ * Repository of all registered tensor types.
+ */
+public final class TensorTypeRegistry {
+
+  /**
+   * Find registered information about a tensor type from its equivalent data type
+   *
+   * @param dataType data type
+   * @return type registered information
+   * @throws IllegalArgumentException if no tensor type for this data type has been registered
+   */
+  public static <T extends TType> TensorTypeInfo<T> find(DataType dataType) {
+    TensorTypeInfo<?> typeInfo = TYPES_BY_CODE.get(dataType.getNumber());
+    if (typeInfo == null) {
+      throw new IllegalArgumentException("No tensor type has been registered for data type " + dataType);
+    }
+    return (TensorTypeInfo<T>)typeInfo;
+  }
+
+  /**
+   * Find registered information about a tensor type from its class
+   *
+   * @param type class implementing {@link TType}
+   * @return type registered information
+   * @throws IllegalArgumentException if the provided class has not been registered as a tensor type
+   */
+  public static <T extends TType> TensorTypeInfo<T> find(Class<T> type) {
+    TensorTypeInfo<?> typeInfo = TYPES_BY_CLASS.get(type);
+    if (typeInfo == null) {
+      throw new IllegalArgumentException("Class \"" + type.getName() + "\" is not registered as a tensor type");
+    }
+    return (TensorTypeInfo<T>)typeInfo;
+  }
+
+  private static final Map<Integer, TensorTypeInfo<?>> TYPES_BY_CODE = new HashMap<>();
+  private static final Map<Class<? extends TType>, TensorTypeInfo<?>> TYPES_BY_CLASS = new HashMap<>();
+
+  private static <T extends TType> void register(Class<T> type) {
+    TensorType typeAnnot = type.getDeclaredAnnotation(TensorType.class);
+    if (typeAnnot == null) {
+      throw new IllegalArgumentException("Class \"" + type.getName() + "\" must be annotated "
+          + "with @TensorType to be registered as a tensor type");
+    }
+    TensorMapper<T> mapper;
+    try {
+      mapper = (TensorMapper<T>)typeAnnot.mapperClass().newInstance();
+    } catch (ReflectiveOperationException e) {
+      throw new IllegalArgumentException("Class \"" + type.getName() + "\" must have a public "
+          + "parameter-less constructor to be used as a tensor mapper");
+    }
+    TensorTypeInfo<T> typeInfo = new TensorTypeInfo<>(type, typeAnnot.dataType(), typeAnnot.byteSize(), mapper);
+    TYPES_BY_CLASS.put(type, typeInfo);
+    TYPES_BY_CODE.put(typeInfo.dataType().getNumber(), typeInfo);
+    TYPES_BY_CODE.put(typeInfo.dataType().getNumber() + 100, typeInfo);
+  }
+
+  static {
+    // TODO (karllessard) scan and registered automatically all annotated tensors types
+    register(TBool.class);
+    register(TFloat64.class);
+    register(TFloat32.class);
+    register(TFloat16.class);
+    register(TInt32.class);
+    register(TInt64.class);
+    register(TString.class);
+    register(TUint8.class);
+    register(TBfloat16.class);
+  }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/Operands.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/Operands.java
index ac48da80326..5706ff1f283 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/Operands.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/Operands.java
@@ -16,10 +16,14 @@
 package org.tensorflow.op;
 
 import java.util.ArrayList;
+import java.util.Collection;
 import java.util.List;
 import org.tensorflow.Operand;
 import org.tensorflow.OperationBuilder;
 import org.tensorflow.Output;
+import org.tensorflow.internal.types.registry.TensorTypeRegistry;
+import org.tensorflow.proto.framework.DataType;
+import org.tensorflow.types.family.TType;
 
 /** Utilities for manipulating operand related types and lists. */
 public final class Operands {
@@ -41,6 +45,31 @@ public static Output<?>[] asOutputs(Iterable<? extends Operand<?>> inputs) {
     return outputList.toArray(new Output<?>[outputList.size()]);
   }
 
+  /**
+   * Converts a tensor type class to a {@link DataType} attribute.
+   *
+   * @param type tensor type class
+   * @return data type
+   */
+  public static <T extends TType> DataType toDataType(Class<? extends T> type) {
+    return TensorTypeRegistry.find(type).dataType();
+  }
+
+  /**
+   * Converts a list of tensor type classes to an array of {@link DataType} attributes.
+   *
+   * @param types tensor type classes
+   * @return an array of data types
+   */
+  public static <T extends TType> DataType[] toDataTypes(Collection<Class<? extends T>> types) {
+    DataType[] dataTypes = new DataType[types.size()];
+    int i = 0;
+    for (Class<? extends TType> type : types) {
+      dataTypes[i++] = toDataType(type);
+    }
+    return dataTypes;
+  }
+
   // Disabled constructor
   private Operands() {}
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Constant.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Constant.java
index 3be83d8173e..1b6aee0284b 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Constant.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Constant.java
@@ -16,7 +16,6 @@
 package org.tensorflow.op.core;
 
 import java.nio.charset.Charset;
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.Output;
@@ -1013,8 +1012,9 @@ public static Constant<TUint8> tensorOf(Scope scope, Shape shape, ByteDataBuffer
   /**
    * Create a constant with data from the given buffer.
    *
+   * @param <T> the tensor type
    * @param scope is a scope used to add the underlying operation.
-   * @param type the tensor datatype.
+   * @param type the tensor type class
    * @param shape the tensor shape.
    * @param data a buffer containing the tensor data.
    * @return a constant of type `type`
@@ -1022,7 +1022,7 @@ public static Constant<TUint8> tensorOf(Scope scope, Shape shape, ByteDataBuffer
    *     buffer
    */
   @Endpoint
-  public static <T extends TType> Constant<T> tensorOf(Scope scope, DataType<T> type, Shape shape,
+  public static <T extends TType> Constant<T> tensorOf(Scope scope, Class<T> type, Shape shape,
       ByteDataBuffer data) {
     try (T value = Tensor.of(type, shape, data)) {
       return create(scope, value);
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Gradients.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Gradients.java
index 2827276c32c..82edab51d40 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Gradients.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Gradients.java
@@ -22,7 +22,6 @@
 import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Output;
-import org.tensorflow.op.Op;
 import org.tensorflow.op.Operands;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Helpers.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Helpers.java
index f9ce837fe60..59682777966 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Helpers.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Helpers.java
@@ -16,7 +16,6 @@
 package org.tensorflow.op.core;
 
 import org.tensorflow.Operand;
-import org.tensorflow.Output;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
@@ -46,8 +45,7 @@ private Helpers() {}
      */
     @Endpoint(name = "variable")
     public static <T extends TType> Variable<T> createVariableWithInit(Scope scope, Operand<T> init, Variable.Options... options) {
-        Output<T> initOutput = init.asOutput();
-        Variable<T> newVar = Variable.create(scope,initOutput.shape(), initOutput.dataType(), options);
+        Variable<T> newVar = Variable.create(scope, init.shape(), init.type(), options);
         Assign<T> assignOp = Assign.create(scope, newVar, init);
         Init.add(scope, assignOp);
         return newVar;
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Init.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Init.java
index e0f64b6b19a..b7b65a973c9 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Init.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Init.java
@@ -35,7 +35,7 @@ public final class Init extends RawOp {
    *   try (Session s = new Session(g)) {
    *     s.run(tf.init());  // initialize all variables
    *
-   *     try (Tensor<TInt32> t = s.runner().fetch(z).run().get(0).expect(TInt32.DTYPE)) {
+   *     try (TInt32 t = (TInt32)s.runner().fetch(z).run().get(0)) {
    *       assertEquals(30, t.data().getInt());
    *     }
    *   }
@@ -62,7 +62,7 @@ public final class Init extends RawOp {
    * try (SavedModelBundle model = SavedModelBundle.load("/path/to/model", "train")) {
    *   model.session().run(Init.DEFAULT_NAME);
    *
-   *   try (Tensor<TInt32> t = s.runner().fetch("z").run().get(0).expect(TInt32.DTYPE)) {
+   *   try (TInt32 t = (TInt32)s.runner().fetch("z").run().get(0)) {
    *     assertEquals(30, t.data().getInt());
    *   }
    * }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Ones.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Ones.java
index 3af0846b441..a57c05f1940 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Ones.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Ones.java
@@ -14,7 +14,6 @@
 ==============================================================================*/
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.Output;
@@ -31,7 +30,7 @@
  * An operator creating a constant initialized with ones of the shape given by `dims`.
  * 
  * <p>For example, the following expression
- * <pre>{@code tf.ones(tf.constant(shape), TFloat32.DTYPE)}</pre>
+ * <pre>{@code tf.ones(tf.constant(shape), TFloat32.class)}</pre>
  * is the equivalent of
  * <pre>{@code tf.fill(tf.constant(shape), tf.constant(1.0f))}</pre>
  *
@@ -45,14 +44,14 @@ public final class Ones<T extends TType> implements Op, Operand<T> {
    *
    * @param scope is a scope used to add the underlying operation
    * @param dims a 1-D operand that represents the shape of the output tensor
-   * @param type the output tensor datatype. Can not be TString.
+   * @param type the output tensor type class. Can not be TString.
    * @return a constant tensor initialized with ones
    * @throws IllegalArgumentException if the tensor type or shape cannot be initialized with ones.
    */
   @Endpoint
-  public static <T extends TType, U extends TNumber> Ones<T> create(Scope scope, Operand<U> dims, DataType<T> type) {
+  public static <T extends TType, U extends TNumber> Ones<T> create(Scope scope, Operand<U> dims, Class<T> type) {
     Scope onesScope = scope.withSubScope("Ones");
-    if (type == TString.DTYPE) {
+    if (type == TString.class) {
       throw new IllegalArgumentException("Can't create Ones of String DataType");
     }
     Operand<T> one = Cast.create(onesScope.withName("One"), Constant.scalarOf(onesScope, 1), type);
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Shapes.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Shapes.java
index 613cb729341..2bf2eecc4cb 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Shapes.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Shapes.java
@@ -15,16 +15,12 @@
 package org.tensorflow.op.core;
 
 import java.util.Arrays;
-
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.Scope;
 import org.tensorflow.op.annotation.Endpoint;
 import org.tensorflow.op.annotation.Operator;
-
-import org.tensorflow.op.math.FloorMod;
-
 import org.tensorflow.op.dtypes.Cast;
+import org.tensorflow.op.math.FloorMod;
 import org.tensorflow.op.math.NotEqual;
 import org.tensorflow.op.math.Sub;
 import org.tensorflow.types.TBool;
@@ -51,8 +47,8 @@
  * Operand<TInt32> numPred = tf.shape.size(predShape, tf.constant(0));
  * Operand<TFloat32> predFlat = tf.shape.flatten(yPred);
  *
- * Shape<TInt64> predShape64 = tf.shape(yPred, TInt64.DTYPE);
- * Operand<TInt64> predSqueezed = tf.shape.squeeze(predShape64, TInt64.DTYPE);
+ * Shape<TInt64> predShape64 = tf.shape(yPred, TInt64.class);
+ * Operand<TInt64> predSqueezed = tf.shape.squeeze(predShape64, TInt64.class);
  * }</pre>
  */
 @Operator(group = "shape")
@@ -68,7 +64,7 @@ public abstract class Shapes {
    */
   @Endpoint(name = "flatten")
   public static <T extends TType> Operand<T> flatten(Scope scope, Operand<T> operand) {
-    return flatten(scope, operand, TInt32.DTYPE);
+    return flatten(scope, operand, TInt32.class);
   }
 
   /**
@@ -78,13 +74,13 @@ public static <T extends TType> Operand<T> flatten(Scope scope, Operand<T> opera
    * @param <U> the shape datatype
    * @param scope current scope
    * @param operand the operand to flatten
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the reshaped operand
    */
   @Endpoint(name = "flatten")
   public static <T extends TType, U extends TNumber> Operand<T> flatten(
-      Scope scope, Operand<T> operand, DataType<U> dType) {
-    Operand<U> flatShape = flatten(scope, Shape.create(scope, operand, dType), dType);
+      Scope scope, Operand<T> operand, Class<U> type) {
+    Operand<U> flatShape = flatten(scope, Shape.create(scope, operand, type), type);
     return Reshape.create(scope, operand, flatShape);
   }
 
@@ -97,7 +93,7 @@ public static <T extends TType, U extends TNumber> Operand<T> flatten(
    */
   @Endpoint(name = "flatten")
   public static Operand<TInt32> flatten(Scope scope, Shape<TInt32> shape) {
-    return flatten(scope, shape, TInt32.DTYPE);
+    return flatten(scope, shape, TInt32.class);
   }
 
   /**
@@ -106,16 +102,16 @@ public static Operand<TInt32> flatten(Scope scope, Shape<TInt32> shape) {
    * @param <U> the shape datatype
    * @param scope current scope
    * @param shape the TensorFlow shape
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the flattened shape
    */
   @Endpoint(name = "flatten")
   public static <U extends TNumber> Operand<U> flatten(
-      Scope scope, Shape<U> shape, DataType<U> dType) {
+      Scope scope, Shape<U> shape, Class<U> type) {
     return ExpandDims.create(
         scope,
-        size(scope, shape, dType),
-        Cast.create(scope, Constant.scalarOf(scope, -1), TInt32.DTYPE));
+        size(scope, shape, type),
+        Cast.create(scope, Constant.scalarOf(scope, -1), TInt32.class));
   }
 
   /**
@@ -127,7 +123,7 @@ public static <U extends TNumber> Operand<U> flatten(
    */
   @Endpoint(name = "size")
   public static Operand<TInt32> size(Scope scope, Shape<TInt32> shape) {
-    return size(scope, shape, TInt32.DTYPE);
+    return size(scope, shape, TInt32.class);
   }
 
   /**
@@ -136,20 +132,20 @@ public static Operand<TInt32> size(Scope scope, Shape<TInt32> shape) {
    * @param <U> the type of the shape
    * @param scope current scope
    * @param shape the TensorFlow shape
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the size
    */
   @Endpoint(name = "size")
   public static <U extends TNumber> Operand<U> size(
-      Scope scope, Shape<U> shape, DataType<U> dType) {
+      Scope scope, Shape<U> shape, Class<U> type) {
     Slice<U> dims =
         Slice.create(
             scope,
             shape,
-            Cast.create(scope, Constant.arrayOf(scope, 0), dType),
+            Cast.create(scope, Constant.arrayOf(scope, 0), type),
             ExpandDims.create(
                 scope,
-                Cast.create(scope, Constant.scalarOf(scope, -1), dType),
+                Cast.create(scope, Constant.scalarOf(scope, -1), type),
                 Constant.scalarOf(scope, -1)));
     return ReduceProd.create(scope, dims, Constant.scalarOf(scope, 0));
   }
@@ -164,7 +160,7 @@ public static <U extends TNumber> Operand<U> size(
    */
   @Endpoint(name = "size")
   public static Operand<TInt32> size(Scope scope, Shape<TInt32> shape, Operand<TInt32> dim) {
-    return size(scope, shape, dim, TInt32.DTYPE);
+    return size(scope, shape, dim, TInt32.class);
   }
 
   /**
@@ -174,20 +170,20 @@ public static Operand<TInt32> size(Scope scope, Shape<TInt32> shape, Operand<TIn
    * @param scope current scope
    * @param shape the TensorFlow shape
    * @param dim the dimension
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the size of the specified dimension
    */
   @Endpoint(name = "size")
   public static <U extends TNumber> Operand<U> size(
-      Scope scope, Shape<U> shape, Operand<U> dim, DataType<U> dType) {
+      Scope scope, Shape<U> shape, Operand<U> dim, Class<U> type) {
     return Slice.create(
         scope,
         shape,
-        ExpandDims.create(scope, dim, Cast.create(scope, Constant.scalarOf(scope, -1), dType)),
+        ExpandDims.create(scope, dim, Cast.create(scope, Constant.scalarOf(scope, -1), type)),
         ExpandDims.create(
             scope,
-            Cast.create(scope, Constant.scalarOf(scope, 1), dType),
-            Cast.create(scope, Constant.scalarOf(scope, -1), dType)));
+            Cast.create(scope, Constant.scalarOf(scope, 1), type),
+            Cast.create(scope, Constant.scalarOf(scope, -1), type)));
   }
 
   /**
@@ -201,7 +197,7 @@ public static <U extends TNumber> Operand<U> size(
   @Endpoint(name = "size")
   public static <T extends TType> Operand<TInt32> size(
       Scope scope, Operand<T> input, Operand<TInt32> dim) {
-    return size(scope, input, dim, TInt32.DTYPE);
+    return size(scope, input, dim, TInt32.class);
   }
 
   /**
@@ -211,13 +207,13 @@ public static <T extends TType> Operand<TInt32> size(
    * @param scope current scope
    * @param input the operand
    * @param dim the dimension
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the size of the specified dimension
    */
   @Endpoint(name = "size")
   public static <T extends TType, U extends TNumber> Operand<U> size(
-      Scope scope, Operand<T> input, Operand<U> dim, DataType<U> dType) {
-    return size(scope, Shape.create(scope, input, dType), dim, dType);
+      Scope scope, Operand<T> input, Operand<U> dim, Class<U> type) {
+    return size(scope, Shape.create(scope, input, type), dim, type);
   }
 
   /**
@@ -229,7 +225,7 @@ public static <T extends TType, U extends TNumber> Operand<U> size(
    */
   @Endpoint(name = "numDimensions")
   public static Operand<TInt32> numDimensions(Scope scope, Shape<TInt32> shape) {
-    return Size.create(scope, shape, TInt32.DTYPE);
+    return Size.create(scope, shape, TInt32.class);
   }
 
   /**
@@ -238,13 +234,13 @@ public static Operand<TInt32> numDimensions(Scope scope, Shape<TInt32> shape) {
    * @param <U> the shape datatype
    * @param scope the curren scope
    * @param shape the shape
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the number of dimensions
    */
   @Endpoint(name = "numDimensions")
   public static <U extends TNumber> Operand<U> numDimensions(
-      Scope scope, Shape<U> shape, DataType<U> dType) {
-    return Size.create(scope, shape, dType);
+      Scope scope, Shape<U> shape, Class<U> type) {
+    return Size.create(scope, shape, type);
   }
 
   /**
@@ -259,7 +255,7 @@ public static <U extends TNumber> Operand<U> numDimensions(
   @Endpoint(name = "reduceDims")
   public static <T extends TType> Operand<T> reduceDims(
       Scope scope, Operand<T> operand, Operand<TInt32> axis) {
-    return reduceDims(scope, operand, axis, TInt32.DTYPE);
+    return reduceDims(scope, operand, axis, TInt32.class);
   }
 
   /**
@@ -270,14 +266,14 @@ public static <T extends TType> Operand<T> reduceDims(
    * @param scope current scope
    * @param operand the operand
    * @param axis the axis
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the reshaped operand
    */
   @Endpoint(name = "reduceDims")
   public static <T extends TType, U extends TNumber> Operand<T> reduceDims(
-      Scope scope, Operand<T> operand, Operand<U> axis, DataType<U> dType) {
-    Shape<U> newShape = Shape.create(scope, operand, dType);
-    return Reshape.create(scope, operand, reduceDims(scope, newShape, axis, dType));
+      Scope scope, Operand<T> operand, Operand<U> axis, Class<U> type) {
+    Shape<U> newShape = Shape.create(scope, operand, type);
+    return Reshape.create(scope, operand, reduceDims(scope, newShape, axis, type));
   }
 
   /**
@@ -290,7 +286,7 @@ public static <T extends TType, U extends TNumber> Operand<T> reduceDims(
    */
   @Endpoint(name = "reduceDims")
   public static Operand<TInt32> reduceDims(Scope scope, Shape<TInt32> shape, Operand<TInt32> axis) {
-    return reduceDims(scope, shape, axis, TInt32.DTYPE);
+    return reduceDims(scope, shape, axis, TInt32.class);
   }
 
   /**
@@ -300,13 +296,13 @@ public static Operand<TInt32> reduceDims(Scope scope, Shape<TInt32> shape, Opera
    * @param scope current scope
    * @param shape the TensorFlow shape
    * @param axis the axis
-   * @param dType the shape datatype
+   * @param type the shape datatype
    * @return the reduced shape
    */
   @Endpoint(name = "reduceDims")
   public static <U extends TNumber> Operand<U> reduceDims(
-      Scope scope, Shape<U> shape, Operand<U> axis, DataType<U> dType) {
-    Size<U> rank = Size.create(scope, shape, dType);
+      Scope scope, Shape<U> shape, Operand<U> axis, Class<U> type) {
+    Size<U> rank = Size.create(scope, shape, type);
     axis = FloorMod.create(scope, axis, rank);
     Sub<U> remainder = Sub.create(scope, rank, axis);
 
@@ -314,7 +310,7 @@ public static <U extends TNumber> Operand<U> reduceDims(
         Slice.create(
             scope,
             shape,
-            Cast.create(scope, Constant.arrayOf(scope, 0), dType),
+            Cast.create(scope, Constant.arrayOf(scope, 0), type),
             ExpandDims.create(scope, axis, Constant.scalarOf(scope, -1)));
 
     Operand<U> dims2 =
@@ -324,7 +320,7 @@ public static <U extends TNumber> Operand<U> reduceDims(
             ExpandDims.create(scope, axis, Constant.scalarOf(scope, -1)),
             ExpandDims.create(
                 scope,
-                Cast.create(scope, Constant.scalarOf(scope, -1), dType),
+                Cast.create(scope, Constant.scalarOf(scope, -1), type),
                 Constant.scalarOf(scope, -1)));
 
     Operand<U> prod =
@@ -343,7 +339,7 @@ public static <U extends TNumber> Operand<U> reduceDims(
    */
   @Endpoint(name = "squeeze")
   public static Operand<TInt32> squeeze(Scope scope, Shape<TInt32> shape) {
-    return squeeze(scope, shape, TInt32.DTYPE);
+    return squeeze(scope, shape, TInt32.class);
   }
 
   /**
@@ -352,14 +348,14 @@ public static Operand<TInt32> squeeze(Scope scope, Shape<TInt32> shape) {
    * @param <U> the shape datatype.
    * @param scope current scope
    * @param shape the TensorFlow shape
-   * @param dType the shape datatype.
+   * @param type the shape datatype.
    * @return the squeezed shape
    */
   @Endpoint(name = "squeeze")
   public static <U extends TNumber> Operand<U> squeeze(
-      Scope scope, Shape<U> shape, DataType<U> dType) {
+      Scope scope, Shape<U> shape, Class<U> type) {
     Operand<TBool> mask =
-        NotEqual.create(scope, shape, Cast.create(scope, OnesLike.create(scope, shape), dType));
+        NotEqual.create(scope, shape, Cast.create(scope, OnesLike.create(scope, shape), type));
 
     return Gather.create(scope, shape, Where.create(scope, mask), Constant.scalarOf(scope, 0));
   }
@@ -373,7 +369,7 @@ public static <U extends TNumber> Operand<U> squeeze(
    */
   @Endpoint(name = "head")
   public static Operand<TInt32> head(Scope scope, Shape<TInt32> shape) {
-    return head(scope, shape, TInt32.DTYPE);
+    return head(scope, shape, TInt32.class);
   }
 
   /**
@@ -381,14 +377,14 @@ public static Operand<TInt32> head(Scope scope, Shape<TInt32> shape) {
    *
    * @param scope current scope
    * @param shape the TensorFlow shape
-   * @param dType the shape datatype.
+   * @param type the shape datatype.
    * @param <U> the shape datatype.
    * @return a 1-dimensional Operand containing the Shape's first dimension
    */
   @Endpoint(name = "head")
   public static <U extends TNumber> Operand<U> head(
-      Scope scope, Shape<U> shape, DataType<U> dType) {
-    return take(scope, shape, Cast.create(scope, Constant.scalarOf(scope, 1), dType), dType);
+      Scope scope, Shape<U> shape, Class<U> type) {
+    return take(scope, shape, Cast.create(scope, Constant.scalarOf(scope, 1), type), type);
   }
 
   /**
@@ -403,7 +399,7 @@ public static <U extends TNumber> Operand<U> head(
    */
   @Endpoint(name = "take")
   public static Operand<TInt32> take(Scope scope, Shape<TInt32> shape, Operand<TInt32> n) {
-    return take(scope, shape, n, TInt32.DTYPE);
+    return take(scope, shape, n, TInt32.class);
   }
 
   /**
@@ -413,18 +409,18 @@ public static Operand<TInt32> take(Scope scope, Shape<TInt32> shape, Operand<TIn
    * @param scope current scope
    * @param shape the TensorFlow shape
    * @param n the number of leading dimensions to get, must be <= than the shape's numDimensions()
-   * @param dType the shape datatype.
+   * @param type the shape datatype.
    * @param <U> the shape datatype.
    * @return a 1-dimensional operand with the dimensions matching * the first n dimensions of the
    *     shape
    */
   @Endpoint(name = "take")
   public static <U extends TNumber> Operand<U> take(
-      Scope scope, Shape<U> shape, Operand<U> n, DataType<U> dType) {
+      Scope scope, Shape<U> shape, Operand<U> n, Class<U> type) {
     return Slice.create(
         scope,
         shape,
-        Cast.create(scope, Constant.arrayOf(scope, 0), dType),
+        Cast.create(scope, Constant.arrayOf(scope, 0), type),
         ExpandDims.create(scope, n, Constant.scalarOf(scope, -1)));
   }
 
@@ -439,7 +435,7 @@ public static <U extends TNumber> Operand<U> take(
    */
   @Endpoint(name = "tail")
   public static Operand<TInt32> tail(Scope scope, Shape<TInt32> shape) {
-    return tail(scope, shape, TInt32.DTYPE);
+    return tail(scope, shape, TInt32.class);
   }
 
   /**
@@ -448,15 +444,15 @@ public static Operand<TInt32> tail(Scope scope, Shape<TInt32> shape) {
    *
    * @param scope current scope
    * @param shape the TensorFlow shape
-   * @param dType the shape datatype.
+   * @param type the shape datatype.
    * @param <U> the shape datatype.
    * @return a 1-dimensional Operand that contains the dimension matching the last dimension of the
    *     Shape
    */
   @Endpoint(name = "tail")
   public static <U extends TNumber> Operand<U> tail(
-      Scope scope, Shape<U> shape, DataType<U> dType) {
-    return takeLast(scope, shape, Cast.create(scope, Constant.scalarOf(scope, 1), dType), dType);
+      Scope scope, Shape<U> shape, Class<U> type) {
+    return takeLast(scope, shape, Cast.create(scope, Constant.scalarOf(scope, 1), type), type);
   }
 
   /**
@@ -472,7 +468,7 @@ public static <U extends TNumber> Operand<U> tail(
   @Endpoint(name = "takeLast")
   public static <U extends TNumber> Operand<TInt32> takeLast(
       Scope scope, Shape<TInt32> shape, Operand<TInt32> n) {
-    return takeLast(scope, shape, n, TInt32.DTYPE);
+    return takeLast(scope, shape, n, TInt32.class);
   }
 
   /**
@@ -482,16 +478,16 @@ public static <U extends TNumber> Operand<TInt32> takeLast(
    * @param scope current scope
    * @param shape the TensorFlow shape
    * @param n the number of leading dimensions to get, must be <= than the shape's numDimensions()
-   * @param dType the shape datatype.
+   * @param type the shape datatype.
    * @param <U> the shape datatype.
    * @return a 1-dimensional operand containing the dimensions matching the last n dimensions of the
    *     shape
    */
   @Endpoint(name = "takeLast")
   public static <U extends TNumber> Operand<U> takeLast(
-      Scope scope, Shape<U> shape, Operand<U> n, DataType<U> dType) {
+      Scope scope, Shape<U> shape, Operand<U> n, Class<U> type) {
 
-    Size<U> rank = Size.create(scope, shape, dType);
+    Size<U> rank = Size.create(scope, shape, type);
     Sub<U> start = Sub.create(scope, rank, n);
     return Slice.create(
         scope,
@@ -499,7 +495,7 @@ public static <U extends TNumber> Operand<U> takeLast(
         ExpandDims.create(scope, start, Constant.scalarOf(scope, -1)),
         ExpandDims.create(
             scope,
-            Cast.create(scope, Constant.scalarOf(scope, -1), dType),
+            Cast.create(scope, Constant.scalarOf(scope, -1), type),
             Constant.scalarOf(scope, -1)));
   }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Zeros.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Zeros.java
index 4aad417b117..a5b5bb137c2 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Zeros.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Zeros.java
@@ -14,7 +14,6 @@
 ==============================================================================*/
 package org.tensorflow.op.core;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Operation;
 import org.tensorflow.Output;
@@ -31,7 +30,7 @@
  * An operator creating a constant initialized with zeros of the shape given by `dims`.
  * 
  * <p>For example, the following expression
- * <pre>{@code tf.zeros(tf.constant(shape), TFloat32.DTYPE)</pre>
+ * <pre>{@code tf.zeros(tf.constant(shape), TFloat32.class)</pre>
  * is the equivalent of
  * <pre>{@code tf.fill(tf.constant(shape), tf.constant(0.0f))</pre>
  *
@@ -51,10 +50,10 @@ public final class Zeros<T extends TType> implements Op, Operand<T> {
    */
   @Endpoint
   @SuppressWarnings("unchecked")
-  public static <T extends TType, U extends TNumber> Zeros<T> create(Scope scope, Operand<U> dims, DataType<T> type) {
+  public static <T extends TType, U extends TNumber> Zeros<T> create(Scope scope, Operand<U> dims, Class<T> type) {
     Scope zerosScope = scope.withSubScope("Zeros");
     Operand<T> zero;
-    if (type == TString.DTYPE) {
+    if (type == TString.class) {
       zero = (Operand<T>)Constant.scalarOf(zerosScope.withName("Zero"), "");
     } else {
       zero = Cast.create(zerosScope.withName("Zero"), Constant.scalarOf(zerosScope, 0), type);
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java
index e823ed9f6bd..92c413f7e52 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SigmoidCrossEntropyWithLogits.java
@@ -72,7 +72,7 @@ public static <T extends TNumber> Operand<T> sigmoidCrossEntropyWithLogits(
     scope = scope.withSubScope("SigmoidCrossEntropyWithLogits");
 
     Operand<T> zeros =
-        Cast.create(scope, ZerosLike.create(scope, logits), logits.asOutput().dataType());
+        Cast.create(scope, ZerosLike.create(scope, logits), logits.asOutput().type());
     Operand<TBool> cond = GreaterEqual.create(scope, logits, zeros);
 
     Operand<T> reluLogits = Select.create(scope, cond, logits, zeros);
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
index 67cbe3fb98c..ddeacbea4d4 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java
@@ -1,6 +1,5 @@
 package org.tensorflow.op.nn;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Scope;
@@ -78,24 +77,22 @@ public static <T extends TNumber, U extends TNumber> Operand<T> softmaxCrossEntr
       axis += logits.shape().numDimensions();
     }
 
-
-    boolean convertToFloat32 =
-        logits.asOutput().dataType() == TFloat16.DTYPE
-            || logits.asOutput().dataType() == TBfloat16.DTYPE;
-    if (convertToFloat32) {
+    if (logits.asOutput().type() == TFloat16.class || logits.asOutput().type() == TBfloat16.class) {
       Operand<TFloat32> result =  softmaxCrossEntropyWithLogits(scope,
-              Cast.create(scope, labels, TFloat32.DTYPE),
-              Cast.create(scope, logits, TFloat32.DTYPE),
+              Cast.create(scope, labels, TFloat32.class),
+              Cast.create(scope, logits, TFloat32.class),
               axis);
-      return Cast.create(scope, result, logits.asOutput().dataType());
-    } else if(!logits.asOutput().dataType().equals(labels.asOutput().dataType())) {
+      return Cast.create(scope, result, logits.asOutput().type());
+    }
+
+    if (logits.asOutput().type() != labels.asOutput().type()) {
       return softmaxCrossEntropyWithLogits(scope,
-              Cast.create(scope, labels, logits.asOutput().dataType()),
+              Cast.create(scope, labels, logits.asOutput().type()),
               logits,
               axis);
     }
 
-    Operand<TInt64> inputRank = Cast.create(scope, Rank.create(scope, logits), TInt64.DTYPE);
+    Operand<TInt64> inputRank = Cast.create(scope, Rank.create(scope, logits), TInt64.class);
     Shape shape = logits.shape();
 
     // Move the dim to the end if dim is not the last dimension.
@@ -167,13 +164,13 @@ private static <T extends TNumber> Operand<T> flattenOuterDims(Scope scope, Oper
       }
     }
 
-    Operand<TInt64> rank = Cast.create(scope, Rank.create(scope, logits), TInt64.DTYPE);
+    Operand<TInt64> rank = Cast.create(scope, Rank.create(scope, logits), TInt64.class);
     Operand<TInt64> rankMinusOne = Sub.create(scope, rank, one);
 
     Operand<TInt64> lastDimSize =
         Slice.create(
             scope,
-            org.tensorflow.op.core.Shape.create(scope, logits, TInt64.DTYPE),
+            org.tensorflow.op.core.Shape.create(scope, logits, TInt64.class),
             rankMinusOne,
             one);
     Operand<TInt64> concat =
@@ -197,15 +194,15 @@ private static <T extends TNumber> Operand<T> flattenOuterDims(Scope scope, Oper
    */
   private static <T extends TNumber, U extends TNumber> Operand<T> moveDimToEnd(
       Scope scope, Operand<T> input, int dimIndex, Operand<U> rank) {
-    DataType<? extends TNumber> rankDType = rank.asOutput().dataType();
-    Operand one = Cast.create(scope, Constant.scalarOf(scope, 1), rankDType);
+    Class<U> rankType = rank.asOutput().type();
+    Operand<U> one = Cast.create(scope, Constant.scalarOf(scope, 1), rankType);
     List<Operand<U>> concatList =
         Arrays.asList(
             Range.create(
-                scope, Cast.create(scope, Constant.scalarOf(scope, dimIndex), rankDType), one, one),
+                scope, Cast.create(scope, Constant.scalarOf(scope, dimIndex), rankType), one, one),
             Range.create(
                 scope,
-                Cast.create(scope, Constant.scalarOf(scope, dimIndex + 1), rankDType),
+                Cast.create(scope, Constant.scalarOf(scope, dimIndex + 1), rankType),
                 one,
                 one));
     return Transpose.create(
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java
index 3598edbe223..54b32bb5c63 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java
@@ -74,11 +74,8 @@ public static <T extends TNumber, U extends TNumber> Operand sparseSoftmaxCrossE
     scope = scope.withSubScope("SparseSoftmaxCrossEntropyWithLogits");
     /** cannot use generics on preciseLogits as it may be recast later */
     Operand preciseLogits = logits;
-    boolean convertToFloat32 =
-        logits.asOutput().dataType() == TFloat16.DTYPE
-            || logits.asOutput().dataType() == TBfloat16.DTYPE;
-    if (convertToFloat32) {
-      preciseLogits = Cast.create(scope, logits, TFloat32.DTYPE);
+    if (logits.asOutput().type() == TFloat16.class || logits.asOutput().type() == TBfloat16.class) {
+      preciseLogits = Cast.create(scope, logits, TFloat32.class);
     }
     Shape labelsStaticShape = labels.shape();
     org.tensorflow.op.core.Shape<TInt32> labelsShape =
@@ -115,8 +112,8 @@ public static <T extends TNumber, U extends TNumber> Operand sparseSoftmaxCrossE
           org.tensorflow.op.nn.raw.SparseSoftmaxCrossEntropyWithLogits.create(
               scope, preciseLogits, labels);
       Operand loss = smax.loss();
-      if (logits.asOutput().dataType() == TFloat16.DTYPE) {
-        loss = Cast.create(scope, loss, TFloat16.DTYPE);
+      if (logits.asOutput().type() == TFloat16.class) {
+        loss = Cast.create(scope, loss, TFloat16.class);
       }
       return loss;
     }
@@ -153,8 +150,8 @@ public static <T extends TNumber, U extends TNumber> Operand sparseSoftmaxCrossE
             scope, preciseLogits, labels);
     Operand cost = smax.loss();
     cost = Reshape.create(scope, cost, labelsShape);
-    if (logits.asOutput().dataType() == TFloat16.DTYPE) {
-      cost = Cast.create(scope, cost, TFloat16.DTYPE);
+    if (logits.asOutput().type() == TFloat16.class) {
+      cost = Cast.create(scope, cost, TFloat16.class);
     }
     return cost;
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBfloat16.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBfloat16.java
index 94c6f8790b5..ef20b5ec2b6 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBfloat16.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBfloat16.java
@@ -18,7 +18,6 @@
 package org.tensorflow.types;
 
 import java.util.function.Consumer;
-import org.tensorflow.DataType;
 import org.tensorflow.Tensor;
 import org.tensorflow.exceptions.TensorFlowException;
 import org.tensorflow.internal.types.TBfloat16Mapper;
@@ -27,6 +26,8 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.ndarray.StdArrays;
 import org.tensorflow.ndarray.buffer.FloatDataBuffer;
+import org.tensorflow.proto.framework.DataType;
+import org.tensorflow.types.annotation.TensorType;
 import org.tensorflow.types.family.TFloating;
 
 /**
@@ -45,12 +46,8 @@
  * <p>Note that some CPUs support the bfloat16 format natively, which can result in faster
  * computation compared to {@link TFloat16} when GPUs are not used.
  */
+@TensorType(dataType = DataType.DT_BFLOAT16, byteSize = 2, mapperClass = TBfloat16Mapper.class)
 public interface TBfloat16 extends FloatNdArray, TFloating {
-  /** readable-name for the data type */
-  static final String NAME = "BFLOAT16";
-
-  /** Type metadata */
-  DataType<TBfloat16> DTYPE = DataType.create(NAME, 14, 2, new TBfloat16Mapper());
 
   /**
    * Allocates a new tensor for storing a single float value.
@@ -59,7 +56,7 @@ public interface TBfloat16 extends FloatNdArray, TFloating {
    * @return the new tensor
    */
   static TBfloat16 scalarOf(float value) {
-    return Tensor.of(DTYPE, Shape.scalar(), data -> data.setFloat(value));
+    return Tensor.of(TBfloat16.class, Shape.scalar(), data -> data.setFloat(value));
   }
 
   /**
@@ -72,7 +69,7 @@ static TBfloat16 vectorOf(float... values) {
     if (values == null) {
       throw new IllegalArgumentException();
     }
-    return Tensor.of(DTYPE, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
+    return Tensor.of(TBfloat16.class, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
   }
 
   /**
@@ -84,7 +81,7 @@ static TBfloat16 vectorOf(float... values) {
    * @return the new tensor
    */
   static TBfloat16 tensorOf(NdArray<Float> src) {
-    return Tensor.of(DTYPE, src.shape(), src::copyTo);
+    return Tensor.of(TBfloat16.class, src.shape(), src::copyTo);
   }
 
   /**
@@ -94,7 +91,7 @@ static TBfloat16 tensorOf(NdArray<Float> src) {
    * @return the new tensor
    */
   static TBfloat16 tensorOf(Shape shape) {
-    return Tensor.of(DTYPE, shape);
+    return Tensor.of(TBfloat16.class, shape);
   }
 
   /**
@@ -105,7 +102,7 @@ static TBfloat16 tensorOf(Shape shape) {
    * @return the new tensor
    */
   static TBfloat16 tensorOf(Shape shape, FloatDataBuffer data) {
-    return Tensor.of(DTYPE, shape, d -> d.write(data));
+    return Tensor.of(TBfloat16.class, shape, d -> d.write(data));
   }
 
   /**
@@ -117,7 +114,7 @@ static TBfloat16 tensorOf(Shape shape, FloatDataBuffer data) {
    * @throws TensorFlowException if the tensor cannot be allocated or initialized
    */
   static TBfloat16 tensorOf(Shape shape, Consumer<TBfloat16> dataInit) {
-    return Tensor.of(DTYPE, shape, dataInit);
+    return Tensor.of(TBfloat16.class, shape, dataInit);
   }
 }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java
index bab5e7910b4..0158c12b910 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java
@@ -18,12 +18,8 @@
 package org.tensorflow.types;
 
 import java.util.function.Consumer;
-import org.tensorflow.DataType;
-import org.tensorflow.RawTensor;
 import org.tensorflow.Tensor;
 import org.tensorflow.exceptions.TensorFlowException;
-import org.tensorflow.internal.buffer.TensorBuffers;
-import org.tensorflow.internal.c_api.TF_Tensor;
 import org.tensorflow.internal.types.TBoolMapper;
 import org.tensorflow.ndarray.BooleanNdArray;
 import org.tensorflow.ndarray.NdArray;
@@ -31,7 +27,8 @@
 import org.tensorflow.ndarray.StdArrays;
 import org.tensorflow.ndarray.buffer.BooleanDataBuffer;
 import org.tensorflow.ndarray.buffer.layout.DataLayouts;
-import org.tensorflow.ndarray.impl.dense.BooleanDenseNdArray;
+import org.tensorflow.proto.framework.DataType;
+import org.tensorflow.types.annotation.TensorType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -41,12 +38,8 @@
  * explicit mapping between Java boolean values and byte buffers using the {@link DataLayouts#BOOL
  * BOOL} layout, which may impact I/O performances.
  */
+@TensorType(dataType = DataType.DT_BOOL, byteSize = 1, mapperClass = TBoolMapper.class)
 public interface TBool extends BooleanNdArray, TType {
-  /** readable-name for the data type */
-  static final String NAME = "BOOL";
-
-  /** Type metadata */
-  DataType<TBool> DTYPE = DataType.create(NAME, 10, 1, new TBoolMapper());
 
   /**
    * Allocates a new tensor for storing a single boolean value.
@@ -55,7 +48,7 @@ public interface TBool extends BooleanNdArray, TType {
    * @return the new tensor
    */
   static TBool scalarOf(boolean value) {
-    return Tensor.of(DTYPE, Shape.scalar(), data -> data.setBoolean(value));
+    return Tensor.of(TBool.class, Shape.scalar(), data -> data.setBoolean(value));
   }
 
   /**
@@ -68,7 +61,7 @@ static TBool vectorOf(boolean... values) {
     if (values == null) {
       throw new IllegalArgumentException();
     }
-    return Tensor.of(DTYPE, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
+    return Tensor.of(TBool.class, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
   }
 
   /**
@@ -80,7 +73,7 @@ static TBool vectorOf(boolean... values) {
    * @return the new tensor
    */
   static TBool tensorOf(NdArray<Boolean> src) {
-    return Tensor.of(DTYPE, src.shape(), src::copyTo);
+    return Tensor.of(TBool.class, src.shape(), src::copyTo);
   }
 
   /**
@@ -90,7 +83,7 @@ static TBool tensorOf(NdArray<Boolean> src) {
    * @return the new tensor
    */
   static TBool tensorOf(Shape shape) {
-    return Tensor.of(DTYPE, shape);
+    return Tensor.of(TBool.class, shape);
   }
 
   /**
@@ -101,7 +94,7 @@ static TBool tensorOf(Shape shape) {
    * @return the new tensor
    */
   static TBool tensorOf(Shape shape, BooleanDataBuffer data) {
-    return Tensor.of(DTYPE, shape, d -> d.write(data));
+    return Tensor.of(TBool.class, shape, d -> d.write(data));
   }
 
   /**
@@ -113,6 +106,6 @@ static TBool tensorOf(Shape shape, BooleanDataBuffer data) {
    * @throws TensorFlowException if the tensor cannot be allocated or initialized
    */
   static TBool tensorOf(Shape shape, Consumer<TBool> dataInit) {
-    return Tensor.of(DTYPE, shape, dataInit);
+    return Tensor.of(TBool.class, shape, dataInit);
   }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat16.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat16.java
index 0decbb66d12..a43a0831f10 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat16.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat16.java
@@ -18,7 +18,6 @@
 package org.tensorflow.types;
 
 import java.util.function.Consumer;
-import org.tensorflow.DataType;
 import org.tensorflow.Tensor;
 import org.tensorflow.exceptions.TensorFlowException;
 import org.tensorflow.internal.types.TFloat16Mapper;
@@ -27,6 +26,8 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.ndarray.StdArrays;
 import org.tensorflow.ndarray.buffer.FloatDataBuffer;
+import org.tensorflow.proto.framework.DataType;
+import org.tensorflow.types.annotation.TensorType;
 import org.tensorflow.types.family.TFloating;
 
 /**
@@ -42,14 +43,9 @@
  * most CPUs do not support this format natively. For CPU computation on 16-bit floats, the {@link
  * TBfloat16} tensor type might be a better option.
  */
+@TensorType(dataType = DataType.DT_HALF, byteSize = 2, mapperClass = TFloat16Mapper.class)
 public interface TFloat16 extends FloatNdArray, TFloating {
 
-  /** readable-name for the data type */
-  static final String NAME = "FLOAT16";
-
-  /** Type metadata */
-  DataType<TFloat16> DTYPE = DataType.create(NAME, 19, 2, new TFloat16Mapper());
-
   /**
    * Allocates a new tensor for storing a single float value.
    *
@@ -57,7 +53,7 @@ public interface TFloat16 extends FloatNdArray, TFloating {
    * @return the new tensor
    */
   static TFloat16 scalarOf(float value) {
-    return Tensor.of(DTYPE, Shape.scalar(), data -> data.setFloat(value));
+    return Tensor.of(TFloat16.class, Shape.scalar(), data -> data.setFloat(value));
   }
 
   /**
@@ -70,7 +66,7 @@ static TFloat16 vectorOf(float... values) {
     if (values == null) {
       throw new IllegalArgumentException();
     }
-    return Tensor.of(DTYPE, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
+    return Tensor.of(TFloat16.class, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
   }
 
   /**
@@ -82,7 +78,7 @@ static TFloat16 vectorOf(float... values) {
    * @return the new tensor
    */
   static TFloat16 tensorOf(NdArray<Float> src) {
-    return Tensor.of(DTYPE, src.shape(), src::copyTo);
+    return Tensor.of(TFloat16.class, src.shape(), src::copyTo);
   }
 
   /**
@@ -92,7 +88,7 @@ static TFloat16 tensorOf(NdArray<Float> src) {
    * @return the new tensor
    */
   static TFloat16 tensorOf(Shape shape) {
-    return Tensor.of(DTYPE, shape);
+    return Tensor.of(TFloat16.class, shape);
   }
 
   /**
@@ -103,7 +99,7 @@ static TFloat16 tensorOf(Shape shape) {
    * @return the new tensor
    */
   static TFloat16 tensorOf(Shape shape, FloatDataBuffer data) {
-    return Tensor.of(DTYPE, shape, d -> d.write(data));
+    return Tensor.of(TFloat16.class, shape, d -> d.write(data));
   }
 
   /**
@@ -115,6 +111,6 @@ static TFloat16 tensorOf(Shape shape, FloatDataBuffer data) {
    * @throws TensorFlowException if the tensor cannot be allocated or initialized
    */
   static TFloat16 tensorOf(Shape shape, Consumer<TFloat16> dataInit) {
-    return Tensor.of(DTYPE, shape, dataInit);
+    return Tensor.of(TFloat16.class, shape, dataInit);
   }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat32.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat32.java
index 6300650811e..35208f7de43 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat32.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat32.java
@@ -18,7 +18,6 @@
 package org.tensorflow.types;
 
 import java.util.function.Consumer;
-import org.tensorflow.DataType;
 import org.tensorflow.Tensor;
 import org.tensorflow.exceptions.TensorFlowException;
 import org.tensorflow.internal.types.TFloat32Mapper;
@@ -27,17 +26,14 @@
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.ndarray.StdArrays;
 import org.tensorflow.ndarray.buffer.FloatDataBuffer;
+import org.tensorflow.proto.framework.DataType;
+import org.tensorflow.types.annotation.TensorType;
 import org.tensorflow.types.family.TFloating;
 
 /** IEEE-754 single-precision 32-bit float tensor type. */
+@TensorType(dataType = DataType.DT_FLOAT, byteSize = 4, mapperClass = TFloat32Mapper.class)
 public interface TFloat32 extends FloatNdArray, TFloating {
 
-  /** readable-name for the data type */
-  static final String NAME = "FLOAT";
-
-  /** Type metadata */
-  DataType<TFloat32> DTYPE = DataType.create(NAME, 1, 4, new TFloat32Mapper());
-
   /**
    * Allocates a new tensor for storing a single float value.
    *
@@ -45,7 +41,7 @@ public interface TFloat32 extends FloatNdArray, TFloating {
    * @return the new tensor
    */
   static TFloat32 scalarOf(float value) {
-    return Tensor.of(DTYPE, Shape.scalar(), data -> data.setFloat(value));
+    return Tensor.of(TFloat32.class, Shape.scalar(), data -> data.setFloat(value));
   }
 
   /**
@@ -58,7 +54,7 @@ static TFloat32 vectorOf(float... values) {
     if (values == null) {
       throw new IllegalArgumentException();
     }
-    return Tensor.of(DTYPE, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
+    return Tensor.of(TFloat32.class, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
   }
 
   /**
@@ -70,7 +66,7 @@ static TFloat32 vectorOf(float... values) {
    * @return the new tensor
    */
   static TFloat32 tensorOf(NdArray<Float> src) {
-    return Tensor.of(DTYPE, src.shape(), src::copyTo);
+    return Tensor.of(TFloat32.class, src.shape(), src::copyTo);
   }
 
   /**
@@ -80,7 +76,7 @@ static TFloat32 tensorOf(NdArray<Float> src) {
    * @return the new tensor
    */
   static TFloat32 tensorOf(Shape shape) {
-    return Tensor.of(DTYPE, shape);
+    return Tensor.of(TFloat32.class, shape);
   }
 
   /**
@@ -91,7 +87,7 @@ static TFloat32 tensorOf(Shape shape) {
    * @return the new tensor
    */
   static TFloat32 tensorOf(Shape shape, FloatDataBuffer data) {
-    return Tensor.of(DTYPE, shape, d -> d.write(data));
+    return Tensor.of(TFloat32.class, shape, d -> d.write(data));
   }
 
   /**
@@ -103,6 +99,6 @@ static TFloat32 tensorOf(Shape shape, FloatDataBuffer data) {
    * @throws TensorFlowException if the tensor cannot be allocated or initialized
    */
   static TFloat32 tensorOf(Shape shape, Consumer<TFloat32> dataInit) {
-    return Tensor.of(DTYPE, shape, dataInit);
+    return Tensor.of(TFloat32.class, shape, dataInit);
   }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat64.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat64.java
index 923b9992400..957612691e5 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat64.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat64.java
@@ -18,31 +18,23 @@
 package org.tensorflow.types;
 
 import java.util.function.Consumer;
-import org.tensorflow.DataType;
-import org.tensorflow.RawTensor;
 import org.tensorflow.Tensor;
 import org.tensorflow.exceptions.TensorFlowException;
-import org.tensorflow.internal.buffer.TensorBuffers;
-import org.tensorflow.internal.c_api.TF_Tensor;
 import org.tensorflow.internal.types.TFloat64Mapper;
 import org.tensorflow.ndarray.DoubleNdArray;
 import org.tensorflow.ndarray.NdArray;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.ndarray.StdArrays;
 import org.tensorflow.ndarray.buffer.DoubleDataBuffer;
-import org.tensorflow.ndarray.impl.dense.DoubleDenseNdArray;
+import org.tensorflow.proto.framework.DataType;
+import org.tensorflow.types.annotation.TensorType;
 import org.tensorflow.types.family.TFloating;
 
 
 /** IEEE-754 double-precision 64-bit float tensor type. */
+@TensorType(dataType = DataType.DT_DOUBLE, byteSize = 8, mapperClass = TFloat64Mapper.class)
 public interface TFloat64 extends DoubleNdArray, TFloating {
 
-  /** readable-name for the data type */
-  static final String NAME = "DOUBLE";
-
-  /** Type metadata */
-  DataType<TFloat64> DTYPE = DataType.create(NAME, 2, 8, new TFloat64Mapper());
-
   /**
    * Allocates a new tensor for storing a single double value.
    *
@@ -50,7 +42,7 @@ public interface TFloat64 extends DoubleNdArray, TFloating {
    * @return the new tensor
    */
   static TFloat64 scalarOf(double value) {
-    return Tensor.of(DTYPE, Shape.scalar(), data -> data.setDouble(value));
+    return Tensor.of(TFloat64.class, Shape.scalar(), data -> data.setDouble(value));
   }
 
   /**
@@ -63,7 +55,7 @@ static TFloat64 vectorOf(double... values) {
     if (values == null) {
       throw new IllegalArgumentException();
     }
-    return Tensor.of(DTYPE, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
+    return Tensor.of(TFloat64.class, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
   }
 
   /**
@@ -75,7 +67,7 @@ static TFloat64 vectorOf(double... values) {
    * @return the new tensor
    */
   static TFloat64 tensorOf(NdArray<Double> src) {
-    return Tensor.of(DTYPE, src.shape(), src::copyTo);
+    return Tensor.of(TFloat64.class, src.shape(), src::copyTo);
   }
 
   /**
@@ -85,7 +77,7 @@ static TFloat64 tensorOf(NdArray<Double> src) {
    * @return the new tensor
    */
   static TFloat64 tensorOf(Shape shape) {
-    return Tensor.of(DTYPE, shape);
+    return Tensor.of(TFloat64.class, shape);
   }
 
   /**
@@ -96,7 +88,7 @@ static TFloat64 tensorOf(Shape shape) {
    * @return the new tensor
    */
   static TFloat64 tensorOf(Shape shape, DoubleDataBuffer data) {
-    return Tensor.of(DTYPE, shape, d -> d.write(data));
+    return Tensor.of(TFloat64.class, shape, d -> d.write(data));
   }
 
   /**
@@ -108,6 +100,6 @@ static TFloat64 tensorOf(Shape shape, DoubleDataBuffer data) {
    * @throws TensorFlowException if the tensor cannot be allocated or initialized
    */
   static TFloat64 tensorOf(Shape shape, Consumer<TFloat64> dataInit) {
-    return Tensor.of(DTYPE, shape, dataInit);
+    return Tensor.of(TFloat64.class, shape, dataInit);
   }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt32.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt32.java
index ccb865e2793..8f6b587795b 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt32.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt32.java
@@ -18,28 +18,20 @@
 package org.tensorflow.types;
 
 import java.util.function.Consumer;
-import org.tensorflow.DataType;
-import org.tensorflow.RawTensor;
 import org.tensorflow.Tensor;
-import org.tensorflow.internal.buffer.TensorBuffers;
-import org.tensorflow.internal.c_api.TF_Tensor;
 import org.tensorflow.internal.types.TInt32Mapper;
 import org.tensorflow.ndarray.IntNdArray;
 import org.tensorflow.ndarray.NdArray;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.ndarray.StdArrays;
 import org.tensorflow.ndarray.buffer.IntDataBuffer;
-import org.tensorflow.ndarray.impl.dense.IntDenseNdArray;
-import org.tensorflow.types.family.TNumber;
+import org.tensorflow.proto.framework.DataType;
+import org.tensorflow.types.annotation.TensorType;
+import org.tensorflow.types.family.TIntegral;
 
 /** 32-bit signed integer tensor type. */
-public interface TInt32 extends IntNdArray, TNumber {
-
-  /** readable-name for the data type */
-  static final String NAME = "INT32";
-
-  /** Type metadata */
-  DataType<TInt32> DTYPE = DataType.create(NAME, 3, 4, new TInt32Mapper());
+@TensorType(dataType = DataType.DT_INT32, byteSize = 4, mapperClass = TInt32Mapper.class)
+public interface TInt32 extends IntNdArray, TIntegral {
 
   /**
    * Allocates a new tensor for storing a single int value.
@@ -48,7 +40,7 @@ public interface TInt32 extends IntNdArray, TNumber {
    * @return the new tensor
    */
   static TInt32 scalarOf(int value) {
-    return Tensor.of(DTYPE, Shape.scalar(), data -> data.setInt(value));
+    return Tensor.of(TInt32.class, Shape.scalar(), data -> data.setInt(value));
   }
 
   /**
@@ -62,7 +54,7 @@ static TInt32 vectorOf(int... values) {
     if (values == null) {
       throw new IllegalArgumentException();
     }
-    return Tensor.of(DTYPE, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
+    return Tensor.of(TInt32.class, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
   }
 
   /**
@@ -74,7 +66,7 @@ static TInt32 vectorOf(int... values) {
    * @return the new tensor
    */
   static TInt32 tensorOf(NdArray<Integer> src) {
-    return Tensor.of(DTYPE, src.shape(), src::copyTo);
+    return Tensor.of(TInt32.class, src.shape(), src::copyTo);
   }
 
   /**
@@ -84,7 +76,7 @@ static TInt32 tensorOf(NdArray<Integer> src) {
    * @return the new tensor
    */
   static TInt32 tensorOf(Shape shape) {
-    return Tensor.of(DTYPE, shape);
+    return Tensor.of(TInt32.class, shape);
   }
 
   /**
@@ -95,7 +87,7 @@ static TInt32 tensorOf(Shape shape) {
    * @return the new tensor
    */
   static TInt32 tensorOf(Shape shape, IntDataBuffer data) {
-    return Tensor.of(DTYPE, shape, d -> d.write(data));
+    return Tensor.of(TInt32.class, shape, d -> d.write(data));
   }
 
   /**
@@ -106,7 +98,7 @@ static TInt32 tensorOf(Shape shape, IntDataBuffer data) {
    * @return the new tensor
    */
   static TInt32 tensorOf(Shape shape, Consumer<TInt32> dataInit) {
-    return Tensor.of(DTYPE, shape, dataInit);
+    return Tensor.of(TInt32.class, shape, dataInit);
   }
 }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt64.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt64.java
index 02763391ff6..867248c5392 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt64.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt64.java
@@ -18,29 +18,21 @@
 package org.tensorflow.types;
 
 import java.util.function.Consumer;
-import org.tensorflow.DataType;
-import org.tensorflow.RawTensor;
 import org.tensorflow.Tensor;
 import org.tensorflow.exceptions.TensorFlowException;
-import org.tensorflow.internal.buffer.TensorBuffers;
-import org.tensorflow.internal.c_api.TF_Tensor;
 import org.tensorflow.internal.types.TInt64Mapper;
 import org.tensorflow.ndarray.LongNdArray;
 import org.tensorflow.ndarray.NdArray;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.ndarray.StdArrays;
 import org.tensorflow.ndarray.buffer.LongDataBuffer;
-import org.tensorflow.ndarray.impl.dense.LongDenseNdArray;
-import org.tensorflow.types.family.TNumber;
+import org.tensorflow.proto.framework.DataType;
+import org.tensorflow.types.annotation.TensorType;
+import org.tensorflow.types.family.TIntegral;
 
 /** 64-bit signed integer tensor type. */
-public interface TInt64 extends LongNdArray, TNumber {
-
-  /** readable-name for the data type */
-  static final String NAME = "INT64";
-
-  /** Type metadata */
-  DataType<TInt64> DTYPE = DataType.create(NAME, 9, 8, new TInt64Mapper());
+@TensorType(dataType = DataType.DT_INT64, byteSize = 8, mapperClass = TInt64Mapper.class)
+public interface TInt64 extends LongNdArray, TIntegral {
 
   /**
    * Allocates a new tensor for storing a single long value.
@@ -49,7 +41,7 @@ public interface TInt64 extends LongNdArray, TNumber {
    * @return the new tensor
    */
   static TInt64 scalarOf(long value) {
-    return Tensor.of(DTYPE, Shape.scalar(), data -> data.setLong(value));
+    return Tensor.of(TInt64.class, Shape.scalar(), data -> data.setLong(value));
   }
 
   /**
@@ -62,7 +54,7 @@ static TInt64 vectorOf(long... values) {
     if (values == null) {
       throw new IllegalArgumentException();
     }
-    return Tensor.of(DTYPE, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
+    return Tensor.of(TInt64.class, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
   }
 
   /**
@@ -74,7 +66,7 @@ static TInt64 vectorOf(long... values) {
    * @return the new tensor
    */
   static TInt64 tensorOf(NdArray<Long> src) {
-    return Tensor.of(DTYPE, src.shape(), src::copyTo);
+    return Tensor.of(TInt64.class, src.shape(), src::copyTo);
   }
 
   /**
@@ -84,7 +76,7 @@ static TInt64 tensorOf(NdArray<Long> src) {
    * @return the new tensor
    */
   static TInt64 tensorOf(Shape shape) {
-    return Tensor.of(DTYPE, shape);
+    return Tensor.of(TInt64.class, shape);
   }
 
   /**
@@ -95,7 +87,7 @@ static TInt64 tensorOf(Shape shape) {
    * @return the new tensor
    */
   static TInt64 tensorOf(Shape shape, LongDataBuffer data) {
-    return Tensor.of(DTYPE, shape, d -> d.write(data));
+    return Tensor.of(TInt64.class, shape, d -> d.write(data));
   }
 
   /**
@@ -107,6 +99,6 @@ static TInt64 tensorOf(Shape shape, LongDataBuffer data) {
    * @throws TensorFlowException if the tensor cannot be allocated or initialized
    */
   static TInt64 tensorOf(Shape shape, Consumer<TInt64> dataInit) {
-    return Tensor.of(DTYPE, shape, dataInit);
+    return Tensor.of(TInt64.class, shape, dataInit);
   }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java
index 6d7f7426c1a..b3000cc2f8a 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java
@@ -20,7 +20,6 @@
 import java.nio.charset.Charset;
 import java.nio.charset.StandardCharsets;
 import java.util.function.Function;
-import org.tensorflow.DataType;
 import org.tensorflow.Tensor;
 import org.tensorflow.internal.types.TStringInitializer;
 import org.tensorflow.internal.types.TStringMapper;
@@ -28,6 +27,8 @@
 import org.tensorflow.ndarray.NdArrays;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.ndarray.buffer.DataBuffer;
+import org.tensorflow.proto.framework.DataType;
+import org.tensorflow.types.annotation.TensorType;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -39,14 +40,9 @@
  * its values initially, so TensorFlow can compute and allocate the right amount of memory. Then the
  * data in the tensor is initialized once and cannot be modified afterwards.
  */
+@TensorType(dataType = DataType.DT_STRING, byteSize = -1, mapperClass = TStringMapper.class)
 public interface TString extends NdArray<String>, TType {
 
-  /** readable-name for the data type */
-  static final String NAME = "STRING";
-
-  /** Type metadata */
-  DataType<TString> DTYPE = DataType.create(NAME, 7, -1, new TStringMapper());
-
   /**
    * Allocates a new tensor for storing a string scalar.
    *
@@ -110,7 +106,7 @@ static TString tensorOf(NdArray<String> src) {
    */
   static TString tensorOf(Charset charset, NdArray<String> src) {
     TStringInitializer<String> initializer = new TStringInitializer<>(src, s -> s.getBytes(charset));
-    return Tensor.of(TString.DTYPE, src.shape(), initializer.computeRequiredSize(), initializer);
+    return Tensor.of(TString.class, src.shape(), initializer.computeRequiredSize(), initializer);
   }
 
   /**
@@ -171,7 +167,7 @@ static TString tensorOf(Charset charset, Shape shape, DataBuffer<String> data) {
    */
   static TString tensorOfBytes(NdArray<byte[]> src) {
     TStringInitializer<byte[]> initializer = new TStringInitializer<>(src, Function.identity());
-    return Tensor.of(TString.DTYPE, src.shape(), initializer.computeRequiredSize(), initializer);
+    return Tensor.of(TString.class, src.shape(), initializer.computeRequiredSize(), initializer);
   }
 
   /**
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint8.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint8.java
index a6f5dba8971..eae86414cb4 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint8.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint8.java
@@ -18,29 +18,21 @@
 package org.tensorflow.types;
 
 import java.util.function.Consumer;
-import org.tensorflow.DataType;
-import org.tensorflow.RawTensor;
 import org.tensorflow.Tensor;
 import org.tensorflow.exceptions.TensorFlowException;
-import org.tensorflow.internal.buffer.TensorBuffers;
-import org.tensorflow.internal.c_api.TF_Tensor;
 import org.tensorflow.internal.types.TUint8Mapper;
 import org.tensorflow.ndarray.ByteNdArray;
 import org.tensorflow.ndarray.NdArray;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.ndarray.StdArrays;
 import org.tensorflow.ndarray.buffer.ByteDataBuffer;
-import org.tensorflow.ndarray.impl.dense.ByteDenseNdArray;
-import org.tensorflow.types.family.TNumber;
+import org.tensorflow.proto.framework.DataType;
+import org.tensorflow.types.annotation.TensorType;
+import org.tensorflow.types.family.TIntegral;
 
 /** 8-bit unsigned integer tensor type. */
-public interface TUint8 extends ByteNdArray, TNumber {
-
-  /** readable-name for the data type */
-  static final String NAME = "UINT8";
-
-  /** Type metadata */
-  DataType<TUint8> DTYPE = DataType.create(NAME, 4, 1, new TUint8Mapper());
+@TensorType(dataType = DataType.DT_UINT8, byteSize = 1, mapperClass = TUint8Mapper.class)
+public interface TUint8 extends ByteNdArray, TIntegral {
 
   /**
    * Allocates a new tensor for storing a single byte value.
@@ -49,7 +41,7 @@ public interface TUint8 extends ByteNdArray, TNumber {
    * @return the new tensor
    */
   static TUint8 scalarOf(byte value) {
-    return Tensor.of(DTYPE, Shape.scalar(), data -> data.setByte(value));
+    return Tensor.of(TUint8.class, Shape.scalar(), data -> data.setByte(value));
   }
 
   /**
@@ -62,7 +54,7 @@ static TUint8 vectorOf(byte... values) {
     if (values == null) {
       throw new IllegalArgumentException();
     }
-    return Tensor.of(DTYPE, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
+    return Tensor.of(TUint8.class, Shape.of(values.length), data -> StdArrays.copyTo(values, data));
   }
 
   /**
@@ -74,7 +66,7 @@ static TUint8 vectorOf(byte... values) {
    * @return the new tensor
    */
   static TUint8 tensorOf(NdArray<Byte> src) {
-    return Tensor.of(DTYPE, src.shape(), src::copyTo);
+    return Tensor.of(TUint8.class, src.shape(), src::copyTo);
   }
 
   /**
@@ -84,7 +76,7 @@ static TUint8 tensorOf(NdArray<Byte> src) {
    * @return the new tensor
    */
   static TUint8 tensorOf(Shape shape) {
-    return Tensor.of(DTYPE, shape);
+    return Tensor.of(TUint8.class, shape);
   }
 
   /**
@@ -95,7 +87,7 @@ static TUint8 tensorOf(Shape shape) {
    * @return the new tensor
    */
   static TUint8 tensorOf(Shape shape, ByteDataBuffer data) {
-    return Tensor.of(DTYPE, shape, d -> d.write(data));
+    return Tensor.of(TUint8.class, shape, d -> d.write(data));
   }
 
   /**
@@ -107,6 +99,6 @@ static TUint8 tensorOf(Shape shape, ByteDataBuffer data) {
    * @throws TensorFlowException if the tensor cannot be allocated or initialized
    */
   static TUint8 tensorOf(Shape shape, Consumer<TUint8> dataInit) {
-    return Tensor.of(DTYPE, shape, dataInit);
+    return Tensor.of(TUint8.class, shape, dataInit);
   }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/annotation/TensorType.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/annotation/TensorType.java
new file mode 100644
index 00000000000..78ab5d7a8b6
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/annotation/TensorType.java
@@ -0,0 +1,53 @@
+/*
+ *  Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+ *
+ *  Licensed under the Apache License, Version 2.0 (the "License");
+ *  you may not use this file except in compliance with the License.
+ *  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ *  Unless required by applicable law or agreed to in writing, software
+ *  distributed under the License is distributed on an "AS IS" BASIS,
+ *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ *  See the License for the specific language governing permissions and
+ *  limitations under the License.
+ *  =======================================================================
+ */
+package org.tensorflow.types.annotation;
+
+import java.lang.annotation.Documented;
+import java.lang.annotation.ElementType;
+import java.lang.annotation.Retention;
+import java.lang.annotation.RetentionPolicy;
+import java.lang.annotation.Target;
+import org.tensorflow.TensorMapper;
+import org.tensorflow.proto.framework.DataType;
+
+/**
+ * Annotation for all tensor types.
+ *
+ * <p>Any interface extending {@link org.tensorflow.types.family.TType TType} to be registered as a
+ * tensor type must be annotated with {@code @TensorType} to provide metadata required for allocating
+ * and mapping tensors of this type.</p>
+ */
+@Documented
+@Retention(RetentionPolicy.RUNTIME)
+@Target(ElementType.TYPE)
+public @interface TensorType {
+
+  /**
+   * The data type of each elements in a tensor of this type
+   */
+  DataType dataType();
+
+  /**
+   * The number of bytes required one element of a tensor of type, -1 for variable-length element tensors
+   */
+  int byteSize();
+
+  /**
+   * The class of the {@link TensorMapper} to allocate and use for mapping tensors of this type
+   */
+  Class<? extends TensorMapper<?>> mapperClass();
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/family/TIntegral.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/family/TIntegral.java
new file mode 100644
index 00000000000..3652ea4613c
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/family/TIntegral.java
@@ -0,0 +1,25 @@
+/*
+ *  Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+ *
+ *  Licensed under the Apache License, Version 2.0 (the "License");
+ *  you may not use this file except in compliance with the License.
+ *  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ *  Unless required by applicable law or agreed to in writing, software
+ *  distributed under the License is distributed on an "AS IS" BASIS,
+ *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ *  See the License for the specific language governing permissions and
+ *  limitations under the License.
+ *  =======================================================================
+ */
+package org.tensorflow.types.family;
+
+/**
+ * Common interface for all integral numeric tensors.
+ *
+ * <p>Operations that only accepts integral values as some of their operands enforce that the tensor
+ * types for these operands to be bound to this interface.
+ */
+public interface TIntegral extends TNumber {}
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/family/TType.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/family/TType.java
index 21d275296c8..2fc423b914e 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/family/TType.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/family/TType.java
@@ -18,6 +18,7 @@
 package org.tensorflow.types.family;
 
 import org.tensorflow.Tensor;
+import org.tensorflow.proto.framework.DataType;
 
 /**
  * Common interface for all typed tensors.
@@ -60,6 +61,16 @@
  */
 public interface TType extends Tensor {
 
+  /**
+   * Returns the type of this tensor as a registered subclass of {@code TType}
+   */
+  Class<? extends TType> type();
+
+  @Override
+  default DataType dataType() {
+    return asRawTensor().dataType();
+  }
+
   @Override
   default long numBytes() {
     return asRawTensor().numBytes();
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/package-info.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/package-info.java
index afbd69fabe5..746ae703694 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/package-info.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/package-info.java
@@ -25,17 +25,14 @@
  * bound to one of the marker interface found in {@link org.tensorflow.types.family}, according
  * to the nature of the data.
  *
- * <p>Each tensor type must provide a static instance of {@link org.tensorflow.DataType}
- * carrying type metadata that should be used for allocating a tensor of this type or to pass
- * this type as an operation argument. For example, metadata about TensorFlow int32 type is
- * found in {@link org.tensorflow.types.TInt32#DTYPE TInt32.DTYPE}.
+ * <p>Each tensor type must be annotated with {@link org.tensorflow.types.annotation.TensorType} to
+ * provide type metadata that should be used for allocating or mapping tensors of this type.
  *
  * <p>Instances of tensor types must also implement the {@link org.tensorflow.ndarray.NdArray NdArray}
- * interface so a user can access directly the tensor data in a n-dimensional space by invoking
- * {@link org.tensorflow.Tensor#data() Tensor.data()}.
+ * interface so a user can access directly the tensor data in a n-dimensional space.
  *
  * <p>Note that while it is always possible to allocate a tensor using the
- * {@link org.tensorflow.Tensor#of(org.tensorflow.DataType, Shape) Tensor.of(...)}
+ * {@link org.tensorflow.Tensor#of(Class, Shape) Tensor.of(...)}
  * method, most tensor types expose factory methods that simplify the creation process, like
  * {@code scalarOf(...)}, {@code vectorOf(...)}, {@code tensorOf(...)}, etc.
  */
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/ConcreteFunctionTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/ConcreteFunctionTest.java
index 72dcfb12430..b2b2c34e223 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/ConcreteFunctionTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/ConcreteFunctionTest.java
@@ -16,7 +16,6 @@
 
 import static org.junit.jupiter.api.Assertions.assertEquals;
 import static org.junit.jupiter.api.Assertions.assertThrows;
-import static org.junit.jupiter.api.Assertions.fail;
 
 import org.junit.jupiter.api.Test;
 import org.tensorflow.op.Ops;
@@ -29,14 +28,14 @@
 public class ConcreteFunctionTest {
 
   private static Signature plusFive(Ops tf) {
-    Placeholder<TFloat32> input = tf.placeholder(TFloat32.DTYPE);
+    Placeholder<TFloat32> input = tf.placeholder(TFloat32.class);
     Add<TFloat32> output = tf.math.add(input, tf.constant(5.0f));
     Init init = tf.init();  // for native resource management tests
     return Signature.builder().key("plusFive").input("x", input).output("y", output).build();
   }
 
   private static Signature minusTwo(Ops tf) {
-    Placeholder<TFloat32> input = tf.placeholder(TFloat32.DTYPE);
+    Placeholder<TFloat32> input = tf.placeholder(TFloat32.class);
     Sub<TFloat32> output = tf.math.sub(input, tf.constant(2.0f));
     return Signature.builder().key("minusTwo").input("x", input).output("y", output).build();
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/EagerOperationBuilderTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/EagerOperationBuilderTest.java
index 6751c513ef3..b39ecec9881 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/EagerOperationBuilderTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/EagerOperationBuilderTest.java
@@ -18,9 +18,9 @@
 import static org.junit.jupiter.api.Assertions.fail;
 
 import org.junit.jupiter.api.Test;
-import org.tensorflow.op.Ops;
 import org.tensorflow.ndarray.Shape;
-import org.tensorflow.types.TFloat32;
+import org.tensorflow.op.Ops;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TInt32;
 
 /** Unit tests for {@link EagerOperationBuilder} class. */
@@ -45,7 +45,7 @@ public void failToBuildOpIfSessionIsClosed() {
       opBuilder = new EagerOperationBuilder(session, "Empty", "empty");
     }
     try {
-      opBuilder.setAttr("dtype", TFloat32.DTYPE);
+      opBuilder.setAttr("dtype", DataType.DT_FLOAT);
       fail();
     } catch (IllegalStateException e) {
       // expected
@@ -90,7 +90,7 @@ public void setAttrs() {
       // dtype, tensor attributes.
       try (TInt32 t = TInt32.scalarOf(1)) {
         opBuilder(session, "Const", "DataTypeAndTensor")
-            .setAttr("dtype", TInt32.DTYPE)
+            .setAttr("dtype", t.dataType())
             .setAttr("value", t)
             .build();
       }
@@ -98,7 +98,7 @@ public void setAttrs() {
       opBuilder(session, "RandomUniform", "DataTypeAndInt")
           .addInput(tf.array(1).asOutput())
           .setAttr("seed", 10)
-          .setAttr("dtype", TFloat32.DTYPE)
+          .setAttr("dtype", DataType.DT_FLOAT)
           .build();
       // list(int), string
       opBuilder(session, "MaxPool", "IntListAndString")
@@ -119,7 +119,7 @@ public void setAttrs() {
           .build();
       // list(shape)
       opBuilder(session, "FIFOQueue", "queue")
-          .setAttr("component_types", new DataType[] {TInt32.DTYPE, TInt32.DTYPE})
+          .setAttr("component_types", new DataType[] {DataType.DT_INT32, DataType.DT_INT32})
           .setAttr("shapes", new Shape[] {Shape.of(2, 2), Shape.of(2, 2, 2)})
           .build();
       // bool
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/EagerOperationTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/EagerOperationTest.java
index a14a295fddd..2920fbdf59f 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/EagerOperationTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/EagerOperationTest.java
@@ -19,10 +19,10 @@
 import static org.junit.jupiter.api.Assertions.fail;
 
 import org.junit.jupiter.api.Test;
-import org.tensorflow.exceptions.TFFailedPreconditionException;
 import org.tensorflow.exceptions.TFInvalidArgumentException;
-import org.tensorflow.op.Ops;
 import org.tensorflow.ndarray.Shape;
+import org.tensorflow.op.Ops;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 
@@ -49,10 +49,10 @@ public void outputDataTypeAndShape() {
          TInt32 t = TInt32.tensorOf(Shape.of(2, 3))) {
       EagerOperation op =
           opBuilder(session, "Const", "OutputAttrs")
-              .setAttr("dtype", TInt32.DTYPE)
+              .setAttr("dtype", t.dataType())
               .setAttr("value", t)
               .build();
-      assertEquals(TInt32.DTYPE, op.dtype(0));
+      assertEquals(DataType.DT_INT32, op.dtype(0));
       assertEquals(2, op.shape(0).size(0));
       assertEquals(3, op.shape(0).size(1));
     }
@@ -72,7 +72,7 @@ public void outputTensor() {
       // Validate that we retrieve the right shape and datatype from the tensor
       // that has been resolved
       assertEquals(0, add.shape(0).numDimensions());
-      assertEquals(TInt32.DTYPE, add.dtype(0));
+      assertEquals(DataType.DT_INT32, add.dtype(0));
     }
   }
 
@@ -123,7 +123,7 @@ public void numOutputs() {
           opBuilder(session, "UniqueWithCountsV2", "unq")
               .addInput(tf.constant(new int[]{1, 2, 1}).asOutput())
               .addInput(tf.constant(new int[]{0}).asOutput())
-              .setAttr("out_idx", TInt32.DTYPE)
+              .setAttr("out_idx", DataType.DT_INT32)
               .build();
       assertEquals(3, op.numOutputs());
     }
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/GraphOperationBuilderTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/GraphOperationBuilderTest.java
index 7573a25ac13..bbb9e23ec90 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/GraphOperationBuilderTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/GraphOperationBuilderTest.java
@@ -21,11 +21,11 @@
 
 import org.junit.jupiter.api.Test;
 import org.tensorflow.exceptions.TFInvalidArgumentException;
+import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Ops;
 import org.tensorflow.op.core.Constant;
-import org.tensorflow.ndarray.Shape;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
-import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
 
 /** Unit tests for {@link org.tensorflow.GraphOperationBuilder}. */
@@ -90,7 +90,7 @@ public void setAttr() {
       // dtype, tensor attributes.
       try (TInt32 t = TInt32.scalarOf(1)) {
         g.opBuilder("Const", "DataTypeAndTensor")
-            .setAttr("dtype", TInt32.DTYPE)
+            .setAttr("dtype", t.dataType())
             .setAttr("value", t)
             .build()
             .output(0);
@@ -106,7 +106,7 @@ public void setAttr() {
       g.opBuilder("RandomUniform", "Int")
           .addInput(tf.array(1).asOutput())
           .setAttr("seed", 10)
-          .setAttr("dtype", TFloat32.DTYPE)
+          .setAttr("dtype", DataType.DT_FLOAT)
           .build();
       assertTrue(hasNode(g, "Int"));
       // list(int)
@@ -132,23 +132,23 @@ public void setAttrShape() {
     try (Graph g = new Graph()) {
       Output<?> n =
           g.opBuilder("Placeholder", "unknown")
-              .setAttr("dtype", TFloat32.DTYPE)
+              .setAttr("dtype", DataType.DT_FLOAT)
               .setAttr("shape", Shape.unknown())
               .build()
               .output(0);
       assertEquals(-1, n.shape().numDimensions());
-      assertEquals(TFloat32.DTYPE, n.dataType());
+      assertEquals(DataType.DT_FLOAT, n.dataType());
 
       n =
           g.opBuilder("Placeholder", "batch_of_vectors")
-              .setAttr("dtype", TFloat32.DTYPE)
+              .setAttr("dtype", DataType.DT_FLOAT)
               .setAttr("shape", Shape.of(-1, 784))
               .build()
               .output(0);
       assertEquals(2, n.shape().numDimensions());
       assertEquals(-1, n.shape().size(0));
       assertEquals(784, n.shape().size(1));
-      assertEquals(TFloat32.DTYPE, n.dataType());
+      assertEquals(DataType.DT_FLOAT, n.dataType());
     }
   }
 
@@ -172,7 +172,7 @@ public void addControlInput() {
         TBool yes = TBool.scalarOf(true);
         TBool no = TBool.scalarOf(false)) {
       Ops tf = Ops.create(g);
-      Output<TBool> placeholder = tf.placeholder(TBool.DTYPE).asOutput();
+      Output<TBool> placeholder = tf.placeholder(TBool.class).asOutput();
       GraphOperation check =
           g.opBuilder("Assert", "assert")
               .addInput(placeholder)
@@ -200,7 +200,7 @@ private static void testSetAttrShapeList(Shape[] shapes) {
       int[][] matrix = new int[][] {{0, 0}, {0, 0}};
       Output<?> queue =
           g.opBuilder("FIFOQueue", "queue")
-              .setAttr("component_types", new DataType[] {TInt32.DTYPE, TInt32.DTYPE})
+              .setAttr("component_types", new DataType[] {DataType.DT_INT32, DataType.DT_INT32})
               .setAttr("shapes", shapes)
               .build()
               .output(0);
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/GraphTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/GraphTest.java
index a9eed79041a..d8ffc1a475b 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/GraphTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/GraphTest.java
@@ -27,6 +27,7 @@
 import org.tensorflow.exceptions.TFInvalidArgumentException;
 import org.tensorflow.op.Ops;
 import org.tensorflow.op.linalg.MatMul;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.proto.framework.GraphDef;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
@@ -42,7 +43,7 @@ public void graphDefRoundTrip() {
       Ops tf = Ops.create(g);
       tf.withName("Y").linalg.matMul(
           tf.withName("A").constant(new int[2][2]),
-          tf.withName("X").placeholder(TInt32.DTYPE),
+          tf.withName("X").placeholder(TInt32.class),
           MatMul.transposeA(true).transposeB(false)
       );
       graphDef = g.toGraphDef();
@@ -140,8 +141,8 @@ public void addGradientsToGraph() {
         Session s = new Session(g)) {
       Ops tf = Ops.create(g);
 
-      Output<TFloat32> x1 = tf.placeholder(TFloat32.DTYPE).output();
-      Output<TFloat32> x2 = tf.placeholder(TFloat32.DTYPE).output();
+      Output<TFloat32> x1 = tf.placeholder(TFloat32.class).output();
+      Output<TFloat32> x2 = tf.placeholder(TFloat32.class).output();
       Output<TFloat32> y0 = tf.math.square(x1).y();
       Output<TFloat32> y1 = tf.math.square(y0).y();
       Output<TFloat32> y2 = tf.math.addN(Arrays.asList(y0, x2)).sum();
@@ -149,13 +150,13 @@ public void addGradientsToGraph() {
       Output<?>[] grads0 = g.addGradients(y1, toArray(x1));
       assertNotNull(grads0);
       assertEquals(1, grads0.length);
-      assertEquals(TFloat32.DTYPE, grads0[0].dataType());
+      assertEquals(DataType.DT_FLOAT, grads0[0].dataType());
 
       Output<?>[] grads1 = g.addGradients(y2, toArray(x1, x2));
       assertNotNull(grads1);
       assertEquals(2, grads1.length);
-      assertEquals(TFloat32.DTYPE, grads1[0].dataType());
-      assertEquals(TFloat32.DTYPE, grads1[1].dataType());
+      assertEquals(DataType.DT_FLOAT, grads1[0].dataType());
+      assertEquals(DataType.DT_FLOAT, grads1[1].dataType());
       
       try (TFloat32 c1 = TFloat32.scalarOf(3.0f);
           TFloat32 c2 = TFloat32.scalarOf(2.0f);
@@ -182,14 +183,14 @@ public void addGradientSumsToGraph() {
         Session s = new Session(g)) {
       Ops tf = Ops.create(g);
 
-      Output<TFloat32> x = tf.placeholder(TFloat32.DTYPE).output();
+      Output<TFloat32> x = tf.placeholder(TFloat32.class).output();
       Output<TFloat32> y0 = tf.math.square(x).y();
       Output<TFloat32> y1 = tf.math.square(y0).y();
 
       Output<?>[] grad = g.addGradients(null, toArray(y0, y1), toArray(x), null);
       assertNotNull(grad);
       assertEquals(1, grad.length);
-      assertEquals(TFloat32.DTYPE, grad[0].dataType());
+      assertEquals(DataType.DT_FLOAT, grad[0].dataType());
 
       try (TFloat32 c = TFloat32.scalarOf(3.0f);
           TFloat32 output = (TFloat32)s.runner()
@@ -208,19 +209,19 @@ public void addGradientsWithInitialValuesToGraph() {
         Session s = new Session(g)) {
       Ops tf = Ops.create(g);
 
-      Output<TFloat32> x = tf.placeholder(TFloat32.DTYPE).output();
+      Output<TFloat32> x = tf.placeholder(TFloat32.class).output();
       Output<TFloat32> y0 = tf.math.square(x).y();
       Output<TFloat32> y1 = tf.math.square(y0).y();
       
       Output<?>[] grad0 = g.addGradients(y1, toArray(y0));
       assertNotNull(grad0);
       assertEquals(1, grad0.length);
-      assertEquals(TFloat32.DTYPE, grad0[0].dataType());
+      assertEquals(DataType.DT_FLOAT, grad0[0].dataType());
 
       Output<?>[] grad1 = g.addGradients(null, toArray(y0), toArray(x), toArray(grad0[0]));
       assertNotNull(grad1);
       assertEquals(1, grad1.length);
-      assertEquals(TFloat32.DTYPE, grad1[0].dataType());
+      assertEquals(DataType.DT_FLOAT, grad1[0].dataType());
 
       try (TFloat32 c = TFloat32.scalarOf(3.0f);
           TFloat32 output = (TFloat32)s.runner()
@@ -238,7 +239,7 @@ public void validateGradientsNames() {
     try (Graph g = new Graph()) {
       Ops tf = Ops.create(g);
 
-      Output<TFloat32> x = tf.placeholder(TFloat32.DTYPE).output();
+      Output<TFloat32> x = tf.placeholder(TFloat32.class).output();
       Output<TFloat32> y0 = tf.math.square(x).y();
 
       Output<?>[] grad0 = g.addGradients(null, toArray(y0), toArray(x), null);
@@ -267,7 +268,7 @@ public void buildWhileLoopSingleInput() {
         Session s = new Session(g)) {
       Ops tf = Ops.create(g);
 
-      Output<?> input = tf.placeholder(TInt32.DTYPE).output();
+      Output<?> input = tf.placeholder(TInt32.class).output();
 
       @SuppressWarnings("unchecked")
       Output<?>[] loopOutputs = g.whileLoop(
@@ -299,8 +300,8 @@ public void buildWhileLoopMultipleInputs() {
         Session s = new Session(g)) {
       Ops tf = Ops.create(g);
 
-      Output<?> input1 = tf.placeholder(TInt32.DTYPE).output();
-      Output<?> input2 = tf.placeholder(TInt32.DTYPE).output();
+      Output<?> input1 = tf.placeholder(TInt32.class).output();
+      Output<?> input2 = tf.placeholder(TInt32.class).output();
       Output<?>[] inputs = toArray(input1, input2);
 
       @SuppressWarnings("unchecked")
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/RawTensorTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/RawTensorTest.java
new file mode 100644
index 00000000000..0d2d8af8b1c
--- /dev/null
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/RawTensorTest.java
@@ -0,0 +1,90 @@
+/*
+ *  Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+ *
+ *  Licensed under the Apache License, Version 2.0 (the "License");
+ *  you may not use this file except in compliance with the License.
+ *  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ *  Unless required by applicable law or agreed to in writing, software
+ *  distributed under the License is distributed on an "AS IS" BASIS,
+ *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ *  See the License for the specific language governing permissions and
+ *  limitations under the License.
+ *  =======================================================================
+ */
+package org.tensorflow;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.junit.jupiter.api.Assertions.assertSame;
+import static org.junit.jupiter.api.Assertions.fail;
+
+import org.junit.jupiter.api.Test;
+import org.tensorflow.ndarray.Shape;
+import org.tensorflow.types.TFloat32;
+import org.tensorflow.types.TInt32;
+import org.tensorflow.types.TString;
+
+public class RawTensorTest {
+
+  @Test
+  public void rawToTypedTensor() {
+    RawTensor rawTensor = RawTensor.allocate(TFloat32.class, Shape.of(2, 2), -1);
+    TFloat32 floatTensor = (TFloat32)rawTensor.asTypedTensor();
+    assertSame(floatTensor.asRawTensor(), rawTensor);
+    try {
+      TInt32 intTensor = (TInt32)rawTensor.asTypedTensor();
+      fail();
+    } catch (ClassCastException e) {
+      // ok
+    }
+  }
+
+  @Test
+  public void allocateTensorWithSize() {
+    try (RawTensor rawTensor = RawTensor.allocate(TFloat32.class, Shape.of(2, 2), 16)) {
+      assertEquals(16, rawTensor.numBytes());
+    }
+    try (RawTensor rawTensor = RawTensor.allocate(TFloat32.class, Shape.of(2, 2), 100)) {
+      assertEquals(100, rawTensor.numBytes());
+    }
+    try (RawTensor rawTensor = RawTensor.allocate(TFloat32.class, Shape.of(2, 2), 10)) {
+      fail();
+    } catch (IllegalArgumentException e) {
+      // ok
+    }
+    try (RawTensor rawTensor = RawTensor.allocate(TString.class, Shape.of(2, 2), 100)) {
+      assertEquals(100, rawTensor.numBytes());
+    }
+  }
+
+  @Test
+  public void allocateTensorWithoutSize() {
+    try (RawTensor rawTensor = RawTensor.allocate(TFloat32.class, Shape.of(2, 2), -1)) {
+      assertEquals(16, rawTensor.numBytes());
+      // ok
+    }
+    try (RawTensor rawTensor = RawTensor.allocate(TString.class, Shape.of(2, 2), -1)) {
+      fail();
+    } catch (IllegalArgumentException e) {
+      // ok
+    }
+  }
+
+  @Test
+  public void failToAllocateTensorFromUnknownShape() {
+    try {
+      RawTensor.allocate(TFloat32.class, Shape.of(3, -1, 3), -1);
+      fail();
+    } catch (IllegalArgumentException e) {
+      // ok
+    }
+    try {
+      RawTensor.allocate(TString.class, Shape.unknown(), 100);
+      fail();
+    } catch (IllegalArgumentException e) {
+      // ok
+    }
+  }
+}
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SavedModelBundleTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SavedModelBundleTest.java
index 417205f1f38..cd8ac7e2ae4 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SavedModelBundleTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SavedModelBundleTest.java
@@ -305,16 +305,16 @@ public void pythonTfFunction() {
   }
 
   private static Signature buildGraphWithVariables(Ops tf, Shape xShape) {
-    Placeholder<TFloat32> x = tf.placeholder(TFloat32.DTYPE, Placeholder.shape(xShape));
+    Placeholder<TFloat32> x = tf.placeholder(TFloat32.class, Placeholder.shape(xShape));
     Variable<TFloat32> y = tf
-        .variable(tf.random.randomUniform(tf.constant(xShape), TFloat32.DTYPE));
+        .variable(tf.random.randomUniform(tf.constant(xShape), TFloat32.class));
     ReduceSum<TFloat32> z = tf.reduceSum(tf.math.add(x, y), tf.array(0, 1));
     Init init = tf.init();
     return Signature.builder().input("input", x).output("reducedSum", z).build();
   }
 
   private static Signature buildIdentityGraph(Ops tf, String signatureKey) {
-    Placeholder<TFloat32> x = tf.placeholder(TFloat32.DTYPE, Placeholder.shape(Shape.scalar()));
+    Placeholder<TFloat32> x = tf.placeholder(TFloat32.class, Placeholder.shape(Shape.scalar()));
     Identity<TFloat32> xprime = tf.identity(x);
     return Signature.builder().key(signatureKey).input("x", x).output("x", xprime).build();
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SessionTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SessionTest.java
index 0556c1ff17f..b1928bff51c 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SessionTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SessionTest.java
@@ -165,7 +165,7 @@ public void runInit() {
     try (Graph g = new Graph()) {
       Ops tf = Ops.create(g);
 
-      Variable<TInt32> var1 = tf.variable(Shape.scalar(), TInt32.DTYPE);
+      Variable<TInt32> var1 = tf.variable(Shape.scalar(), TInt32.class);
       tf.initAdd(tf.assign(var1, tf.constant(10)));
       Variable<TInt32> var2 = tf.variable(tf.constant(20));
       Add<TInt32> add = tf.math.add(var1, var2);
@@ -185,7 +185,7 @@ public void runInitByName() {
     try (Graph g = new Graph()) {
       Ops tf = Ops.create(g);
 
-      Variable<TInt32> var1 = tf.variable(Shape.scalar(), TInt32.DTYPE);
+      Variable<TInt32> var1 = tf.variable(Shape.scalar(), TInt32.class);
       tf.initAdd(tf.assign(var1, tf.constant(10)));
       Variable<TInt32> var2 = tf.variable(tf.constant(20));
       Add<TInt32> add = tf.math.add(var1, var2);
@@ -212,8 +212,8 @@ public void save() throws IOException  {
     Path testFolder = Files.createTempDirectory("tf-session-save-test");
     try (Graph g = new Graph()) {
       Ops tf = Ops.create(g);
-      Variable<TFloat32> x = tf.variable(tf.random.randomUniform(tf.constant(Shape.of(3, 3L)), TFloat32.DTYPE));
-      Variable<TFloat32> y = tf.variable(tf.random.randomUniform(tf.constant(Shape.of(3, 3L)), TFloat32.DTYPE));
+      Variable<TFloat32> x = tf.variable(tf.random.randomUniform(tf.constant(Shape.of(3, 3L)), TFloat32.class));
+      Variable<TFloat32> y = tf.variable(tf.random.randomUniform(tf.constant(Shape.of(3, 3L)), TFloat32.class));
       Init init = tf.init();
 
       try (Session s = new Session(g)) {
@@ -241,7 +241,7 @@ private static ConfigProto singleThreadConfigProto() {
   private static void transpose_A_times_X(Ops tf, int[][] a) {
     tf.withName("Y").linalg.matMul(
         tf.withName("A").constant(a),
-        tf.withName("X").placeholder(TInt32.DTYPE),
+        tf.withName("X").placeholder(TInt32.class),
         MatMul.transposeA(true).transposeB(false)
     );
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SignatureTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SignatureTest.java
index 8931ecbbde1..e1436358a68 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SignatureTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SignatureTest.java
@@ -14,17 +14,11 @@
 ==============================================================================*/
 package org.tensorflow;
 
-import static org.junit.jupiter.api.Assertions.assertEquals;
 import static org.junit.jupiter.api.Assertions.assertNull;
 import static org.junit.jupiter.api.Assertions.assertThrows;
 
 import org.junit.jupiter.api.Test;
 import org.tensorflow.op.Ops;
-import org.tensorflow.op.core.Init;
-import org.tensorflow.op.core.Placeholder;
-import org.tensorflow.op.math.Add;
-import org.tensorflow.op.math.Sub;
-import org.tensorflow.types.TFloat32;
 
 public class SignatureTest {
 
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/TensorTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/TensorTest.java
index 4da9bce9e90..9415a986222 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/TensorTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/TensorTest.java
@@ -30,9 +30,6 @@
 import java.nio.IntBuffer;
 import java.nio.LongBuffer;
 import org.junit.jupiter.api.Test;
-import org.tensorflow.op.Ops;
-import org.tensorflow.ndarray.Shape;
-import org.tensorflow.ndarray.buffer.DataBuffers;
 import org.tensorflow.ndarray.BooleanNdArray;
 import org.tensorflow.ndarray.DoubleNdArray;
 import org.tensorflow.ndarray.FloatNdArray;
@@ -40,7 +37,11 @@
 import org.tensorflow.ndarray.LongNdArray;
 import org.tensorflow.ndarray.NdArray;
 import org.tensorflow.ndarray.NdArrays;
+import org.tensorflow.ndarray.Shape;
 import org.tensorflow.ndarray.StdArrays;
+import org.tensorflow.ndarray.buffer.DataBuffers;
+import org.tensorflow.op.Ops;
+import org.tensorflow.proto.framework.DataType;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TFloat64;
@@ -71,14 +72,14 @@ public void createWithRawData() {
 
     // validate creating a tensor using a raw data byte buffers
     {
-      try (TBool t = Tensor.of(TBool.DTYPE, bools_shape, DataBuffers.of(bools_))) {
+      try (TBool t = Tensor.of(TBool.class, bools_shape, DataBuffers.of(bools_))) {
         boolean[] actual = new boolean[bools_.length];
         t.read(DataBuffers.of(actual));
         assertArrayEquals(bools, actual);
       }
 
       // note: the buffer is expected to contain raw TF_STRING (as per C API)
-      try (TString t = Tensor.of(TString.DTYPE, strings_shape, DataBuffers.of(strings_))) {
+      try (TString t = Tensor.of(TString.class, strings_shape, DataBuffers.of(strings_))) {
         assertEquals(strings, t.getObject());
       }
     }
@@ -95,7 +96,7 @@ public void createWithRawData() {
     }
 
     // validate shape checking
-    try (TBool t = Tensor.of(TBool.DTYPE, Shape.of(bools_.length * 2), DataBuffers.of(bools_))) {
+    try (TBool t = Tensor.of(TBool.class, Shape.of(bools_.length * 2), DataBuffers.of(bools_))) {
       fail("should have failed on incompatible buffer");
     } catch (IllegalArgumentException e) {
       // expected
@@ -267,44 +268,51 @@ public void readFromRawData() {
   @Test
   public void scalars() {
     try (TFloat32 t = TFloat32.scalarOf(2.718f)) {
-      assertEquals(TFloat32.DTYPE, t.dataType());
+      assertEquals(TFloat32.class, t.type());
+      assertEquals(DataType.DT_FLOAT, t.dataType());
       assertEquals(0, t.shape().numDimensions());
       assertEquals(2.718f, t.getFloat(), EPSILON_F);
     }
 
     try (TFloat64 t = TFloat64.scalarOf(3.1415)) {
-      assertEquals(TFloat64.DTYPE, t.dataType());
+      assertEquals(TFloat64.class, t.type());
+      assertEquals(DataType.DT_DOUBLE, t.dataType());
       assertEquals(0, t.shape().numDimensions());
       assertEquals(3.1415, t.getDouble(), EPSILON);
     }
 
     try (TInt32 t = TInt32.scalarOf(-33)) {
-      assertEquals(TInt32.DTYPE, t.dataType());
+      assertEquals(TInt32.class, t.type());
+      assertEquals(DataType.DT_INT32, t.dataType());
       assertEquals(0, t.shape().numDimensions());
       assertEquals(-33, t.getInt());
     }
 
     try (TInt64 t = TInt64.scalarOf(8589934592L)) {
-      assertEquals(TInt64.DTYPE, t.dataType());
+      assertEquals(TInt64.class, t.type());
+      assertEquals(DataType.DT_INT64, t.dataType());
       assertEquals(0, t.shape().numDimensions());
       assertEquals(8589934592L, t.getLong());
     }
 
     try (TBool t = TBool.scalarOf(true)) {
-      assertEquals(TBool.DTYPE, t.dataType());
+      assertEquals(TBool.class, t.type());
+      assertEquals(DataType.DT_BOOL, t.dataType());
       assertEquals(0, t.shape().numDimensions());
       assertTrue(t.getBoolean());
     }
 
     try (TString t = TString.scalarOf("sombrero")) {
-      assertEquals(TString.DTYPE, t.dataType());
+      assertEquals(TString.class, t.type());
+      assertEquals(DataType.DT_STRING, t.dataType());
       assertEquals(0, t.shape().numDimensions());
       assertEquals("sombrero", t.getObject());
     }
 
     final byte[] bytes = {1, 2, 3, 4};
     try (TString t = TString.tensorOfBytes(NdArrays.scalarOfObject(bytes))) {
-      assertEquals(TString.DTYPE, t.dataType());
+      assertEquals(TString.class, t.type());
+      assertEquals(DataType.DT_STRING, t.dataType());
       assertEquals(0, t.shape().numDimensions());
       assertArrayEquals(bytes, t.asBytes().getObject());
     }
@@ -314,7 +322,8 @@ public void scalars() {
   public void nDimensional() {
     DoubleNdArray vector = StdArrays.ndCopyOf(new double[]{1.414, 2.718, 3.1415});
     try (TFloat64 t = TFloat64.tensorOf(vector)) {
-      assertEquals(TFloat64.DTYPE, t.dataType());
+      assertEquals(TFloat64.class, t.type());
+      assertEquals(DataType.DT_DOUBLE, t.dataType());
       assertEquals(1, t.shape().numDimensions());
       assertEquals(3, t.shape().size(0));
       assertEquals(vector, t);
@@ -322,7 +331,8 @@ public void nDimensional() {
 
     IntNdArray matrix = StdArrays.ndCopyOf(new int[][]{{1, 2, 3}, {4, 5, 6}});
     try (TInt32 t = TInt32.tensorOf(matrix)) {
-      assertEquals(TInt32.DTYPE, t.dataType());
+      assertEquals(TInt32.class, t.type());
+      assertEquals(DataType.DT_INT32, t.dataType());
       assertEquals(2, t.shape().numDimensions());
       assertEquals(2, t.shape().size(0));
       assertEquals(3, t.shape().size(1));
@@ -333,7 +343,8 @@ public void nDimensional() {
       {{1}, {3}, {5}, {7}, {9}}, {{2}, {4}, {6}, {8}, {0}},
     });
     try (TInt64 t = TInt64.tensorOf(threeD)) {
-      assertEquals(TInt64.DTYPE, t.dataType());
+      assertEquals(TInt64.class, t.type());
+      assertEquals(DataType.DT_INT64, t.dataType());
       assertEquals(3, t.shape().numDimensions());
       assertEquals(2, t.shape().size(0));
       assertEquals(5, t.shape().size(1));
@@ -347,7 +358,8 @@ public void nDimensional() {
       {{{false, true, false, true}, {false, true, true, false}}},
     });
     try (TBool t = TBool.tensorOf(fourD)) {
-      assertEquals(TBool.DTYPE, t.dataType());
+      assertEquals(TBool.class, t.type());
+      assertEquals(DataType.DT_BOOL, t.dataType());
       assertEquals(4, t.shape().numDimensions());
       assertEquals(3, t.shape().size(0));
       assertEquals(1, t.shape().size(1));
@@ -366,7 +378,8 @@ public void testNDimensionalStringTensor() {
       }
     }
     try (TString t = TString.tensorOf(matrix)) {
-      assertEquals(TString.DTYPE, t.dataType());
+      assertEquals(TString.class, t.type());
+      assertEquals(DataType.DT_STRING, t.dataType());
       assertEquals(2, t.shape().numDimensions());
       assertEquals(4, t.shape().size(0));
       assertEquals(3, t.shape().size(1));
@@ -376,7 +389,8 @@ public void testNDimensionalStringTensor() {
     NdArray<byte[]> byteMatrix = NdArrays.ofObjects(byte[].class, matrix.shape());
     matrix.scalars().forEachIndexed((i, s) -> byteMatrix.setObject(s.getObject().getBytes(UTF_8), i));
     try (TString t = TString.tensorOfBytes(byteMatrix)) {
-      assertEquals(TString.DTYPE, t.dataType());
+      assertEquals(TString.class, t.type());
+      assertEquals(DataType.DT_STRING, t.dataType());
       assertEquals(2, t.shape().numDimensions());
       assertEquals(4, t.shape().size(0));
       assertEquals(3, t.shape().size(1));
@@ -389,7 +403,8 @@ public void testNDimensionalStringTensor() {
   public void testUint8TensorFromArray() {
     byte[] vector = new byte[] {1, 2, 3, 4};
     try (TUint8 t = TUint8.vectorOf(vector)) {
-      assertEquals(TUint8.DTYPE, t.dataType());
+      assertEquals(TUint8.class, t.type());
+      assertEquals(DataType.DT_UINT8, t.dataType());
       assertEquals(1, t.shape().numDimensions());
       assertEquals(4, t.shape().size(0));
 
@@ -403,7 +418,8 @@ public void testUint8TensorFromArray() {
   public void testCreateFromArrayOfBoxed() {
     Integer[] vector = new Integer[] {1, 2, 3, 4};
     try (TInt32 t = TInt32.tensorOf(Shape.of(4), d -> d.write(DataBuffers.ofObjects(vector)))) {
-      assertEquals(TInt32.DTYPE, t.dataType());
+      assertEquals(TInt32.class, t.type());
+      assertEquals(DataType.DT_INT32, t.dataType());
       assertEquals(1, t.shape().numDimensions());
       assertEquals(4, t.shape().size(0));
 
@@ -445,14 +461,14 @@ public void tensorWithZeroDimension() {
 
   @Test
   public void allocateTensorWithSize() {
-    try (TInt32 t = Tensor.of(TInt32.DTYPE, Shape.of(2, 2, 2), 8 * TInt32.DTYPE.byteSize())) {
+    try (TInt32 t = Tensor.of(TInt32.class, Shape.of(2, 2, 2), 8 * 4)) {
       // ok
     }
-    try (TInt32 t = Tensor.of(TInt32.DTYPE, Shape.of(2, 2, 2), 9 * TInt32.DTYPE.byteSize())) {
+    try (TInt32 t = Tensor.of(TInt32.class, Shape.of(2, 2, 2), 9 * 4)) {
       // ok (size requested is larger that minimum space required)
     }
     try {
-      Tensor.of(TInt32.DTYPE, Shape.of(2, 2, 2), 8 * TInt32.DTYPE.byteSize() - 1);
+      Tensor.of(TInt32.class, Shape.of(2, 2, 2), 8 * 4 - 1);
       fail();
     } catch (IllegalArgumentException e) {
       // as expected
@@ -499,6 +515,7 @@ public void fromHandle() {
     final FloatNdArray matrix = StdArrays.ndCopyOf(new float[][]{{1, 2, 3}, {4, 5, 6}});
     try (TFloat32 src = TFloat32.tensorOf(matrix)) {
       TFloat32 cpy = (TFloat32)RawTensor.fromHandle(src.asRawTensor().nativeHandle()).asTypedTensor();
+      assertEquals(src.type(), cpy.type());
       assertEquals(src.dataType(), cpy.dataType());
       assertEquals(src.shape().numDimensions(), cpy.shape().numDimensions());
       assertEquals(src.shape(), cpy.shape());
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/ScopeTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/ScopeTest.java
index c97dc83f510..62881dcee8c 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/ScopeTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/ScopeTest.java
@@ -23,7 +23,6 @@
 import org.tensorflow.Graph;
 import org.tensorflow.Output;
 import org.tensorflow.Session;
-import org.tensorflow.Tensor;
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.family.TType;
 
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/GeneratedOperationsTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/GeneratedOperationsTest.java
index ede179740e5..b1ebd469eb3 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/GeneratedOperationsTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/GeneratedOperationsTest.java
@@ -22,10 +22,9 @@
 import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Session;
-import org.tensorflow.Tensor;
+import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Op;
 import org.tensorflow.op.Ops;
-import org.tensorflow.ndarray.Shape;
 import org.tensorflow.types.TInt32;
 
 public final class GeneratedOperationsTest {
@@ -70,7 +69,7 @@ public void testControlDependencies() {
     try (Graph g = new Graph();
         Session sess = new Session(g)) {
       Ops ops = Ops.create(g);
-      Operand<TInt32> variable = ops.variable(Shape.scalar(), TInt32.DTYPE);
+      Operand<TInt32> variable = ops.variable(Shape.scalar(), TInt32.class);
       Operand<?> initVariable = ops.assign(variable, ops.constant(0));
       ArrayList<Op> controls = new ArrayList<>();
       controls.add(ops.assign(variable, ops.constant(3)));
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/GradientsTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/GradientsTest.java
index 6bab99095e4..80150b64bb6 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/GradientsTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/GradientsTest.java
@@ -37,7 +37,7 @@ public void createGradients() {
         Session sess = new Session(g)) {
       Ops tf = Ops.create(g);
 
-      Output<TFloat32> x = tf.placeholder(TFloat32.DTYPE).output();
+      Output<TFloat32> x = tf.placeholder(TFloat32.class).output();
       Output<TFloat32> y0 = tf.math.square(x).y();
       Output<TFloat32> y1 = tf.math.square(y0).y();
 
@@ -64,7 +64,7 @@ public void createGradientsWithSum() {
         Session sess = new Session(g)) {
       Ops tf = Ops.create(g);
 
-      Output<TFloat32> x = tf.placeholder(TFloat32.DTYPE).output();
+      Output<TFloat32> x = tf.placeholder(TFloat32.class).output();
       Output<TFloat32> y0 = tf.math.square(x).y();
       Output<TFloat32> y1 = tf.math.square(y0).y();
 
@@ -89,7 +89,7 @@ public void createGradientsWithInitialValues() {
         Session sess = new Session(g)) {
       Ops tf = Ops.create(g);
 
-      Output<TFloat32> x = tf.placeholder(TFloat32.DTYPE).output();
+      Output<TFloat32> x = tf.placeholder(TFloat32.class).output();
       Output<TFloat32> y0 = tf.math.square(x).y();
       Output<TFloat32> y1 = tf.math.square(y0).y();
 
@@ -115,7 +115,7 @@ public void validateGradientsNames() {
     try (Graph g = new Graph()) {
       Ops tf = Ops.create(g).withSubScope("sub");
 
-      Output<TFloat32> x = tf.placeholder(TFloat32.DTYPE).output();
+      Output<TFloat32> x = tf.placeholder(TFloat32.class).output();
       Output<TFloat32> y = tf.math.square(x).y();
 
       Gradients grad0 = Gradients.create(tf.scope(), y, Arrays.asList(x));
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/ShapesTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/ShapesTest.java
index 083beca923c..39c04c942af 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/ShapesTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/ShapesTest.java
@@ -14,18 +14,14 @@
 ==============================================================================*/
 package org.tensorflow.op.core;
 
-import java.util.concurrent.atomic.AtomicInteger;
-
 import static org.junit.jupiter.api.Assertions.assertEquals;
 
+import java.util.concurrent.atomic.AtomicInteger;
 import org.junit.jupiter.api.Test;
-
-import org.junit.jupiter.api.TestTemplate;
-import org.tensorflow.Graph;
 import org.tensorflow.EagerSession;
+import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Session;
-import org.tensorflow.Tensor;
 import org.tensorflow.op.Scope;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TInt32;
@@ -40,11 +36,11 @@ public void testFlatten_Operand() {
         Session session = new Session(g)) {
       Scope scope = new Scope(g);
       Operand<TFloat32> operand = Constant.arrayOf(scope, new float[] {1, 2, 3, 4, 5, 6, 7, 8});
-      Shape<TInt64> expResult = Shape.create(scope, operand, TInt64.DTYPE);
+      Shape<TInt64> expResult = Shape.create(scope, operand, TInt64.class);
       Operand<TFloat32> reshaped =
           Reshape.create(scope, operand, Constant.vectorOf(scope, new long[] {4, 2, 1}));
       Operand<TFloat32> actual = Shapes.flatten(scope, reshaped);
-      Shape<TInt64> tfshape = Shape.create(scope, actual, TInt64.DTYPE);
+      Shape<TInt64> tfshape = Shape.create(scope, actual, TInt64.class);
 
       AtomicInteger index = new AtomicInteger();
       try (TInt64 result1 = (TInt64)session.runner().fetch(tfshape.asOutput()).run().get(0);
@@ -63,11 +59,11 @@ public void testFlatten_Shape() {
     try (EagerSession session = EagerSession.create()) {
       Scope scope = new Scope(session);
       Operand<TFloat32> operand = Constant.arrayOf(scope, new float[] {1, 2, 3, 4, 5, 6, 7, 8});
-      Shape<TInt64> expShape = Shape.create(scope, operand, TInt64.DTYPE);
+      Shape<TInt64> expShape = Shape.create(scope, operand, TInt64.class);
       Operand<TFloat32> actual =
           Reshape.create(scope, operand, Constant.vectorOf(scope, new long[] {4, 2, 1}));
-      Shape<TInt64> tfshape = Shape.create(scope, actual, TInt64.DTYPE);
-      Operand<TInt64> flattened = Shapes.flatten(scope, tfshape, TInt64.DTYPE);
+      Shape<TInt64> tfshape = Shape.create(scope, actual, TInt64.class);
+      Operand<TInt64> flattened = Shapes.flatten(scope, tfshape, TInt64.class);
 
       AtomicInteger index = new AtomicInteger();
       flattened
@@ -89,8 +85,8 @@ public void testSize_Shape() {
       Operand<TFloat32> operand = Constant.arrayOf(scope, new float[] {1, 2, 3, 4, 5, 6, 7, 8});
       Operand<TFloat32> actual =
           Reshape.create(scope, operand, Constant.vectorOf(scope, new long[] {4, 2, 1}));
-      Shape<TInt64> tfshape = Shape.create(scope, actual, TInt64.DTYPE);
-      Operand<TInt64> size = Shapes.size(scope, tfshape, TInt64.DTYPE);
+      Shape<TInt64> tfshape = Shape.create(scope, actual, TInt64.class);
+      Operand<TInt64> size = Shapes.size(scope, tfshape, TInt64.class);
 
       AtomicInteger index = new AtomicInteger();
       try (TInt64 result1 = (TInt64)session.runner().fetch(size.asOutput()).run().get(0)) {
@@ -405,7 +401,7 @@ public void testPrependLong() {
       Scope scope = new Scope(g);
       Operand<TFloat32> operand = Constant.arrayOf(scope, new float[] {1, 2, 3, 4, 5, 6, 7, 8});
       Operand<TFloat32> actual = Reshape.create(scope, operand, Constant.vectorOf(scope, new long[] {4, 2}));
-      Shape<TInt64> tfshape = Shape.create(scope, actual, TInt64.DTYPE);
+      Shape<TInt64> tfshape = Shape.create(scope, actual, TInt64.class);
 
       Operand<TInt64> prepend = Shapes.prepend(scope, tfshape, 1L);
       AtomicInteger index = new AtomicInteger();
@@ -462,8 +458,8 @@ public void testPrependShapeTInt64() {
       Operand<TFloat32> operand2 = Constant.arrayOf(scope, new float[] {1, 2, 3, 4, 5, 6, 7, 8});
       Operand<TFloat32> actual2 =
           Reshape.create(scope, operand2, Constant.vectorOf(scope, new long[] {2, 4}));
-      Shape<TInt64> tfshape1 = Shape.create(scope, actual1, TInt64.DTYPE);
-      Shape<TInt64> tfshape2 = Shape.create(scope, actual2, TInt64.DTYPE);
+      Shape<TInt64> tfshape1 = Shape.create(scope, actual1, TInt64.class);
+      Shape<TInt64> tfshape2 = Shape.create(scope, actual2, TInt64.class);
 
       Operand<TInt64> prepend = Shapes.prepend(scope, tfshape1, tfshape2);
       AtomicInteger index = new AtomicInteger();
@@ -487,7 +483,7 @@ public void testAppendLong() {
       Scope scope = new Scope(g);
       Operand<TFloat32> operand = Constant.arrayOf(scope, new float[] {1, 2, 3, 4, 5, 6, 7, 8});
       Operand<TFloat32> actual = Reshape.create(scope, operand, Constant.vectorOf(scope, new long[] {4, 2}));
-      Shape<TInt64> tfshape = Shape.create(scope, actual, TInt64.DTYPE);
+      Shape<TInt64> tfshape = Shape.create(scope, actual, TInt64.class);
 
       Operand<TInt64> append = Shapes.append(scope, tfshape, 2L);
       AtomicInteger index = new AtomicInteger();
@@ -568,8 +564,8 @@ public void testAppendShapeTInt64() {
       Operand<TFloat32> operand2 = Constant.arrayOf(scope, new float[] {1, 2, 3, 4, 5, 6, 7, 8});
       Operand<TFloat32> actual2 =
           Reshape.create(scope, operand2, Constant.vectorOf(scope, new long[] {2, 4}));
-      Shape<TInt64> tfshape1 = Shape.create(scope, actual1, TInt64.DTYPE);
-      Shape<TInt64> tfshape2 = Shape.create(scope, actual2, TInt64.DTYPE);
+      Shape<TInt64> tfshape1 = Shape.create(scope, actual1, TInt64.class);
+      Shape<TInt64> tfshape2 = Shape.create(scope, actual2, TInt64.class);
 
       Operand<TInt64> append = Shapes.append(scope, tfshape1, tfshape2);
       AtomicInteger index = new AtomicInteger();
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/ZerosTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/ZerosTest.java
index 204bd4b10f3..4121baf3af1 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/ZerosTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/ZerosTest.java
@@ -23,7 +23,6 @@
 import org.junit.jupiter.api.Test;
 import org.tensorflow.Graph;
 import org.tensorflow.Session;
-import org.tensorflow.Tensor;
 import org.tensorflow.op.Scope;
 import org.tensorflow.types.TBool;
 import org.tensorflow.types.TFloat32;
@@ -41,7 +40,7 @@ public void createIntZeros() {
         Session sess = new Session(g)) {
       Scope scope = new Scope(g);
       long[] shape = {2, 2};
-      Zeros<TInt32> op = Zeros.create(scope, Constant.vectorOf(scope, shape), TInt32.DTYPE);
+      Zeros<TInt32> op = Zeros.create(scope, Constant.vectorOf(scope, shape), TInt32.class);
       try (TInt32 result = (TInt32)sess.runner().fetch(op).run().get(0)) {
         result.scalars().forEach(s -> assertEquals(0, s.getInt()));
       }
@@ -54,7 +53,7 @@ public void createFloatZeros() {
         Session sess = new Session(g)) {
       Scope scope = new Scope(g);
       long[] shape = {2, 2};
-      Zeros<TFloat32> op = Zeros.create(scope, Constant.vectorOf(scope, shape), TFloat32.DTYPE);
+      Zeros<TFloat32> op = Zeros.create(scope, Constant.vectorOf(scope, shape), TFloat32.class);
       try (TFloat32 result = (TFloat32)sess.runner().fetch(op.asOutput()).run().get(0)) {
         result.scalars().forEach(s -> assertEquals(0.0f, s.getFloat(), 0));
       }
@@ -67,7 +66,7 @@ public void createDoubleZeros() {
         Session sess = new Session(g)) {
       Scope scope = new Scope(g);
       long[] shape = {2, 2};
-      Zeros<TFloat64> op = Zeros.create(scope, Constant.vectorOf(scope, shape), TFloat64.DTYPE);
+      Zeros<TFloat64> op = Zeros.create(scope, Constant.vectorOf(scope, shape), TFloat64.class);
       try (TFloat64 result = (TFloat64)sess.runner().fetch(op.asOutput()).run().get(0)) {
         result.scalars().forEach(s -> assertEquals(0.0f, s.getDouble(), 0));
       }
@@ -80,7 +79,7 @@ public void createLongZeros() {
         Session sess = new Session(g)) {
       Scope scope = new Scope(g);
       long[] shape = {2, 2};
-      Zeros<TInt64> op = Zeros.create(scope, Constant.vectorOf(scope, shape), TInt64.DTYPE);
+      Zeros<TInt64> op = Zeros.create(scope, Constant.vectorOf(scope, shape), TInt64.class);
       try (TInt64 result = (TInt64)sess.runner().fetch(op.asOutput()).run().get(0)) {
         result.scalars().forEach(s -> assertEquals(0L, s.getLong()));
       }
@@ -93,7 +92,7 @@ public void createBooleanZeros() {
         Session sess = new Session(g)) {
       Scope scope = new Scope(g);
       long[] shape = {2, 2};
-      Zeros<TBool> op = Zeros.create(scope, Constant.vectorOf(scope, shape), TBool.DTYPE);
+      Zeros<TBool> op = Zeros.create(scope, Constant.vectorOf(scope, shape), TBool.class);
       try (TBool result = (TBool)sess.runner().fetch(op.asOutput()).run().get(0)) {
         result.scalars().forEach(s -> assertFalse(s.getBoolean()));
       }
@@ -106,7 +105,7 @@ public void createUint8Zeros() {
         Session sess = new Session(g)) {
       Scope scope = new Scope(g);
       long[] shape = {2, 2};
-      Zeros<TUint8> op = Zeros.create(scope, Constant.vectorOf(scope, shape), TUint8.DTYPE);
+      Zeros<TUint8> op = Zeros.create(scope, Constant.vectorOf(scope, shape), TUint8.class);
       try (TUint8 result = (TUint8)sess.runner().fetch(op.asOutput()).run().get(0)) {
         result.scalars().forEach(s -> assertEquals(0, s.getByte()));
       }
@@ -119,7 +118,7 @@ public void createStringZeros() {
         Session sess = new Session(g)) {
       Scope scope = new Scope(g);
       long[] shape = {2, 2};
-      Zeros<TString> op = Zeros.create(scope, Constant.vectorOf(scope, shape), TString.DTYPE);
+      Zeros<TString> op = Zeros.create(scope, Constant.vectorOf(scope, shape), TString.class);
       try (TString result = (TString)sess.runner().fetch(op.asOutput()).run().get(0)) {
         result.scalars().forEach(s -> assertTrue(s.getObject().isEmpty()));
       }
@@ -132,7 +131,7 @@ public void operationsComposingZerosAreCorrectlyNamed() {
         Session sess = new Session(g)) {
       Scope scope = new Scope(g);
       long[] shape = {2, 2};
-      Zeros<TFloat32> zeros = Zeros.create(scope.withSubScope("test"), Constant.vectorOf(scope, shape), TFloat32.DTYPE);
+      Zeros<TFloat32> zeros = Zeros.create(scope.withSubScope("test"), Constant.vectorOf(scope, shape), TFloat32.class);
       List<?> results = sess.runner().addTarget("test/Zeros/Zero").addTarget("test/Zeros/Fill").run();
     }
   }
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/types/TInt32Test.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/types/TInt32Test.java
index 9ea7f952f04..a2ab28b6219 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/types/TInt32Test.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/types/TInt32Test.java
@@ -17,8 +17,6 @@
 
 package org.tensorflow.types;
 
-import static org.junit.jupiter.api.Assertions.assertEquals;
-
 import org.tensorflow.ndarray.NdArray;
 import org.tensorflow.ndarray.NdArrays;
 import org.tensorflow.ndarray.Shape;
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/activations/ELU.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/activations/ELU.java
index ae3d7e8c896..2f2f16f2752 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/activations/ELU.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/activations/ELU.java
@@ -14,7 +14,6 @@
 =======================================================================*/
 package org.tensorflow.framework.activations;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TBool;
@@ -89,9 +88,9 @@ public Operand<T> call(Operand<T> input) {
     Operand<T> result = tf.nn.elu(input);
     if (alpha == 1.0) return result;
     else {
-      DataType<T> dataType = input.asOutput().dataType();
-      Operand<T> y = tf.math.mul(result, tf.dtypes.cast(tf.constant(alpha), dataType));
-      Operand<TBool> cond = tf.math.greater(result, tf.dtypes.cast(tf.constant(0), dataType));
+      Class<T> inputType = input.type();
+      Operand<T> y = tf.math.mul(result, tf.dtypes.cast(tf.constant(alpha), inputType));
+      Operand<TBool> cond = tf.math.greater(result, tf.dtypes.cast(tf.constant(0), inputType));
       return tf.select(cond, result, y);
     }
   }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/activations/HardSigmoid.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/activations/HardSigmoid.java
index a486cbdc601..0b7cf573b8e 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/activations/HardSigmoid.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/activations/HardSigmoid.java
@@ -14,7 +14,6 @@
 =======================================================================*/
 package org.tensorflow.framework.activations;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.family.TFloating;
@@ -63,12 +62,12 @@ public HardSigmoid(Ops tf) {
    */
   @Override
   public Operand<T> call(Operand<T> input) {
-    DataType<T> dataType = input.asOutput().dataType();
-    Operand<T> point2 = tf.dtypes.cast(tf.constant(0.2), dataType);
-    Operand<T> point5 = tf.dtypes.cast(tf.constant(0.5), dataType);
+    Class<T> inputType = input.type();
+    Operand<T> point2 = tf.dtypes.cast(tf.constant(0.2), inputType);
+    Operand<T> point5 = tf.dtypes.cast(tf.constant(0.5), inputType);
 
     Operand<T> x = tf.math.add(tf.math.mul(input, point2), point5);
     return tf.clipByValue(
-        x, tf.dtypes.cast(tf.constant(0), dataType), tf.dtypes.cast(tf.constant(1), dataType));
+        x, tf.dtypes.cast(tf.constant(0), inputType), tf.dtypes.cast(tf.constant(1), inputType));
   }
 }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/activations/ReLU.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/activations/ReLU.java
index c24cf71077d..aef6ebf2992 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/activations/ReLU.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/activations/ReLU.java
@@ -14,7 +14,6 @@
 =======================================================================*/
 package org.tensorflow.framework.activations;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.Ops;
 import org.tensorflow.op.math.Greater;
@@ -98,8 +97,7 @@ public ReLU(Ops tf, float alpha, float maxValue, float threshold) {
   /** {@inheritDoc} */
   @Override
   public Operand<T> call(Operand<T> input) {
-
-    DataType<T> dataType = input.asOutput().dataType();
+    Class<T> inputType = input.type();
 
     boolean clipMax = !Float.isNaN(maxValue);
     Operand<T> negativePart = null;
@@ -110,7 +108,7 @@ public Operand<T> call(Operand<T> input) {
       if (threshold != 0) {
         negativePart =
             tf.nn.relu(
-                tf.math.add(tf.math.neg(input), tf.dtypes.cast(tf.constant(threshold), dataType)));
+                tf.math.add(tf.math.neg(input), tf.dtypes.cast(tf.constant(threshold), inputType)));
       } else {
         negativePart = tf.nn.relu(tf.math.neg(input));
       }
@@ -119,8 +117,8 @@ public Operand<T> call(Operand<T> input) {
     Operand<T> lInput;
     if (threshold != 0) {
       // computes input for input > threshold else 0
-      Greater greater = tf.math.greater(input, tf.dtypes.cast(tf.constant(threshold), dataType));
-      lInput = tf.math.mul(input, tf.dtypes.cast(greater, dataType));
+      Greater greater = tf.math.greater(input, tf.dtypes.cast(tf.constant(threshold), inputType));
+      lInput = tf.math.mul(input, tf.dtypes.cast(greater, inputType));
     } else if (maxValue == 6) {
       // if no threshold, then can use nn.relu6 native TF op for performance
       lInput = tf.nn.relu6(input);
@@ -129,15 +127,15 @@ public Operand<T> call(Operand<T> input) {
       lInput = tf.nn.relu(input);
     }
     if (clipMax) {
-      Operand<T> lmaxValue = tf.dtypes.cast(tf.constant(maxValue), dataType);
-      Operand<T> zero = tf.dtypes.cast(tf.constant(0), dataType);
+      Operand<T> lmaxValue = tf.dtypes.cast(tf.constant(maxValue), inputType);
+      Operand<T> zero = tf.dtypes.cast(tf.constant(0), inputType);
       lInput = tf.clipByValue(lInput, zero, lmaxValue);
     }
 
     if (alpha != 0.) {
       lInput =
           tf.math.sub(
-              lInput, tf.math.mul(tf.dtypes.cast(tf.constant(alpha), dataType), negativePart));
+              lInput, tf.math.mul(tf.dtypes.cast(tf.constant(alpha), inputType), negativePart));
     }
     return lInput;
   }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/Dataset.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/Dataset.java
index 007bcb01a40..7ac73f616e2 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/Dataset.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/Dataset.java
@@ -15,7 +15,6 @@
  */
 package org.tensorflow.framework.data;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.framework.data.impl.BatchDataset;
 import org.tensorflow.framework.data.impl.MapDataset;
@@ -33,6 +32,7 @@
 import java.util.Iterator;
 import java.util.List;
 import java.util.function.Function;
+import org.tensorflow.types.family.TType;
 
 /**
  * Represents a potentially large list of independent elements (samples), and allows iteration and
@@ -41,11 +41,11 @@
 public abstract class Dataset implements Iterable<List<Operand<?>>> {
   protected Ops tf;
   private Operand<?> variant;
-  private List<DataType<?>> outputTypes;
+  private List<Class<? extends TType>> outputTypes;
   private List<Shape> outputShapes;
 
   public Dataset(
-      Ops tf, Operand<?> variant, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+      Ops tf, Operand<?> variant, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     if (tf == null) {
       throw new IllegalArgumentException("Ops accessor cannot be null.");
     }
@@ -261,12 +261,12 @@ public DatasetIterator makeOneShotIterator() {
    * @param tf Ops Accessor
    * @param tensors A list of {@code Operand<?>} representing components of this dataset (e.g.
    *     features, labels)
-   * @param outputTypes A list of `DataType` objects representing the data type of each component of
+   * @param outputTypes A list of tensor type classes representing the data type of each component of
    *     this dataset.
    * @return A new `Dataset`
    */
   public static Dataset fromTensorSlices(
-      Ops tf, List<Operand<?>> tensors, List<DataType<?>> outputTypes) {
+      Ops tf, List<Operand<?>> tensors, List<Class<? extends TType>> outputTypes) {
     return new TensorSliceDataset(tf, tensors, outputTypes);
   }
 
@@ -288,7 +288,7 @@ public Operand<?> getVariant() {
   }
 
   /** Get a list of output types for each component of this dataset. */
-  public List<DataType<?>> getOutputTypes() {
+  public List<Class<? extends TType>> getOutputTypes() {
     return this.outputTypes;
   }
 
@@ -305,7 +305,7 @@ public Ops getOpsInstance() {
   public String toString() {
     return "Dataset{"
         + "outputTypes="
-        + Arrays.toString(getOutputTypes().stream().map(DataType::name).toArray())
+        + Arrays.toString(getOutputTypes().stream().map(Class::getSimpleName).toArray())
         + ", outputShapes="
         + Arrays.toString(getOutputShapes().stream().map(Shape::toString).toArray())
         + "}";
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/DatasetIterator.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/DatasetIterator.java
index 0bad6a41214..a3aa290a8c8 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/DatasetIterator.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/DatasetIterator.java
@@ -15,7 +15,6 @@
  */
 package org.tensorflow.framework.data;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.op.Op;
@@ -25,6 +24,7 @@
 import java.util.ArrayList;
 import java.util.Iterator;
 import java.util.List;
+import org.tensorflow.types.family.TType;
 
 /**
  * Represents the state of an iteration through a tf.data Datset. DatasetIterator is not a
@@ -106,7 +106,7 @@ public class DatasetIterator implements Iterable<List<Operand<?>>> {
   private Operand<?> iteratorResource;
   private Op initializer;
 
-  protected List<DataType<?>> outputTypes;
+  protected List<Class<? extends TType>> outputTypes;
   protected List<Shape> outputShapes;
 
   /**
@@ -115,7 +115,7 @@ public class DatasetIterator implements Iterable<List<Operand<?>>> {
    * @param iteratorResource An Operand representing the iterator (e.g. constructed from
    *     `tf.data.iterator` or `tf.data.anonymousIterator`)
    * @param initializer An `Op` that should be run to initialize this iterator
-   * @param outputTypes A list of `DataType` objects corresponding to the types of each component of
+   * @param outputTypes A list of classes corresponding to the tensor type of each component of
    *     a dataset element.
    * @param outputShapes A list of `Shape` objects corresponding to the shapes of each component of
    *     a dataset element.
@@ -124,7 +124,7 @@ public DatasetIterator(
       Ops tf,
       Operand<?> iteratorResource,
       Op initializer,
-      List<DataType<?>> outputTypes,
+      List<Class<? extends TType>> outputTypes,
       List<Shape> outputShapes) {
 
     this.tf = tf;
@@ -137,7 +137,7 @@ public DatasetIterator(
   public DatasetIterator(
       Ops tf,
       Operand<?> iteratorResource,
-      List<DataType<?>> outputTypes,
+      List<Class<? extends TType>> outputTypes,
       List<Shape> outputShapes) {
     this.tf = tf;
     this.iteratorResource = iteratorResource;
@@ -229,14 +229,14 @@ public Op makeInitializer(Dataset dataset) {
    * Creates a new iterator from a "structure" defined by `outputShapes` and `outputTypes`.
    *
    * @param tf Ops accessor
-   * @param outputTypes A list of `DataType` objects repesenting the types of each component of a
+   * @param outputTypes A list of classes repesenting the tensor type of each component of a
    *     dataset element.
    * @param outputShapes A list of Shape objects representing the shape of each component of a
    *     dataset element.
    * @return A new DatasetIterator
    */
   public static DatasetIterator fromStructure(
-      Ops tf, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+      Ops tf, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     Operand<?> iteratorResource =
         tf.scope().env() instanceof Graph
             ? tf.data.iterator(EMPTY_SHARED_NAME, "", outputTypes, outputShapes)
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/DatasetOptional.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/DatasetOptional.java
index 925252c7298..6617c33eaf7 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/DatasetOptional.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/DatasetOptional.java
@@ -15,7 +15,6 @@
  */
 package org.tensorflow.framework.data;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.Ops;
 import org.tensorflow.ndarray.Shape;
@@ -23,6 +22,7 @@
 
 import java.util.ArrayList;
 import java.util.List;
+import org.tensorflow.types.family.TType;
 
 /**
  * An optional represents the result of a dataset getNext operation that may fail, when the end of
@@ -36,11 +36,11 @@ public Operand<?> getOptionalVariant() {
   }
 
   private Operand<?> optionalVariant;
-  private List<DataType<?>> outputTypes;
+  private List<Class<? extends TType>> outputTypes;
   private List<Shape> outputShapes;
 
   public DatasetOptional(
-      Ops tf, Operand<?> optionalVariant, List<DataType<?>> outputTypes, List<Shape> outputShapes) {
+      Ops tf, Operand<?> optionalVariant, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) {
     this.tf = tf;
     this.optionalVariant = optionalVariant;
     this.outputTypes = outputTypes;
@@ -75,7 +75,7 @@ public List<Operand<?>> getValue() {
   public static DatasetOptional fromComponents(
       Ops tf,
       List<Operand<?>> components,
-      List<DataType<?>> outputTypes,
+      List<Class<? extends TType>> outputTypes,
       List<Shape> outputShapes) {
     Operand<?> optionalVariant = tf.data.optionalFromValue(components);
     return new DatasetOptional(tf, optionalVariant, outputTypes, outputShapes);
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/BatchDataset.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/BatchDataset.java
index 277b049cf6f..f0561b2e61e 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/BatchDataset.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/BatchDataset.java
@@ -15,7 +15,6 @@
  */
 package org.tensorflow.framework.data.impl;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.framework.data.Dataset;
 import org.tensorflow.op.Ops;
@@ -25,6 +24,7 @@
 import org.tensorflow.types.TInt64;
 
 import java.util.List;
+import org.tensorflow.types.family.TType;
 
 public class BatchDataset extends Dataset {
   public BatchDataset(
@@ -32,7 +32,7 @@ public BatchDataset(
       Operand<?> variant,
       Constant<TInt64> batchSize,
       Constant<TBool> dropRemainder,
-      List<DataType<?>> outputTypes,
+      List<Class<? extends TType>> outputTypes,
       List<Shape> outputShapes) {
     super(
         tf,
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/SkipDataset.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/SkipDataset.java
index 6731bac60b3..63b4208480b 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/SkipDataset.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/SkipDataset.java
@@ -15,7 +15,6 @@
  */
 package org.tensorflow.framework.data.impl;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.framework.data.Dataset;
 import org.tensorflow.op.Ops;
@@ -24,6 +23,7 @@
 import org.tensorflow.types.TInt64;
 
 import java.util.List;
+import org.tensorflow.types.family.TType;
 
 public class SkipDataset extends Dataset {
 
@@ -31,7 +31,7 @@ public SkipDataset(
       Ops tf,
       Operand<?> variant,
       Constant<TInt64> count,
-      List<DataType<?>> outputTypes,
+      List<Class<? extends TType>> outputTypes,
       List<Shape> outputShapes) {
     super(
         tf,
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TFRecordDataset.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TFRecordDataset.java
index ed721b13ebf..00297152e90 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TFRecordDataset.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TFRecordDataset.java
@@ -34,7 +34,7 @@ public TFRecordDataset(
     super(
         tf,
         tf.data.tfRecordDataset(filenames, compressionType, bufferSize),
-        Collections.singletonList(TString.DTYPE),
+        Collections.singletonList(TString.class),
         Collections.singletonList(Shape.scalar()));
   }
 }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TakeDataset.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TakeDataset.java
index 08c57d44a73..39ca9759e74 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TakeDataset.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TakeDataset.java
@@ -15,7 +15,6 @@
  */
 package org.tensorflow.framework.data.impl;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.framework.data.Dataset;
 import org.tensorflow.op.Ops;
@@ -24,6 +23,7 @@
 import org.tensorflow.types.TInt64;
 
 import java.util.List;
+import org.tensorflow.types.family.TType;
 
 public class TakeDataset extends Dataset {
 
@@ -31,7 +31,7 @@ public TakeDataset(
       Ops tf,
       Operand<?> variant,
       Constant<TInt64> count,
-      List<DataType<?>> outputTypes,
+      List<Class<? extends TType>> outputTypes,
       List<Shape> outputShapes) {
     super(
         tf,
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TensorSliceDataset.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TensorSliceDataset.java
index 495014f1753..46639ea2aad 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TensorSliceDataset.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TensorSliceDataset.java
@@ -15,7 +15,6 @@
  */
 package org.tensorflow.framework.data.impl;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.framework.data.Dataset;
 import org.tensorflow.op.Ops;
@@ -23,10 +22,11 @@
 
 import java.util.List;
 import java.util.stream.Collectors;
+import org.tensorflow.types.family.TType;
 
 public class TensorSliceDataset extends Dataset {
 
-  public TensorSliceDataset(Ops tf, List<Operand<?>> components, List<DataType<?>> outputTypes) {
+  public TensorSliceDataset(Ops tf, List<Operand<?>> components, List<Class<? extends TType>> outputTypes) {
     super(tf, makeVariant(tf, components, outputTypes), outputTypes, outputShapes(components));
   }
 
@@ -35,7 +35,7 @@ private static List<Shape> outputShapes(List<Operand<?>> components) {
   }
 
   private static Operand<?> makeVariant(
-      Ops tf, List<Operand<?>> components, List<DataType<?>> outputTypes) {
+      Ops tf, List<Operand<?>> components, List<Class<? extends TType>> outputTypes) {
     if (!(components.size() == outputTypes.size())) {
       throw new IllegalArgumentException(
           "Lists `tensors` and `dtypes` must have the same number of elements.");
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TextLineDataset.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TextLineDataset.java
index 4ef47825211..c9a26304778 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TextLineDataset.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/data/impl/TextLineDataset.java
@@ -34,7 +34,7 @@ public TextLineDataset(
     super(
         tf,
         tf.data.textLineDataset(filenames, compressionType, bufferSize),
-        Collections.singletonList(TString.DTYPE),
+        Collections.singletonList(TString.class),
         Collections.singletonList(Shape.scalar()));
   }
 }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Constant.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Constant.java
index b4544de9bd0..4a2df86d74b 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Constant.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Constant.java
@@ -14,10 +14,11 @@
 =======================================================================*/
 package org.tensorflow.framework.initializers;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.Ops;
+import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
+import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -29,7 +30,7 @@
  *      Constant&lt;TFloat32&gt; initializer =
  *              new org.tensorflow.framework.initializers.Constant&lt;&gt;(tf, 3f);
  *      Operand&lt;TFloat32&gt; values =
- *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * @param <T> The Type for the call operation
@@ -85,17 +86,17 @@ public Constant(Ops tf, boolean value) {
 
   /** {@inheritDoc} */
   @Override
-  public Operand<T> call(Operand<TInt64> dims, DataType<T> dtype) {
-    if (!(dtype.isNumeric() || dtype.isBoolean())) {
-      throw new IllegalArgumentException("DataType must be numeric or boolean: " + dtype.name());
+  public Operand<T> call(Operand<TInt64> dims, Class<T> type) {
+    if (!TNumber.class.isAssignableFrom(type) && type != TBool.class) {
+      throw new IllegalArgumentException("Tensor type must be numeric or boolean: " + type.getSimpleName());
     }
     switch (valueType) {
       case LONG:
-        return tf.fill(dims, tf.dtypes.cast(tf.constant(longValue), dtype));
+        return tf.fill(dims, tf.dtypes.cast(tf.constant(longValue), type));
       case DOUBLE:
-        return tf.fill(dims, tf.dtypes.cast(tf.constant(doubleValue), dtype));
+        return tf.fill(dims, tf.dtypes.cast(tf.constant(doubleValue), type));
       default:
-        return tf.fill(dims, tf.dtypes.cast(tf.constant(booleanValue), dtype));
+        return tf.fill(dims, tf.dtypes.cast(tf.constant(booleanValue), type));
     }
   }
 
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Glorot.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Glorot.java
index 3d5d37b91d3..290e4e80b57 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Glorot.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Glorot.java
@@ -16,8 +16,7 @@
 package org.tensorflow.framework.initializers;
 
 import org.tensorflow.op.Ops;
-import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
+import org.tensorflow.types.family.TFloating;
 
 /**
  * The Glorot initializer, also called Xavier initializer.
@@ -44,7 +43,7 @@
  *             new org.tensorflow.framework.initializers.Glorot&lt;&gt;(tf,
  *             Distribution.TRUNCATED_NORMAL, seed);
  *     Operand&lt;TFloat32&gt; values =
- *             initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *             initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * <p>Glorot Uniform:
@@ -55,7 +54,7 @@
  *             new org.tensorflow.framework.initializers.Glorot&lt;&gt;(tf,
  *             Distribution.UNIFORM, seed);
  *     Operand&lt;TFloat32&gt; values =
- *             initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *             initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * <p><b>NOTE:</b>
@@ -66,11 +65,10 @@
  * <p></p>
  *
  * @param <T> The TType for the call operation
- * @param <U> The TNumber for the call operation
  * @see VarianceScaling.Distribution
  * @see <a href="http://proceedings.mlr.press/v9/glorot10a.html">Glorot et al., 2010</a>
  */
-public class Glorot<T extends TType, U extends TNumber> extends VarianceScaling<T, U> {
+public class Glorot<T extends TFloating> extends VarianceScaling<T> {
 
   public static final double SCALE = 1.0;
 
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/He.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/He.java
index ce99da80bf7..9b1a0887af0 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/He.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/He.java
@@ -15,8 +15,7 @@
 package org.tensorflow.framework.initializers;
 
 import org.tensorflow.op.Ops;
-import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
+import org.tensorflow.types.family.TFloating;
 
 /**
  * He initializer.
@@ -39,7 +38,7 @@
  *             new org.tensorflow.framework.initializers.He&lt;&gt;(tf,
  *             Distribution.TRUNCATED_NORMAL, seed););
  *     Operand&lt;TFloat32&gt; values =
- *             initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *             initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * <p>He Uniform:
@@ -50,7 +49,7 @@
  *             new org.tensorflow.framework.initializers.He&lt;&gt;(tf,
  *             Distribution.UNIFORM, seed););
  *     Operand&lt;TFloat32&gt; values =
- *             initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *             initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * <p><b>NOTE:</b>
@@ -61,12 +60,11 @@
  * <p></p>
  *
  * @param <T> The TType for the call operation
- * @param <U> The TNumber for the call operation
  * @see <a
  *     href="https://www.cv-foundation.org/openaccess/content_iccv_2015/html/He_Delving_Deep_into_ICCV_2015_paper.html">He
  *     et al., 2015</a>
  */
-public class He<T extends TType, U extends TNumber> extends VarianceScaling<T, U> {
+public class He<T extends TFloating> extends VarianceScaling<T> {
 
   public static final double SCALE = 2.0;
 
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Identity.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Identity.java
index 34e6cd790f4..f672c9f1e85 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Identity.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Identity.java
@@ -14,13 +14,12 @@
 =======================================================================*/
 package org.tensorflow.framework.initializers;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.framework.utils.ShapeUtils;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TInt64;
-import org.tensorflow.types.family.TType;
+import org.tensorflow.types.family.TFloating;
 
 /**
  * Initializer that generates the identity matrix.
@@ -33,12 +32,12 @@
  *     Identity&lt;TFloat32&gt; initializer =
  *             new org.tensorflow.framework.initializers.Identity&lt;&gt;(tf);
  *     Operand&lt;TFloat32&gt; values =
- *             initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *             initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * @param <T> The TType for the call operation
  */
-public class Identity<T extends TType> extends BaseInitializer<T> {
+public class Identity<T extends TFloating> extends BaseInitializer<T> {
   public static final double GAIN_DEFAULT = 1.0;
 
   private final double gain;
@@ -66,10 +65,7 @@ public Identity(Ops tf, double gain) {
 
   /** {@inheritDoc} */
   @Override
-  public Operand<T> call(Operand<TInt64> dims, DataType<T> dtype) {
-    if (!dtype.isFloating()) {
-      throw new IllegalArgumentException("DataType must be a float type: " + dtype.name());
-    }
+  public Operand<T> call(Operand<TInt64> dims, Class<T> type) {
     Shape shape = ShapeUtils.toShape(tf.scope(), dims);
     if (shape.numDimensions() != 2) {
       throw new IllegalArgumentException("2D matrix required, got " + shape.numDimensions());
@@ -79,9 +75,9 @@ public Operand<T> call(Operand<TInt64> dims, DataType<T> dtype) {
     Shape diagShape = Shape.of(diagSize);
 
     Operand<T> op;
-    Operand<T> zero = tf.dtypes.cast(tf.constant(0), dtype);
+    Operand<T> zero = tf.dtypes.cast(tf.constant(0), type);
     Operand<T> diagOnes =
-        tf.fill(tf.constant(diagShape.asArray()), tf.dtypes.cast(tf.constant(1.0), dtype));
+        tf.fill(tf.constant(diagShape.asArray()), tf.dtypes.cast(tf.constant(1.0), type));
     if (isSquare) {
       op =
           tf.linalg.matrixDiag(
@@ -91,10 +87,10 @@ public Operand<T> call(Operand<TInt64> dims, DataType<T> dtype) {
               tf.constant((int) shape.size(1)),
               zero);
     } else {
-      Operand<T> zeroMatrix = tf.zeros(dims, dtype);
+      Operand<T> zeroMatrix = tf.zeros(dims, type);
       op = tf.linalg.matrixSetDiag(zeroMatrix, diagOnes, tf.constant(0));
     }
 
-    return tf.math.mul(op, tf.dtypes.cast(tf.constant(gain), dtype));
+    return tf.math.mul(op, tf.dtypes.cast(tf.constant(gain), type));
   }
 }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Initializer.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Initializer.java
index 59dce1fc02e..4beb218783b 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Initializer.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Initializer.java
@@ -14,7 +14,6 @@
 =======================================================================*/
 package org.tensorflow.framework.initializers;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.family.TType;
@@ -30,8 +29,8 @@ public interface Initializer<T extends TType> {
    * Generates the operation used to perform the initialization.
    *
    * @param dims the shape dimensions
-   * @param dtype the data type
+   * @param type the type of tensor
    * @return An operand for the initialization.
    */
-  Operand<T> call(Operand<TInt64> dims, DataType<T> dtype);
+  Operand<T> call(Operand<TInt64> dims, Class<T> type);
 }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/LeCun.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/LeCun.java
index e2268412fc3..38e68ef688b 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/LeCun.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/LeCun.java
@@ -15,8 +15,7 @@
 package org.tensorflow.framework.initializers;
 
 import org.tensorflow.op.Ops;
-import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
+import org.tensorflow.types.family.TFloating;
 
 /**
  * LeCun normal initializer.
@@ -42,7 +41,7 @@
  *              new org.tensorflow.framework.initializers.LeCunNormal&lt;&gt;(tf,
  *               Distribution.TRUNCATED_NORMAL, seed);
  *      Operand&lt;TFloat32&gt; values =
- *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * <p>LeCun Uniform:
@@ -53,7 +52,7 @@
  *              new org.tensorflow.framework.initializers.LeCunNormal&lt;&gt;(tf,
  *               Distribution.UNIFORM, seed);
  *      Operand&lt;TFloat32&gt; values =
- *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * *
@@ -68,7 +67,6 @@
  * <p>
  *
  * @param <T> The TType for the call operation
- * @param <U> The TNumber for the call operation
  * @see <a
  *     href="https://papers.nips.cc/paper/6698-self-normalizing-neural-networks">Self-Normalizing
  *     Neural Networks, Klambauer et al., 2017</a>
@@ -76,7 +74,7 @@
  *     al., 1998</a>
  * @see VarianceScaling.Distribution
  */
-public class LeCun<T extends TType, U extends TNumber> extends VarianceScaling<T, U> {
+public class LeCun<T extends TFloating> extends VarianceScaling<T> {
 
   /**
    * Creates a LeCunNormal Initializer
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Ones.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Ones.java
index b78f34e3d35..b8eb0c418e9 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Ones.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Ones.java
@@ -14,10 +14,11 @@
 =======================================================================*/
 package org.tensorflow.framework.initializers;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.Ops;
+import org.tensorflow.types.TBool;
 import org.tensorflow.types.TInt64;
+import org.tensorflow.types.family.TNumber;
 import org.tensorflow.types.family.TType;
 
 /**
@@ -29,7 +30,7 @@
  *      Ones&lt;TFloat32&gt; initializer =
  *              new org.tensorflow.framework.initializers.Ones&lt;&gt;(tf);
  *      Operand&lt;TFloat32&gt; values =
- *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * @param <T> The TType for the call operation
@@ -45,7 +46,7 @@ public class Ones<T extends TType> extends BaseInitializer<T> {
    *      Ones&lt;TFloat32&gt; initializer =
    *              new org.tensorflow.framework.initializers.Ones&lt;&gt;(tf);
    *      Operand&lt;TFloat32&gt; values =
-   *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+   *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
    * </pre>
    *
    * @param tf the TensorFlow Ops
@@ -56,10 +57,10 @@ public Ones(Ops tf) {
 
   /** {@inheritDoc} */
   @Override
-  public Operand<T> call(Operand<TInt64> dims, DataType<T> dtype) {
-    if (!(dtype.isNumeric() || dtype.isBoolean())) {
-      throw new IllegalArgumentException("DataType must be numeric or boolean: " + dtype.name());
+  public Operand<T> call(Operand<TInt64> dims, Class<T> type) {
+    if (!TNumber.class.isAssignableFrom(type) && type != TBool.class) {
+      throw new IllegalArgumentException("Tensor type must be numeric or boolean: " + type.getSimpleName());
     }
-    return tf.fill(dims, tf.dtypes.cast(tf.constant(1.0), dtype));
+    return tf.fill(dims, tf.dtypes.cast(tf.constant(1.0), type));
   }
 }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Orthogonal.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Orthogonal.java
index 48e2c56d5be..a5b466e118e 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Orthogonal.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Orthogonal.java
@@ -14,7 +14,6 @@
 =======================================================================*/
 package org.tensorflow.framework.initializers;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.Output;
 import org.tensorflow.framework.utils.ShapeUtils;
@@ -22,8 +21,7 @@
 import org.tensorflow.op.Ops;
 import org.tensorflow.op.linalg.Qr;
 import org.tensorflow.types.TInt64;
-import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
+import org.tensorflow.types.family.TFloating;
 
 /**
  * Initializer that generates an orthogonal matrix.
@@ -44,13 +42,12 @@
  *      Orthogonal&lt;TFloat32, TFloat32&gt; initializer =
  *              new org.tensorflow.framework.initializers.Orthogonal&lt;&gt;(tf);
  *      Operand&lt;TFloat32&gt; values =
- *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * @param <T> The TType for the call operation
- * @param <U> The TNumber for the call operation
  */
-public class Orthogonal<T extends TType, U extends TNumber> extends BaseInitializer<T> {
+public class Orthogonal<T extends TFloating> extends BaseInitializer<T> {
 
   public static final double GAIN_DEFAULT = 1.0;
 
@@ -84,10 +81,7 @@ public Orthogonal(Ops tf, double gain, long seed) {
 
   /** {@inheritDoc} */
   @Override
-  public Operand<T> call(Operand<TInt64> dims, DataType<T> dtype) {
-    if (!dtype.isFloating()) {
-      throw new IllegalArgumentException("Expected floating point type, got " + dtype.name());
-    }
+  public Operand<T> call(Operand<TInt64> dims, Class<T> type) {
     Shape dimsShape = ShapeUtils.toShape(tf.scope(), dims);
     if (dimsShape.numDimensions() < 2) {
       throw new IllegalArgumentException(
@@ -100,22 +94,17 @@ public Operand<T> call(Operand<TInt64> dims, DataType<T> dtype) {
     long numCols = dimsShape.size(i);
     Shape flatShape = Shape.of(Math.max(numRows, numCols), Math.min(numRows, numCols));
     long[] seeds = {seed, 0};
-    @SuppressWarnings("unchecked")
-    DataType<U> numdType = (DataType<U>) dtype;
-    @SuppressWarnings("unchecked")
     Operand<T> op =
-        (Operand<T>)
-            tf.random.statelessRandomNormal(tf.constant(flatShape), tf.constant(seeds), numdType);
-
+        tf.random.statelessRandomNormal(tf.constant(flatShape), tf.constant(seeds), type);
     Qr.Options qrOptions = Qr.fullMatrices(false);
     Qr<T> qrOp = tf.linalg.qr(op, qrOptions);
     Output<T> qo = qrOp.q();
     Output<T> ro = qrOp.r();
     Operand<T> diagOp =
-        tf.linalg.matrixDiagPart(ro, tf.constant(0), tf.dtypes.cast(tf.constant(0), dtype));
+        tf.linalg.matrixDiagPart(ro, tf.constant(0), tf.dtypes.cast(tf.constant(0), type));
     Operand<T> qop = tf.math.mul(qo, tf.math.sign(diagOp));
     if (numRows < numCols) qop = tf.linalg.transpose(qop, null);
 
-    return tf.math.mul(qop, tf.dtypes.cast(tf.constant(this.gain), dtype));
+    return tf.math.mul(qop, tf.dtypes.cast(tf.constant(this.gain), type));
   }
 }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/RandomNormal.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/RandomNormal.java
index f2d8a0d8e6e..38ab194a56b 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/RandomNormal.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/RandomNormal.java
@@ -14,12 +14,10 @@
 =======================================================================*/
 package org.tensorflow.framework.initializers;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TInt64;
-import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
+import org.tensorflow.types.family.TFloating;
 
 /**
  * Initializer that generates tensors with a normal distribution.
@@ -31,13 +29,13 @@
  *     RandomNormal&lt;TFloat32, TFloat32&gt; initializer =
  *              new org.tensorflow.framework.initializers.RandomNormal&lt;&gt;(tf, seed);
  *     Operand&lt;TFloat32&gt; values =
- *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * @param <T> The TType for the call operation
- * @param <U> The TNumber for the call operation
  */
-public class RandomNormal<T extends TType, U extends TNumber> extends BaseInitializer<T> {
+public class RandomNormal<T extends TFloating> extends BaseInitializer<T> {
+
   public static final double MEAN_DEFAULT = 0.0;
   public static final double STDDEV_DEFAULT = 1.0;
 
@@ -87,16 +85,10 @@ public RandomNormal(Ops tf, double mean, double stddev, long seed) {
 
   /** {@inheritDoc} */
   @Override
-  public Operand<T> call(Operand<TInt64> dims, DataType<T> dtype) {
-    if (!dtype.isNumeric())
-      throw new IllegalArgumentException("The data type must be numeric. Found : " + dtype.name());
+  public Operand<T> call(Operand<TInt64> dims, Class<T> type) {
     long[] seeds = {seed, 0};
-    @SuppressWarnings("unchecked")
-    DataType<U> numdType = (DataType<U>) dtype;
-    @SuppressWarnings("unchecked")
-    Operand<T> distOp =
-        (Operand<T>) tf.random.statelessRandomNormal(dims, tf.constant(seeds), numdType);
-    Operand<T> op = tf.math.mul(distOp, tf.dtypes.cast(tf.constant(this.stddev), dtype));
-    return tf.math.add(op, tf.dtypes.cast(tf.constant(mean), dtype));
+    Operand<T> distOp = tf.random.statelessRandomNormal(dims, tf.constant(seeds), type);
+    Operand<T> op = tf.math.mul(distOp, tf.dtypes.cast(tf.constant(this.stddev), type));
+    return tf.math.add(op, tf.dtypes.cast(tf.constant(mean), type));
   }
 }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/RandomUniform.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/RandomUniform.java
index b665729675d..787af15f709 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/RandomUniform.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/RandomUniform.java
@@ -14,13 +14,12 @@
 =======================================================================*/
 package org.tensorflow.framework.initializers;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.Ops;
 import org.tensorflow.op.random.RandomUniformInt;
 import org.tensorflow.types.TInt64;
+import org.tensorflow.types.family.TIntegral;
 import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
 
 /**
  * Initializer that generates tensors with a uniform distribution.
@@ -32,13 +31,12 @@
  *     RandomUniform&lt;TFloat32, TFloat32&gt; initializer =
  *              new org.tensorflow.framework.initializers.RandomUniform&lt;&gt;(tf, seed);
  *     Operand&lt;TFloat32&gt; values =
- *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * @param <T> The TType for the call operation
- * @param <U> The TNumber for the call operation
  */
-public class RandomUniform<T extends TType, U extends TNumber> extends BaseInitializer<T> {
+public class RandomUniform<T extends TNumber> extends BaseInitializer<T> {
 
   public static final double MINVAL_DEFAULT = -0.05;
   public static final double MAXVAL_DEFAULT = 0.05;
@@ -77,39 +75,28 @@ public RandomUniform(Ops tf, double minval, double maxval, long seed) {
 
   /** {@inheritDoc} */
   @Override
-  public Operand<T> call(Operand<TInt64> dims, DataType<T> dtype) {
-    if (!dtype.isNumeric())
-      throw new IllegalArgumentException("The data type must be numeric. Found : " + dtype.name());
-    @SuppressWarnings("unchecked")
-    DataType<U> numdType = (DataType<U>) dtype;
-    Operand<U> distOp;
-
-    if (dtype.isInteger()) {
+  public Operand<T> call(Operand<TInt64> dims, Class<T> type) {
+    Operand<T> distOp;
+    if (TIntegral.class.isAssignableFrom(type)) {
       RandomUniformInt.Options options = RandomUniformInt.seed(this.seed);
       distOp =
           tf.random.randomUniformInt(
               dims,
-              tf.dtypes.cast(tf.constant(this.minval), numdType),
-              tf.dtypes.cast(tf.constant(this.maxval), numdType),
+              tf.dtypes.cast(tf.constant(this.minval), type),
+              tf.dtypes.cast(tf.constant(this.maxval), type),
               options);
-      @SuppressWarnings("unchecked")
-      Operand<T> distOpT = (Operand<T>) distOp;
-      return distOpT;
     } else {
       long[] seeds = {seed, 0};
-      distOp = tf.random.statelessRandomUniform(dims, tf.constant(seeds), numdType);
-      @SuppressWarnings("unchecked")
-      Operand<T> distOpT = (Operand<T>) distOp;
+      distOp = tf.random.statelessRandomUniform(dims, tf.constant(seeds), type);
       if (this.minval == 0) {
         if (this.maxval != 1.0) {
-          distOpT = tf.math.mul(distOpT, tf.dtypes.cast(tf.constant(this.maxval), dtype));
+          distOp = tf.math.mul(distOp, tf.dtypes.cast(tf.constant(this.maxval), type));
         }
       } else {
-        distOpT =
-            tf.math.mul(distOpT, tf.dtypes.cast(tf.constant(this.maxval - this.minval), dtype));
-        distOpT = tf.math.add(distOpT, tf.dtypes.cast(tf.constant(this.minval), dtype));
+        distOp = tf.math.mul(distOp, tf.dtypes.cast(tf.constant(this.maxval - this.minval), type));
+        distOp = tf.math.add(distOp, tf.dtypes.cast(tf.constant(this.minval), type));
       }
-      return distOpT;
     }
+    return distOp;
   }
 }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/TruncatedNormal.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/TruncatedNormal.java
index c71cf9a630e..d3cfec26338 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/TruncatedNormal.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/TruncatedNormal.java
@@ -14,12 +14,10 @@
 =======================================================================*/
 package org.tensorflow.framework.initializers;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TInt64;
-import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
+import org.tensorflow.types.family.TFloating;
 
 /**
  * Initializer that generates a truncated normal distribution.
@@ -31,13 +29,12 @@
  *     TruncatedNormal&lt;TFloat32, TFloat32&gt; initializer =
  *              new org.tensorflow.framework.initializers.TruncatedNormal&lt;&gt;(tf, seed);
  *     Operand&lt;TFloat32&gt; values =
- *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * @param <T> The TType for the call operation
- * @param <U> The TNumber for the call operation
  */
-public class TruncatedNormal<T extends TType, U extends TNumber> extends BaseInitializer<T> {
+public class TruncatedNormal<T extends TFloating> extends BaseInitializer<T> {
 
   public static final double MEAN_DEFAULT = 0.0;
   public static final double STDDEV_DEFAULT = 0.05;
@@ -76,17 +73,11 @@ public TruncatedNormal(Ops tf, double mean, double stddev, long seed) {
 
   /** {@inheritDoc} */
   @Override
-  public Operand<T> call(Operand<TInt64> dims, DataType<T> dtype) {
-    if (!dtype.isNumeric())
-      throw new IllegalArgumentException("The data type must be numeric. Found : " + dtype.name());
+  public Operand<T> call(Operand<TInt64> dims, Class<T> type) {
     long[] seeds = {seed,0};
-    @SuppressWarnings("unchecked")
-    DataType<U> numdType = (DataType<U>) dtype;
-    Operand<U> distOp = tf.random.statelessTruncatedNormal(dims, tf.constant(seeds), numdType);
-    @SuppressWarnings("unchecked")
-    Operand<T> distOpT = (Operand<T>) distOp;
+    Operand<T> distOp = tf.random.statelessTruncatedNormal(dims, tf.constant(seeds), type);
     return tf.math.add(
-        tf.math.mul(distOpT, tf.dtypes.cast(tf.constant(stddev), dtype)),
-        tf.dtypes.cast(tf.constant(mean), dtype));
+        tf.math.mul(distOp, tf.dtypes.cast(tf.constant(stddev), type)),
+        tf.dtypes.cast(tf.constant(mean), type));
   }
 }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/VarianceScaling.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/VarianceScaling.java
index fd33adadd5c..5d951450505 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/VarianceScaling.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/VarianceScaling.java
@@ -14,20 +14,16 @@
 =======================================================================*/
 package org.tensorflow.framework.initializers;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.framework.utils.ShapeUtils;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TInt64;
-import org.tensorflow.types.family.TNumber;
-import org.tensorflow.types.family.TType;
+import org.tensorflow.types.family.TFloating;
 
 /**
  * Initializer capable of adapting its scale to the shape of weights tensors.
  *
- * <p>
- *
  * <p>With <code>distribution=TRUNCATED_NORMAL or NORMAL</code>, samples are drawn from
  * a truncated/untruncated normal distribution with a mean of zero and a standard deviation (after
  * truncation, if used) <code>stddev = Math.sqrt(scale / n)</code>, where <code>n</code> is:
@@ -50,15 +46,14 @@
  *          new org.tensorflow.framework.initializers.VarianceScaling&lt;&gt;(
  *              tf, scale, Mode.FAN_IN, Distribution.UNIFORM, seed);
  *      Operand&lt;TFloat32&gt; values =
- *          initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *          initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * @param <T> The TType for the call operation
- * @param <U> The TNumber for the call operation
  * @see VarianceScaling.Mode
  * @see VarianceScaling.Distribution
  */
-public class VarianceScaling<T extends TType, U extends TNumber> extends BaseInitializer<T> {
+public class VarianceScaling<T extends TFloating> extends BaseInitializer<T> {
 
   public static final double SCALE_DEFAULT = 1.0;
   public static final Mode MODE_DEFAULT = Mode.FAN_IN;
@@ -102,10 +97,7 @@ public VarianceScaling(Ops tf, double scale, Mode mode, Distribution distributio
 
   /** {@inheritDoc} */
   @Override
-  public Operand<T> call(Operand<TInt64> dims, DataType<T> dtype) {
-    if (!dtype.isFloating()) {
-      throw new IllegalArgumentException("Expected floating point type, got " + dtype.name());
-    }
+  public Operand<T> call(Operand<TInt64> dims, Class<T> type) {
     Shape shape = ShapeUtils.toShape(this.tf.scope(), dims);
     double lscale = this.scale;
     double[] fans /* fanIn, fanOut */ = computeFans(shape);
@@ -120,32 +112,28 @@ public Operand<T> call(Operand<TInt64> dims, DataType<T> dtype) {
         lscale /= Math.max(1., (fans[0] + fans[1]) / 2.);
         break;
     }
-    Operand<U> distOp;
-    Operand<U> mulOp = null;
-    @SuppressWarnings("unchecked")
-    DataType<U> numdType = (DataType<U>) dtype;
+    Operand<T> distOp;
+    Operand<T> mulOp = null;
     double stddev;
     long[] seeds = {seed, 0};
     switch (distribution) {
       case TRUNCATED_NORMAL:
-        distOp = tf.random.statelessTruncatedNormal(dims, tf.constant(seeds), numdType);
+        distOp = tf.random.statelessTruncatedNormal(dims, tf.constant(seeds), type);
         stddev = Math.sqrt(lscale) / .87962566103423978;
-        mulOp = tf.math.mul(distOp, tf.dtypes.cast(tf.constant(stddev), numdType));
+        mulOp = tf.math.mul(distOp, tf.dtypes.cast(tf.constant(stddev), type));
         break;
       case NORMAL:
-        distOp = tf.random.statelessRandomNormal(dims, tf.constant(seeds), numdType);
+        distOp = tf.random.statelessRandomNormal(dims, tf.constant(seeds), type);
         stddev = Math.sqrt(lscale);
-        mulOp = tf.math.mul(distOp, tf.dtypes.cast(tf.constant(stddev), numdType));
+        mulOp = tf.math.mul(distOp, tf.dtypes.cast(tf.constant(stddev), type));
         break;
       case UNIFORM:
-        distOp = tf.random.statelessRandomUniform(dims, tf.constant(seeds), numdType);
+        distOp = tf.random.statelessRandomUniform(dims, tf.constant(seeds), type);
         stddev = Math.sqrt(3.0 * lscale);
-        mulOp = tf.math.mul(distOp, tf.dtypes.cast(tf.constant(stddev), numdType));
+        mulOp = tf.math.mul(distOp, tf.dtypes.cast(tf.constant(stddev), type));
         break;
     }
-
-    // Need to cast TNumber <U> to TType <T>
-    return (Operand<T>) mulOp;
+    return mulOp;
   }
 
   /**
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Zeros.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Zeros.java
index 09dd512ffaa..4298493ac44 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Zeros.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/initializers/Zeros.java
@@ -14,7 +14,6 @@
 =======================================================================*/
 package org.tensorflow.framework.initializers;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TInt64;
@@ -29,7 +28,7 @@
  *      Zeros&lt;TFloat32&gt; initializer =
  *              new org.tensorflow.framework.initializers.Zeros&lt;&gt;(tf);
  *      Operand&lt;TFloat32&gt; values =
- *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.DTYPE);
+ *              initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
  * </pre>
  *
  * @param <T> The TType for the call operation
@@ -46,7 +45,7 @@ public Zeros(Ops tf) {
   }
 
   @Override
-  public Operand<T> call(Operand<TInt64> dims, DataType<T> dtype) {
+  public Operand<T> call(Operand<TInt64> dims, Class<T> dtype) {
     return tf.zeros(dims, dtype);
   }
 }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/BinaryCrossentropy.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/BinaryCrossentropy.java
index effdf990f71..c7edfcca24e 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/BinaryCrossentropy.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/BinaryCrossentropy.java
@@ -217,8 +217,8 @@ public <T extends TNumber, U extends TNumber> Operand<T> call(
               getTF(),
               "predictions range check [0-1]",
               predictions,
-              cast(getTF(), getTF().constant(0), predictions.asOutput().dataType()),
-              cast(getTF(), getTF().constant(1), predictions.asOutput().dataType()));
+              cast(getTF(), getTF().constant(0), predictions.type()),
+              cast(getTF(), getTF().constant(1), predictions.type()));
 
     } else {
       lPredictions = predictions;
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/CategoricalCrossentropy.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/CategoricalCrossentropy.java
index 6c03fa81b31..77c6ab2bf87 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/CategoricalCrossentropy.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/CategoricalCrossentropy.java
@@ -256,8 +256,8 @@ public <T extends TNumber, U extends TNumber> Operand<T> call(
               getTF(),
               "predictions range check [0-1]",
               predictions,
-              cast(getTF(), getTF().constant(0), predictions.asOutput().dataType()),
-              cast(getTF(), getTF().constant(1), predictions.asOutput().dataType()));
+              cast(getTF(), getTF().constant(0), predictions.type()),
+              cast(getTF(), getTF().constant(1), predictions.type()));
 
     } else {
       lPredictions = predictions;
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/Hinge.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/Hinge.java
index 1e497783841..88b4a7aa056 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/Hinge.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/Hinge.java
@@ -124,16 +124,13 @@ public Hinge(Ops tf, String name, Reduction reduction) {
   public <T extends TNumber, U extends TNumber> Operand<T> call(
       Operand<U> labels, Operand<T> predictions, Operand<T> sampleWeights) {
     @SuppressWarnings("unchecked")
-    Operand<T> tLabels = predictions.asOutput().dataType() == labels.asOutput().dataType() ?
-            (Operand<T>)labels :
-            cast(tf,  labels, predictions.asOutput().dataType());
+    Operand<T> tLabels = predictions.type() == labels.type() ?
+            (Operand<T>)labels : cast(tf,  labels, predictions.type());
     tLabels = LossesHelper.valueCheck(
             getTF(),
             "labels value check [-1, 0, 1]",
             tLabels,
-            cast(getTF(), getTF().constant(new int[] { -1, 0, 1}),
-                    predictions.asOutput().dataType()));
-
+            cast(getTF(), getTF().constant(new int[] { -1, 0, 1}), predictions.type()));
     Operand<T> losses = Losses.hinge(getTF(), tLabels, predictions);
     return LossesHelper.computeWeightedLoss(getTF(), losses, getReduction(), sampleWeights);
   }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/Losses.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/Losses.java
index 5a9dbf5bf01..81d9e13c8a9 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/Losses.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/Losses.java
@@ -14,7 +14,6 @@
 =======================================================================*/
 package org.tensorflow.framework.losses;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.framework.losses.impl.LossTuple;
 import org.tensorflow.framework.losses.impl.LossesHelper;
@@ -51,7 +50,7 @@ public class Losses {
    */
   public static <T extends TNumber, U extends TNumber> Operand<T> meanAbsoluteError(
       Ops tf, Operand<U> labels, Operand<T> predictions) {
-    Operand<T> tLabels = cast(tf, labels, predictions.asOutput().dataType());
+    Operand<T> tLabels = cast(tf, labels, predictions.type());
     LossTuple<T> ops = LossesHelper.squeezeOrExpandDimensions(tf, tLabels, predictions, null);
     predictions = ops.getTarget();
     tLabels = ops.getLabels();
@@ -73,7 +72,7 @@ public static <T extends TNumber, U extends TNumber> Operand<T> meanAbsoluteErro
    */
   public static <T extends TNumber, U extends TNumber> Operand<T> meanSquaredError(
       Ops tf, Operand<U> labels, Operand<T> predictions) {
-    Operand<T> tLabels = cast(tf, labels, predictions.asOutput().dataType());
+    Operand<T> tLabels = cast(tf, labels, predictions.type());
     LossTuple<T> ops = LossesHelper.squeezeOrExpandDimensions(tf, tLabels, predictions, null);
     predictions = ops.getTarget();
     tLabels = ops.getLabels();
@@ -94,8 +93,8 @@ public static <T extends TNumber, U extends TNumber> Operand<T> meanSquaredError
    */
   public static <T extends TNumber, U extends TNumber> Operand<T> meanAbsolutePercentageError(
       Ops tf, Operand<U> labels, Operand<T> predictions) {
-    DataType<T> dataType = predictions.asOutput().dataType();
-    Operand<T> tLabels = cast(tf, labels, dataType);
+    Class<T> predictionType = predictions.type();
+    Operand<T> tLabels = cast(tf, labels, predictionType);
     LossTuple<T> ops = LossesHelper.squeezeOrExpandDimensions(tf, tLabels, predictions, null);
     predictions = ops.getTarget();
     tLabels = ops.getLabels();
@@ -103,8 +102,8 @@ public static <T extends TNumber, U extends TNumber> Operand<T> meanAbsolutePerc
         tf.math.abs(
             tf.math.div(
                 tf.math.sub(tLabels, predictions),
-                tf.math.maximum(tf.math.abs(tLabels), cast(tf, tf.constant(EPSILON), dataType))));
-    return tf.math.mul(cast(tf, tf.constant(100), dataType), tf.math.mean(diff, tf.constant(-1)));
+                tf.math.maximum(tf.math.abs(tLabels), cast(tf, tf.constant(EPSILON), predictionType))));
+    return tf.math.mul(cast(tf, tf.constant(100), predictionType), tf.math.mean(diff, tf.constant(-1)));
   }
 
   /**
@@ -121,14 +120,14 @@ public static <T extends TNumber, U extends TNumber> Operand<T> meanAbsolutePerc
    */
   public static <T extends TNumber, U extends TNumber> Operand<T> meanSquaredLogarithmicError(
       Ops tf, Operand<U> labels, Operand<T> predictions) {
-    DataType<T> dataType = predictions.asOutput().dataType();
-    Operand<T> tLabels = cast(tf, labels, dataType);
+    Class<T> predictionType = predictions.type();
+    Operand<T> tLabels = cast(tf, labels, predictionType);
     LossTuple<T> ops = LossesHelper.squeezeOrExpandDimensions(tf, tLabels, predictions, null);
     predictions = ops.getTarget();
     tLabels = ops.getLabels();
 
-    Operand<T> epsilonConst = cast(tf, tf.constant(EPSILON), dataType);
-    Operand<T> one = cast(tf, tf.constant(1), dataType);
+    Operand<T> epsilonConst = cast(tf, tf.constant(EPSILON), predictionType);
+    Operand<T> one = cast(tf, tf.constant(1), predictionType);
 
     Operand<T> firstLog = tf.math.log(tf.math.add(tf.math.maximum(predictions, epsilonConst), one));
     Operand<T> secondLog = tf.math.log(tf.math.add(tf.math.maximum(tLabels, epsilonConst), one));
@@ -152,8 +151,7 @@ public static <T extends TNumber, U extends TNumber> Operand<T> meanSquaredLogar
    */
   public static <T extends TNumber, U extends TNumber> Operand<T> binaryCrossentropy(
       Ops tf, Operand<U> labels, Operand<T> predictions, boolean fromLogits, float labelSmoothing) {
-    DataType<T> dataType = predictions.asOutput().dataType();
-    Operand<T> tLabels = cast(tf, labels, dataType);
+    Operand<T> tLabels = cast(tf, labels, predictions.type());
     LossTuple<T> ops = LossesHelper.squeezeOrExpandDimensions(tf, tLabels, predictions, null);
     predictions = ops.getTarget();
     tLabels = ops.getLabels();
@@ -193,9 +191,9 @@ private static <T extends TNumber> Operand<T> binaryCrossentropyHelper(
     }
     */
 
-    DataType<T> dataType = output.asOutput().dataType();
-    Operand<T> one = cast(tf, tf.constant(1), dataType);
-    Operand<T> epsilonConst = cast(tf, tf.constant(EPSILON), dataType);
+    Class<T> outputType = output.type();
+    Operand<T> one = cast(tf, tf.constant(1), outputType);
+    Operand<T> epsilonConst = cast(tf, tf.constant(EPSILON), outputType);
     Operand<T> oneMinusEpsilonConst = tf.math.sub(one, epsilonConst);
     output = tf.clipByValue(output, epsilonConst, oneMinusEpsilonConst);
 
@@ -231,8 +229,8 @@ public static <T extends TNumber, U extends TNumber> Operand<T> categoricalCross
       boolean fromLogits,
       float labelSmoothing,
       int axis) {
-    DataType<T> dataType = predictions.asOutput().dataType();
-    Operand<T> tLabels = cast(tf, labels, dataType);
+    Class<T> predictionType = predictions.type();
+    Operand<T> tLabels = cast(tf, labels, predictionType);
     LossTuple<T> ops = LossesHelper.squeezeOrExpandDimensions(tf, tLabels, predictions, null);
     predictions = ops.getTarget();
     tLabels = ops.getLabels();
@@ -256,8 +254,8 @@ public static <T extends TNumber, U extends TNumber> Operand<T> categoricalCross
     }
     */
 
-    Operand<T> one = cast(tf, tf.constant(1), dataType);
-    Operand<T> epsilonConst = cast(tf, tf.constant(EPSILON), dataType);
+    Operand<T> one = cast(tf, tf.constant(1), predictionType);
+    Operand<T> epsilonConst = cast(tf, tf.constant(EPSILON), predictionType);
     Operand<T> oneMinusEpsilonConst = tf.math.sub(one, epsilonConst);
     predictions =
         tf.math.div(
@@ -284,13 +282,13 @@ public static <T extends TNumber, U extends TNumber> Operand<T> categoricalCross
    */
   public static <T extends TNumber, U extends TNumber> Operand<T> categoricalHinge(
       Ops tf, Operand<U> labels, Operand<T> predictions) {
-    DataType<T> dataType = predictions.asOutput().dataType();
-    Operand<T> tLabels = cast(tf, labels, dataType);
+    Class<T> predictionType = predictions.type();
+    Operand<T> tLabels = cast(tf, labels, predictionType);
     LossTuple<T> lossTuple = LossesHelper.squeezeOrExpandDimensions(tf, tLabels, predictions, null);
     predictions = lossTuple.getTarget();
     tLabels = lossTuple.getLabels();
-    Operand<T> one = cast(tf, tf.constant(1), dataType);
-    Operand<T> zero = cast(tf, tf.constant(0), dataType);
+    Operand<T> one = cast(tf, tf.constant(1), predictionType);
+    Operand<T> zero = cast(tf, tf.constant(0), predictionType);
 
     Operand<T> pos =
         tf.reduceSum(
@@ -330,8 +328,7 @@ public static <T extends TNumber, U extends TNumber> Operand<T> categoricalHinge
    */
   public static <T extends TNumber, U extends TNumber> Operand<T> cosineSimilarity(
       Ops tf, Operand<U> labels, Operand<T> predictions, int axis) {
-    DataType<T> dataType = predictions.asOutput().dataType();
-    Operand<T> tLabels = cast(tf, labels, dataType);
+    Operand<T> tLabels = cast(tf, labels, predictions.type());
     LossTuple<T> lossTuple = LossesHelper.squeezeOrExpandDimensions(tf, tLabels, predictions, null);
     predictions = lossTuple.getTarget();
     tLabels = lossTuple.getLabels();
@@ -357,13 +354,13 @@ public static <T extends TNumber, U extends TNumber> Operand<T> cosineSimilarity
    */
   public static <T extends TNumber, U extends TNumber> Operand<T> hinge(
       Ops tf, Operand<U> labels, Operand<T> predictions) {
-    DataType<T> dataType = predictions.asOutput().dataType();
-    Operand<T> tLabels = cast(tf, labels, dataType);
+    Class<T> predictionType = predictions.type();
+    Operand<T> tLabels = cast(tf, labels, predictionType);
     LossTuple<T> lossTuple = LossesHelper.squeezeOrExpandDimensions(tf, tLabels, predictions, null);
     predictions = lossTuple.getTarget();
     tLabels = lossTuple.getLabels();
-    Operand<T> one = cast(tf, tf.constant(1), dataType);
-    Operand<T> zero = cast(tf, tf.constant(0), dataType);
+    Operand<T> one = cast(tf, tf.constant(1), predictionType);
+    Operand<T> zero = cast(tf, tf.constant(0), predictionType);
 
     tLabels = maybeConvertLabels(tf, tLabels);
 
@@ -393,15 +390,15 @@ public static <T extends TNumber, U extends TNumber> Operand<T> hinge(
    */
   public static <T extends TNumber, U extends TNumber> Operand<T> huber(
       Ops tf, Operand<U> labels, Operand<T> predictions, float delta) {
-    DataType<T> dataType = predictions.asOutput().dataType();
-    Operand<T> tLabels = cast(tf, labels, dataType);
+    Class<T> predictionType = predictions.type();
+    Operand<T> tLabels = cast(tf, labels, predictionType);
     LossTuple<T> lossTuple = LossesHelper.squeezeOrExpandDimensions(tf, tLabels, predictions, null);
     predictions = lossTuple.getTarget();
     tLabels = lossTuple.getLabels();
 
     Operand<T> error = tf.math.sub(predictions, tLabels);
-    Operand<T> deltaConst = cast(tf, tf.constant(delta), dataType);
-    Operand<T> point5 = cast(tf, tf.constant(0.5), dataType);
+    Operand<T> deltaConst = cast(tf, tf.constant(delta), predictionType);
+    Operand<T> point5 = cast(tf, tf.constant(0.5), predictionType);
     Operand<T> absError = tf.math.abs(error);
     Operand<T> quadratic = tf.math.minimum(absError, deltaConst);
     Operand<T> linear = tf.math.sub(absError, quadratic);
@@ -424,13 +421,13 @@ public static <T extends TNumber, U extends TNumber> Operand<T> huber(
    */
   public static <T extends TNumber, U extends TNumber> Operand<T> kullbackLeiblerDivergence(
       Ops tf, Operand<U> labels, Operand<T> predictions) {
-    DataType<T> dataType = predictions.asOutput().dataType();
-    Operand<T> tLabels = cast(tf, labels, dataType);
+    Class<T> predictionType = predictions.type();
+    Operand<T> tLabels = cast(tf, labels, predictionType);
     LossTuple<T> lossTuple = LossesHelper.squeezeOrExpandDimensions(tf, tLabels, predictions, null);
     predictions = lossTuple.getTarget();
     tLabels = lossTuple.getLabels();
-    Operand<T> one = cast(tf, tf.constant(1), dataType);
-    Operand<T> epsilonConst = cast(tf, tf.constant(EPSILON), dataType);
+    Operand<T> one = cast(tf, tf.constant(1), predictionType);
+    Operand<T> epsilonConst = cast(tf, tf.constant(EPSILON), predictionType);
 
     tLabels = tf.clipByValue(tLabels, epsilonConst, one);
     predictions = tf.clipByValue(predictions, epsilonConst, one);
@@ -454,13 +451,13 @@ public static <T extends TNumber, U extends TNumber> Operand<T> kullbackLeiblerD
    */
   public static <T extends TNumber, U extends TNumber> Operand<T> logCosh(
       Ops tf, Operand<U> labels, Operand<T> predictions) {
-    DataType<T> dataType = predictions.asOutput().dataType();
-    Operand<T> tLabels = cast(tf, labels, dataType);
+    Class<T> predictionType = predictions.type();
+    Operand<T> tLabels = cast(tf, labels, predictionType);
     LossTuple<T> lossTuple = LossesHelper.squeezeOrExpandDimensions(tf, tLabels, predictions, null);
     predictions = lossTuple.getTarget();
     tLabels = lossTuple.getLabels();
-    Operand<T> minusTwo = cast(tf, tf.constant(-2), dataType);
-    Operand<T> two = cast(tf, tf.constant(2), dataType);
+    Operand<T> minusTwo = cast(tf, tf.constant(-2), predictionType);
+    Operand<T> two = cast(tf, tf.constant(2), predictionType);
 
     Operand<T> diff = tf.math.sub(predictions, tLabels);
     Softplus<T> softplus = tf.math.softplus(tf.math.mul(minusTwo, diff));
@@ -482,12 +479,12 @@ public static <T extends TNumber, U extends TNumber> Operand<T> logCosh(
    */
   public static <T extends TNumber, U extends TNumber> Operand<T> poisson(
       Ops tf, Operand<U> labels, Operand<T> predictions) {
-    DataType<T> dataType = predictions.asOutput().dataType();
-    Operand<T> tLabels = cast(tf, labels, dataType);
+    Class<T> predictionType = predictions.type();
+    Operand<T> tLabels = cast(tf, labels, predictionType);
     LossTuple<T> lossTuple = LossesHelper.squeezeOrExpandDimensions(tf, tLabels, predictions, null);
     predictions = lossTuple.getTarget();
     tLabels = lossTuple.getLabels();
-    Operand<T> epsilonConst = cast(tf, tf.constant(EPSILON), dataType);
+    Operand<T> epsilonConst = cast(tf, tf.constant(EPSILON), predictionType);
 
     return tf.math.mean(
         tf.math.sub(
@@ -509,9 +506,9 @@ public static <T extends TNumber, U extends TNumber> Operand<T> poisson(
    */
   public static <T extends TNumber, U extends TNumber> Operand<T> sparseCategoricalCrossentropy(
       Ops tf, Operand<U> labels, Operand<T> predictions, boolean fromLogits, int axis) {
-    DataType<T> dataType = predictions.asOutput().dataType();
-    Operand<T> epsilonConst = cast(tf, tf.constant(EPSILON), dataType);
-    Operand<T> one = cast(tf, tf.constant(1), dataType);
+    Class<T> predictionType = predictions.type();
+    Operand<T> epsilonConst = cast(tf, tf.constant(EPSILON), predictionType);
+    Operand<T> one = cast(tf, tf.constant(1), predictionType);
     Operand<T> oneMinusEpsilonConst = tf.math.sub(one, epsilonConst);
 
     /* TODO need ability to walk back inputs
@@ -546,7 +543,7 @@ public static <T extends TNumber, U extends TNumber> Operand<T> sparseCategorica
       predictions = tf.linalg.transpose(predictions, tf.constant(axisNew));
     }
 
-    Operand<TInt64> iLabels = cast(tf, labels, TInt64.DTYPE);
+    Operand<TInt64> iLabels = cast(tf, labels, TInt64.class);
 
     // Try to adjust the shape so that rank of labels = rank of logits - 1.
     Shape labelsShape = labels.shape();
@@ -586,13 +583,13 @@ public static <T extends TNumber, U extends TNumber> Operand<T> sparseCategorica
    */
   public static <T extends TNumber, U extends TNumber> Operand<T> squaredHinge(
       Ops tf, Operand<U> labels, Operand<T> predictions) {
-    DataType<T> dataType = predictions.asOutput().dataType();
-    Operand<T> tLabels = cast(tf, labels, dataType);
+    Class<T> predictionType = predictions.type();
+    Operand<T> tLabels = cast(tf, labels, predictionType);
     LossTuple<T> lossTuple = LossesHelper.squeezeOrExpandDimensions(tf, tLabels, predictions, null);
     predictions = lossTuple.getTarget();
     tLabels = lossTuple.getLabels();
-    Operand<T> one = cast(tf, tf.constant(1), dataType);
-    Operand<T> zero = cast(tf, tf.constant(0), dataType);
+    Operand<T> one = cast(tf, tf.constant(1), predictionType);
+    Operand<T> zero = cast(tf, tf.constant(0), predictionType);
 
     tLabels = maybeConvertLabels(tf, tLabels);
     return tf.math.mean(
@@ -614,9 +611,9 @@ public static <T extends TNumber, U extends TNumber> Operand<T> squaredHinge(
    */
   private static <T extends TNumber> Operand<T> smoothBinaryLabels(
       Ops tf, Operand<T> labels, float labelSmoothing) {
-    DataType<T> dataType = labels.asOutput().dataType();
-    Operand<T> oneMinusSmoothing = cast(tf, tf.constant(1.f - labelSmoothing), dataType);
-    Operand<T> halfSmoothing = cast(tf, tf.constant(0.5F * labelSmoothing), dataType);
+    Class<T> labelType = labels.type();
+    Operand<T> oneMinusSmoothing = cast(tf, tf.constant(1.f - labelSmoothing), labelType);
+    Operand<T> halfSmoothing = cast(tf, tf.constant(0.5F * labelSmoothing), labelType);
     return tf.math.add(tf.math.mul(labels, oneMinusSmoothing), halfSmoothing);
   }
 
@@ -633,12 +630,12 @@ private static <T extends TNumber> Operand<T> smoothBinaryLabels(
    */
   private static <T extends TNumber> Operand<T> smoothCategoricalLabels(
       Ops tf, Operand<T> labels, float labelSmoothing) {
-    DataType<T> dataType = labels.asOutput().dataType();
-    Operand<T> smoothing = cast(tf, tf.constant(labelSmoothing), dataType);
+    Class<T> labelType = labels.type();
+    Operand<T> smoothing = cast(tf, tf.constant(labelSmoothing), labelType);
     Shape labelsShape = labels.shape();
     int numDims = labelsShape.numDimensions();
-    Operand<T> numClasses = cast(tf, tf.constant(labelsShape.size(numDims - 1)), dataType);
-    Operand<T> oneMinusSmoothing = cast(tf, tf.constant(1.f - labelSmoothing), dataType);
+    Operand<T> numClasses = cast(tf, tf.constant(labelsShape.size(numDims - 1)), labelType);
+    Operand<T> oneMinusSmoothing = cast(tf, tf.constant(1.f - labelSmoothing), labelType);
     return tf.math.add(tf.math.mul(labels, oneMinusSmoothing), tf.math.div(smoothing, numClasses));
   }
 
@@ -656,7 +653,7 @@ public static <T extends TNumber> Operand<T> l2Normalize(Ops tf, Operand<T> x, i
         tf.reduceSum(tf.math.square(x), tf.constant(axis), ReduceSum.keepDims(Boolean.TRUE));
     Operand<T> invNorm =
         tf.math.rsqrt(
-            tf.math.maximum(squareSum, cast(tf, tf.constant(1e-12F), x.asOutput().dataType())));
+            tf.math.maximum(squareSum, cast(tf, tf.constant(1e-12F), x.type())));
     return tf.math.mul(x, invNorm);
   }
 
@@ -669,11 +666,11 @@ public static <T extends TNumber> Operand<T> l2Normalize(Ops tf, Operand<T> x, i
    * @return the labels, possibly converted into -1/1.
    */
   private static <T extends TNumber> Operand<T> maybeConvertLabels(Ops tf, Operand<T> labels) {
-    DataType<T> dataType = labels.asOutput().dataType();
+    Class<T> labelType = labels.type();
 
-    Operand<T> one = cast(tf, tf.constant(1), dataType);
-    Operand<T> zero = cast(tf, tf.constant(0), dataType);
-    Operand<T> two = cast(tf, tf.constant(2), dataType);
+    Operand<T> one = cast(tf, tf.constant(1), labelType);
+    Operand<T> zero = cast(tf, tf.constant(0), labelType);
+    Operand<T> two = cast(tf, tf.constant(2), labelType);
     Operand<TBool> areZeros = tf.math.equal(labels, zero);
     Operand<TBool> areOnes = tf.math.equal(labels, one);
     Operand<TBool> isBinary =
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/SparseCategoricalCrossentropy.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/SparseCategoricalCrossentropy.java
index 5586a4da889..ea765e6f8fd 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/SparseCategoricalCrossentropy.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/SparseCategoricalCrossentropy.java
@@ -205,8 +205,8 @@ public <T extends TNumber, U extends TNumber> Operand<T> call(
                       getTF(),
                       "predictions range check [0-1]",
                       predictions,
-                      cast(getTF(), getTF().constant(0), predictions.asOutput().dataType()),
-                      cast(getTF(), getTF().constant(1), predictions.asOutput().dataType()));
+                      cast(getTF(), getTF().constant(0), predictions.type()),
+                      cast(getTF(), getTF().constant(1), predictions.type()));
 
     } else {
       lPredictions = predictions;
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/SquaredHinge.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/SquaredHinge.java
index 182ce592e55..4ad4c1c726c 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/SquaredHinge.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/SquaredHinge.java
@@ -125,15 +125,13 @@ public SquaredHinge(Ops tf, String name, Reduction reduction) {
   public <T extends TNumber, U extends TNumber> Operand<T> call(
       Operand<U> labels, Operand<T> predictions, Operand<T> sampleWeights) {
     @SuppressWarnings("unchecked")
-    Operand<T> tLabels = predictions.asOutput().dataType() == labels.asOutput().dataType() ?
-            (Operand<T>)labels :
-            cast(tf,  labels, predictions.asOutput().dataType());
+    Operand<T> tLabels = predictions.type() == labels.type() ?
+            (Operand<T>)labels : cast(tf,  labels, predictions.type());
     tLabels = LossesHelper.valueCheck(
             getTF(),
             "labels value check [-1, 0, 1]",
             tLabels,
-            cast(getTF(), getTF().constant(new int[] { -1, 0, 1}),
-                    predictions.asOutput().dataType()));
+            cast(getTF(), getTF().constant(new int[] { -1, 0, 1}), predictions.type()));
     Operand<T> losses = Losses.squaredHinge(getTF(), tLabels, predictions);
     return LossesHelper.computeWeightedLoss(getTF(), losses, getReduction(), sampleWeights);
   }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/impl/LossesHelper.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/impl/LossesHelper.java
index fbc92f14d31..10067db91ba 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/impl/LossesHelper.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/losses/impl/LossesHelper.java
@@ -14,7 +14,6 @@
 =======================================================================*/
 package org.tensorflow.framework.losses.impl;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.framework.losses.Reduction;
 import org.tensorflow.ndarray.Shape;
@@ -249,17 +248,17 @@ public static <T extends TNumber> LossTuple<T> removeSqueezableDimensions(
    */
   public static <T extends TNumber> Operand<T> computeWeightedLoss(
       Ops tf, Operand<T> loss, Reduction reduction, Operand<T> sampleWeight) {
-    DataType<T> dataType = loss.asOutput().dataType();
+    Class<T> inputType = loss.type();
     if (sampleWeight == null) {
-      sampleWeight = cast(tf, tf.constant(1), dataType);
+      sampleWeight = cast(tf, tf.constant(1), inputType);
     }
     LossTuple<T> result = squeezeOrExpandDimensions(tf, null, loss, sampleWeight);
     loss = result.getTarget();
     sampleWeight = result.getSampleWeights();
 
-    Operand<T> weightedLosses = tf.math.mul(loss, cast(tf, sampleWeight, dataType));
+    Operand<T> weightedLosses = tf.math.mul(loss, cast(tf, sampleWeight, inputType));
     loss = reduceWeightedLoss(tf, weightedLosses, reduction);
-    return cast(tf, loss, dataType);
+    return cast(tf, loss, inputType);
   }
 
   /**
@@ -300,7 +299,7 @@ public static <T extends TNumber> Operand<T> safeMean(
       Ops tf, Operand<T> losses, long numElements) {
     Operand<T> totalLoss = tf.reduceSum(losses, allAxes(tf, losses));
     return tf.math.divNoNan(
-        totalLoss, cast(tf, tf.constant(numElements), losses.asOutput().dataType()));
+        totalLoss, cast(tf, tf.constant(numElements), losses.type()));
   }
 
   /**
@@ -386,7 +385,7 @@ public static <T extends TNumber> Operand<T> valueCheck(
       Ops tf, String prefix, Operand<T> values, Operand<T> allowedValues) {
     Operand<T> flatValues =
         tf.reshape(values, tf.constant(Shape.of(values.shape().size())));
-    SetDiff1d<T, TInt32> diff = tf.setDiff1d(flatValues, allowedValues, TInt32.DTYPE);
+    SetDiff1d<T, TInt32> diff = tf.setDiff1d(flatValues, allowedValues, TInt32.class);
     long diffSize = diff.out().shape().size();
 
     if (diffSize != Shape.UNKNOWN_SIZE) {
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaDelta.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaDelta.java
index 0adf5f58910..822eb490f22 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaDelta.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaDelta.java
@@ -141,10 +141,10 @@ protected void createSlots(List<Output<? extends TType>> variables) {
    */
   private <T extends TType> void createAdaDeltaSlot(Output<T> v) {
     Operand<T> accumulatorInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.type()));
     createSlot(v.asOutput(), ACCUMULATOR, accumulatorInitializer);
     Operand<T> updateInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.type()));
     createSlot(v.asOutput(), ACCUMULATOR_UPDATE, updateInitializer);
   }
 
@@ -157,9 +157,9 @@ protected <T extends TType> Op applyDense(Output<T> gradient, Output<T> variable
         variable,
         accumSlot,
         accumUpdateSlot,
-        tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()),
-        tf.dtypes.cast(tf.constant(rho), gradient.dataType()),
-        tf.dtypes.cast(tf.constant(epsilon), gradient.dataType()),
+        tf.dtypes.cast(tf.constant(learningRate), gradient.type()),
+        tf.dtypes.cast(tf.constant(rho), gradient.type()),
+        tf.dtypes.cast(tf.constant(epsilon), gradient.type()),
         gradient);
   }
 
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGrad.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGrad.java
index 1a7f4675662..08f5f18a9cd 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGrad.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGrad.java
@@ -131,7 +131,7 @@ protected void createSlots(List<Output<? extends TType>> variables) {
    */
   private <T extends TType> void createAdaGradSlot(Output<T> v) {
     Operand<T> initializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(initialAccumulatorValue), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(initialAccumulatorValue), v.type()));
     createSlot(v.asOutput(), ACCUMULATOR, initializer);
   }
 
@@ -140,7 +140,7 @@ private <T extends TType> void createAdaGradSlot(Output<T> v) {
   protected <T extends TType> Op applyDense(Output<T> gradient, Output<T> variable) {
     Variable<T> slot = getSlot(variable, ACCUMULATOR).get();
     return tf.train.applyAdagrad(
-        variable, slot, tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()), gradient);
+        variable, slot, tf.dtypes.cast(tf.constant(learningRate), gradient.type()), gradient);
   }
 
   /** {@inheritDoc} */
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGradDA.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGradDA.java
index f76217fda85..df624e41c4e 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGradDA.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/AdaGradDA.java
@@ -187,7 +187,7 @@ protected void createSlots(List<Output<? extends TType>> variables) {
     for (Output<? extends TType> v : variables) {
       createAdaGradDASlot(v);
     }
-    globalStep = tf.withName("adagrad-da-global-step").variable(Shape.scalar(), TInt64.DTYPE);
+    globalStep = tf.withName("adagrad-da-global-step").variable(Shape.scalar(), TInt64.class);
     Assign<TInt64> globalStepInitializer = tf.assign(globalStep, tf.constant(0L));
     graph.addInitializer(globalStepInitializer);
   }
@@ -199,10 +199,10 @@ protected void createSlots(List<Output<? extends TType>> variables) {
    * @param <T> the datatype of the variable.
    */
   private <T extends TType> void createAdaGradDASlot(Output<T> v) {
-    Operand<T> initializer = tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+    Operand<T> initializer = tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.type()));
     createSlot(v.asOutput(), ACCUMULATOR, initializer);
     Operand<T> sqInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(initialAccumulatorValue), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(initialAccumulatorValue), v.type()));
     createSlot(v.asOutput(), SQUARED_ACCUMULATOR, sqInitializer);
   }
 
@@ -216,9 +216,9 @@ protected <T extends TType> Op applyDense(Output<T> gradient, Output<T> variable
         gradSlot,
         gradSquaredSlot,
         gradient,
-        tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()),
-        tf.dtypes.cast(tf.constant(l1Strength), gradient.dataType()),
-        tf.dtypes.cast(tf.constant(l2Strength), gradient.dataType()),
+        tf.dtypes.cast(tf.constant(learningRate), gradient.type()),
+        tf.dtypes.cast(tf.constant(l1Strength), gradient.type()),
+        tf.dtypes.cast(tf.constant(l2Strength), gradient.type()),
         globalStep);
   }
 
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adam.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adam.java
index 8f620678781..72598d12543 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adam.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adam.java
@@ -189,10 +189,10 @@ protected void createSlots(List<Output<? extends TType>> variables) {
     for (Output<? extends TType> v : variables) {
       createAdamSlot(v.asOutput());
     }
-    betaOnePower = tf.withName("beta1_power").variable(Shape.scalar(), TFloat32.DTYPE);
+    betaOnePower = tf.withName("beta1_power").variable(Shape.scalar(), TFloat32.class);
     Assign<TFloat32> betaOnePowerInit = tf.assign(betaOnePower, tf.constant(betaOne));
     graph.addInitializer(betaOnePowerInit);
-    betaTwoPower = tf.withName("beta2_power").variable(Shape.scalar(), TFloat32.DTYPE);
+    betaTwoPower = tf.withName("beta2_power").variable(Shape.scalar(), TFloat32.class);
     Assign<TFloat32> betaTwoPowerInit = tf.assign(betaTwoPower, tf.constant(betaTwo));
     graph.addInitializer(betaTwoPowerInit);
   }
@@ -215,10 +215,10 @@ protected Optional<Op> prepare(String scopeName) {
    */
   private <T extends TType> void createAdamSlot(Output<T> v) {
     Operand<T> firstMomentInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.type()));
     createSlot(v.asOutput(), FIRST_MOMENT, firstMomentInitializer);
     Operand<T> secondMomentInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.type()));
     createSlot(v.asOutput(), SECOND_MOMENT, secondMomentInitializer);
   }
 
@@ -231,12 +231,12 @@ protected <T extends TType> Op applyDense(Output<T> gradient, Output<T> variable
         variable,
         firstMomentSlot,
         secondMomentSlot,
-        tf.dtypes.cast(betaOnePower, gradient.dataType()),
-        tf.dtypes.cast(betaTwoPower, gradient.dataType()),
-        tf.dtypes.cast(learningRateConst, gradient.dataType()),
-        tf.dtypes.cast(betaOneConst, gradient.dataType()),
-        tf.dtypes.cast(betaTwoConst, gradient.dataType()),
-        tf.dtypes.cast(epsilonConst, gradient.dataType()),
+        tf.dtypes.cast(betaOnePower, gradient.type()),
+        tf.dtypes.cast(betaTwoPower, gradient.type()),
+        tf.dtypes.cast(learningRateConst, gradient.type()),
+        tf.dtypes.cast(betaOneConst, gradient.type()),
+        tf.dtypes.cast(betaTwoConst, gradient.type()),
+        tf.dtypes.cast(epsilonConst, gradient.type()),
         gradient);
   }
 
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adamax.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adamax.java
index 335d83cedfa..cd95bb3bd07 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adamax.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Adamax.java
@@ -137,7 +137,7 @@ protected void createSlots(List<Output<? extends TType>> variables) {
     for (Output<? extends TType> v : variables) {
       createAdamaxSlot(v.asOutput());
     }
-    betaOnePower = tf.withName("beta1_power").variable(Shape.scalar(), TFloat32.DTYPE);
+    betaOnePower = tf.withName("beta1_power").variable(Shape.scalar(), TFloat32.class);
     Assign<TFloat32> betaOnePowerInit = tf.assign(betaOnePower, tf.constant(betaOne));
     ((Graph) tf.scope().env()).addInitializer(betaOnePowerInit);
   }
@@ -150,10 +150,10 @@ protected void createSlots(List<Output<? extends TType>> variables) {
    */
   private <T extends TType> void createAdamaxSlot(Output<T> v) {
     Operand<T> firstMomentInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.type()));
     createSlot(v.asOutput(), FIRST_MOMENT, firstMomentInitializer);
     Operand<T> secondMomentInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.type()));
     createSlot(v.asOutput(), SECOND_MOMENT, secondMomentInitializer);
   }
 
@@ -167,11 +167,11 @@ protected <T extends TType> Op applyDense(Output<T> gradient, Output<T> variable
         variable,
         firstMomentSlot,
         secondMomentSlot,
-        tf.dtypes.cast(betaOnePower, gradient.dataType()),
-        tf.dtypes.cast(learningRateConst, gradient.dataType()),
-        tf.dtypes.cast(betaOneConst, gradient.dataType()),
-        tf.dtypes.cast(betaTwoConst, gradient.dataType()),
-        tf.dtypes.cast(epsilonConst, gradient.dataType()),
+        tf.dtypes.cast(betaOnePower, gradient.type()),
+        tf.dtypes.cast(learningRateConst, gradient.type()),
+        tf.dtypes.cast(betaOneConst, gradient.type()),
+        tf.dtypes.cast(betaTwoConst, gradient.type()),
+        tf.dtypes.cast(epsilonConst, gradient.type()),
         gradient);
   }
 
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Ftrl.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Ftrl.java
index 04c34a2535e..66314d2ffe0 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Ftrl.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Ftrl.java
@@ -230,10 +230,10 @@ protected void createSlots(List<Output<? extends TType>> variables) {
    */
   private <T extends TType> void createFtrlSlot(Output<T> v) {
     Operand<T> initializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(initialAccumulatorValue), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(initialAccumulatorValue), v.type()));
     createSlot(v.asOutput(), ACCUMULATOR, initializer);
     Operand<T> linearInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.type()));
     createSlot(v.asOutput(), LINEAR_ACCUMULATOR, linearInitializer);
   }
 
@@ -248,12 +248,12 @@ protected <T extends TType> Op applyDense(Output<T> gradient, Output<T> variable
         accumSlot, // accum
         linearSlot, // linear
         gradient, // gradient
-        tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()), // lr
-        tf.dtypes.cast(tf.constant(l1RegularizationStrength), gradient.dataType()), // l1
-        tf.dtypes.cast(tf.constant(l2RegularizationStrength), gradient.dataType()), // l2
+        tf.dtypes.cast(tf.constant(learningRate), gradient.type()), // lr
+        tf.dtypes.cast(tf.constant(l1RegularizationStrength), gradient.type()), // l1
+        tf.dtypes.cast(tf.constant(l2RegularizationStrength), gradient.type()), // l2
         tf.dtypes.cast(
-            tf.constant(l2ShrinkageRegularizationStrength), gradient.dataType()), // l2Shrinkage
-        tf.dtypes.cast(tf.constant(learningRatePower), gradient.dataType()), // lrPower
+            tf.constant(l2ShrinkageRegularizationStrength), gradient.type()), // l2Shrinkage
+        tf.dtypes.cast(tf.constant(learningRatePower), gradient.type()), // lrPower
         options);
   }
 
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/GradientDescent.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/GradientDescent.java
index e307855e636..a373b2e5b55 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/GradientDescent.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/GradientDescent.java
@@ -66,7 +66,7 @@ public GradientDescent(Graph graph, String name, float learningRate) {
   @Override
   protected <T extends TType> Op applyDense(Output<T> gradient, Output<T> variable) {
     return tf.train.applyGradientDescent(
-        variable, tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()), gradient);
+        variable, tf.dtypes.cast(tf.constant(learningRate), gradient.type()), gradient);
   }
 
   /** {@inheritDoc} */
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Momentum.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Momentum.java
index 111727d26fa..f6640409d60 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Momentum.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Momentum.java
@@ -125,7 +125,7 @@ protected void createSlots(List<Output<? extends TType>> variables) {
    * @param <T> the data type of the variable
    */
   private <T extends TType> void createMomentumSlot(Output<T> v) {
-    Operand<T> initializer = tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+    Operand<T> initializer = tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.type()));
     createSlot(v.asOutput(), MOMENTUM, initializer);
   }
 
@@ -136,9 +136,9 @@ protected <T extends TType> Op applyDense(Output<T> gradient, Output<T> variable
     return tf.train.applyMomentum(
         variable,
         slot,
-        tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()),
+        tf.dtypes.cast(tf.constant(learningRate), gradient.type()),
         gradient,
-        tf.dtypes.cast(tf.constant(momentum), gradient.dataType()),
+        tf.dtypes.cast(tf.constant(momentum), gradient.type()),
         ApplyMomentum.useNesterov(useNesterov));
   }
 
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Nadam.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Nadam.java
index 48e5135c952..f9900a8ee78 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Nadam.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Nadam.java
@@ -1,6 +1,5 @@
 package org.tensorflow.framework.optimizers;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Output;
@@ -142,15 +141,15 @@ protected void createSlots(List<Output<? extends TType>> variables) {
     for (Output<? extends TType> v : variables) {
       createNadamSlot(v.asOutput());
     }
-    betaOnePower = tf.withName("beta1_power").variable(Shape.scalar(), TFloat32.DTYPE);
+    betaOnePower = tf.withName("beta1_power").variable(Shape.scalar(), TFloat32.class);
     Assign<TFloat32> betaOnePowerInit = tf.assign(betaOnePower, tf.constant(betaOne));
     ((Graph) tf.scope().env()).addInitializer(betaOnePowerInit);
 
-    betaTwoPower = tf.withName("beta2_power").variable(Shape.scalar(), TFloat32.DTYPE);
+    betaTwoPower = tf.withName("beta2_power").variable(Shape.scalar(), TFloat32.class);
     Assign<TFloat32> betaTwoPowerInit = tf.assign(betaTwoPower, tf.constant(betaTwo));
     ((Graph) tf.scope().env()).addInitializer(betaTwoPowerInit);
 
-    momentum = tf.withName("momentum").variable(Shape.scalar(), TFloat32.DTYPE);
+    momentum = tf.withName("momentum").variable(Shape.scalar(), TFloat32.class);
     Assign<TFloat32> momentumInit = tf.assign(momentum, tf.constant(1.0F));
     ((Graph) tf.scope().env()).addInitializer(momentumInit);
   }
@@ -163,14 +162,14 @@ protected void createSlots(List<Output<? extends TType>> variables) {
    */
   private <T extends TType> void createNadamSlot(Output<T> v) {
     Operand<T> firstMomentInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.type()));
     createSlot(v.asOutput(), FIRST_MOMENT, firstMomentInitializer);
     Operand<T> secondMomentInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.type()));
     createSlot(v.asOutput(), SECOND_MOMENT, secondMomentInitializer);
 
     Operand<T> momentumInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(1.0f), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(1.0f), v.type()));
     createSlot(v.asOutput(), MOMENTUM, momentumInitializer);
   }
 
@@ -198,7 +197,7 @@ protected Optional<Op> prepare(String scopeName) {
                     point5,
                     tf.math.pow(
                         decayBaseConst,
-                        tf.math.mul(decayConst, tf.dtypes.cast(localStepConst, TFloat32.DTYPE))))));
+                        tf.math.mul(decayConst, tf.dtypes.cast(localStepConst, TFloat32.class))))));
 
     mT1 =
         tf.math.mul(
@@ -209,7 +208,7 @@ protected Optional<Op> prepare(String scopeName) {
                     point5,
                     tf.math.pow(
                         decayBaseConst,
-                        tf.math.mul(decayConst, tf.dtypes.cast(nextStepConst, TFloat32.DTYPE))))));
+                        tf.math.mul(decayConst, tf.dtypes.cast(nextStepConst, TFloat32.class))))));
 
     Operand<TFloat32> mScheduleNew = tf.math.mul(momentum, mT);
 
@@ -222,57 +221,57 @@ protected Optional<Op> prepare(String scopeName) {
     oneMinusMScheduleNew = tf.math.sub(one, mScheduleNew);
     oneMinusMScheduleNext = tf.math.sub(one, mScheduleNext);
     vTPrimeDenominator =
-        tf.math.sub(one, tf.math.pow(betaTwoConst, tf.dtypes.cast(localStepConst, TFloat32.DTYPE)));
+        tf.math.sub(one, tf.math.pow(betaTwoConst, tf.dtypes.cast(localStepConst, TFloat32.class)));
     return Optional.empty();
   }
 
   /** {@inheritDoc} */
   @Override
   protected <T extends TType> Op applyDense(Output<T> gradient, Output<T> variable) {
-    DataType<T> dType = gradient.dataType();
+    Class<T> type = gradient.type();
     Variable<T> m = getSlot(variable, FIRST_MOMENT).get(); // first Moment
     Variable<T> v = getSlot(variable, SECOND_MOMENT).get(); // Second Moment
 
     //  gPrime = grad / coefficients['oneMinusMScheduleNew']
-    Operand<T> gPrime = tf.math.div(gradient, tf.dtypes.cast(oneMinusMScheduleNew, dType));
+    Operand<T> gPrime = tf.math.div(gradient, tf.dtypes.cast(oneMinusMScheduleNew, type));
     // mT = (coefficients['beta_1_t'] * m + coefficients['one_minus_beta_1_t'] * grad)
     Operand<T> mT =
         tf.math.add(
-            tf.math.mul(tf.dtypes.cast(betaOneConst, dType), m),
-            tf.math.mul(tf.dtypes.cast(oneMinusBeta1, dType), gradient));
+            tf.math.mul(tf.dtypes.cast(betaOneConst, type), m),
+            tf.math.mul(tf.dtypes.cast(oneMinusBeta1, type), gradient));
     // mT = state_ops.assign(m, mT, use_locking=self._use_locking)
     // update m
     mT = tf.assign(m, mT, Assign.useLocking(true));
 
     // mTPrime = mT / coefficients['oneMinusMScheduleNext']
-    Operand<T> mTPrime = tf.math.div(mT, tf.dtypes.cast(oneMinusMScheduleNext, dType));
+    Operand<T> mTPrime = tf.math.div(mT, tf.dtypes.cast(oneMinusMScheduleNext, type));
 
     // vT = (coefficients['beta_2_t'] * v + coefficients['one_minus_beta_2_t'] *
     // math_ops.square(grad))
     Operand<T> vT =
         tf.math.add(
-            tf.math.mul(tf.dtypes.cast(betaTwoConst, dType), v),
-            tf.math.mul(tf.dtypes.cast(oneMinusBeta2, dType), tf.math.square(gradient)));
+            tf.math.mul(tf.dtypes.cast(betaTwoConst, type), v),
+            tf.math.mul(tf.dtypes.cast(oneMinusBeta2, type), tf.math.square(gradient)));
     // vT = state_ops.assign(v, vT, use_locking=self._use_locking)
     // update v
     vT = tf.assign(v, vT, Assign.useLocking(true));
 
     // vTPrime = vT / coefficients['vTPrimeDenominator']
-    Operand<T> vTPrime = tf.math.div(vT, tf.dtypes.cast(vTPrimeDenominator, dType));
+    Operand<T> vTPrime = tf.math.div(vT, tf.dtypes.cast(vTPrimeDenominator, type));
 
     // m_t_bar = (coefficients['oneMinusMT'] * gPrime + coefficients['mT1'] * mTPrime)
     Operand<T> m_t_bar =
         tf.math.add(
-            tf.math.mul(tf.dtypes.cast(oneMinusMT, dType), gPrime),
-            tf.math.mul(tf.dtypes.cast(mT1, dType), mTPrime));
+            tf.math.mul(tf.dtypes.cast(oneMinusMT, type), gPrime),
+            tf.math.mul(tf.dtypes.cast(mT1, type), mTPrime));
     // varT = var - coefficients['lr_t'] * m_t_bar / (math_ops.sqrt(vTPrime) +
     // coefficients['epsilon'])
     Operand<T> varT =
         tf.math.sub(
             variable,
             tf.math.div(
-                tf.math.mul(tf.dtypes.cast(learningRateConst, dType), m_t_bar),
-                tf.math.add(tf.math.sqrt(vTPrime), tf.dtypes.cast(epsilonConst, dType))));
+                tf.math.mul(tf.dtypes.cast(learningRateConst, type), m_t_bar),
+                tf.math.add(tf.math.sqrt(vTPrime), tf.dtypes.cast(epsilonConst, type))));
 
     return tf.assign(variable, varT, Assign.useLocking(true));
   }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizer.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizer.java
index 70f065814f7..fdf56da4a67 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizer.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/Optimizer.java
@@ -220,7 +220,7 @@ private <T extends TType> Optional<Variable<T>> getSlot(String varName, String s
   protected <T extends TType> void createSlot(
       Output<T> variable, String slotName, Operand<T> initializer) {
     Variable<T> slot =
-        tf.withName(createName(variable, slotName)).variable(variable.shape(), variable.dataType());
+        tf.withName(createName(variable, slotName)).variable(variable.shape(), variable.type());
     Assign<T> slotInit = tf.assign(slot, initializer);
     graph.addInitializer(slotInit);
     String varName = variable.op().name();
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/RMSProp.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/RMSProp.java
index 9a48a9b8a7a..b3729dc367f 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/RMSProp.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/optimizers/RMSProp.java
@@ -175,14 +175,14 @@ protected void createSlots(List<Output<? extends TType>> variables) {
    */
   private <T extends TType> void createRMSPropSlot(Output<T> v) {
     Operand<T> rmsInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(1.0f), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(1.0f), v.type()));
     createSlot(v.asOutput(), RMS, rmsInitializer);
     Operand<T> momentumInitializer =
-        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+        tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.type()));
     createSlot(v.asOutput(), MOMENTUM, momentumInitializer);
     if (centered) {
       Operand<T> mgInitializer =
-          tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.dataType()));
+          tf.fill(tf.shape(v), tf.dtypes.cast(tf.constant(0.0f), v.type()));
       createSlot(v.asOutput(), MG, mgInitializer);
     }
   }
@@ -199,20 +199,20 @@ protected <T extends TType> Op applyDense(Output<T> gradient, Output<T> variable
           mgSlot,
           rmsSlot,
           momentumSlot,
-          tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()),
-          tf.dtypes.cast(tf.constant(decay), gradient.dataType()),
-          tf.dtypes.cast(tf.constant(momentum), gradient.dataType()),
-          tf.dtypes.cast(tf.constant(epsilon), gradient.dataType()),
+          tf.dtypes.cast(tf.constant(learningRate), gradient.type()),
+          tf.dtypes.cast(tf.constant(decay), gradient.type()),
+          tf.dtypes.cast(tf.constant(momentum), gradient.type()),
+          tf.dtypes.cast(tf.constant(epsilon), gradient.type()),
           gradient);
     }
     return tf.train.applyRmsProp(
         variable,
         rmsSlot,
         momentumSlot,
-        tf.dtypes.cast(tf.constant(learningRate), gradient.dataType()),
-        tf.dtypes.cast(tf.constant(decay), gradient.dataType()),
-        tf.dtypes.cast(tf.constant(momentum), gradient.dataType()),
-        tf.dtypes.cast(tf.constant(epsilon), gradient.dataType()),
+        tf.dtypes.cast(tf.constant(learningRate), gradient.type()),
+        tf.dtypes.cast(tf.constant(decay), gradient.type()),
+        tf.dtypes.cast(tf.constant(momentum), gradient.type()),
+        tf.dtypes.cast(tf.constant(epsilon), gradient.type()),
         gradient);
   }
 
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/utils/CastHelper.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/utils/CastHelper.java
index aec75e6078a..b0fe48967dd 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/utils/CastHelper.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/utils/CastHelper.java
@@ -15,7 +15,6 @@
  */
 package org.tensorflow.framework.utils;
 
-import org.tensorflow.DataType;
 import org.tensorflow.Operand;
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.family.TType;
@@ -35,8 +34,8 @@ public class CastHelper {
    */
   @SuppressWarnings("unchecked")
   public static <T extends TType, U extends TType> Operand<T> cast(
-          Ops tf, Operand<U> value, DataType<T> requiredType) {
-    return (value.asOutput().dataType() == requiredType)
+          Ops tf, Operand<U> value, Class<T> requiredType) {
+    return (value.type() == requiredType)
         ? (Operand<T>) value
         : tf.dtypes.cast(value, requiredType);
   }
diff --git a/tensorflow-framework/src/main/java/org/tensorflow/framework/utils/ShapeUtils.java b/tensorflow-framework/src/main/java/org/tensorflow/framework/utils/ShapeUtils.java
index 87a43941a16..4ca2c789f28 100644
--- a/tensorflow-framework/src/main/java/org/tensorflow/framework/utils/ShapeUtils.java
+++ b/tensorflow-framework/src/main/java/org/tensorflow/framework/utils/ShapeUtils.java
@@ -21,7 +21,7 @@
 import org.tensorflow.types.TInt32;
 import org.tensorflow.types.TInt64;
 import org.tensorflow.types.TUint8;
-import org.tensorflow.types.family.TNumber;
+import org.tensorflow.types.family.TIntegral;
 
 import java.util.ArrayList;
 import java.util.Arrays;
@@ -36,7 +36,7 @@ public class ShapeUtils {
    * @param dims the Operand containing the shape values
    * @return a new Shape based on an Operand that contains dimensions
    */
-  public static <T extends TNumber> Shape toShape(Scope scope, Operand<T> dims) {
+  public static <T extends TIntegral> Shape toShape(Scope scope, Operand<T> dims) {
     long[] longDims = getLongArray(scope, dims);
     return Shape.of(longDims);
   }
@@ -62,12 +62,12 @@ public static int[] getIntArray(Scope scope, Operand<TInt32> dims) {
    * @return the long array
    * @throws java.lang.IllegalArgumentException if the dims type is not an integer
    */
-  public static <T extends TNumber> long[] getLongArray(Scope scope, Operand<T> dims) {
+  public static <T extends TIntegral> long[] getLongArray(Scope scope, Operand<T> dims) {
     if (scope.env().isEager()) {
       return getLongArray(dims.asTensor());
     }
     try (Session session = new Session((Graph)scope.env());
-        Tensor tensor = session.runner().fetch(dims).run().get(0)) {
+        TIntegral tensor = (TIntegral)session.runner().fetch(dims).run().get(0)) {
       return getLongArray(tensor);
     }
   }
@@ -79,7 +79,7 @@ public static <T extends TNumber> long[] getLongArray(Scope scope, Operand<T> di
    * @return the long array
    * @throws java.lang.IllegalArgumentException if the dims type is not an integer
    */
-  public static long[] getLongArray(Tensor dims) {
+  public static <T extends TIntegral> long[] getLongArray(T dims) {
     List<Long> result = new ArrayList<>();
     if (dims instanceof TInt32) {
       ((TInt32)dims).scalars().forEach(s -> result.add((long) s.getInt()));
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/ELUTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/ELUTest.java
index e608224a50d..914b94dfada 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/ELUTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/ELUTest.java
@@ -20,7 +20,6 @@
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
 
 import static org.junit.jupiter.api.Assertions.assertThrows;
 
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/ExponentialTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/ExponentialTest.java
index a0fd1f60b47..1157c582168 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/ExponentialTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/ExponentialTest.java
@@ -20,7 +20,6 @@
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
 
 import static org.junit.jupiter.api.Assertions.assertThrows;
 
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/HardSigmoidTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/HardSigmoidTest.java
index b1eaab8de22..35f57c47f66 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/HardSigmoidTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/HardSigmoidTest.java
@@ -20,7 +20,6 @@
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
 
 import static org.junit.jupiter.api.Assertions.assertThrows;
 
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/ReLUTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/ReLUTest.java
index f54401515ab..a0aa2c4b453 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/ReLUTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/ReLUTest.java
@@ -90,8 +90,8 @@ public void testCallFloat16() {
         Ops tf = session.getTF();
         ReLU<TFloat16> instance = new ReLU<>(tf);
         Operand<TFloat16> result =
-            instance.call(tf.dtypes.cast(tf.constant(input), TFloat16.DTYPE));
-        session.evaluate(tf.dtypes.cast(tf.constant(expected), TFloat16.DTYPE), result);
+            instance.call(tf.dtypes.cast(tf.constant(input), TFloat16.class));
+        session.evaluate(tf.dtypes.cast(tf.constant(expected), TFloat16.class), result);
       }
   }
 
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SELUTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SELUTest.java
index caba5c43ba8..8bad6f1f066 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SELUTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SELUTest.java
@@ -20,7 +20,6 @@
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
 
 import static org.junit.jupiter.api.Assertions.assertThrows;
 
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SigmoidTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SigmoidTest.java
index ffb16cf077a..9dca622c3ec 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SigmoidTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SigmoidTest.java
@@ -20,7 +20,6 @@
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
 
 import static org.junit.jupiter.api.Assertions.assertThrows;
 
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SoftmaxTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SoftmaxTest.java
index a3ff89cc407..05ec3a4f716 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SoftmaxTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SoftmaxTest.java
@@ -18,11 +18,8 @@
 import org.tensorflow.Operand;
 import org.tensorflow.framework.utils.TestSession;
 import org.tensorflow.op.Ops;
-import org.tensorflow.op.core.ReduceMax;
-import org.tensorflow.op.core.ReduceSum;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
 
 import static org.junit.jupiter.api.Assertions.assertThrows;
 
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SwishTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SwishTest.java
index 5739bccd3d5..7576789320b 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SwishTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/activations/SwishTest.java
@@ -20,7 +20,6 @@
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TFloat32;
 import org.tensorflow.types.TFloat64;
-import org.tensorflow.types.TInt32;
 
 import static org.junit.jupiter.api.Assertions.assertThrows;
 
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/data/BatchDatasetTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/data/BatchDatasetTest.java
index 48800d4dc1b..2d282e5dcf7 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/data/BatchDatasetTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/data/BatchDatasetTest.java
@@ -17,7 +17,6 @@
 
 import org.junit.jupiter.api.Test;
 import org.tensorflow.Operand;
-import org.tensorflow.Tensor;
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TInt32;
 
@@ -40,16 +39,14 @@ public void testEagerBatchDataset() {
             Arrays.asList(
                 tf.constant(testMatrix1),
                 tf.constant(testMatrix2)),
-            Arrays.asList(TInt32.DTYPE, TInt32.DTYPE))
+            Arrays.asList(TInt32.class, TInt32.class))
         .batch(2);
 
     int count = 0;
     for (List<Operand<?>> components : dataset) {
       try (TInt32 batch1 =
                (TInt32)components.get(0).asTensor();
-           TInt32 batch2 =
-               (TInt32)components.get(1).asTensor();) {
-
+           TInt32 batch2 = (TInt32)components.get(1).asTensor()) {
         assertEquals(testMatrix1.slice(range(count, count + 2)), batch1);
         assertEquals(testMatrix2.slice(range(count, count + 2)), batch2);
 
@@ -66,7 +63,7 @@ public void testDropLastBatch() {
             Arrays.asList(
                 tf.constant(testMatrix1),
                 tf.constant(testMatrix2)),
-            Arrays.asList(TInt32.DTYPE, TInt32.DTYPE))
+            Arrays.asList(TInt32.class, TInt32.class))
         .batch(3, true);
 
     int count = 0;
@@ -74,9 +71,7 @@ public void testDropLastBatch() {
 
       try (TInt32 batch1 =
                (TInt32)components.get(0).asTensor();
-           TInt32 batch2 =
-               (TInt32)components.get(1).asTensor();) {
-
+          TInt32 batch2 = (TInt32)components.get(1).asTensor()) {
         assertEquals(testMatrix1.slice(range(count, count + 3)), batch1);
         assertEquals(testMatrix2.slice(range(count, count + 3)), batch2);
 
@@ -93,7 +88,7 @@ public void testKeepLastBatch() {
             Arrays.asList(
                 tf.constant(testMatrix1),
                 tf.constant(testMatrix2)),
-            Arrays.asList(TInt32.DTYPE, TInt32.DTYPE))
+            Arrays.asList(TInt32.class, TInt32.class))
         .batch(3, false);
 
     int count = 0;
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/data/DatasetIteratorTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/data/DatasetIteratorTest.java
index 448e90a17ea..882a64ba54d 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/data/DatasetIteratorTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/data/DatasetIteratorTest.java
@@ -16,11 +16,10 @@
 package org.tensorflow.framework.data;
 
 import org.junit.jupiter.api.Test;
-import org.tensorflow.DataType;
 import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Session;
-import org.tensorflow.Tensor;
+import org.tensorflow.types.family.TType;
 import org.tensorflow.exceptions.TFOutOfRangeException;
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TInt32;
@@ -39,7 +38,7 @@ public void testGraphIteration() {
 
       List<Operand<?>> tensors = Arrays.asList(tf.constant(testMatrix1), tf.constant(testMatrix2));
 
-      List<DataType<?>> dataTypes = Arrays.asList(TInt32.DTYPE, TInt32.DTYPE);
+      List<Class<? extends TType>> dataTypes = Arrays.asList(TInt32.class, TInt32.class);
 
       Dataset dataset = Dataset.fromTensorSlices(tf, tensors, dataTypes);
       DatasetIterator iterator = dataset.makeOneShotIterator();
@@ -77,14 +76,13 @@ public void testEagerIteration() {
 
     List<Operand<?>> tensors = Arrays.asList(tf.constant(testMatrix1), tf.constant(testMatrix2));
 
-    List<DataType<?>> dataTypes = Arrays.asList(TInt32.DTYPE, TInt32.DTYPE);
+    List<Class<? extends TType>> dataTypes = Arrays.asList(TInt32.class, TInt32.class);
 
     Dataset dataset = Dataset.fromTensorSlices(tf, tensors, dataTypes);
     int count = 0;
     for (List<Operand<?>> outputs : dataset) {
       try (TInt32 batch1 = (TInt32)outputs.get(0).asTensor();
-          TInt32 batch2 = (TInt32)outputs.get(1).asTensor(); ) {
-
+          TInt32 batch2 = (TInt32)outputs.get(1).asTensor()) {
         assertEquals(testMatrix1.get(count), batch1);
         assertEquals(testMatrix2.get(count), batch2);
 
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/data/MapDatasetTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/data/MapDatasetTest.java
index ede0a1aa61d..5f203427563 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/data/MapDatasetTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/data/MapDatasetTest.java
@@ -17,11 +17,10 @@
 
 import org.junit.jupiter.api.BeforeEach;
 import org.junit.jupiter.api.Test;
-import org.tensorflow.DataType;
 import org.tensorflow.Graph;
 import org.tensorflow.Operand;
 import org.tensorflow.Session;
-import org.tensorflow.Tensor;
+import org.tensorflow.types.family.TType;
 import org.tensorflow.exceptions.TFOutOfRangeException;
 import org.tensorflow.op.Ops;
 import org.tensorflow.ndarray.IntNdArray;
@@ -60,12 +59,13 @@ public void testGraphIteration() {
 
       List<Operand<?>> tensors = Arrays.asList(tf.constant(testMatrix1), tf.constant(testMatrix2));
 
-      List<DataType<?>> dataTypes = Arrays.asList(TInt32.DTYPE, TInt32.DTYPE);
+      List<Class<? extends TType>> dataTypes = Arrays.asList(TInt32.class, TInt32.class);
 
       Dataset dataset =
           Dataset.fromTensorSlices(tf, tensors, dataTypes)
               .mapAllComponents(
-                  component -> tf.math.mul(component.asOutput().expect(TInt32.DTYPE), tf.constant(2)));
+                  component ->
+                      tf.math.mul(component.asOutput().expect(TInt32.class), tf.constant(2)));
 
       DatasetIterator iterator = dataset.makeOneShotIterator();
       List<Operand<?>> components = iterator.getNext();
@@ -104,18 +104,17 @@ public void testEagerIteration() {
 
     List<Operand<?>> tensors = Arrays.asList(tf.constant(testMatrix1), tf.constant(testMatrix2));
 
-    List<DataType<?>> dataTypes = Arrays.asList(TInt32.DTYPE, TInt32.DTYPE);
+    List<Class<? extends TType>> dataTypes = Arrays.asList(TInt32.class, TInt32.class);
 
     Dataset dataset =
         Dataset.fromTensorSlices(tf, tensors, dataTypes)
             .mapAllComponents(
-                op -> tf.math.mul(op.asOutput().expect(TInt32.DTYPE), tf.constant(2)));
+                op -> tf.math.mul(op.asOutput().expect(TInt32.class), tf.constant(2)));
 
     int count = 0;
     for (List<Operand<?>> outputs : dataset) {
       try (TInt32 XBatch = (TInt32)outputs.get(0).asTensor();
-          TInt32 yBatch = (TInt32)outputs.get(1).asTensor(); ) {
-
+          TInt32 yBatch = (TInt32)outputs.get(1).asTensor()) {
         assertEquals(mapped1.get(count), XBatch);
         assertEquals(mapped2.get(count), yBatch);
 
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/data/SkipDatasetTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/data/SkipDatasetTest.java
index 6dc877cc6eb..d0cdb4527a5 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/data/SkipDatasetTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/data/SkipDatasetTest.java
@@ -17,7 +17,6 @@
 
 import org.junit.jupiter.api.Test;
 import org.tensorflow.Operand;
-import org.tensorflow.Tensor;
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TInt32;
 
@@ -35,14 +34,13 @@ public void testEagerSkipDataset() {
         Dataset.fromTensorSlices(
                 tf,
                 Arrays.asList(tf.constant(testMatrix1), tf.constant(testMatrix2)),
-                Arrays.asList(TInt32.DTYPE, TInt32.DTYPE))
+                Arrays.asList(TInt32.class, TInt32.class))
             .skip(2);
 
     int count = 2;
     for (List<Operand<?>> components : dataset) {
       try (TInt32 batch1 = (TInt32)components.get(0).asTensor();
-          TInt32 batch2 =
-              (TInt32)components.get(1).asTensor(); ) {
+          TInt32 batch2 = (TInt32)components.get(1).asTensor()) {
         assertEquals(testMatrix1.get(count), batch1);
         assertEquals(testMatrix2.get(count), batch2);
         count++;
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/data/TakeDatasetTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/data/TakeDatasetTest.java
index 626fe719936..79a2e79c72e 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/data/TakeDatasetTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/data/TakeDatasetTest.java
@@ -17,7 +17,6 @@
 
 import org.junit.jupiter.api.Test;
 import org.tensorflow.Operand;
-import org.tensorflow.Tensor;
 import org.tensorflow.op.Ops;
 import org.tensorflow.types.TInt32;
 
@@ -36,14 +35,13 @@ public void testEagerTakeDataset() {
         Dataset.fromTensorSlices(
                 tf,
                 Arrays.asList(tf.constant(testMatrix1), tf.constant(testMatrix2)),
-                Arrays.asList(TInt32.DTYPE, TInt32.DTYPE))
+                Arrays.asList(TInt32.class, TInt32.class))
             .take(4);
 
     int count = 0;
     for (List<Operand<?>> components : dataset) {
       try (TInt32 batch1 = (TInt32)components.get(0).asTensor();
-          TInt32 batch2 = (TInt32)components.get(1).asTensor(); ) {
-
+          TInt32 batch2 = (TInt32)components.get(1).asTensor()) {
         assertEquals(testMatrix1.get(count), batch1);
         assertEquals(testMatrix2.get(count), batch2);
         count++;
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/ConstantTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/ConstantTest.java
index 46e4232d5ae..4e81e0620e6 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/ConstantTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/ConstantTest.java
@@ -52,7 +52,7 @@ public void testCallUInt() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
         Constant<TUint8> instance = new Constant<>(tf, 0xf);
-        Operand<TUint8> operand = instance.call(tf.constant(shape), TUint8.DTYPE);
+        Operand<TUint8> operand = instance.call(tf.constant(shape), TUint8.class);
         session.evaluate(expected, operand);
       }
   }
@@ -68,7 +68,7 @@ public void testCallInt() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
         Constant<TInt32> instance = new Constant<>(tf, 0xf);
-        Operand<TInt32> operand = instance.call(tf.constant(shape), TInt32.DTYPE);
+        Operand<TInt32> operand = instance.call(tf.constant(shape), TInt32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -84,7 +84,7 @@ public void testCallLong() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
         Constant<TInt64> instance = new Constant<>(tf, 0xffL);
-        Operand<TInt64> operand = instance.call(tf.constant(shape), TInt64.DTYPE);
+        Operand<TInt64> operand = instance.call(tf.constant(shape), TInt64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -98,7 +98,7 @@ public void testCallFloat() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
         Constant<TFloat32> instance = new Constant<>(tf, 12.F);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -113,7 +113,7 @@ public void testCallDouble() {
         Shape shape = Shape.of(2, 2);
 
         Constant<TFloat64> instance = new Constant<>(tf, 11.);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -130,7 +130,7 @@ public void testCallString() {
               Shape shape = Shape.of(2, 2);
 
               Constant<TString> instance = new Constant<>(tf, 22);
-              instance.call(tf.constant(shape), TString.DTYPE);
+              instance.call(tf.constant(shape), TString.class);
               fail("IllegalArgumentException  should have been thrown for TString");
             }
           });
@@ -146,7 +146,7 @@ public void testCallBool() {
         Boolean[] expected = {true, true, true, true};
 
         Constant<TBool> instance = new Constant<>(tf, true);
-        Operand<TBool> operand = instance.call(tf.constant(shape), TBool.DTYPE);
+        Operand<TBool> operand = instance.call(tf.constant(shape), TBool.class);
         session.evaluate(expected, operand);
       }
   }
@@ -159,8 +159,8 @@ public void testReproducible() {
         Shape shape = Shape.of(2, 2);
 
         Constant<TFloat64> instance = new Constant<>(tf, 11.);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/GlorotTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/GlorotTest.java
index a68bf2a0a98..e9769806928 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/GlorotTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/GlorotTest.java
@@ -51,9 +51,9 @@ public void testCallNormalFloat() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        Glorot<TFloat32, TFloat32> instance = new Glorot<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
+        Glorot<TFloat32> instance = new Glorot<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
 
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -68,8 +68,8 @@ public void testCallNormalDouble() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
 
-        Glorot<TFloat64, TFloat64> instance = new Glorot<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Glorot<TFloat64> instance = new Glorot<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -82,8 +82,8 @@ public void testCallUniformFloat() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        Glorot<TFloat32, TFloat32> instance = new Glorot<>(tf, Distribution.UNIFORM, SEED);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        Glorot<TFloat32> instance = new Glorot<>(tf, Distribution.UNIFORM, SEED);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -97,8 +97,8 @@ public void testCallUniformDouble() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        Glorot<TFloat64, TFloat64> instance = new Glorot<>(tf, Distribution.UNIFORM, SEED);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Glorot<TFloat64> instance = new Glorot<>(tf, Distribution.UNIFORM, SEED);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -109,9 +109,9 @@ public void testCallNormalReproducible() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        Glorot<TFloat64, TFloat64> instance = new Glorot<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Glorot<TFloat64> instance = new Glorot<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
@@ -122,9 +122,9 @@ public void testCallUniformReproducible() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        Glorot<TFloat64, TFloat64> instance = new Glorot<>(tf, Distribution.UNIFORM, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Glorot<TFloat64> instance = new Glorot<>(tf, Distribution.UNIFORM, SEED);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
@@ -135,10 +135,10 @@ public void testCallNORMALReproducible() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        Glorot<TFloat64, TFloat64> instance =
+        Glorot<TFloat64> instance =
             new Glorot<>(tf, Distribution.NORMAL, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/HeTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/HeTest.java
index 468759d347f..8953fa3005e 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/HeTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/HeTest.java
@@ -51,8 +51,8 @@ public void testCallNormalFloat() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        He<TFloat32, TFloat32> instance = new He<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        He<TFloat32> instance = new He<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -66,8 +66,8 @@ public void testCallNormalDouble() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        He<TFloat64, TFloat64> instance = new He<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        He<TFloat64> instance = new He<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -80,8 +80,8 @@ public void testCallFloat() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        He<TFloat32, TFloat32> instance = new He<>(tf, Distribution.UNIFORM, SEED);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        He<TFloat32> instance = new He<>(tf, Distribution.UNIFORM, SEED);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -95,8 +95,8 @@ public void testCallDouble() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        He<TFloat64, TFloat64> instance = new He<>(tf, Distribution.UNIFORM, SEED);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        He<TFloat64> instance = new He<>(tf, Distribution.UNIFORM, SEED);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -107,9 +107,9 @@ public void testCallNormalReproducible() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        He<TFloat64, TFloat64> instance = new He<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        He<TFloat64> instance = new He<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
@@ -120,9 +120,9 @@ public void testCallUniformReproducible() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        He<TFloat64, TFloat64> instance = new He<>(tf, Distribution.UNIFORM, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        He<TFloat64> instance = new He<>(tf, Distribution.UNIFORM, SEED);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
@@ -133,9 +133,9 @@ public void testCallNORMALReproducible() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        He<TFloat64, TFloat64> instance = new He<>(tf, Distribution.NORMAL, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        He<TFloat64> instance = new He<>(tf, Distribution.NORMAL, SEED);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/IdentityTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/IdentityTest.java
index adb6c0c118a..6eee5473937 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/IdentityTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/IdentityTest.java
@@ -45,23 +45,6 @@ public void setUp() {}
   @AfterEach
   public void tearDown() {}
 
-  /** Test of call method, of class Orthogonal. */
-  @Test
-  public void testCallInt() {
-    for (TestSession.Mode tfMode : tfModes)
-      assertThrows(
-          java.lang.IllegalArgumentException.class,
-          () -> {
-            try (TestSession session = TestSession.createTestSession(tfMode)) {
-              Ops tf = session.getTF();
-              Shape shape = Shape.of(10, 10);
-              Identity<TInt32> instance = new Identity<>(tf, 2.);
-              instance.call(tf.constant(shape), TInt32.DTYPE);
-              fail("Should have thrown IllegalArgumentException on Integer type");
-            }
-          });
-  }
-
   /** Test of call method, of class Constant. */
   @Test
   public void testCallFloat() {
@@ -82,7 +65,7 @@ public void testCallFloat() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(10, 10);
         Identity<TFloat32> instance = new Identity<>(tf, 2.);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -108,7 +91,7 @@ public void testCallDouble() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(10, 10);
         Identity<TFloat64> instance = new Identity<>(tf, 2.);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -121,8 +104,8 @@ public void testReproducible() {
         Shape shape = Shape.of(2, 2);
 
         Identity<TFloat64> instance = new Identity<>(tf, 2.);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/LeCunTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/LeCunTest.java
index 6033f9e12a5..336850a5549 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/LeCunTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/LeCunTest.java
@@ -51,8 +51,8 @@ public void testCallNormalFloat() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        LeCun<TFloat32, TFloat32> instance = new LeCun<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        LeCun<TFloat32> instance = new LeCun<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -66,8 +66,8 @@ public void testCallNormalDouble() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        LeCun<TFloat64, TFloat64> instance = new LeCun<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        LeCun<TFloat64> instance = new LeCun<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -80,8 +80,8 @@ public void testCallUniformFloat() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        LeCun<TFloat32, TFloat32> instance = new LeCun<>(tf, Distribution.UNIFORM, SEED);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        LeCun<TFloat32> instance = new LeCun<>(tf, Distribution.UNIFORM, SEED);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -95,8 +95,8 @@ public void testCallUniformDouble() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        LeCun<TFloat64, TFloat64> instance = new LeCun<>(tf, Distribution.UNIFORM, SEED);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        LeCun<TFloat64> instance = new LeCun<>(tf, Distribution.UNIFORM, SEED);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -107,9 +107,9 @@ public void testCallNormalReproducible() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        LeCun<TFloat64, TFloat64> instance = new LeCun<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        LeCun<TFloat64> instance = new LeCun<>(tf, Distribution.TRUNCATED_NORMAL, SEED);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
@@ -120,9 +120,9 @@ public void testCallUniformReproducible() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        LeCun<TFloat64, TFloat64> instance = new LeCun<>(tf, Distribution.UNIFORM, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        LeCun<TFloat64> instance = new LeCun<>(tf, Distribution.UNIFORM, SEED);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
@@ -133,9 +133,9 @@ public void testCallNORMALReproducible() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        LeCun<TFloat64, TFloat64> instance = new LeCun<>(tf, Distribution.NORMAL, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        LeCun<TFloat64> instance = new LeCun<>(tf, Distribution.NORMAL, SEED);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/OnesTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/OnesTest.java
index bbd2ba3d384..053ba5dd7ff 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/OnesTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/OnesTest.java
@@ -52,7 +52,7 @@ public void testCallUInt() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
         Ones<TUint8> instance = new Ones<>(tf);
-        Operand<TUint8> operand = instance.call(tf.constant(shape), TUint8.DTYPE);
+        Operand<TUint8> operand = instance.call(tf.constant(shape), TUint8.class);
         session.evaluate(expected, operand);
       }
   }
@@ -66,7 +66,7 @@ public void testCallInt() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
         Ones<TInt32> instance = new Ones<>(tf);
-        Operand<TInt32> operand = instance.call(tf.constant(shape), TInt32.DTYPE);
+        Operand<TInt32> operand = instance.call(tf.constant(shape), TInt32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -80,7 +80,7 @@ public void testCallLong() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
         Ones<TInt64> instance = new Ones<>(tf);
-        Operand<TInt64> operand = instance.call(tf.constant(shape), TInt64.DTYPE);
+        Operand<TInt64> operand = instance.call(tf.constant(shape), TInt64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -94,7 +94,7 @@ public void testCallFloat() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
         Ones<TFloat32> instance = new Ones<>(tf);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -109,7 +109,7 @@ public void testCallDouble() {
         Shape shape = Shape.of(2, 2);
 
         Ones<TFloat64> instance = new Ones<>(tf);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -126,7 +126,7 @@ public void testCallString() {
               Shape shape = Shape.of(2, 2);
 
               Ones<TString> instance = new Ones<>(tf);
-              instance.call(tf.constant(shape), TString.DTYPE);
+              instance.call(tf.constant(shape), TString.class);
               fail("IllegalArgumentException should have been thrown for TString");
             }
           });
@@ -141,7 +141,7 @@ public void testCallBool() {
         Shape shape = Shape.of(2, 2);
 
         Ones<TBool> instance = new Ones<>(tf);
-        Operand<TBool> operand = instance.call(tf.constant(shape), TBool.DTYPE);
+        Operand<TBool> operand = instance.call(tf.constant(shape), TBool.class);
         session.evaluate(expected, operand);
       }
   }
@@ -154,8 +154,8 @@ public void testReproducible() {
         Shape shape = Shape.of(2, 2);
 
         Ones<TFloat64> instance = new Ones<>(tf);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/OrthogonalTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/OrthogonalTest.java
index a4fff5fd19c..22b89d9177c 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/OrthogonalTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/OrthogonalTest.java
@@ -47,23 +47,6 @@ public void setUp() {}
   @AfterEach
   public void tearDown() {}
 
-  /** Test of call method, of class Orthogonal. */
-  @Test
-  public void testCallInt() {
-    for (TestSession.Mode tfMode : tfModes)
-      assertThrows(
-          java.lang.IllegalArgumentException.class,
-          () -> {
-            try (TestSession session = TestSession.createTestSession(tfMode)) {
-              Ops tf = session.getTF();
-              Shape shape = Shape.of(10, 10);
-              Orthogonal<TInt32, TInt32> instance = new Orthogonal<>(tf, GAIN_VALUE, SEED);
-              instance.call(tf.constant(shape), TInt32.DTYPE);
-              fail("Should have thrown IllegalArgumentException on Integer type");
-            }
-          });
-  }
-
   /** Test of call method, of class Orthogonal. */
   @Test
   public void testCallFloat() {
@@ -173,8 +156,8 @@ public void testCallFloat() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(10, 10);
-        Orthogonal<TFloat32, TFloat32> instance = new Orthogonal<>(tf, GAIN_VALUE, SEED);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        Orthogonal<TFloat32> instance = new Orthogonal<>(tf, GAIN_VALUE, SEED);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -288,8 +271,8 @@ public void testCallDouble() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(10, 10);
-        Orthogonal<TFloat64, TFloat64> instance = new Orthogonal<>(tf, GAIN_VALUE, SEED);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Orthogonal<TFloat64> instance = new Orthogonal<>(tf, GAIN_VALUE, SEED);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -301,9 +284,9 @@ public void testReproducible() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
 
-        Orthogonal<TFloat64, TFloat64> instance = new Orthogonal<>(tf, GAIN_VALUE, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Orthogonal<TFloat64> instance = new Orthogonal<>(tf, GAIN_VALUE, SEED);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/RandomNormalTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/RandomNormalTest.java
index 50aec670503..3b2b3bdb243 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/RandomNormalTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/RandomNormalTest.java
@@ -52,9 +52,9 @@ public void testCalltestSoftmaxFloat() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        RandomNormal<TFloat32, TFloat32> instance =
+        RandomNormal<TFloat32> instance =
             new RandomNormal<>(tf, MEAN_VALUE, STDDEV_VALUE, SEED);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -68,9 +68,9 @@ public void testCalltestSoftmaxDouble() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        RandomNormal<TFloat64, TFloat64> instance =
+        RandomNormal<TFloat64> instance =
             new RandomNormal<>(tf, MEAN_VALUE, STDDEV_VALUE, SEED);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -82,10 +82,10 @@ public void testReproducible() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
 
-        RandomNormal<TFloat64, TFloat64> instance =
+        RandomNormal<TFloat64> instance =
             new RandomNormal<>(tf, MEAN_VALUE, STDDEV_VALUE, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/RandomUniformTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/RandomUniformTest.java
index d3f9af74209..23e26083a9b 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/RandomUniformTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/RandomUniformTest.java
@@ -53,9 +53,9 @@ public void testCallInt() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        RandomUniform<TInt32, TFloat64> instance =
+        RandomUniform<TInt32> instance =
             new RandomUniform<>(tf, MIN_VALUE, MAX_VALUE, SEED);
-        Operand<TInt32> operand = instance.call(tf.constant(shape), TInt32.DTYPE);
+        Operand<TInt32> operand = instance.call(tf.constant(shape), TInt32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -68,9 +68,9 @@ public void testCallFloat() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        RandomUniform<TFloat32, TFloat32> instance =
+        RandomUniform<TFloat32> instance =
             new RandomUniform<>(tf, MIN_VALUE, MAX_VALUE, SEED);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -84,9 +84,9 @@ public void testCallDouble() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        RandomUniform<TFloat64, TFloat64> instance =
+        RandomUniform<TFloat64> instance =
             new RandomUniform<>(tf, MIN_VALUE, MAX_VALUE, SEED);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -98,10 +98,10 @@ public void testReproducible() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
 
-        RandomUniform<TFloat64, TFloat64> instance =
+        RandomUniform<TFloat64> instance =
             new RandomUniform<>(tf, MIN_VALUE, MAX_VALUE, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/TruncatedNormalTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/TruncatedNormalTest.java
index 0a551df2f38..96bf915e199 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/TruncatedNormalTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/TruncatedNormalTest.java
@@ -52,9 +52,9 @@ public void testCallFloat() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        TruncatedNormal<TFloat32, TFloat32> instance =
+        TruncatedNormal<TFloat32> instance =
             new TruncatedNormal<>(tf, MEAN_VALUE, STDDEV_VALUE, SEED);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -68,9 +68,9 @@ public void testCallDouble() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        TruncatedNormal<TFloat64, TFloat64> instance =
+        TruncatedNormal<TFloat64> instance =
             new TruncatedNormal<>(tf, MEAN_VALUE, STDDEV_VALUE, SEED);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -82,10 +82,10 @@ public void testReproducible() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
 
-        TruncatedNormal<TFloat64, TFloat64> instance =
+        TruncatedNormal<TFloat64> instance =
             new TruncatedNormal<>(tf, MEAN_VALUE, STDDEV_VALUE, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/VarianceScalingTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/VarianceScalingTest.java
index 77e0dd7afc7..159affb07e2 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/VarianceScalingTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/VarianceScalingTest.java
@@ -50,14 +50,14 @@ public void testCallFloat1FanInTruncatedNormal() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        VarianceScaling<TFloat32, TFloat32> instance =
+        VarianceScaling<TFloat32> instance =
             new VarianceScaling<>(
                 tf,
                 1.0,
                 VarianceScaling.Mode.FAN_IN,
                 VarianceScaling.Distribution.TRUNCATED_NORMAL,
                 SEED);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -71,14 +71,14 @@ public void testCallDouble1FanInTruncatedNormal() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        VarianceScaling<TFloat64, TFloat64> instance =
+        VarianceScaling<TFloat64> instance =
             new VarianceScaling<>(
                 tf,
                 1.0,
                 VarianceScaling.Mode.FAN_IN,
                 VarianceScaling.Distribution.TRUNCATED_NORMAL,
                 SEED);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -91,14 +91,14 @@ public void testCallFloat1FanInNormal() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        VarianceScaling<TFloat32, TFloat32> instance =
+        VarianceScaling<TFloat32> instance =
             new VarianceScaling<>(
                 tf,
                 1.0,
                 VarianceScaling.Mode.FAN_IN,
                 VarianceScaling.Distribution.NORMAL,
                 SEED);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -112,14 +112,14 @@ public void testCalltestSoftmaxDouble1FanInNormal() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        VarianceScaling<TFloat64, TFloat64> instance =
+        VarianceScaling<TFloat64> instance =
             new VarianceScaling<>(
                 tf,
                 1.0,
                 VarianceScaling.Mode.FAN_IN,
                 VarianceScaling.Distribution.NORMAL,
                 SEED);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -132,10 +132,10 @@ public void testCalltestSoftmaxFloat1FanInUNIFORM() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        VarianceScaling<TFloat32, TFloat32> instance =
+        VarianceScaling<TFloat32> instance =
             new VarianceScaling<>(
                 tf, 1.0, VarianceScaling.Mode.FAN_IN, VarianceScaling.Distribution.UNIFORM, SEED);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -149,10 +149,10 @@ public void testCalltestSoftmaxDouble1FanInUNIFORM() {
       try (TestSession session = TestSession.createTestSession(tfMode)) {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
-        VarianceScaling<TFloat64, TFloat64> instance =
+        VarianceScaling<TFloat64> instance =
             new VarianceScaling<>(
                 tf, 1.0, VarianceScaling.Mode.FAN_IN, VarianceScaling.Distribution.UNIFORM, SEED);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -164,11 +164,11 @@ public void testReproducible1() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
 
-        VarianceScaling<TFloat64, TFloat64> instance =
+        VarianceScaling<TFloat64> instance =
             new VarianceScaling<>(
                 tf, 1.0, VarianceScaling.Mode.FAN_IN, VarianceScaling.Distribution.UNIFORM, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
@@ -180,15 +180,15 @@ public void testReproducible2() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
 
-        VarianceScaling<TFloat64, TFloat64> instance =
+        VarianceScaling<TFloat64> instance =
             new VarianceScaling<>(
                 tf,
                 1.0,
                 VarianceScaling.Mode.FAN_IN,
                 VarianceScaling.Distribution.NORMAL,
                 SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
@@ -200,15 +200,15 @@ public void testReproducible3() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
 
-        VarianceScaling<TFloat64, TFloat64> instance =
+        VarianceScaling<TFloat64> instance =
             new VarianceScaling<>(
                 tf,
                 1.0,
                 VarianceScaling.Mode.FAN_OUT,
                 VarianceScaling.Distribution.TRUNCATED_NORMAL,
                 SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
@@ -220,11 +220,11 @@ public void testReproducible4() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
 
-        VarianceScaling<TFloat64, TFloat64> instance =
+        VarianceScaling<TFloat64> instance =
             new VarianceScaling<>(
                 tf, 1.0, VarianceScaling.Mode.FAN_AVG, VarianceScaling.Distribution.UNIFORM, SEED);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/ZerosTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/ZerosTest.java
index 975678add19..21bad6ff360 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/ZerosTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/initializers/ZerosTest.java
@@ -49,7 +49,7 @@ public void testCallUInt() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
         Zeros<TUint8> instance = new Zeros<>(tf);
-        Operand<TUint8> operand = instance.call(tf.constant(shape), TUint8.DTYPE);
+        Operand<TUint8> operand = instance.call(tf.constant(shape), TUint8.class);
         session.evaluate(expected, operand);
       }
   }
@@ -63,7 +63,7 @@ public void testCallInt() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
         Zeros<TInt32> instance = new Zeros<>(tf);
-        Operand<TInt32> operand = instance.call(tf.constant(shape), TInt32.DTYPE);
+        Operand<TInt32> operand = instance.call(tf.constant(shape), TInt32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -77,7 +77,7 @@ public void testCallLong() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
         Zeros<TInt64> instance = new Zeros<>(tf);
-        Operand<TInt64> operand = instance.call(tf.constant(shape), TInt64.DTYPE);
+        Operand<TInt64> operand = instance.call(tf.constant(shape), TInt64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -91,7 +91,7 @@ public void testCallFloat() {
         Ops tf = session.getTF();
         Shape shape = Shape.of(2, 2);
         Zeros<TFloat32> instance = new Zeros<>(tf);
-        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.DTYPE);
+        Operand<TFloat32> operand = instance.call(tf.constant(shape), TFloat32.class);
         session.evaluate(expected, operand);
       }
   }
@@ -106,7 +106,7 @@ public void testCallDouble() {
         Shape shape = Shape.of(2, 2);
 
         Zeros<TFloat64> instance = new Zeros<>(tf);
-        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(expected, operand);
       }
   }
@@ -120,7 +120,7 @@ public void testCallString() {
         Shape shape = Shape.of(2, 2);
 
         Zeros<TString> instance = new Zeros<>(tf);
-        Operand<TString> operand = instance.call(tf.constant(shape), TString.DTYPE);
+        Operand<TString> operand = instance.call(tf.constant(shape), TString.class);
         session.evaluateString(operand, String::isEmpty);
       }
   }
@@ -135,7 +135,7 @@ public void testCallBool() {
         Shape shape = Shape.of(2, 2);
 
         Zeros<TBool> instance = new Zeros<>(tf);
-        Operand<TBool> operand = instance.call(tf.constant(shape), TBool.DTYPE);
+        Operand<TBool> operand = instance.call(tf.constant(shape), TBool.class);
         session.evaluate(expected, operand);
       }
   }
@@ -148,8 +148,8 @@ public void testReproducible() {
         Shape shape = Shape.of(2, 2);
 
         Zeros<TFloat64> instance = new Zeros<>(tf);
-        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.DTYPE);
-        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.DTYPE);
+        Operand<TFloat64> operand1 = instance.call(tf.constant(shape), TFloat64.class);
+        Operand<TFloat64> operand2 = instance.call(tf.constant(shape), TFloat64.class);
         session.evaluate(operand1, operand2);
       }
   }
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaDeltaTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaDeltaTest.java
index 339157c99d1..86a3200ac81 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaDeltaTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaDeltaTest.java
@@ -89,8 +89,8 @@ public void testBasic() {
           float[] var1Init = {3.0F, 4.0F};
           float[] fgrads = {grad, grad};
           Shape shape = Shape.of(var0Init.length);
-          Variable<TFloat32> var0 = tf.withName("var0").variable(shape, TFloat32.DTYPE);
-          Variable<TFloat32> var1 = tf.withName("var1").variable(shape, TFloat32.DTYPE);
+          Variable<TFloat32> var0 = tf.withName("var0").variable(shape, TFloat32.class);
+          Variable<TFloat32> var1 = tf.withName("var1").variable(shape, TFloat32.class);
 
           Assign<TFloat32> var0Initializer = tf.assign(var0, tf.constant(var0Init));
           Assign<TFloat32> var1Initializer = tf.assign(var1, tf.constant(var1Init));
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradDATest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradDATest.java
index ef9053ff1eb..d5b2657a4fc 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradDATest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradDATest.java
@@ -64,8 +64,8 @@ public void testBasic() {
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
-      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
-      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.class);
+      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.class);
 
       Assign<TFloat32> var0Initializer = tf.assign(var0, tf.constant(var0Init));
       Assign<TFloat32> var1Initializer = tf.assign(var1, tf.constant(var1Init));
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradTest.java
index 03717083efc..8182dc5b00d 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdaGradTest.java
@@ -79,8 +79,8 @@ public void testBasic() {
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
-      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
-      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.class);
+      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.class);
 
       Assign<TFloat32> var0Initializer = tf.assign(var0, tf.constant(var0Init));
       Assign<TFloat32> var1Initializer = tf.assign(var1, tf.constant(var1Init));
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java
index d2592026f12..49154882a0f 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamTest.java
@@ -16,7 +16,6 @@
 
 import org.junit.jupiter.api.*;
 import org.tensorflow.Graph;
-import org.tensorflow.Tensor;
 import org.tensorflow.framework.utils.ND;
 import org.tensorflow.framework.utils.TestSession;
 import org.tensorflow.ndarray.FloatNdArray;
@@ -80,8 +79,8 @@ public void testBasic() {
       Ops tf = instance.getTF();
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
-      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
-      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.class);
+      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.class);
 
       Assign<TFloat32> var0Initializer = tf.assign(var0, tf.constant(var0Init));
       Assign<TFloat32> var1Initializer = tf.assign(var1, tf.constant(var1Init));
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamaxTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamaxTest.java
index ac322f952db..60c17674dfe 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamaxTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/AdamaxTest.java
@@ -16,7 +16,6 @@
 
 import org.junit.jupiter.api.*;
 import org.tensorflow.Graph;
-import org.tensorflow.Tensor;
 import org.tensorflow.framework.utils.ND;
 import org.tensorflow.framework.utils.TestSession;
 import org.tensorflow.ndarray.FloatNdArray;
@@ -101,8 +100,8 @@ public void testBasic() {
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
-      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
-      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.class);
+      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.class);
 
       Assign<TFloat32> var0Initializer = tf.assign(var0, tf.constant(var0Init));
       Assign<TFloat32> var1Initializer = tf.assign(var1, tf.constant(var1Init));
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/FtrlTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/FtrlTest.java
index 597f8e52bcd..7698d76f957 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/FtrlTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/FtrlTest.java
@@ -76,8 +76,8 @@ public void testFtrlWithL1L2L2Shrinkage() {
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
-      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
-      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.class);
+      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.class);
 
       Assign<TFloat32> var0Initializer = tf.assign(var0, tf.constant(var0Init));
       Assign<TFloat32> var1Initializer = tf.assign(var1, tf.constant(var1Init));
@@ -141,8 +141,8 @@ public void testFtrlWithL1() {
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
-      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
-      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.class);
+      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.class);
 
       Assign<TFloat32> var0Initializer = tf.assign(var0, tf.constant(var0Init));
       Assign<TFloat32> var1Initializer = tf.assign(var1, tf.constant(var1Init));
@@ -207,8 +207,8 @@ public void testFtrlWithL1L2() {
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
-      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
-      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.class);
+      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.class);
 
       Assign<TFloat32> var0Initializer = tf.assign(var0, tf.constant(var0Init));
       Assign<TFloat32> var1Initializer = tf.assign(var1, tf.constant(var1Init));
@@ -273,8 +273,8 @@ public void doTestFtrlwithoutRegularization() {
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
-      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
-      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.class);
+      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.class);
 
       Assign<TFloat32> var0Initializer = tf.assign(var0, tf.constant(var0Init));
       Assign<TFloat32> var1Initializer = tf.assign(var1, tf.constant(var1Init));
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/GradientDescentTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/GradientDescentTest.java
index 4362c54d815..aefcc537979 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/GradientDescentTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/GradientDescentTest.java
@@ -61,8 +61,8 @@ public void testBasic() {
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
-      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
-      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.class);
+      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.class);
 
       Assign<TFloat32> var0Initializer = tf.assign(var0, tf.constant(var0Init));
       Assign<TFloat32> var1Initializer = tf.assign(var1, tf.constant(var1Init));
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/MomentumTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/MomentumTest.java
index 3649fbd8287..80a8d9b5fd6 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/MomentumTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/MomentumTest.java
@@ -77,8 +77,8 @@ public void testBasic() {
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
-      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
-      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.class);
+      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.class);
 
       Assign<TFloat32> var0Initializer = tf.assign(var0, tf.constant(var0Init));
       Assign<TFloat32> var1Initializer = tf.assign(var1, tf.constant(var1Init));
@@ -130,8 +130,8 @@ public void testMomentum() {
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
-      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
-      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.class);
+      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.class);
 
       Assign<TFloat32> var0Initializer = tf.assign(var0, tf.constant(var0Init));
       Assign<TFloat32> var1Initializer = tf.assign(var1, tf.constant(var1Init));
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/NadamTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/NadamTest.java
index e064e793a37..849f2fbfec1 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/NadamTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/NadamTest.java
@@ -16,7 +16,6 @@
 
 import org.junit.jupiter.api.*;
 import org.tensorflow.Graph;
-import org.tensorflow.Tensor;
 import org.tensorflow.framework.utils.ND;
 import org.tensorflow.framework.utils.TestSession;
 import org.tensorflow.ndarray.FloatNdArray;
@@ -102,8 +101,8 @@ public void testBasic() {
 
       Shape shape0 = Shape.of(var0Init.length);
       Shape shape1 = Shape.of(var1Init.length);
-      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
-      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+      Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.class);
+      Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.class);
 
       Assign<TFloat32> var0Initializer = tf.assign(var0, tf.constant(var0Init));
       Assign<TFloat32> var1Initializer = tf.assign(var1, tf.constant(var1Init));
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/RMSPropTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/RMSPropTest.java
index 202fb21ef68..3b002cd1dbe 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/RMSPropTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/optimizers/RMSPropTest.java
@@ -87,8 +87,8 @@ public void testDense() {
 
         Shape shape0 = Shape.of(var0Init.length);
         Shape shape1 = Shape.of(var1Init.length);
-        Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.DTYPE);
-        Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.DTYPE);
+        Variable<TFloat32> var0 = tf.withName("var0").variable(shape0, TFloat32.class);
+        Variable<TFloat32> var1 = tf.withName("var1").variable(shape1, TFloat32.class);
 
         Assign<TFloat32> var0Initializer = tf.assign(var0, tf.constant(var0Init));
         Assign<TFloat32> var1Initializer = tf.assign(var1, tf.constant(var1Init));
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/EagerTestSession.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/EagerTestSession.java
index 1f5f2f16053..7884308c9fb 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/EagerTestSession.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/EagerTestSession.java
@@ -84,8 +84,8 @@ public EagerSession getEagerSession() {
   /** {@inheritDoc} */
   @Override
   public <T extends TNumber> void evaluate(double expected, Operand<T> input) {
-    DataType<T> dtype = input.asOutput().dataType();
-    if (dtype == TFloat32.DTYPE) {
+    Class<T> inputType = input.type();
+    if (inputType == TFloat32.class) {
       Operand<TFloat32> o = (Operand<TFloat32>) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -95,7 +95,7 @@ public <T extends TNumber> void evaluate(double expected, Operand<T> input) {
       }
       index.set(0);
       o.asTensor().scalars().forEach(f -> assertEquals(expected, f.getFloat(), epsilon));
-    } else if (dtype == TFloat64.DTYPE) {
+    } else if (inputType == TFloat64.class) {
       Operand<TFloat64> o = (Operand<TFloat64>) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -105,7 +105,7 @@ public <T extends TNumber> void evaluate(double expected, Operand<T> input) {
       }
       index.set(0);
       o.asTensor().scalars().forEach(f -> assertEquals(expected, f.getDouble(), epsilon));
-    } else if (dtype == TInt32.DTYPE) {
+    } else if (inputType == TInt32.class) {
       Operand<TInt32> o = (Operand<TInt32>) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -115,7 +115,7 @@ public <T extends TNumber> void evaluate(double expected, Operand<T> input) {
       }
       index.set(0);
       o.asTensor().scalars().forEach(f -> assertEquals((int) expected, f.getInt()));
-    } else if (dtype == TInt64.DTYPE) {
+    } else if (inputType == TInt64.class) {
       Operand<TInt64> o = (Operand<TInt64>) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -125,7 +125,7 @@ public <T extends TNumber> void evaluate(double expected, Operand<T> input) {
       }
       index.set(0);
       o.asTensor().scalars().forEach(f -> assertEquals((long) expected, f.getLong()));
-    } else if (dtype == TUint8.DTYPE) {
+    } else if (inputType == TUint8.class) {
       Operand<TUint8> o = (Operand<TUint8>) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -146,8 +146,8 @@ public <T extends TNumber> void evaluate(Number[] expected, Output<T> input) {
         expected.length,
         size,
         () -> String.format("expected length (%d) != to input length (%d)", expected.length, size));
-    DataType<T> dtype = input.dataType();
-    if (dtype == TFloat32.DTYPE) {
+    Class<T> inputType = input.type();
+    if (inputType == TFloat32.class) {
       Output<TFloat32> o = (Output<TFloat32>) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -162,7 +162,7 @@ public <T extends TNumber> void evaluate(Number[] expected, Output<T> input) {
               f ->
                   assertEquals(
                       expected[index.getAndIncrement()].floatValue(), f.getFloat(), epsilon));
-    } else if (dtype == TFloat64.DTYPE) {
+    } else if (inputType == TFloat64.class) {
       Output<TFloat64> o = (Output<TFloat64>) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -177,7 +177,7 @@ public <T extends TNumber> void evaluate(Number[] expected, Output<T> input) {
               f ->
                   assertEquals(
                       expected[index.getAndIncrement()].doubleValue(), f.getDouble(), epsilon));
-    } else if (dtype == TInt32.DTYPE) {
+    } else if (inputType == TInt32.class) {
       Output<TInt32> o = (Output<TInt32>) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -189,7 +189,7 @@ public <T extends TNumber> void evaluate(Number[] expected, Output<T> input) {
       o.asTensor()
           .scalars()
           .forEach(f -> assertEquals(expected[index.getAndIncrement()].intValue(), f.getInt()));
-    } else if (dtype == TInt64.DTYPE) {
+    } else if (inputType == TInt64.class) {
       Output<TInt64> o = (Output<TInt64>) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -201,7 +201,7 @@ public <T extends TNumber> void evaluate(Number[] expected, Output<T> input) {
       o.asTensor()
           .scalars()
           .forEach(f -> assertEquals(expected[index.getAndIncrement()].longValue(), f.getLong()));
-    } else if (dtype == TUint8.DTYPE) {
+    } else if (inputType == TUint8.class) {
       Output<TUint8> o = (Output<TUint8>) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -219,8 +219,8 @@ public <T extends TNumber> void evaluate(Number[] expected, Output<T> input) {
   /** {@inheritDoc} */
   @Override
   public <T extends TType> void evaluate(FloatNdArray expected, Output<T> input) {
-    DataType<T> dtype = input.dataType();
-    if (dtype == TFloat32.DTYPE) {
+    Class<T> inputType = input.type();
+    if (inputType == TFloat32.class) {
       Output<TFloat32> o = (Output<TFloat32>) input;
       AtomicLong index = new AtomicLong();
       if (debug) {
@@ -233,7 +233,7 @@ public <T extends TType> void evaluate(FloatNdArray expected, Output<T> input) {
           .scalars()
           .forEach(
               f -> assertEquals(expected.getFloat(index.getAndIncrement()), f.getFloat(), epsilon));
-    } else if (dtype == TFloat64.DTYPE) {
+    } else if (inputType == TFloat64.class) {
       Output<TFloat64> o = (Output<TFloat64>) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -247,7 +247,7 @@ public <T extends TType> void evaluate(FloatNdArray expected, Output<T> input) {
           .forEach(
               f ->
                   assertEquals(expected.getFloat(index.getAndIncrement()), f.getDouble(), epsilon));
-    } else if (dtype == TInt32.DTYPE) {
+    } else if (inputType == TInt32.class) {
       Output<TInt32> o = (Output<TInt32>) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -259,7 +259,7 @@ public <T extends TType> void evaluate(FloatNdArray expected, Output<T> input) {
       for (IntNdArray f : o.asTensor().scalars()) {
         assertEquals((int) expected.getFloat(index.getAndIncrement()), f.getInt());
       }
-    } else if (dtype == TInt64.DTYPE) {
+    } else if (inputType == TInt64.class) {
       Output<TInt64> o = (Output<TInt64>) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -272,7 +272,7 @@ public <T extends TType> void evaluate(FloatNdArray expected, Output<T> input) {
           .scalars()
           .forEach(
               f -> assertEquals((long) expected.getFloat(index.getAndIncrement()), f.getLong()));
-    } else if (dtype == TUint8.DTYPE) {
+    } else if (inputType == TUint8.class) {
       Output<TUint8> o = (Output<TUint8>) input;
       AtomicInteger index = new AtomicInteger();
       if (debug) {
@@ -320,9 +320,9 @@ public void evaluateString(Output<TString> input, Predicate<String> predicate) {
   @Override
   public <T extends TType> void evaluate(Output<T> input, Predicate<Number> predicate) {
     AtomicInteger index = new AtomicInteger();
-    DataType<T> dtype = input.asOutput().dataType();
+    Class<T> inputType = input.type();
     boolean isScalar = input.shape().equals(Shape.scalar());
-    if (dtype == TFloat32.DTYPE) {
+    if (inputType == TFloat32.class) {
       Output<TFloat32> o = (Output<TFloat32>) input;
       if (debug) {
         if (isScalar) {
@@ -346,7 +346,7 @@ public <T extends TType> void evaluate(Output<T> input, Predicate<Number> predic
             .scalars()
             .forEachIndexed((idx, f) -> assertTrue(predicate.test(o.asTensor().getFloat())));
       }
-    } else if (dtype == TFloat64.DTYPE) {
+    } else if (inputType == TFloat64.class) {
       Output<TFloat64> o = (Output<TFloat64>) input;
       if (debug) {
         if (isScalar) {
@@ -370,7 +370,7 @@ public <T extends TType> void evaluate(Output<T> input, Predicate<Number> predic
             .scalars()
             .forEachIndexed((idx, f) -> assertTrue(predicate.test(o.asTensor().getDouble())));
       }
-    } else if (dtype == TFloat16.DTYPE) {
+    } else if (inputType == TFloat16.class) {
       Output<TFloat16> o = (Output<TFloat16>) input;
       if (debug) {
         if (isScalar) {
@@ -394,7 +394,7 @@ public <T extends TType> void evaluate(Output<T> input, Predicate<Number> predic
             .scalars()
             .forEachIndexed((idx, f) -> assertTrue(predicate.test(o.asTensor().getFloat())));
       }
-    } else if (dtype == TInt32.DTYPE) {
+    } else if (inputType == TInt32.class) {
       Output<TInt32> o = (Output<TInt32>) input;
       if (debug) {
         if (isScalar) {
@@ -418,7 +418,7 @@ public <T extends TType> void evaluate(Output<T> input, Predicate<Number> predic
             .scalars()
             .forEachIndexed((idx, f) -> assertTrue(predicate.test(o.asTensor().getInt())));
       }
-    } else if (dtype == TInt64.DTYPE) {
+    } else if (inputType == TInt64.class) {
       Output<TInt64> o = (Output<TInt64>) input;
       if (debug) {
         if (isScalar) {
@@ -442,7 +442,7 @@ public <T extends TType> void evaluate(Output<T> input, Predicate<Number> predic
             .scalars()
             .forEachIndexed((idx, f) -> assertTrue(predicate.test(o.asTensor().getLong())));
       }
-    } else if (dtype == TUint8.DTYPE) {
+    } else if (inputType == TUint8.class) {
       Output<TUint8> o = (Output<TUint8>) input;
       if (debug) {
         if (isScalar) {
@@ -467,7 +467,7 @@ public <T extends TType> void evaluate(Output<T> input, Predicate<Number> predic
             .forEachIndexed((idx, f) -> assertTrue(predicate.test(o.asTensor().getByte())));
       }
     } else {
-      fail("Unexpected DataType: " + dtype);
+      fail("Unexpected Class: " + inputType);
     }
   }
 
@@ -522,9 +522,9 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
         : String.format(
             "expected shape (%s) != to input shape (%s)",
             expected.shape().toString(), input.shape().toString());
-    DataType<T> dtype = input.asOutput().dataType();
+    Class<T> inputType = input.asOutput().type();
     boolean isScalar = input.shape().equals(Shape.scalar());
-    if (dtype == TFloat32.DTYPE) {
+    if (inputType == TFloat32.class) {
       Output<TFloat32> x = (Output<TFloat32>) expected;
       Output<TFloat32> o = (Output<TFloat32>) input;
       AtomicInteger index = new AtomicInteger();
@@ -550,7 +550,7 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
             .forEachIndexed(
                 (idx, f) -> assertEquals(x.asTensor().getFloat(idx), f.getFloat(), epsilon));
       }
-    } else if (dtype == TFloat64.DTYPE) {
+    } else if (inputType == TFloat64.class) {
       Output<TFloat64> x = (Output<TFloat64>) expected;
       Output<TFloat64> o = (Output<TFloat64>) input;
       AtomicInteger index = new AtomicInteger();
@@ -576,7 +576,7 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
             .forEachIndexed(
                 (idx, f) -> assertEquals(x.asTensor().getDouble(idx), f.getDouble(), epsilon));
       }
-    } else if (dtype == TInt32.DTYPE) {
+    } else if (inputType == TInt32.class) {
       Output<TInt32> x = (Output<TInt32>) expected;
       Output<TInt32> o = (Output<TInt32>) input;
       AtomicInteger index = new AtomicInteger();
@@ -601,7 +601,7 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
             .scalars()
             .forEachIndexed((idx, f) -> assertEquals(x.asTensor().getInt(idx), f.getInt()));
       }
-    } else if (dtype == TInt64.DTYPE) {
+    } else if (inputType == TInt64.class) {
       Output<TInt64> x = (Output<TInt64>) expected;
       Output<TInt64> o = (Output<TInt64>) input;
       AtomicInteger index = new AtomicInteger();
@@ -626,7 +626,7 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
             .scalars()
             .forEachIndexed((idx, f) -> assertEquals(x.asTensor().getLong(idx), f.getLong()));
       }
-    } else if (dtype == TUint8.DTYPE) {
+    } else if (inputType == TUint8.class) {
       Output<TUint8> x = (Output<TUint8>) expected;
       Output<TUint8> o = (Output<TUint8>) input;
       AtomicInteger index = new AtomicInteger();
@@ -651,7 +651,7 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
             .scalars()
             .forEachIndexed((idx, f) -> assertEquals(x.asTensor().getByte(idx), f.getByte()));
       }
-    } else if (dtype == TString.DTYPE) {
+    } else if (inputType == TString.class) {
       Output<TString> x = (Output<TString>) expected;
       Output<TString> o = (Output<TString>) input;
       AtomicInteger index = new AtomicInteger();
@@ -676,7 +676,7 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
             .scalars()
             .forEachIndexed((idx, f) -> assertEquals(x.asTensor().getObject(idx), f.getObject()));
       }
-    } else if (dtype == TBool.DTYPE) {
+    } else if (inputType == TBool.class) {
       Output<TBool> x = (Output<TBool>) expected;
       Output<TBool> o = (Output<TBool>) input;
       AtomicInteger index = new AtomicInteger();
@@ -707,51 +707,51 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
   /** {@inheritDoc} */
   @Override
   public <T extends TType> void print(PrintWriter writer, Output<T> input) {
-    DataType<T> dtype = input.asOutput().dataType();
-    if (dtype == TFloat32.DTYPE) {
+    Class<T> inputType = input.asOutput().type();
+    if (inputType == TFloat32.class) {
       Output<TFloat32> o = (Output<TFloat32>) input;
       AtomicInteger index = new AtomicInteger();
       o.asTensor()
           .scalars()
           .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()));
-    } else if (dtype == TFloat64.DTYPE) {
+    } else if (inputType == TFloat64.class) {
       Output<TFloat64> o = (Output<TFloat64>) input;
       AtomicInteger index = new AtomicInteger();
       o.asTensor()
           .scalars()
           .forEach(f -> System.out.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()));
-    } else if (dtype == TInt32.DTYPE) {
+    } else if (inputType == TInt32.class) {
       Output<TInt32> o = (Output<TInt32>) input;
       AtomicInteger index = new AtomicInteger();
       o.asTensor()
           .scalars()
           .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getInt()));
-    } else if (dtype == TInt64.DTYPE) {
+    } else if (inputType == TInt64.class) {
       Output<TInt64> o = (Output<TInt64>) input;
       AtomicInteger index = new AtomicInteger();
       o.asTensor()
           .scalars()
           .forEach(f -> System.out.printf("%d). %d\n", index.getAndIncrement(), f.getLong()));
-    } else if (dtype == TUint8.DTYPE) {
+    } else if (inputType == TUint8.class) {
       Output<TUint8> o = (Output<TUint8>) input;
       AtomicInteger index = new AtomicInteger();
       o.asTensor()
           .scalars()
           .forEach(f -> System.out.printf("%d). %x\n", index.getAndIncrement(), f.getByte()));
-    } else if (dtype == TString.DTYPE) {
+    } else if (inputType == TString.class) {
       Output<TString> o = (Output<TString>) input;
       AtomicInteger index = new AtomicInteger();
       o.asTensor()
           .scalars()
           .forEach(f -> System.out.printf("%d). %s\n", index.getAndIncrement(), f.getObject()));
-    } else if (dtype == TBool.DTYPE) {
+    } else if (inputType == TBool.class) {
       Output<TBool> o = (Output<TBool>) input;
       AtomicInteger index = new AtomicInteger();
       o.asTensor()
           .scalars()
           .forEach(f -> System.out.printf("%d). %b\n", index.getAndIncrement(), f.getBoolean()));
     } else {
-      writer.println("Unexpected DataType: " + dtype);
+      writer.println("Unexpected Class: " + inputType);
     }
     writer.flush();
   }
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/GraphTestSession.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/GraphTestSession.java
index 6df79a4432a..33c4e064e69 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/GraphTestSession.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/utils/GraphTestSession.java
@@ -126,8 +126,8 @@ public void run(Op op) {
    */
   @Override
   public <T extends TNumber> void evaluate(double expected, Operand<T> input) {
-    DataType<T> dtype = input.asOutput().dataType();
-    if (dtype == TFloat32.DTYPE) {
+    Class<T> inputType = input.type();
+    if (inputType == TFloat32.class) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (TFloat32 result =
@@ -142,7 +142,7 @@ public <T extends TNumber> void evaluate(double expected, Operand<T> input) {
           (TFloat32)this.getGraphSession().runner().fetch(input).run().get(0)) {
         result.scalars().forEach(f -> assertEquals((float) expected, f.getFloat(), epsilon));
       }
-    } else if (dtype == TFloat64.DTYPE) {
+    } else if (inputType == TFloat64.class) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (TFloat64 result =
@@ -157,7 +157,7 @@ public <T extends TNumber> void evaluate(double expected, Operand<T> input) {
           (TFloat64)this.getGraphSession().runner().fetch(input).run().get(0)) {
         result.scalars().forEach(f -> assertEquals(expected, f.getDouble(), epsilon));
       }
-    } else if (dtype == TInt32.DTYPE) {
+    } else if (inputType == TInt32.class) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (TInt32 result =
@@ -172,7 +172,7 @@ public <T extends TNumber> void evaluate(double expected, Operand<T> input) {
           (TInt32)this.getGraphSession().runner().fetch(input).run().get(0)) {
         result.scalars().forEach(f -> assertEquals((int) expected, f.getInt()));
       }
-    } else if (dtype == TInt64.DTYPE) {
+    } else if (inputType == TInt64.class) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (TInt64 result =
@@ -187,7 +187,7 @@ public <T extends TNumber> void evaluate(double expected, Operand<T> input) {
           (TInt64)this.getGraphSession().runner().fetch(input).run().get(0)) {
         result.scalars().forEach(f -> assertEquals((long) expected, f.getLong()));
       }
-    } else if (dtype == TUint8.DTYPE) {
+    } else if (inputType == TUint8.class) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (TUint8 result =
@@ -203,7 +203,7 @@ public <T extends TNumber> void evaluate(double expected, Operand<T> input) {
         result.scalars().forEach(f -> assertEquals((long) expected, f.getByte()));
       }
     } else {
-      fail("Unexpected DataType: " + dtype);
+      fail("Unexpected type class: " + inputType);
     }
   }
 
@@ -217,8 +217,8 @@ public <T extends TNumber> void evaluate(Number[] expected, Output<T> input) {
         expected.length,
         size,
         () -> String.format("expected length (%d) != to input length (%d)", expected.length, size));
-    DataType<T> dtype = input.asOutput().dataType();
-    if (dtype == TFloat32.DTYPE) {
+    Class<T> inputType = input.type();
+    if (inputType == TFloat32.class) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (TFloat32 result =
@@ -238,7 +238,7 @@ public <T extends TNumber> void evaluate(Number[] expected, Output<T> input) {
                     assertEquals(
                         expected[index.getAndIncrement()].floatValue(), f.getFloat(), epsilon));
       }
-    } else if (dtype == TFloat64.DTYPE) {
+    } else if (inputType == TFloat64.class) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (TFloat64 result =
@@ -258,7 +258,7 @@ public <T extends TNumber> void evaluate(Number[] expected, Output<T> input) {
                     assertEquals(
                         expected[index.getAndIncrement()].doubleValue(), f.getDouble(), epsilon));
       }
-    } else if (dtype == TInt32.DTYPE) {
+    } else if (inputType == TInt32.class) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (TInt32 result =
@@ -275,7 +275,7 @@ public <T extends TNumber> void evaluate(Number[] expected, Output<T> input) {
             .scalars()
             .forEach(f -> assertEquals(expected[index.getAndIncrement()].intValue(), f.getInt()));
       }
-    } else if (dtype == TInt64.DTYPE) {
+    } else if (inputType == TInt64.class) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (TInt64 result =
@@ -292,7 +292,7 @@ public <T extends TNumber> void evaluate(Number[] expected, Output<T> input) {
             .scalars()
             .forEach(f -> assertEquals(expected[index.getAndIncrement()].longValue(), f.getLong()));
       }
-    } else if (dtype == TUint8.DTYPE) {
+    } else if (inputType == TUint8.class) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (TUint8 result =
@@ -310,7 +310,7 @@ public <T extends TNumber> void evaluate(Number[] expected, Output<T> input) {
             .forEach(f -> assertEquals(expected[index.getAndIncrement()].longValue(), f.getByte()));
       }
     } else {
-      fail("Unexpected DataType: " + dtype);
+      fail("Unexpected type class: " + inputType);
     }
   }
 
@@ -319,8 +319,8 @@ public <T extends TNumber> void evaluate(Number[] expected, Output<T> input) {
    */
   @Override
   public <T extends TType> void evaluate(FloatNdArray expected, Output<T> input) {
-    DataType<T> dtype = input.asOutput().dataType();
-    if (dtype == TFloat32.DTYPE) {
+    Class<T> inputType = input.type();
+    if (inputType == TFloat32.class) {
       AtomicLong index = new AtomicLong();
       if (debug) {
         try (TFloat32 result =
@@ -340,7 +340,7 @@ public <T extends TType> void evaluate(FloatNdArray expected, Output<T> input) {
                     assertEquals(
                         expected.getFloat(index.getAndIncrement()), f.getFloat(), epsilon));
       }
-    } else if (dtype == TFloat64.DTYPE) {
+    } else if (inputType == TFloat64.class) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (TFloat64 result =
@@ -360,7 +360,7 @@ public <T extends TType> void evaluate(FloatNdArray expected, Output<T> input) {
                     assertEquals(
                         expected.getFloat(index.getAndIncrement()), f.getDouble(), epsilon));
       }
-    } else if (dtype == TInt32.DTYPE) {
+    } else if (inputType == TInt32.class) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (TInt32 result =
@@ -378,7 +378,7 @@ public <T extends TType> void evaluate(FloatNdArray expected, Output<T> input) {
             .forEach(
                 f -> assertEquals((int) expected.getFloat(index.getAndIncrement()), f.getInt()));
       }
-    } else if (dtype == TInt64.DTYPE) {
+    } else if (inputType == TInt64.class) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (TInt64 result =
@@ -396,7 +396,7 @@ public <T extends TType> void evaluate(FloatNdArray expected, Output<T> input) {
             .forEach(
                 f -> assertEquals((long) expected.getFloat(index.getAndIncrement()), f.getLong()));
       }
-    } else if (dtype == TUint8.DTYPE) {
+    } else if (inputType == TUint8.class) {
       AtomicInteger index = new AtomicInteger();
       if (debug) {
         try (TUint8 result =
@@ -415,7 +415,7 @@ public <T extends TType> void evaluate(FloatNdArray expected, Output<T> input) {
                 f -> assertEquals((long) expected.getFloat(index.getAndIncrement()), f.getByte()));
       }
     } else {
-      fail("Unexpected DataType: " + dtype);
+      fail("Unexpected type class: " + inputType);
     }
   }
 
@@ -485,15 +485,15 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
         "expected shape (%s) != to input shape (%s)",
         expected.shape().toString(), input.shape().toString());
     AtomicInteger index = new AtomicInteger();
-    DataType<T> dtype = input.asOutput().dataType();
-    if (!dtype.equals(expected.dataType())) {
+    Class<T> inputType = input.type();
+    if (!inputType.equals(expected.type())) {
       throw new IllegalArgumentException(
           String.format(
               "Both data type must be equal, inout = %s, expected = %s",
-              dtype, expected.dataType()));
+              inputType, expected.dataType()));
     }
     boolean isScalar = input.shape().equals(Shape.scalar());
-    if (dtype == TFloat32.DTYPE) {
+    if (inputType == TFloat32.class) {
       final Output<TFloat32> finalExpected = (Output<TFloat32>) expected;
       if (debug) {
         try (TFloat32 result =
@@ -531,7 +531,7 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
                       assertEquals(expectedResult.getFloat(idx), f.getFloat(), epsilon));
         }
       }
-    } else if (dtype == TFloat64.DTYPE) {
+    } else if (inputType == TFloat64.class) {
       final Output<TFloat64> finalExpected = (Output<TFloat64>) expected;
       if (debug) {
         try (TFloat64 result =
@@ -569,7 +569,7 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
                       assertEquals(expectedResult.getDouble(idx), f.getDouble(), epsilon));
         }
       }
-    } else if (dtype == TFloat16.DTYPE) {
+    } else if (inputType == TFloat16.class) {
       final Output<TFloat16> finalExpected = (Output<TFloat16>) expected;
       if (debug) {
         try (TFloat16 result =
@@ -607,7 +607,7 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
                       assertEquals(expectedResult.getFloat(idx), f.getFloat(), epsilon));
         }
       }
-    } else if (dtype == TInt32.DTYPE) {
+    } else if (inputType == TInt32.class) {
       final Output<TInt32> finalExpected = (Output<TInt32>) expected;
       if (debug) {
         try (TInt32 result =
@@ -642,7 +642,7 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
                   (idx, f) -> assertEquals(expectedResult.getInt(idx), f.getInt(), epsilon));
         }
       }
-    } else if (dtype == TInt64.DTYPE) {
+    } else if (inputType == TInt64.class) {
       final Output<TInt64> finalExpected = (Output<TInt64>) expected;
       if (debug) {
         try (TInt64 result =
@@ -680,7 +680,7 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
                       assertEquals(expectedResult.getLong(idx), f.getLong(), epsilon));
         }
       }
-    } else if (dtype == TUint8.DTYPE) {
+    } else if (inputType == TUint8.class) {
       final Output<TUint8> finalExpected = (Output<TUint8>) expected;
       if (debug) {
         try (TUint8 result =
@@ -718,7 +718,7 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
                       assertEquals(expectedResult.getByte(idx), f.getByte(), epsilon));
         }
       }
-    } else if (dtype == TBool.DTYPE) {
+    } else if (inputType == TBool.class) {
       final Output<TBool> finalExpected = (Output<TBool>) expected;
       if (debug) {
         try (TBool result =
@@ -755,7 +755,7 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
                   (idx, f) -> assertEquals(expectedResult.getBoolean(idx), f.getBoolean()));
         }
       }
-    } else if (dtype == TString.DTYPE) {
+    } else if (inputType == TString.class) {
       final Output<TString> finalExpected = (Output<TString>) expected;
       if (debug) {
         try (TString result =
@@ -793,7 +793,7 @@ public <T extends TType> void evaluate(Output<T> expected, Output<T> input) {
         }
       }
     } else {
-      fail("Unexpected DataType: " + dtype);
+      fail("Unexpected type class: " + inputType);
     }
   }
 
@@ -841,9 +841,9 @@ public void evaluateString(Output<TString> input, Predicate<String> predicate) {
   @Override
   public <T extends TType> void evaluate(Output<T> input, Predicate<Number> predicate) {
     AtomicInteger index = new AtomicInteger();
-    DataType<T> dtype = input.asOutput().dataType();
+    Class<T> inputType = input.type();
     boolean isScalar = input.shape().equals(Shape.scalar());
-    if (dtype == TFloat32.DTYPE) {
+    if (inputType == TFloat32.class) {
       if (debug) {
         try (TFloat32 result =
             (TFloat32)this.getGraphSession().runner().fetch(input).run().get(0)) {
@@ -873,7 +873,7 @@ public <T extends TType> void evaluate(Output<T> input, Predicate<Number> predic
               .forEachIndexed((idx, f) -> assertTrue(predicate.test(result.getFloat())));
         }
       }
-    } else if (dtype == TFloat64.DTYPE) {
+    } else if (inputType == TFloat64.class) {
       if (debug) {
         try (TFloat64 result =
             (TFloat64)this.getGraphSession().runner().fetch(input).run().get(0)) {
@@ -903,7 +903,7 @@ public <T extends TType> void evaluate(Output<T> input, Predicate<Number> predic
               .forEachIndexed((idx, f) -> assertTrue(predicate.test(result.getDouble())));
         }
       }
-    } else if (dtype == TInt32.DTYPE) {
+    } else if (inputType == TInt32.class) {
       if (debug) {
         try (TInt32 result =
             (TInt32)this.getGraphSession().runner().fetch(input).run().get(0)) {
@@ -932,7 +932,7 @@ public <T extends TType> void evaluate(Output<T> input, Predicate<Number> predic
               .forEachIndexed((idx, f) -> assertTrue(predicate.test(result.getInt())));
         }
       }
-    } else if (dtype == TInt64.DTYPE) {
+    } else if (inputType == TInt64.class) {
       if (debug) {
         try (TInt64 result =
             (TInt64)this.getGraphSession().runner().fetch(input).run().get(0)) {
@@ -962,7 +962,7 @@ public <T extends TType> void evaluate(Output<T> input, Predicate<Number> predic
               .forEachIndexed((idx, f) -> assertTrue(predicate.test(result.getLong())));
         }
       }
-    } else if (dtype == TUint8.DTYPE) {
+    } else if (inputType == TUint8.class) {
       if (debug) {
         try (TUint8 result =
             (TUint8)this.getGraphSession().runner().fetch(input).run().get(0)) {
@@ -993,7 +993,7 @@ public <T extends TType> void evaluate(Output<T> input, Predicate<Number> predic
         }
       }
     } else {
-      fail("Unexpected DataType: " + dtype);
+      fail("Unexpected type class: " + inputType);
     }
   }
 
@@ -1004,8 +1004,8 @@ public <T extends TType> void evaluate(Output<T> input, Predicate<Number> predic
   public <T extends TType> void print(PrintWriter writer, Output<T> input) {
     boolean isScalar = input.shape().size() == 1;
 
-    DataType<T> dtype = input.dataType();
-    if (dtype == TFloat32.DTYPE) {
+    Class<T> inputType = input.type();
+    if (inputType == TFloat32.class) {
       AtomicInteger index = new AtomicInteger();
       try (TFloat32 result =
           (TFloat32)this.getGraphSession().runner().fetch(input).run().get(0)) {
@@ -1018,7 +1018,7 @@ public <T extends TType> void print(PrintWriter writer, Output<T> input) {
                   (idx, f) -> writer.printf("%d). %f\n", index.getAndIncrement(), f.getFloat()));
         }
       }
-    } else if (dtype == TFloat64.DTYPE) {
+    } else if (inputType == TFloat64.class) {
       AtomicInteger index = new AtomicInteger();
 
       try (TFloat64 result =
@@ -1033,7 +1033,7 @@ public <T extends TType> void print(PrintWriter writer, Output<T> input) {
                   (idx, f) -> writer.printf("%d). %f\n", index.getAndIncrement(), f.getDouble()));
         }
       }
-    } else if (dtype == TInt32.DTYPE) {
+    } else if (inputType == TInt32.class) {
       AtomicInteger index = new AtomicInteger();
 
       try (TInt32 result =
@@ -1048,7 +1048,7 @@ public <T extends TType> void print(PrintWriter writer, Output<T> input) {
                   (idx, f) -> writer.printf("%d). %d\n", index.getAndIncrement(), f.getInt()));
         }
       }
-    } else if (dtype == TInt64.DTYPE) {
+    } else if (inputType == TInt64.class) {
       AtomicInteger index = new AtomicInteger();
 
       try (TInt64 result =
@@ -1063,7 +1063,7 @@ public <T extends TType> void print(PrintWriter writer, Output<T> input) {
                   (idx, f) -> writer.printf("%d). %d\n", index.getAndIncrement(), f.getLong()));
         }
       }
-    } else if (dtype == TUint8.DTYPE) {
+    } else if (inputType == TUint8.class) {
       AtomicInteger index = new AtomicInteger();
 
       try (TUint8 result =
@@ -1078,7 +1078,7 @@ public <T extends TType> void print(PrintWriter writer, Output<T> input) {
                   (idx, f) -> writer.printf("%d). %x\n", index.getAndIncrement(), f.getByte()));
         }
       }
-    } else if (dtype == TBool.DTYPE) {
+    } else if (inputType == TBool.class) {
       AtomicInteger index = new AtomicInteger();
 
       try (TBool result =
@@ -1093,7 +1093,7 @@ public <T extends TType> void print(PrintWriter writer, Output<T> input) {
                   (idx, f) -> writer.printf("%d). %b\n", index.getAndIncrement(), f.getBoolean()));
         }
       }
-    } else if (dtype == TString.DTYPE) {
+    } else if (inputType == TString.class) {
       AtomicInteger index = new AtomicInteger();
 
       try (TString result =
@@ -1109,7 +1109,7 @@ public <T extends TType> void print(PrintWriter writer, Output<T> input) {
         }
       }
     } else {
-      writer.println("Unexpected DataType: " + dtype);
+      writer.println("Unexpected type class: " + inputType);
     }
     writer.flush();
   }
diff --git a/tensorflow-framework/tensorflow-data.md b/tensorflow-framework/tensorflow-data.md
index 99cd3321788..df0ec190b9f 100644
--- a/tensorflow-framework/tensorflow-data.md
+++ b/tensorflow-framework/tensorflow-data.md
@@ -39,8 +39,7 @@ FloatNdArray labels = NdArrays.vectorOf(0, 1, 1, 0);
 ```
 
 A dataset can be constructed from a list of the constant `Operand`s generated
-from this dataset, and a list of `DataType` objects corresponding
-to the type of each component:
+from this dataset, and a list of classes corresponding to the tensor type of each component:
 
 Note: Each of the input components must share the same first "batch" dimension.
 
@@ -48,7 +47,7 @@ Note: Each of the input components must share the same first "batch" dimension.
 Ops tf = // ... TensorFlow Ops accessor (either graph or eager)
 Dataset dataset = Dataset.fromTensorSlices(
     Arrays.asList(tf.constant(features), tf.constant(labels)),
-    Arrays.asList(TInt32.DTYPE, TInt32.DTYPE)
+    Arrays.asList(TInt32.class, TInt32.class)
 );
 ```
 
@@ -79,9 +78,6 @@ The primary use of a dataset is for iteration over its elements.
 Each row (or batch) element is represented as a list of tensor components, with
 type `List<Operand<?>>`. The tensor components of this element can be accessed using `List.get(int index)`.
 
-It is recommended to use `Tensor.expect(DataType<?> dtype)` to restore types
-to the retrieved tensors.
-
 #### Using DatastetIterator
 The `DatasetIterator` class provides abstractions for creating and using
 iterators in graph and eager mode. These will be explained here; however
@@ -89,7 +85,7 @@ end-users should only interact with `DatasetIterator` objects through the method
 provided in the `Dataset` class (examples to follow).
 
 To construct an iterator for a dataset of a specific structure, use
-the static method `DatasetIterator.fromStructure(Ops tf, List<DataType<?>> outputTypes, List<Shape> outputShapes)`. This creates a `DatasetIterator` object
+the static method `DatasetIterator.fromStructure(Ops tf, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes)`. This creates a `DatasetIterator` object
 which can be used with any dataset of a matching structure.
 
 Once a `DatasetIterator` is created, it can be initialized on a `Dataset` intsance using `DatasetIterator.makeInitializer(Dataset dataset)`. This will initialize (or re-initialize) the iterator to start at the beginning