From 4c90dd815c6117401daf62d8f40ab5fa3e633e6f Mon Sep 17 00:00:00 2001 From: klessard Date: Mon, 26 Apr 2021 09:44:50 -0400 Subject: [PATCH] Move ndarray library to its own repository --- README.md | 8 +- ndarray/README.md | 122 - ndarray/pom.xml | 91 - .../tensorflow/ndarray/BooleanNdArray.java | 108 - .../org/tensorflow/ndarray/ByteNdArray.java | 108 - .../org/tensorflow/ndarray/DoubleNdArray.java | 108 - .../org/tensorflow/ndarray/FloatNdArray.java | 108 - .../ndarray/IllegalRankException.java | 27 - .../org/tensorflow/ndarray/IntNdArray.java | 108 - .../org/tensorflow/ndarray/LongNdArray.java | 108 - .../java/org/tensorflow/ndarray/NdArray.java | 302 -- .../tensorflow/ndarray/NdArraySequence.java | 67 - .../java/org/tensorflow/ndarray/NdArrays.java | 495 --- .../java/org/tensorflow/ndarray/Shape.java | 447 -- .../java/org/tensorflow/ndarray/Shaped.java | 51 - .../org/tensorflow/ndarray/ShortNdArray.java | 108 - .../org/tensorflow/ndarray/StdArrays.java | 3809 ----------------- .../ndarray/buffer/BooleanDataBuffer.java | 165 - .../ndarray/buffer/ByteDataBuffer.java | 232 - .../tensorflow/ndarray/buffer/DataBuffer.java | 324 -- .../ndarray/buffer/DataBufferWindow.java | 93 - .../ndarray/buffer/DataBuffers.java | 457 -- .../ndarray/buffer/DataStorageVisitor.java | 147 - .../ndarray/buffer/DoubleDataBuffer.java | 165 - .../ndarray/buffer/FloatDataBuffer.java | 165 - .../ndarray/buffer/IntDataBuffer.java | 165 - .../ndarray/buffer/LongDataBuffer.java | 165 - .../ndarray/buffer/ShortDataBuffer.java | 165 - .../buffer/layout/BooleanDataLayout.java | 65 - .../ndarray/buffer/layout/ByteDataLayout.java | 65 - .../ndarray/buffer/layout/DataLayout.java | 129 - .../ndarray/buffer/layout/DataLayouts.java | 96 - .../buffer/layout/DoubleDataLayout.java | 65 - .../buffer/layout/FloatDataLayout.java | 65 - .../ndarray/buffer/layout/IntDataLayout.java | 66 - .../ndarray/buffer/layout/LongDataLayout.java | 65 - .../buffer/layout/ShortDataLayout.java | 65 - .../ndarray/impl/AbstractNdArray.java | 92 - .../tensorflow/ndarray/impl/Validator.java | 55 - .../impl/buffer/AbstractDataBuffer.java | 182 - .../impl/buffer/AbstractDataBufferWindow.java | 48 - .../ndarray/impl/buffer/Validator.java | 132 - .../adapter/AbstractDataBufferAdapter.java | 68 - .../adapter/BooleanDataBufferAdapter.java | 116 - .../buffer/adapter/ByteDataBufferAdapter.java | 135 - .../buffer/adapter/DataBufferAdapter.java | 47 - .../adapter/DataBufferAdapterFactory.java | 142 - .../adapter/DoubleDataBufferAdapter.java | 116 - .../adapter/FloatDataBufferAdapter.java | 116 - .../buffer/adapter/IntDataBufferAdapter.java | 116 - .../buffer/adapter/LongDataBufferAdapter.java | 116 - .../adapter/ShortDataBufferAdapter.java | 116 - .../impl/buffer/layout/Bfloat16Layout.java | 54 - .../impl/buffer/layout/BoolLayout.java | 47 - .../impl/buffer/layout/Float16Layout.java | 119 - .../impl/buffer/layout/StringLayout.java | 48 - .../impl/buffer/misc/ArrayDataBuffer.java | 126 - .../impl/buffer/misc/BitSetDataBuffer.java | 183 - .../buffer/misc/BooleanArrayDataBuffer.java | 176 - .../buffer/misc/MiscDataBufferFactory.java | 40 - .../buffer/nio/AbstractNioDataBuffer.java | 41 - .../impl/buffer/nio/ByteNioDataBuffer.java | 185 - .../impl/buffer/nio/DoubleNioDataBuffer.java | 147 - .../impl/buffer/nio/FloatNioDataBuffer.java | 147 - .../impl/buffer/nio/IntNioDataBuffer.java | 147 - .../impl/buffer/nio/LongNioDataBuffer.java | 147 - .../impl/buffer/nio/NioDataBufferFactory.java | 61 - .../impl/buffer/nio/ShortNioDataBuffer.java | 147 - .../buffer/raw/AbstractRawDataBuffer.java | 94 - .../impl/buffer/raw/BooleanRawDataBuffer.java | 146 - .../impl/buffer/raw/ByteRawDataBuffer.java | 185 - .../impl/buffer/raw/DoubleRawDataBuffer.java | 149 - .../impl/buffer/raw/FloatRawDataBuffer.java | 150 - .../impl/buffer/raw/IntRawDataBuffer.java | 149 - .../impl/buffer/raw/LongRawDataBuffer.java | 149 - .../impl/buffer/raw/RawDataBufferFactory.java | 148 - .../impl/buffer/raw/RawDataBufferWindow.java | 19 - .../impl/buffer/raw/ShortRawDataBuffer.java | 149 - .../impl/buffer/raw/UnsafeMemoryHandle.java | 195 - .../impl/buffer/raw/UnsafeReference.java | 64 - .../impl/dense/AbstractDenseNdArray.java | 163 - .../impl/dense/BooleanDenseNdArray.java | 91 - .../ndarray/impl/dense/ByteDenseNdArray.java | 91 - .../ndarray/impl/dense/DataTransfer.java | 136 - .../ndarray/impl/dense/DenseNdArray.java | 63 - .../impl/dense/DoubleDenseNdArray.java | 91 - .../ndarray/impl/dense/FloatDenseNdArray.java | 91 - .../ndarray/impl/dense/IntDenseNdArray.java | 91 - .../ndarray/impl/dense/LongDenseNdArray.java | 91 - .../ndarray/impl/dense/ShortDenseNdArray.java | 91 - .../ndarray/impl/dense/Validator.java | 49 - .../impl/dimension/AbstractDimension.java | 45 - .../ndarray/impl/dimension/Axis.java | 61 - .../ndarray/impl/dimension/Dimension.java | 36 - .../impl/dimension/DimensionalSpace.java | 224 - .../impl/dimension/IndexedDimension.java | 69 - .../impl/dimension/ReducedDimension.java | 62 - .../dimension/RelativeDimensionalSpace.java | 32 - .../impl/sequence/CoordinatesIncrementor.java | 38 - .../impl/sequence/FastElementSequence.java | 81 - .../sequence/IndexedPositionIterator.java | 28 - .../IndexedSequentialPositionIterator.java | 51 - .../impl/sequence/NdPositionIterator.java | 70 - .../impl/sequence/PositionIterator.java | 42 - .../sequence/SequentialPositionIterator.java | 55 - .../impl/sequence/SingleElementSequence.java | 71 - .../impl/sequence/SlicingElementSequence.java | 77 - .../org/tensorflow/ndarray/index/All.java | 57 - .../java/org/tensorflow/ndarray/index/At.java | 74 - .../tensorflow/ndarray/index/Ellipsis.java | 48 - .../tensorflow/ndarray/index/Hyperslab.java | 90 - .../org/tensorflow/ndarray/index/Index.java | 131 - .../org/tensorflow/ndarray/index/Indices.java | 363 -- .../org/tensorflow/ndarray/index/NewAxis.java | 53 - .../tensorflow/ndarray/index/Sequence.java | 52 - .../org/tensorflow/ndarray/index/Slice.java | 89 - .../tensorflow/ndarray/index/SliceFrom.java | 86 - .../org/tensorflow/ndarray/index/SliceTo.java | 86 - .../org/tensorflow/ndarray/index/Step.java | 83 - .../ndarray/BooleanNdArrayTestBase.java | 57 - .../ndarray/ByteNdArrayTestBase.java | 55 - .../ndarray/DoubleNdArrayTestBase.java | 55 - .../ndarray/FloatNdArrayTestBase.java | 55 - .../org/tensorflow/ndarray/IndexTest.java | 205 - .../ndarray/IntNdArrayTestBase.java | 55 - .../ndarray/LongNdArrayTestBase.java | 55 - .../tensorflow/ndarray/NdArrayTestBase.java | 338 -- .../org/tensorflow/ndarray/ShapeTest.java | 170 - .../ndarray/ShortNdArrayTestBase.java | 55 - .../org/tensorflow/ndarray/StdArraysTest.java | 211 - .../ndarray/benchmark/NdArrayBenchmark.java | 163 - .../buffer/BooleanDataBufferTestBase.java | 142 - .../buffer/ByteDataBufferTestBase.java | 145 - .../ndarray/buffer/DataBufferTestBase.java | 293 -- .../buffer/DoubleDataBufferTestBase.java | 135 - 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29 - .../buffer/nio/FloatNioDataBufferTest.java | 29 - .../impl/buffer/nio/IntNioDataBufferTest.java | 29 - .../buffer/nio/LongNioDataBufferTest.java | 29 - .../buffer/nio/ShortNioDataBufferTest.java | 29 - .../buffer/raw/BooleanRawDataBufferTest.java | 28 - .../buffer/raw/ByteRawDataBufferTest.java | 28 - .../buffer/raw/DoubleRawDataBufferTest.java | 28 - .../buffer/raw/FloatRawDataBufferTest.java | 28 - .../impl/buffer/raw/IntRawDataBufferTest.java | 28 - .../buffer/raw/LongRawDataBufferTest.java | 28 - .../buffer/raw/ShortRawDataBufferTest.java | 28 - .../impl/dense/BooleanDenseNdArrayTest.java | 35 - .../impl/dense/ByteDenseNdArrayTest.java | 35 - .../ndarray/impl/dense/DenseNdArrayTest.java | 51 - .../impl/dense/DoubleDenseNdArrayTest.java | 35 - .../impl/dense/FloatDenseNdArrayTest.java | 35 - .../impl/dense/IntDenseNdArrayTest.java | 35 - .../impl/dense/LongDenseNdArrayTest.java | 35 - .../impl/dense/ShortDenseNdArrayTest.java | 35 - .../impl/dense/StringDenseNdArrayTest.java | 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ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/BooleanDenseNdArrayTest.java delete mode 100644 ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/ByteDenseNdArrayTest.java delete mode 100644 ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/DenseNdArrayTest.java delete mode 100644 ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/DoubleDenseNdArrayTest.java delete mode 100644 ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/FloatDenseNdArrayTest.java delete mode 100644 ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/IntDenseNdArrayTest.java delete mode 100644 ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/LongDenseNdArrayTest.java delete mode 100644 ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/ShortDenseNdArrayTest.java delete mode 100644 ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/StringDenseNdArrayTest.java delete mode 100644 ndarray/src/test/java/org/tensorflow/ndarray/impl/sequence/ElementSequenceTest.java delete mode 100644 ndarray/src/test/resources/COPYRIGHT.txt delete mode 100644 ndarray/src/test/resources/castle.jpg diff --git a/README.md b/README.md index 53fe11a2036..39ca44a74e6 100644 --- a/README.md +++ b/README.md @@ -27,13 +27,7 @@ The following describes the layout of the repository and its different artifacts * Primary API for building and training neural networks with TensorFlow * Intended audience: neural network developers * For more information: [tensorflow-framework/README.md](tensorflow-framework/README.md) - -* `ndarray` - * Generic utility library for n-dimensional data I/O operations - * Used by TensorFlow but does not depend on TensorFlow - * Intended audience: any developer who needs a Java n-dimensional array implementation, whether or not they - use it with TensorFlow - + ## Communication diff --git a/ndarray/README.md b/ndarray/README.md deleted file mode 100644 index 0c76eecd08f..00000000000 --- a/ndarray/README.md +++ /dev/null @@ -1,122 +0,0 @@ -# NdArray Java Library - -## Introduction - -NdArray is a library exposing utilities for manipulating data in a n-dimensional space in Java. -Unlike other Java artifacts distributed by TensorFlow, this library does not depend on the TensorFlow -runtime, therefore is very lightweight and can be used by any kind of Java project. - -To import the NdArray library in your project, simply add the following dependency: -```xml - - org.tensorflow - ndarray - 0.3.1 - -``` - -### Data Buffers - -Instances of `DataBuffer` map contiguous segments of memory with 64-bits indexing and supports -generic parametrization while still allowing direct access to primitive types. Such segments -could be standard Java arrays, JDK NIO buffers or native memory. In addition, it can serialize and -deserialize data of any type (and not only primitive types, as with `java.util.nio`). - -```java -// Allocate a buffer of 4K int values -IntDataBuffer bufferA = DataBuffers.ofInts(4096L); -assertEquals(4096L, bufferA.size()); - -// Write an int array at the beginning of the buffer -bufferA.write(new int[] { 1, 2, 3 }); -assertEquals(3, bufferA.getInt(2)); - -// Slice buffer after its first value -IntDataBuffer bufferB = bufferA.offset(1); -assertEquals(4095L, bufferB.size()); -assertEquals(2, bufferB.getInt(0)); - -// Resize a buffer to 10 elements -IntDataBuffer bufferC = bufferA.narrow(10); -assertEquals(10L, bufferB.size()); -assertEquals(2, bufferB.getInt(0)); -``` - -### ND Arrays - -Instances of `NdArray` are used to view memory segments stored in a `DataBuffer` as a -multidimensional arrays and to provide an API for traversing, reading, writing and slicing -their data. The goal of these tools is to replace the usage of standard multidimensional Java arrays -(e.g. `new int[][][]`) since those results in slow performances, from the non-contiguous -storage of their data and the multiple dereferences required to access their values. - -```java -// Allocating a 3D matrix of 2x3x2 -IntNdArray matrix3d = NdArrays.ofInts(Shape.of(2, 3, 2)); -assertEquals(3, matrix3d.rank()); - -// Initializing 3D matrix data with vectors from the first dimension (index 0) -matrix3d.elements(0).forEach(matrix -> { - assertEquals(2, matrix.rank()); - assertEquals(Shape.of(3, 2), matrix.shape()); - matrix - .set(NdArrays.vectorOf(1, 2), 0) - .set(NdArrays.vectorOf(3, 4), 1) - .set(NdArrays.vectorOf(5, 6), 2); -}); - -// Visit all scalars of 3D matrix, printing their coordinates and value -matrix3d.scalars().forEachIdx((coords, scalar) -> - System.out.println("Scalar at " + Arrays.toString(coords) + " has value " + scalar.getInt()) -); - -// Retrieving the second vector of the first matrix -IntNdArray vector = matrix3d.get(0, 1); -assertEquals(1, vector.rank()); - -// Rewriting the values of the vector using a primitive array -vector.write(new int[] { 7, 8 }); -assertEquals(7, matrix3d.getInt(0, 1, 0)); -assertEquals(8, matrix3d.getInt(0, 1, 1)); - -// Slicing the 3D matrix so we only keep the second element of the second dimension -IntNdArray slice = matrix3d.slice(all(), at(1)); -assertEquals(2, slice.rank()); -assertEquals(Shape.of(2, 2), slice.shape()); -assertEquals(7, slice.getInt(0, 0)); // (0, 1, 0) in the original matrix -assertEquals(3, slice.getInt(1, 0)); // (1, 1, 0) in the original matrix -``` - -## Integration with TensorFlow - -The NdArray library is independent of the TensorFlow runtime library, making it a good choice for -manipulating multi-dimensional data structures from anywhere. But as an example, here -is how it is actually being used by the [TensorFlow Core API](https://github.com/tensorflow/java/tree/master/tensorflow-core/tensorflow-core-api): - -```java -// Allocate a tensor of 32-bits integer of the shape (2, 3, 2) -Tensor tensor = TInt32.ofShape(2, 3, 2); - -// Access tensor memory directly -IntNdArray tensorData = tensor.data(); -assertEquals(3, tensorData.rank()); -assertEquals(12, tensorData.size()); - -try (EagerSession session = EagerSession.create()) { - Ops tf = Ops.create(session); - - // Initialize tensor memory with zeros and take a snapshot - tensorData.scalars().forEach(scalar -> scalar.setInt(0)); - Constant x = tf.constant(tensor); - - // Initialize the same tensor memory with ones and take a snapshot - tensorData.scalars().forEach(scalar -> scalar.setInt(1)); - Constant y = tf.constant(tensor); - - // Subtract y from x and validate the result - Sub sub = tf.math.sub(x, y); - sub.data().scalars().forEach(scalar -> - assertEquals(-1, scalar.getInt()) - ); -} -``` diff --git a/ndarray/pom.xml b/ndarray/pom.xml deleted file mode 100644 index 36acfa5705b..00000000000 --- a/ndarray/pom.xml +++ /dev/null @@ -1,91 +0,0 @@ - - - 4.0.0 - - - org.tensorflow - tensorflow-java - 0.4.0-SNAPSHOT - - ndarray - jar - - TensorFlow NdArray Library - - Utility library for N-dimensional data I/O operations. - - - - org.tensorflow.ndarray - - - - - org.junit.jupiter - junit-jupiter-api - test - - - org.junit.jupiter - junit-jupiter-engine - test - - - org.openjdk.jmh - jmh-core - test - - - org.openjdk.jmh - jmh-generator-annprocess - test - - - - - - - maven-jar-plugin - 3.2.0 - - - - ${java.module.name} - - - - - - org.apache.maven.plugins - maven-surefire-plugin - 2.22.2 - - 1 - false - -Xmx2G -XX:MaxPermSize=256m - - **/*Test.java - - - - - - - diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/BooleanNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/BooleanNdArray.java deleted file mode 100644 index 5b4bedb1c84..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/BooleanNdArray.java +++ /dev/null @@ -1,108 +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.ndarray; - -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.index.Index; - -/** - * An {@link NdArray} of booleans. - */ -public interface BooleanNdArray extends NdArray { - - /** - * Returns the boolean value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  BooleanNdArray matrix = NdArrays.ofBooleans(shape(2, 2));  // matrix rank = 2
-   *  matrix.getBoolean(0, 1);  // succeeds, returns false
-   *  matrix.getBoolean(0);  // throws IllegalRankException
-   *
-   *  BooleanNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.getBoolean();  // succeeds, returns false
-   * }
- * - * @param coordinates coordinates of the scalar to resolve - * @return value of that scalar - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar element - */ - boolean getBoolean(long... coordinates); - - /** - * Assigns the boolean value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  BooleanNdArray matrix = NdArrays.ofBooleans(shape(2, 2));  // matrix rank = 2
-   *  matrix.setBoolean(true, 0, 1);  // succeeds
-   *  matrix.setBoolean(true, 0);  // throws IllegalRankException
-   *
-   *  BooleanNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.setBoolean(true);  // succeeds
-   * }
- * - * @param value the value to assign - * @param coordinates coordinates of the scalar to assign - * @return this array - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar element - */ - BooleanNdArray setBoolean(boolean value, long... coordinates); - - @Override - BooleanNdArray slice(Index... indices); - - @Override - BooleanNdArray get(long... coordinates); - - @Override - BooleanNdArray set(NdArray src, long... coordinates); - - @Override - default Boolean getObject(long... coordinates) { - return getBoolean(coordinates); - } - - @Override - default BooleanNdArray setObject(Boolean value, long... coordinates) { - return setBoolean(value, coordinates); - } - - @Override - NdArraySequence elements(int dimensionIdx); - - @Override - NdArraySequence scalars(); - - @Override - BooleanNdArray copyTo(NdArray dst); - - @Override - BooleanNdArray read(DataBuffer dst); - - BooleanNdArray read(BooleanDataBuffer dst); - - @Override - BooleanNdArray write(DataBuffer src); - - BooleanNdArray write(BooleanDataBuffer src); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/ByteNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/ByteNdArray.java deleted file mode 100644 index 0e6f118f5ef..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/ByteNdArray.java +++ /dev/null @@ -1,108 +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.ndarray; - -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.index.Index; - -/** - * An {@link NdArray} of bytes. - */ -public interface ByteNdArray extends NdArray { - - /** - * Returns the byte value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  ByteNdArray matrix = NdArrays.ofBytes(shape(2, 2));  // matrix rank = 2
-   *  matrix.getByte(0, 1);  // succeeds, returns 0
-   *  matrix.getByte(0);  // throws IllegalRankException
-   *
-   *  ByteNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.getByte();  // succeeds, returns 0
-   * }
- * - * @param coordinates coordinates of the scalar to resolve - * @return value of that scalar - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar element - */ - byte getByte(long... coordinates); - - /** - * Assigns the byte value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  ByteNdArray matrix = NdArrays.ofBytes(shape(2, 2));  // matrix rank = 2
-   *  matrix.setByte(10, 0, 1);  // succeeds
-   *  matrix.setByte(10, 0);  // throws IllegalRankException
-   *
-   *  ByteNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.setByte(10);  // succeeds
-   * }
- * - * @param value the value to assign - * @param coordinates coordinates of the scalar to assign - * @return this array - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar element - */ - ByteNdArray setByte(byte value, long... coordinates); - - @Override - ByteNdArray slice(Index... indices); - - @Override - ByteNdArray get(long... coordinates); - - @Override - ByteNdArray set(NdArray src, long... coordinates); - - @Override - default Byte getObject(long... coordinates) { - return getByte(coordinates); - } - - @Override - default ByteNdArray setObject(Byte value, long... coordinates) { - return setByte(value, coordinates); - } - - @Override - NdArraySequence elements(int dimensionIdx); - - @Override - NdArraySequence scalars(); - - @Override - ByteNdArray copyTo(NdArray dst); - - @Override - ByteNdArray read(DataBuffer dst); - - ByteNdArray read(ByteDataBuffer dst); - - @Override - ByteNdArray write(DataBuffer src); - - ByteNdArray write(ByteDataBuffer src); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/DoubleNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/DoubleNdArray.java deleted file mode 100644 index 80e99b01877..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/DoubleNdArray.java +++ /dev/null @@ -1,108 +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.ndarray; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.index.Index; - -/** - * An {@link NdArray} of doubles. - */ -public interface DoubleNdArray extends NdArray { - - /** - * Returns the double value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  DoubleNdArray matrix = NdArrays.ofDoubles(shape(2, 2));  // matrix rank = 2
-   *  matrix.getDouble(0, 1);  // succeeds, returns 0.0
-   *  matrix.getDouble(0);  // throws IllegalRankException
-   *
-   *  DoubleNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.getDouble();  // succeeds, returns 0.0
-   * }
- * - * @param coordinates coordinates of the scalar to resolve - * @return value of that scalar - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar element - */ - double getDouble(long... coordinates); - - /** - * Assigns the double value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  DoubleNdArray matrix = NdArrays.ofDoubles(shape(2, 2));  // matrix rank = 2
-   *  matrix.setDouble(10.0, 0, 1);  // succeeds
-   *  matrix.setDouble(10.0, 0);  // throws IllegalRankException
-   *
-   *  DoubleNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.setDouble(10.0);  // succeeds
-   * }
- * - * @param value value to assign - * @param coordinates coordinates of the scalar to assign - * @return this array - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar element - */ - DoubleNdArray setDouble(double value, long... coordinates); - - @Override - DoubleNdArray slice(Index... indices); - - @Override - DoubleNdArray get(long... coordinates); - - @Override - DoubleNdArray set(NdArray src, long... coordinates); - - @Override - default Double getObject(long... coordinates) { - return getDouble(coordinates); - } - - @Override - default DoubleNdArray setObject(Double value, long... coordinates) { - return setDouble(value, coordinates); - } - - @Override - NdArraySequence elements(int dimensionIdx); - - @Override - NdArraySequence scalars(); - - @Override - DoubleNdArray copyTo(NdArray dst); - - @Override - DoubleNdArray read(DataBuffer dst); - - DoubleNdArray read(DoubleDataBuffer dst); - - @Override - DoubleNdArray write(DataBuffer src); - - DoubleNdArray write(DoubleDataBuffer src); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/FloatNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/FloatNdArray.java deleted file mode 100644 index 8d4fbf5c1ed..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/FloatNdArray.java +++ /dev/null @@ -1,108 +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.ndarray; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.index.Index; - -/** - * An {@link NdArray} of floats. - */ -public interface FloatNdArray extends NdArray { - - /** - * Returns the float value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  FloatNdArray matrix = NdArrays.ofFloats(shape(2, 2));  // matrix rank = 2
-   *  matrix.getFloat(0, 1);  // succeeds, returns 0.0f
-   *  matrix.getFloat(0);  // throws IllegalRankException
-   *
-   *  FloatNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.getFloat();  // succeeds, returns 0.0f
-   * }
- * - * @param coordinates coordinates of the scalar to resolve - * @return value of that scalar - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar element - */ - float getFloat(long... coordinates); - - /** - * Assigns the float value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  FloatNdArray matrix = NdArrays.ofFloats(shape(2, 2));  // matrix rank = 2
-   *  matrix.setFloat(10.0f, 0, 1);  // succeeds
-   *  matrix.setFloat(10.0f, 0);  // throws IllegalRankException
-   *
-   *  FloatNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.setFloat(10.0f);  // succeeds
-   * }
- * - * @param value value to assign - * @param coordinates coordinates of the scalar to assign - * @return this array - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar element - */ - FloatNdArray setFloat(float value, long... coordinates); - - @Override - FloatNdArray slice(Index... coordinates); - - @Override - FloatNdArray get(long... coordinates); - - @Override - FloatNdArray set(NdArray src, long... coordinates); - - @Override - default Float getObject(long... coordinates) { - return getFloat(coordinates); - } - - @Override - default FloatNdArray setObject(Float value, long... coordinates) { - return setFloat(value, coordinates); - } - - @Override - NdArraySequence elements(int dimensionIdx); - - @Override - NdArraySequence scalars(); - - @Override - FloatNdArray copyTo(NdArray dst); - - @Override - FloatNdArray read(DataBuffer dst); - - FloatNdArray read(FloatDataBuffer dst); - - @Override - FloatNdArray write(DataBuffer src); - - FloatNdArray write(FloatDataBuffer src); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/IllegalRankException.java b/ndarray/src/main/java/org/tensorflow/ndarray/IllegalRankException.java deleted file mode 100644 index b816d338d7e..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/IllegalRankException.java +++ /dev/null @@ -1,27 +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.ndarray; - -/** - * Exception thrown when an operation cannot be completed because of the rank of the targeted array. - */ -public class IllegalRankException extends IllegalArgumentException { - - public IllegalRankException(String message) { - super(message); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/IntNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/IntNdArray.java deleted file mode 100644 index aa2cc652d69..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/IntNdArray.java +++ /dev/null @@ -1,108 +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.ndarray; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.index.Index; - -/** - * An {@link NdArray} of integers. - */ -public interface IntNdArray extends NdArray { - - /** - * Returns the integer value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  IntNdArray matrix = NdArrays.ofInts(shape(2, 2));  // matrix rank = 2
-   *  matrix.getInt(0, 1);  // succeeds, returns 0
-   *  matrix.getInt(0);  // throws IllegalRankException
-   *
-   *  IntNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.getInt();  // succeeds, returns 0
-   * }
- * - * @param coordinates coordinates of the scalar to resolve - * @return value of that scalar - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar element - */ - int getInt(long... coordinates); - - /** - * Assigns the integer value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  IntNdArray matrix = NdArrays.ofInts(shape(2, 2));  // matrix rank = 2
-   *  matrix.setInt(10, 0, 1);  // succeeds
-   *  matrix.setInt(10, 0);  // throws IllegalRankException
-   *
-   *  IntNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.setInt(10);  // succeeds
-   * }
- * - * @param value value to assign - * @param coordinates coordinates of the scalar to assign - * @return this array - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar element - */ - IntNdArray setInt(int value, long... coordinates); - - @Override - IntNdArray slice(Index... indices); - - @Override - IntNdArray get(long... coordinates); - - @Override - IntNdArray set(NdArray src, long... coordinates); - - @Override - default Integer getObject(long... coordinates) { - return getInt(coordinates); - } - - @Override - default IntNdArray setObject(Integer value, long... coordinates) { - return setInt(value, coordinates); - } - - @Override - NdArraySequence elements(int dimensionIdx); - - @Override - NdArraySequence scalars(); - - @Override - IntNdArray copyTo(NdArray dst); - - @Override - IntNdArray read(DataBuffer dst); - - IntNdArray read(IntDataBuffer dst); - - @Override - IntNdArray write(DataBuffer src); - - IntNdArray write(IntDataBuffer src); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/LongNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/LongNdArray.java deleted file mode 100644 index 3e5be6dc7ec..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/LongNdArray.java +++ /dev/null @@ -1,108 +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.ndarray; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.index.Index; - -/** - * An {@link NdArray} of longs. - */ -public interface LongNdArray extends NdArray { - - /** - * Returns the long value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  LongNdArray matrix = NdArrays.ofLongs(shape(2, 2));  // matrix rank = 2
-   *  matrix.getLong(0, 1);  // succeeds, returns 0L
-   *  matrix.getLong(0);  // throws IllegalRankException
-   *
-   *  LongNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.getLong();  // succeeds, returns 0L
-   * }
- * - * @param coordinates coordinates of the scalar to resolve - * @return value of that scalar - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar element - */ - long getLong(long... coordinates); - - /** - * Assigns the long value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  LongNdArray matrix = NdArrays.ofLongs(shape(2, 2));  // matrix rank = 2
-   *  matrix.setLong(10L, 0, 1);  // succeeds
-   *  matrix.setLong(10L, 0);  // throws IllegalRankException
-   *
-   *  LongNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.setLong(10L);  // succeeds
-   * }
- * - * @param value value to assign - * @param coordinates coordinates of the scalar to assign - * @return this array - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar element - */ - LongNdArray setLong(long value, long... coordinates); - - @Override - LongNdArray slice(Index... indices); - - @Override - LongNdArray get(long... coordinates); - - @Override - LongNdArray set(NdArray src, long... coordinates); - - @Override - default Long getObject(long... coordinates) { - return getLong(coordinates); - } - - @Override - default LongNdArray setObject(Long value, long... coordinates) { - return setLong(value, coordinates); - } - - @Override - NdArraySequence elements(int dimensionIdx); - - @Override - NdArraySequence scalars(); - - @Override - LongNdArray copyTo(NdArray dst); - - @Override - LongNdArray read(DataBuffer dst); - - LongNdArray read(LongDataBuffer dst); - - @Override - LongNdArray write(DataBuffer src); - - LongNdArray write(LongDataBuffer src); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/NdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/NdArray.java deleted file mode 100644 index 6686abd9148..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/NdArray.java +++ /dev/null @@ -1,302 +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.ndarray; - -import java.util.function.BiConsumer; -import java.util.function.Consumer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.index.Index; - -/** - * A data structure of N-dimensions. - * - *

The `NdArray` interface creates an abstraction between the physical storage of a data record, - * which can be linear or segmented, and its logical representation. In general, they achieve - * better performances than standard multi-dimensional arrays in Java by mapping directly linear - * data segments in memory. - * - *

Like {@link DataBuffer}, {@code NdArray} instances support 64-bits indexing so they can be - * used to map very large data records. They also support special coordinates that allow traversing - * their values in any direction or to select only a subset of them. - * - *

Example of usage: - * 

{@code
- *    // Creates a 2x3x2 matrix (of rank 3)
- *    FloatNdArray matrix3d = NdArrays.ofFloats(shape(2, 3, 2));
- *
- *    // Initialize sub-matrices data with vectors
- *    matrix.set(NdArrays.vectorOf(1.0f, 2.0f), 0, 0)
- *          .set(NdArrays.vectorOf(3.0f, 4.0f), 0, 1)
- *          .set(NdArrays.vectorOf(5.0f, 6.0f), 0, 2)
- *          .set(NdArrays.vectorOf(7.0f, 8.0f), 1, 0)
- *          .set(NdArrays.vectorOf(9.0f, 10.0f), 1, 1)
- *          .set(NdArrays.vectorOf(11.0f, 12.0f), 1, 2);
- *
- *    // Access the second 3x2 matrix (of rank 2)
- *    FloatNdArray matrix = matrix3d.get(1);
- *
- *    // Access directly the float value at (1, 0) from the second matrix
- *    assertEquals(9.0f, matrix.getFloat(1, 0));
- * }
- * - * @param the type of values to be mapped - */ -public interface NdArray extends Shaped { - - /** - * Returns a sequence of all elements at a given dimension. - * - *

Logically, the N-dimensional array can be flatten in a single vector, where the scalars of - * the {@code (n - 1)}th element precedes those of the {@code (n)}th element, for a total of - * {@link #size()} values. - * - *

For example, given a {@code n x m} matrix on the {@code [x, y]} axes, elements are iterated in - * the following order: - *

x0y0, x0y1, ..., x0ym-1, x1y0, x1y1, ..., xn-1ym-1 - * - *

The returned sequence can then be iterated to visit each elements, either by calling - * {@link NdArraySequence#forEach(Consumer)} or {@link NdArraySequence#forEachIndexed(BiConsumer)}. - * 

{@code
-   *    // Iterate matrix for initializing each of its vectors
-   *    matrixOfFloats.elements(0).forEach(v -> {
-   *      v.set(vector(1.0f, 2.0f, 3.0f));
-   *    });
-   *
-   *    // Iterate a vector for reading each of its scalar
-   *    vectorOfFloats.scalars().forEachIdx((coords, s) -> {
-   *      System.out.println("Value " + s.getFloat() + " found at " + coords);
-   *    });
-   * }
- * - * @param dimensionIdx index of the dimension - * @return an {@code NdArray} sequence - * @throws IllegalArgumentException if {@code dimensionIdx} is greater or equal to the total - * number of dimensions of this array - */ - NdArraySequence> elements(int dimensionIdx); - - /** - * Returns a sequence of all scalars in this array. - * - *

This is equivalent to call {@code elements(shape().numDimensions() - 1)} - * - * @return an {@code NdArray} sequence - */ - NdArraySequence> scalars(); - - /** - * Creates a multi-dimensional view (or slice) of this array by mapping one or more dimensions - * to the given index selectors. - * - *

Slices allow to traverse an N-dimensional array in any of its axis and/or to filter only - * elements of interest. For example, for a given matrix on the {@code [x, y]} axes, it is - * possible to iterate elements at {@code y=0} for all {@code x}. - * - *

Any changes applied to the returned slice affect the data of this array as well, as there - * is no copy involved. - * - *

Example of usage: - * 

{@code
-   *    FloatNdArray matrix3d = NdArrays.ofFloats(shape(3, 2, 4));  // with [x, y, z] axes
-   *
-   *    // Iterates elements on the x axis by preserving only the 3rd value on the z axis,
-   *    // (i.e. [x, y, 2])
-   *    matrix3d.slice(all(), all(), at(2)).elements(0).forEach(m -> {
-   *      assertEquals(shape(2), m); // y=2, z=0 (scalar)
-   *    });
-   *
-   *    // Creates a slice that contains only the last element of the y axis and elements with an
-   *    // odd `z` coordinate.
-   *    FloatNdArray slice = matrix3d.slice(all(), at(1), odd());
-   *    assertEquals(shape(3, 2), slice.shape());  // x=3, y=0 (scalar), z=2 (odd coordinates)
-   *
-   *    // Iterates backward the elements on the x axis
-   *    matrix3d.slice(flip()).elements(0).forEach(m -> {
-   *      assertEquals(shape(2, 4), m);  // y=2, z=4
-   *    });
-   * }
- * - * @param indices index selectors per dimensions, starting from dimension 0 of this array. - * @return the element resulting of the index selection - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their - * respective dimension - */ - NdArray slice(Index... indices); - - /** - * Returns the N-dimensional element of this array at the given coordinates. - * - *

Elements of any of the dimensions of this array can be retrieved. For example, if the number - * of coordinates is equal to the number of dimensions of this array, then a rank-0 (scalar) array - * is returned, which value can then be obtained by calling `array.getObject()`. - * - *

Any changes applied to the returned elements affect the data of this array as well, as there - * is no copy involved. - * - *

Note that invoking this method is an equivalent and more efficient way to slice this array - * on single scalar, i.e. {@code array.get(x, y, z)} is equal to - * {@code array.slice(at(x), at(y), at(z))} - * - * @param coordinates coordinates of the element to access, none will return this array - * @return the element at this index - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their - * respective dimension - */ - NdArray get(long... coordinates); - - /** - * Assigns the value of the N-dimensional element found at the given coordinates. - * - *

The number of coordinates provided can be anywhere between 0 and rank - 1. For example: - * 

{@code
-   *  FloatNdArray matrix = NdArrays.ofFloats(shape(2, 2));  // matrix rank = 2
-   *  matrix.set(vector(10.0f, 20.0f), 0);  // success
-   *  matrix.set(scalar(10.0f), 1, 0); // success
-   * }
- * - * @param src an array of the values to assign - * @param coordinates coordinates of the element to assign - * @return this array - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their - * respective dimension - */ - NdArray set(NdArray src, long... coordinates); - - /** - * Returns the value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  FloatNdArray matrix = NdArrays.ofFloats(shape(2, 2));  // matrix rank = 2
-   *  matrix.getObject(0, 1);  // succeeds, returns 0.0f
-   *  matrix.getObject(0);  // throws IllegalRankException
-   *
-   *  FloatNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.getObject();  // succeeds, returns 0.0f
-   * }
- * - * Note: if this array stores values of a primitive type, prefer the usage of the specialized - * method in the subclass for that type. For example, {@code floatArray.getFloat(0); }. - * - * @param coordinates coordinates of the scalar to resolve - * @return value of that scalar - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their - * respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar - * element - */ - T getObject(long... coordinates); - - /** - * Assigns the value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  FloatNdArray matrix = NdArrays.ofFloats(shape(2, 2));  // matrix rank = 2
-   *  matrix.setObject(10.0f, 0, 1);  // succeeds
-   *  matrix.setObject(10.0f, 0);  // throws IllegalRankException
-   *
-   *  FloatNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.setObject(10.0f);  // succeeds
-   * }
- * - * Note: if this array stores values of a primitive type, prefer the usage of the specialized - * method in the subclass for that type. For example, {@code floatArray.setFloat(10.0f, 0); } - * - * @param value the value to assign - * @param coordinates coordinates of the scalar to assign - * @return this array - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their - * respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar - * element - */ - NdArray setObject(T value, long... coordinates); - - /** - * Copy the content of this array to the destination array. - * - *

The {@link #shape()} of the destination array must be equal to the shape of this array, or - * an exception is thrown. After the copy, the content of both arrays can be altered - * independently, without affecting each other. - * - * @param dst array to receive a copy of the content of this array - * @return this array - * @throws IllegalArgumentException if the shape of {@code dst} is not equal to the shape of this - * array - */ - NdArray copyTo(NdArray dst); - - /** - * Read the content of this N-dimensional array into the destination buffer. - * - *

The size of the buffer must be equal or greater to the {@link #size()} of this - * array, or an exception is thrown. After the copy, content of the buffer and of the array can be - * altered independently, without affecting each other. - * - * @param dst the destination buffer - * @return this array - * @throws java.nio.BufferOverflowException if the buffer cannot hold the content of this array - * @see DataBuffer#size() - */ - NdArray read(DataBuffer dst); - - /** - * Write the content of this N-dimensional array from the source buffer. - * - *

The size of the buffer must be equal or greater to the {@link #size()} of this - * array, or an exception is thrown. After the copy, content of the buffer and of the array can be - * altered independently, without affecting each other. - * - * @param src the source buffer - * @return this array - * @throws java.nio.BufferUnderflowException if the buffer has not enough remaining data to write - * into this array - * @see DataBuffer#size() - */ - NdArray write(DataBuffer src); - - /** - * Checks equality between n-dimensional arrays. - * - *

An array is equal to another object if this object is another {@link NdArray} of the - * same shape, type and the elements are equal and in the same order. For example: - * - * 

{@code
-   * IntNdArray array = NdArrays.ofInts(Shape.of(2, 2))
-   *    .set(NdArrays.vectorOf(1, 2), 0)
-   *    .set(NdArrays.vectorOf(3, 4), 1);
-   *
-   * assertEquals(array, StdArrays.ndCopyOf(new int[][] {{1, 2}, {3, 4}}));  // true
-   * assertEquals(array, StdArrays.ndCopyOf(new Integer[][] {{1, 2}, {3, 4}}));  // true, as Integers are equal to ints
-   * assertNotEquals(array, NdArrays.vectorOf(1, 2, 3, 4));  // false, different shapes
-   * assertNotEquals(array, StdArrays.ndCopyOf(new int[][] {{3, 4}, {1, 2}}));  // false, different order
-   * assertNotEquals(array, StdArrays.ndCopyOf(new long[][] {{1L, 2L}, {3L, 4L}}));  // false, different types
-   * }
- * - *

Note that the computation required to verify equality between two arrays can be expensive - * in some cases and therefore, it is recommended to not use this method in a critical path - * where performances matter. - * - * @param obj object to compare this array with - * @return true if this array is equal to the provided object - */ - @Override - boolean equals(Object obj); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/NdArraySequence.java b/ndarray/src/main/java/org/tensorflow/ndarray/NdArraySequence.java deleted file mode 100644 index afb930e278b..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/NdArraySequence.java +++ /dev/null @@ -1,67 +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.ndarray; - -import java.util.function.BiConsumer; -import org.tensorflow.ndarray.buffer.DataBufferWindow; - -/** - * A sequence of elements of an N-dimensional array. - * - *

An {@code NdArraySequence} is used to traverse an {@code NdArray} in a given dimension - * and visit each of its elements. For example, given a {@code n x m} matrix on the {@code [x, y]} axes, - * elements are iterated in the following order: - *

x0y0, x0y1, ..., x0ym-1, x1y0, x1y1, ..., xn-1ym-1 - * - * @param data type of the array being iterated - */ -public interface NdArraySequence> extends Iterable { - - /** - * Visit each elements of this iteration and their respective coordinates. - * - *

Important: the consumer method should not keep a reference to the coordinates - * as they might be mutable and reused during the iteration to improve performance. - * - * @param consumer method to invoke for each elements - */ - void forEachIndexed(BiConsumer consumer); - - /** - * Returns each element as a new slice. - * - *

Unlike conventional Java collections, elements of a {@code NdArraySequence} are transient, i.e. new {@code NdArray} - * instances are allocated for each iteration. To improve performance, the same instance can be recycled to view - * all elements of this sequence, using a {@link DataBufferWindow}. - * - *

In some cases though, it might be preferable to disable such optimizations to ensure that each element returned is a - * new slice of the original array. For example, if one or more elements visited must live beyond the scope of the sequence - * iteration, {@code asSlices()} makes sure that all elements returned by the sequence are unique instances. - * - * 

{@code
-   *     final List vectors = new ArrayList<>();
-   *     IntNdArray matrix = NdArrays.ofInts(Shape.of(6, 6));
-   *     ndArray.elements(0).forEach(e -> vectors::add);  // Not safe, as `e` might always be the same recycled instance
-   *     ndArray.elements(0).asSlices().forEach(e -> vectors::add);  // Safe, each `e` is a distinct NdArray instance
-   * }
- * - * @return a sequence that returns each elements iterated as a new slice - * @see DataBufferWindow - */ - NdArraySequence asSlices(); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/NdArrays.java b/ndarray/src/main/java/org/tensorflow/ndarray/NdArrays.java deleted file mode 100644 index 8ad55cae7ed..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/NdArrays.java +++ /dev/null @@ -1,495 +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.ndarray; - -import org.tensorflow.ndarray.impl.dense.DenseNdArray; -import org.tensorflow.ndarray.impl.dense.IntDenseNdArray; -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.impl.dense.BooleanDenseNdArray; -import org.tensorflow.ndarray.impl.dense.ByteDenseNdArray; -import org.tensorflow.ndarray.impl.dense.DoubleDenseNdArray; -import org.tensorflow.ndarray.impl.dense.FloatDenseNdArray; -import org.tensorflow.ndarray.impl.dense.LongDenseNdArray; -import org.tensorflow.ndarray.impl.dense.ShortDenseNdArray; - -/** - * Utility class for instantiating {@link NdArray} objects. - */ -public final class NdArrays { - - // BYTE ARRAYS - - /** - * Creates byte scalar (rank 0) initialized with the given value. - * - * @param value scalar value - * @return new byte scalar - */ - public static ByteNdArray scalarOf(byte value) { - return ofBytes(Shape.scalar()).setByte(value); - } - - /** - * Creates a byte vector (rank 1) initialized with the given values. - * - *

Modifying the data of the returned vector will also impact the values in the array - * passed in parameter. - * - * @param values vector values - * @return new byte vector - * @throws IllegalArgumentException if values is null - */ - public static ByteNdArray vectorOf(byte... values) { - if (values == null) { - throw new IllegalArgumentException("Values cannot be null"); - } - return wrap(Shape.of(values.length), DataBuffers.of(values, false, false)); - } - - /** - * Creates an N-dimensional array of bytes of the given shape. - * - *

All values are initialized to zeros. - * - * @param shape shape of the array - * @return new byte N-dimensional array - * @throws IllegalArgumentException if shape is null or has unknown dimensions - */ - public static ByteNdArray ofBytes(Shape shape) { - if (shape == null) { - throw new IllegalArgumentException("Shape cannot be null"); - } - return wrap(shape, DataBuffers.ofBytes(shape.size())); - } - - /** - * Wraps a buffer in a byte N-dimensional array of a given shape. - * - * @param shape shape of the array - * @param buffer buffer to wrap - * @return new byte N-dimensional array - * @throws IllegalArgumentException if shape is null, has unknown dimensions or has size bigger - * in the buffer size - */ - public static ByteNdArray wrap(Shape shape, ByteDataBuffer buffer) { - return ByteDenseNdArray.create(buffer, shape); - } - - // LONG ARRAYS - - /** - * Creates long scalar (rank 0) initialized with the given value. - * - * @param value scalar value - * @return new long scalar - */ - public static LongNdArray scalarOf(long value) { - return ofLongs(Shape.scalar()).setLong(value); - } - - /** - * Creates a long vector (rank 1) initialized with the given values. - * - *

Modifying the data of the returned vector will also impact the values in the array - * passed in parameter. - * - * @param values vector values - * @return new long vector - * @throws IllegalArgumentException if values is null - */ - public static LongNdArray vectorOf(long... values) { - if (values == null) { - throw new IllegalArgumentException(); - } - return wrap(Shape.of(values.length), DataBuffers.of(values, false, false)); - } - - /** - * Creates an N-dimensional array of longs of the given shape. - * - *

All values are initialized to zeros. - * - * @param shape shape of the array - * @return new long N-dimensional array - * @throws IllegalArgumentException if shape is null or has unknown dimensions - */ - public static LongNdArray ofLongs(Shape shape) { - return wrap(shape, DataBuffers.ofLongs(shape.size())); - } - - /** - * Wraps a buffer in a long N-dimensional array of a given shape. - * - * @param shape shape of the array - * @param buffer buffer to wrap - * @return new long N-dimensional array - * @throws IllegalArgumentException if shape is null, has unknown dimensions or has size bigger - * in the buffer size - */ - public static LongNdArray wrap(Shape shape, LongDataBuffer buffer) { - return LongDenseNdArray.create(buffer, shape); - } - - // INT ARRAYS - - /** - * Creates long scalar (rank 0) initialized with the given value. - * - * @param value scalar value - * @return new long scalar - */ - public static IntNdArray scalarOf(int value) { - return ofInts(Shape.scalar()).setInt(value); - } - - /** - * Creates a int vector (rank 1) initialized with the given values. - * - *

Modifying the data of the returned vector will also impact the values in the array - * passed in parameter. - * - * @param values vector values - * @return new int vector - * @throws IllegalArgumentException if values is null - */ - public static IntNdArray vectorOf(int... values) { - if (values == null) { - throw new IllegalArgumentException(); - } - return wrap(Shape.of(values.length), DataBuffers.of(values, false, false)); - } - - /** - * Creates an N-dimensional array of ints of the given shape. - * - *

All values are initialized to zeros. - * - * @param shape shape of the array - * @return new int N-dimensional array - * @throws IllegalArgumentException if shape is null or has unknown dimensions - */ - public static IntNdArray ofInts(Shape shape) { - return wrap(shape, DataBuffers.ofInts(shape.size())); - } - - /** - * Wraps a buffer in an int N-dimensional array of a given shape. - * - * @param shape shape of the array - * @param buffer buffer to wrap - * @return new int N-dimensional array - * @throws IllegalArgumentException if shape is null, has unknown dimensions or has size bigger - * in the buffer size - */ - public static IntNdArray wrap(Shape shape, IntDataBuffer buffer) { - return IntDenseNdArray.create(buffer, shape); - } - - // SHORT ARRAYS - - /** - * Creates short scalar (rank 0) initialized with the given value. - * - * @param value scalar value - * @return new short scalar - */ - public static ShortNdArray scalarOf(short value) { - return ofShorts(Shape.scalar()).setShort(value); - } - - /** - * Creates a short vector (rank 1) initialized with the given values. - * - *

Modifying the data of the returned vector will also impact the values in the array - * passed in parameter. - * - * @param values vector values - * @return new short vector - * @throws IllegalArgumentException if values is null - */ - public static ShortNdArray vectorOf(short... values) { - if (values == null) { - throw new IllegalArgumentException(); - } - return wrap(Shape.of(values.length), DataBuffers.of(values, false, false)); - } - - /** - * Creates an N-dimensional array of shorts of the given shape. - * - *

All values are initialized to zeros. - * - * @param shape shape of the array - * @return new short N-dimensional array - * @throws IllegalArgumentException if shape is null or has unknown dimensions - */ - public static ShortNdArray ofShorts(Shape shape) { - return wrap(shape, DataBuffers.ofShorts(shape.size())); - } - - /** - * Wraps a buffer in a short N-dimensional array of a given shape. - * - * @param shape shape of the array - * @param buffer buffer to wrap - * @return new short N-dimensional array - * @throws IllegalArgumentException if shape is null, has unknown dimensions or has size bigger - * in the buffer size - */ - public static ShortNdArray wrap(Shape shape, ShortDataBuffer buffer) { - return ShortDenseNdArray.create(buffer, shape); - } - - // FLOAT ARRAYS - - /** - * Creates float scalar (rank 0) initialized with the given value. - * - * @param value scalar value - * @return new float scalar - */ - public static FloatNdArray scalarOf(float value) { - return ofFloats(Shape.scalar()).setFloat(value); - } - - /** - * Creates a float vector (rank 1) initialized with the given values. - * - *

Modifying the data of the returned vector will also impact the values in the array - * passed in parameter. - * - * @param values vector values - * @return new float vector - * @throws IllegalArgumentException if values is null - */ - public static FloatNdArray vectorOf(float... values) { - if (values == null) { - throw new IllegalArgumentException(); - } - return wrap(Shape.of(values.length), DataBuffers.of(values, false, false)); - } - - /** - * Creates an N-dimensional array of floats of the given shape. - * - *

All values are initialized to zeros. - * - * @param shape shape of the array - * @return new float N-dimensional array - * @throws IllegalArgumentException if shape is null or has unknown dimensions - */ - public static FloatNdArray ofFloats(Shape shape) { - return wrap(shape, DataBuffers.ofFloats(shape.size())); - } - - /** - * Wraps a buffer in a float N-dimensional array of a given shape. - * - * @param shape shape of the array - * @param buffer buffer to wrap - * @return new float N-dimensional array - * @throws IllegalArgumentException if shape is null, has unknown dimensions or has size bigger - * in the buffer size - */ - public static FloatNdArray wrap(Shape shape, FloatDataBuffer buffer) { - return FloatDenseNdArray.create(buffer, shape); - } - - // DOUBLE ARRAYS - - /** - * Creates double scalar (rank 0) initialized with the given value. - * - * @param value scalar value - * @return new double scalar - */ - public static DoubleNdArray scalarOf(double value) { - return ofDoubles(Shape.scalar()).setDouble(value); - } - - /** - * Creates a double vector (rank 1) initialized with the given values. - * - *

Modifying the data of the returned vector will also impact the values in the array - * passed in parameter. - * - * @param values vector values - * @return new double vector - * @throws IllegalArgumentException if values is null - */ - public static DoubleNdArray vectorOf(double... values) { - if (values == null) { - throw new IllegalArgumentException(); - } - return wrap(Shape.of(values.length), DataBuffers.of(values, false, false)); - } - - /** - * Creates an N-dimensional array of doubles of the given shape. - * - *

All values are initialized to zeros. - * - * @param shape shape of the array - * @return new double N-dimensional array - * @throws IllegalArgumentException if shape is null or has unknown dimensions - */ - public static DoubleNdArray ofDoubles(Shape shape) { - return wrap(shape, DataBuffers.ofDoubles(shape.size())); - } - - /** - * Wraps a buffer in a double N-dimensional array of a given shape. - * - * @param shape shape of the array - * @param buffer buffer to wrap - * @return new double N-dimensional array - * @throws IllegalArgumentException if shape is null, has unknown dimensions or has size bigger - * in the buffer size - */ - public static DoubleNdArray wrap(Shape shape, DoubleDataBuffer buffer) { - return DoubleDenseNdArray.create(buffer, shape); - } - - // BOOLEAN ARRAYS - - /** - * Creates boolean scalar (rank 0) initialized with the given value. - * - * @param value scalar value - * @return new boolean scalar - */ - public static BooleanNdArray scalarOf(boolean value) { - return ofBooleans(Shape.scalar()).setBoolean(value); - } - - /** - * Creates a boolean vector (rank 1) initialized with the given values. - * - *

Modifying the data of the returned vector will also impact the values in the array - * passed in parameter. - * - * @param values vector values - * @return new boolean vector - * @throws IllegalArgumentException if values is null - */ - public static BooleanNdArray vectorOf(boolean... values) { - if (values == null) { - throw new IllegalArgumentException(); - } - return wrap(Shape.of(values.length), DataBuffers.of(values, false, false)); - } - - /** - * Creates an N-dimensional array of booleans of the given shape. - * - *

All values are initialized to zeros. - * - * @param shape shape of the array - * @return new boolean N-dimensional array - * @throws IllegalArgumentException if shape is null or has unknown dimensions - */ - public static BooleanNdArray ofBooleans(Shape shape) { - return wrap(shape, DataBuffers.ofBooleans(shape.size())); - } - - /** - * Wraps a buffer in a boolean N-dimensional array of a given shape. - * - * @param shape shape of the array - * @param buffer buffer to wrap - * @return new boolean N-dimensional array - * @throws IllegalArgumentException if shape is null, has unknown dimensions or has size bigger - * in the buffer size - */ - public static BooleanNdArray wrap(Shape shape, BooleanDataBuffer buffer) { - return BooleanDenseNdArray.create(buffer, shape); - } - - // OBJECT ARRAYS - - /** - * Creates scalar (rank 0) initialized with the given value. - * - * @param value scalar value - * @param the data type - * @return new scalar - */ - @SuppressWarnings("unchecked") - public static NdArray scalarOfObject(T value) { - if (value == null) { - throw new IllegalArgumentException(); - } - return ofObjects((Class)value.getClass(), Shape.scalar()).setObject(value); - } - - /** - * Creates a vector (rank 1) initialized with the given values. - * - *

Modifying the data of the returned vector will also impact the values in the array - * passed in parameter. - * - * @param values vector values - * @param the data type - * @return new vector - * @throws IllegalArgumentException if values is null - */ - @SafeVarargs - public static NdArray vectorOfObjects(T... values) { - if (values == null || values.length == 0) { - throw new IllegalArgumentException("Null or zero length input supplied to vectorOfObjects."); - } - return wrap(Shape.of(values.length), DataBuffers.of(values, false, false)); - } - - /** - * Creates an N-dimensional array of the given shape. - * - *

All values are initialized to zeros. - * - * @param clazz class of the data to be stored in this array - * @param shape shape of the array - * @param the data type - * @return new N-dimensional array - * @throws IllegalArgumentException if shape is null or has unknown dimensions - */ - public static NdArray ofObjects(Class clazz, Shape shape) { - return wrap(shape, DataBuffers.ofObjects(clazz, shape.size())); - } - - /** - * Wraps a buffer in an N-dimensional array of a given shape. - * - * @param shape shape of the array - * @param buffer buffer to wrap - * @param the data type - * @return new N-dimensional array - * @throws IllegalArgumentException if shape is null, has unknown dimensions or has size bigger - * in the buffer size - */ - public static NdArray wrap(Shape shape, DataBuffer buffer) { - return DenseNdArray.wrap(buffer, shape); - } -} - diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/Shape.java b/ndarray/src/main/java/org/tensorflow/ndarray/Shape.java deleted file mode 100644 index 85a905408c7..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/Shape.java +++ /dev/null @@ -1,447 +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.ndarray; - -import java.util.Arrays; - -/** - * The shape of a Tensor or {@link NdArray}. - * - *

A {@code Shape} defines sizes along its axes. It may contain an unknown size for one of the - * axes or may be totally unknown, in which case not even the number of axes is known. If the size - * of an axis is unknown, {@link Shape#UNKNOWN_SIZE} should be used as its size. - */ -public final class Shape { - - /** The size of an unknown axis or the total unknown size for an unknown Shape. */ - public static long UNKNOWN_SIZE = -1L; - - /** - * Creates a Shape representing an unknown number of dimensions. - * - * @return A Shape for which {@link Shape#isUnknown()} is true, never null. - */ - public static Shape unknown() { - return new Shape(null); - } - - /** - * Creates a Shape representing a scalar value. - * - * @return A Shape without dimensions for which {@link Shape#isScalar()} is true, never null. - */ - public static Shape scalar() { - return new Shape(new long[0]); - } - - /** - * Create a Shape representing a scalar or an N-dimensional value. - * - *

Creates a Shape representing a scalar or an N-dimensional value (N being at least 1), with - * the provided size for each dimension. A -1 indicates that the size of the corresponding - * dimension is unknown. If no sizes are provided, a Shape representing a scalar is created. For - * example: - * - * 

{@code
-   * // A 2-element vector.
-   * Shape vector = Shape.of(2);
-   *
-   * // A 2x3 matrix.
-   * Shape matrix = Shape.of(2, 3);
-   *
-   * // A matrix with 4 columns but an unknown number of rows.
-   * // This is typically used to indicate the shape of tensors that represent
-   * // a variable-sized batch of values. The Shape below might represent a
-   * // variable-sized batch of 4-element vectors.
-   * Shape batch = Shape.of(-1, 4);
-   *
-   * // A scalar. For readability, you should prefer calling Shape.scalar()
-   * Shape scalar = Shape.of()
-   * }
- * - * @param dimensionSizes number of elements in each dimension of this shape, if any, or - * {@link Shape#UNKNOWN_SIZE} if unknown. - * @return a new shape - */ - public static Shape of(long... dimensionSizes) { - if (dimensionSizes == null || dimensionSizes.length == 0) { - return scalar(); - } - return new Shape(dimensionSizes); - } - - /** - * Returns the total number of elements a Tensor with this Shape would have. - * - *

If {@link Shape#isUnknown()} is true or {@link Shape#hasUnknownDimension()} is true, {@link - * Shape#UNKNOWN_SIZE} is returned. - * - * @return The total number of elements a Tensor with this shape would have if it can be - * calculated, else {@link Shape#UNKNOWN_SIZE}. - */ - public long size() { - if (size == null) { - size = computeSize(dimensionSizes); - } - return size; - } - - /** - * The size of the dimension with the given index. - * - *

If {@link Shape#isUnknown()} is true or the size of the dimension with the given index has - * an unknown size, {@link Shape#UNKNOWN_SIZE} is returned. - * - * @param i the index of the dimension to get the size for. If this Shape has a known number of - * dimensions, it must be < {@link Shape#numDimensions()}. The index may be negative, in which - * case the position is counted from the end of the shape. E.g.: {@code size(-1)} returns the - * size of the last dimension, {@code size(-2)} the size of the second to last dimension etc. - * @return The size of the dimension with the given index if known, {@link Shape#UNKNOWN_SIZE} - * otherwise. - */ - public long size(int i) { - if (dimensionSizes == null) { - return UNKNOWN_SIZE; - } else if (i >= 0) { - return dimensionSizes[i]; - } else { - return dimensionSizes[dimensionSizes.length + i]; - } - } - - /** - * Returns the number of dimensions of this Shape. -1 if unknown, 0 for a scalar, 1 for a vector, - * 2 for a matrix etc. - */ - public int numDimensions() { - return dimensionSizes != null ? dimensionSizes.length : -1; - } - - /** Returns whether one or more dimensions of this Shape have an unknown size. */ - public boolean hasUnknownDimension() { - if (dimensionSizes == null) { - return true; - } - for (long dimSize : dimensionSizes) { - if (dimSize == UNKNOWN_SIZE) { - return true; - } - } - return false; - } - - /** Returns whether this Shape represents a scalar. */ - public boolean isScalar() { - return dimensionSizes != null && dimensionSizes.length == 0; - } - - /** Returns whether this Shape is the shape of a vector. */ - public boolean isVector() { - return dimensionSizes != null && dimensionSizes.length == 1; - } - - /** Returns whether this Shape is the shape of a matrix */ - public boolean isMatrix() { - return dimensionSizes != null && dimensionSizes.length == 2; - } - - /** Returns whether the number of dimensions of this Shape is unknown. */ - public boolean isUnknown() { - return dimensionSizes == null; - } - - /** - * Returns a defensive copy of the this Shape's axes. Changes to the returned array to not change - * this Shape's state. Returns null if {@link Shape#isUnknown()} is true. - */ - public long[] asArray() { - if (this.dimensionSizes == null) { - return null; - } else { - return Arrays.copyOf(dimensionSizes, dimensionSizes.length); - } - } - - @Override - public int hashCode() { - return dimensionSizes != null ? Arrays.hashCode(dimensionSizes) : super.hashCode(); - } - - /** - * Equals implementation for Shapes. Two Shapes are considered equal iff: - * - *

- *

    - *
  • the number of dimensions is defined and equal for both - *
  • the size of each dimension is defined and equal for both - *
- * - *

If either Shape has unknown dimensions (even if they are the same in both) or if either - * shape has an unknown number of dimensions (even if both return {@code true} for {@link - * Shape#isUnknown()}), they are not considered equal! However, a shape will always equal itself, - * even if it is unknown or contains unknown dimensions. - */ - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - // Shapes are equivalent if all of their dimensions are equals - if (obj instanceof Shape) { - Shape otherShape = (Shape) obj; - if (otherShape.hasUnknownDimension()) { - return false; - } - return Arrays.equals(dimensionSizes, otherShape.dimensionSizes); - } - return false; - } - - /** Succinct description of the Shape meant for debugging. */ - @Override - public String toString() { - return Arrays.toString(dimensionSizes); - } - - private Shape(long[] dimensionSizes) { - this.dimensionSizes = dimensionSizes; - } - - private final long[] dimensionSizes; - private Long size; - - /** - * Returns a 1-dimensional Shape with first dimension matching the first dimension of this Shape. - */ - public Shape head() { - return take(1); - } - - /** - * Returns an n-dimensional Shape with the dimensions matching the first n dimensions of this - * shape - * - * @param n the number of leading dimensions to get, must be <= than {@link Shape#numDimensions()} - * @return an n-dimensional Shape with the first n dimensions matching the first n dimensions of - * this Shape - */ - public Shape take(int n) { - if (n > numDimensions()) { - throw new ArrayIndexOutOfBoundsException( - "Cannot take " + n + " dimensions, shape has only " + numDimensions() + "."); - } - long[] newDimensions = new long[n]; - System.arraycopy(dimensionSizes, 0, newDimensions, 0, n); - return Shape.of(newDimensions); - } - - /** Returns a new Shape, with this Shape's first dimension removed. */ - public Shape tail() { - if (dimensionSizes.length < 2) return Shape.of(); - return Shape.of(Arrays.copyOfRange(dimensionSizes, 1, dimensionSizes.length)); - } - - /** - * Returns an n-dimensional Shape with the dimensions matching the last n dimensions of this - * Shape. - * - * @param n the number of trailing dimensions to get, must be <= than {@link - * Shape#numDimensions()} - * @return an n-dimensional shape with the dimensions matching the last n dimensions of this - * Shape, never null - */ - public Shape takeLast(int n) { - if (n > numDimensions()) { - throw new ArrayIndexOutOfBoundsException( - "Cannot take last " + n + " dimensions, shape has only " + numDimensions() + "."); - } - long[] newDimensions = new long[n]; - System.arraycopy(dimensionSizes, numDimensions() - n, newDimensions, 0, n); - return Shape.of(newDimensions); - } - - /** - * Return a {@code end - begin} dimensional shape with dimensions matching this Shape from {@code begin} to {@code end}. - * @param begin Where to start the sub-shape. - * @param end Where to end the sub-shape, exclusive. - * @return the sub-shape bounded by begin and end. - */ - public Shape subShape(int begin, int end){ - if (end > numDimensions()) { - throw new ArrayIndexOutOfBoundsException( - "End index " + end + " out of bounds: shape only has " + numDimensions() + " dimensions."); - } - if (begin < 0) { - throw new ArrayIndexOutOfBoundsException( - "Begin index " + begin + " out of bounds: cannot be less than 0."); - } - - long[] newDimensions = new long[end - begin]; - System.arraycopy(dimensionSizes, begin, newDimensions, 0, end - begin); - return Shape.of(newDimensions); - } - - /** - * Returns a new Shape, with a new first dimension added. In order for this call to succeed, - * {@link Shape#isUnknown()} must be {@code false}. - * - * @param firstDimension the dimension to prepend - * @return a new shape with the given dimension first, followed by this Shape's dimensions, never - * null - */ - public Shape prepend(long firstDimension) { - long[] newDimensions = new long[dimensionSizes.length + 1]; - newDimensions[0] = firstDimension; - System.arraycopy(dimensionSizes, 0, newDimensions, 1, dimensionSizes.length); - - return Shape.of(newDimensions); - } - - /** - * Returns a new Shape, with a new last dimension added. In order for this call to succeed, {@link - * Shape#isUnknown()} must be {@code false}. - * - * @param lastDimension the dimension to append - * @return a new Shape with this Shape's dimensions followed by the given dimension, never null - */ - public Shape append(long lastDimension) { - long[] newDimensions = new long[dimensionSizes.length + 1]; - newDimensions[newDimensions.length - 1] = lastDimension; - System.arraycopy(dimensionSizes, 0, newDimensions, 0, dimensionSizes.length); - - return Shape.of(newDimensions); - } - - /** - * Returns a new Shape, with another Shape's dimensions prepended. For both this Shape and the - * other Shape, {@link Shape#isUnknown()} must return false. E.g. {@code - * Shape.of(3,4).prepend(Shape.of(1,2)) => Shape.of(1,2,3,4) } - * - * @param other another Shape, must not be {@code null}, must not be unknown - * @return A new Shape consisting of the given Shape's dimensions followed by this Shape's - * dimensions, never null - */ - public Shape prepend(Shape other) { - long[] newDimensions = new long[other.dimensionSizes.length + dimensionSizes.length]; - System.arraycopy(other.dimensionSizes, 0, newDimensions, 0, other.dimensionSizes.length); - System.arraycopy( - dimensionSizes, 0, newDimensions, other.dimensionSizes.length, dimensionSizes.length); - return Shape.of(newDimensions); - } - - /** - * Returns a new Shape, with another Shapes' dimensions appended. For both this Shape and the - * other Shape, {@link Shape#isUnknown()} must return false. E.g. @code - * Shape.of(3,4).append(Shape.of(1,2)) => Shape.of(3,4,1,2) } - * - * @param other another Shape, must not be {@code null}, must not be unknown - * @return A new Shape consisting of this Shape's dimensions followed by the given Shape's - * dimensions - */ - public Shape append(Shape other) { - long[] newDimensions = new long[dimensionSizes.length + other.dimensionSizes.length]; - System.arraycopy(dimensionSizes, 0, newDimensions, 0, dimensionSizes.length); - System.arraycopy( - other.dimensionSizes, 0, newDimensions, dimensionSizes.length, other.dimensionSizes.length); - return Shape.of(newDimensions); - } - - private static long computeSize(long[] dimensionSizes) { - if (dimensionSizes == null) { - return UNKNOWN_SIZE; - } - long computedSize = 1L; - for (long dimensionSize : dimensionSizes) { - if (dimensionSize == UNKNOWN_SIZE) { - return UNKNOWN_SIZE; - } - computedSize *= dimensionSize; - } - return computedSize; - } - - /** - * Determines whether another shape is compatible with this one. - * - *

- * - *

Two possibly-partially-defined shapes are compatible if there exists a fully-defined shape - * that both shapes can represent. Thus, compatibility allows the shape inference code to reason - * about partially-defined shapes. For example: - * - *

    - *
  • Shape.unknown() is compatible with all shapes. - *
  • Shape(UNKNOWN_SIZE, UNKNOWN_SIZE) is compatible with all two-dimensional - * shapes, such as Shape(32, 784), and also Shape.unknown(). It is - * not compatible with, for example, Shape(UNKNOWN_SIZE) or - * Shape(UNKNOWN_SIZE, UNKNOWN_SIZE, UNKNOWN_SIZE). - *
  • Shape(32, UNKNOWN_SIZE) is compatible with all two-dimensional shapes with - * size 32 in the 0th dimension, and also Shape(UNKNOWN_SIZE, UNKNOWN_SIZE) and - * Shape.unknown(). It is not compatible with, for example, Shape(32) - * , Shape(32, UNKNOWN_SIZE, 1) or Shape(64, UNKNOWN_SIZE). - *
  • Shape(32, 784) is compatible with itself, and also - * Shape(32, UNKNOWN_SIZE), Shape(UNKNOWN_SIZE, 784), - * Shape(UNKNOWN_SIZE, UNKNOWN_SIZE) and Shape.unknown(). It is not - * compatible with, for example, Shape(32, 1, 784) or Shape(UNKNOWN_SIZE) - * . - *
- * - *

The compatibility relation is reflexive and symmetric, but not transitive. For example, - * Shape(32, 784) is compatible with Shape.unknown(), and - * Shape.unknown() is compatible with Shape(4, 4), but Shape(32, 784) - * is not compatible with Shape(4, 4). - * - *

Compatibility is not the same as broadcasting. Compatible shapes must have the same number - * of dimensions and for each dimension pair, one dimension has to equal the other dimensions or - * at least one of the dimensions in the pair has to be UNKNOWN_SIZE. - * - *

Broadcasting allows different dimensions, but paired dimensions have to either be equal, or - * one dimension must be 1. If one shape has less dimensions than another shape, the smaller shape - * is "stretched" with dimensions of 1. - * - * @param shape The other shape - * @return true, if the two shapes are compatible. - */ - public boolean isCompatibleWith(Shape shape) { - if (!this.isUnknown() && !shape.isUnknown()) { - if (numDimensions() != shape.numDimensions()) { - return false; - } - for (int i = 0; i < numDimensions(); i++) { - if (!isCompatible(size(i), shape.size(i))) { - return false; - } - } - } - return true; - } - - /** - * Test to see if two shape dimensions are compatible. - * - *

The dimensions are compatible if either dimension is Shape.UNKNOWN_SIZE or both - * dimensions are equal - * - * @param dim the first dimension - * @param otherDim the second dimension - * @return true, if both dimensions are compatible - */ - public static boolean isCompatible(long dim, long otherDim) { - return dim == Shape.UNKNOWN_SIZE || otherDim == Shape.UNKNOWN_SIZE || dim == otherDim; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/Shaped.java b/ndarray/src/main/java/org/tensorflow/ndarray/Shaped.java deleted file mode 100644 index fbe19d75623..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/Shaped.java +++ /dev/null @@ -1,51 +0,0 @@ -/* - 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.ndarray; - -import java.util.function.BiConsumer; -import java.util.function.Consumer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.index.Index; - -/** - * Any data container with a given {@link Shape}. - */ -public interface Shaped { - - /** - * @return the shape of this container - */ - Shape shape(); - - /** - * @return the rank of this container - */ - default int rank() { - return shape().numDimensions(); - } - - /** - * Computes and returns the total size of this container, in number of values. - * - *

For example, given a 3x3x2 matrix, the return value will be 18. - * - * @return number of values in this element - */ - default long size() { - return shape().size(); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/ShortNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/ShortNdArray.java deleted file mode 100644 index f9335b4d5d2..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/ShortNdArray.java +++ /dev/null @@ -1,108 +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.ndarray; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.index.Index; - -/** - * An {@link NdArray} of shorts. - */ -public interface ShortNdArray extends NdArray { - - /** - * Returns the short value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  ShortNdArray matrix = NdArrays.ofShorts(shape(2, 2));  // matrix rank = 2
-   *  matrix.getShort(0, 1);  // succeeds, returns 0.0f
-   *  matrix.getShort(0);  // throws IllegalRankException
-   *
-   *  ShortNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.getShort();  // succeeds, returns 0.0f
-   * }
- * - * @param coordinates coordinates of the scalar to resolve - * @return value of that scalar - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar element - */ - short getShort(long... coordinates); - - /** - * Assigns the short value of the scalar found at the given coordinates. - * - *

To access the scalar element, the number of coordinates provided must be equal to the number - * of dimensions of this array (i.e. its rank). For example: - * 

{@code
-   *  ShortNdArray matrix = NdArrays.ofShorts(shape(2, 2));  // matrix rank = 2
-   *  matrix.setShort(10.0f, 0, 1);  // succeeds
-   *  matrix.setShort(10.0f, 0);  // throws IllegalRankException
-   *
-   *  ShortNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
-   *  scalar.setShort(10.0f);  // succeeds
-   * }
- * - * @param value value to assign - * @param coordinates coordinates of the scalar to assign - * @return this array - * @throws IndexOutOfBoundsException if some coordinates are outside the limits of their respective dimension - * @throws IllegalRankException if number of coordinates is not sufficient to access a scalar element - */ - ShortNdArray setShort(short value, long... coordinates); - - @Override - ShortNdArray slice(Index... coordinates); - - @Override - ShortNdArray get(long... coordinates); - - @Override - ShortNdArray set(NdArray src, long... coordinates); - - @Override - default Short getObject(long... coordinates) { - return getShort(coordinates); - } - - @Override - default ShortNdArray setObject(Short value, long... coordinates) { - return setShort(value, coordinates); - } - - @Override - NdArraySequence elements(int dimensionIdx); - - @Override - NdArraySequence scalars(); - - @Override - ShortNdArray copyTo(NdArray dst); - - @Override - ShortNdArray read(DataBuffer dst); - - ShortNdArray read(ShortDataBuffer dst); - - @Override - ShortNdArray write(DataBuffer src); - - ShortNdArray write(ShortDataBuffer src); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/StdArrays.java b/ndarray/src/main/java/org/tensorflow/ndarray/StdArrays.java deleted file mode 100644 index 7d847bd1a9c..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/StdArrays.java +++ /dev/null @@ -1,3809 +0,0 @@ -package org.tensorflow.ndarray; - -import static org.tensorflow.ndarray.NdArrays.vectorOf; - -import java.lang.reflect.Array; -import org.tensorflow.ndarray.buffer.DataBuffers; - -/** - * Utility class for working with {@link NdArray} instances mixed with standard Java arrays. - */ -public final class StdArrays { - - /** - * Copy an array of ints in a new {@link IntNdArray} - * - * @param array source array - * @return the {@code IntNdArray} copy - */ - public static IntNdArray ndCopyOf(int[] array) { - IntNdArray ndArray = NdArrays.ofInts(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 2-dimensional array of ints in a new {@link IntNdArray} - * - * @param array source array - * @return the {@code IntNdArray} copy - */ - public static IntNdArray ndCopyOf(int[][] array) { - IntNdArray ndArray = NdArrays.ofInts(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 3-dimensional array of ints in a new {@link IntNdArray} - * - * @param array source array - * @return the {@code IntNdArray} copy - */ - public static IntNdArray ndCopyOf(int[][][] array) { - IntNdArray ndArray = NdArrays.ofInts(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 4-dimensional array of ints in a new {@link IntNdArray} - * - * @param array source array - * @return the {@code IntNdArray} copy - */ - public static IntNdArray ndCopyOf(int[][][][] array) { - IntNdArray ndArray = NdArrays.ofInts(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 5-dimensional array of ints in a new {@link IntNdArray} - * - * @param array source array - * @return the {@code IntNdArray} copy - */ - public static IntNdArray ndCopyOf(int[][][][][] array) { - IntNdArray ndArray = NdArrays.ofInts(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 6-dimensional array of ints in a new {@link IntNdArray} - * - * @param array source array - * @return the {@code IntNdArray} copy - */ - public static IntNdArray ndCopyOf(int[][][][][][] array) { - IntNdArray ndArray = NdArrays.ofInts(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy an array of longs in a new {@link LongNdArray} - * - * @param array source array - * @return the {@code LongNdArray} copy - */ - public static LongNdArray ndCopyOf(long[] array) { - LongNdArray ndArray = NdArrays.ofLongs(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 2-dimensional array of longs in a new {@link LongNdArray} - * - * @param array source array - * @return the {@code LongNdArray} copy - */ - public static LongNdArray ndCopyOf(long[][] array) { - LongNdArray ndArray = NdArrays.ofLongs(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 3-dimensional array of longs in a new {@link LongNdArray} - * - * @param array source array - * @return the {@code LongNdArray} copy - */ - public static LongNdArray ndCopyOf(long[][][] array) { - LongNdArray ndArray = NdArrays.ofLongs(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 4-dimensional array of longs in a new {@link LongNdArray} - * - * @param array source array - * @return the {@code LongNdArray} copy - */ - public static LongNdArray ndCopyOf(long[][][][] array) { - LongNdArray ndArray = NdArrays.ofLongs(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 5-dimensional array of longs in a new {@link LongNdArray} - * - * @param array source array - * @return the {@code LongNdArray} copy - */ - public static LongNdArray ndCopyOf(long[][][][][] array) { - LongNdArray ndArray = NdArrays.ofLongs(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 6-dimensional array of longs in a new {@link LongNdArray} - * - * @param array source array - * @return the {@code LongNdArray} copy - */ - public static LongNdArray ndCopyOf(long[][][][][][] array) { - LongNdArray ndArray = NdArrays.ofLongs(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy an array of floats in a new {@link FloatNdArray} - * - * @param array source array - * @return the {@code FloatNdArray} copy - */ - public static FloatNdArray ndCopyOf(float[] array) { - FloatNdArray ndArray = NdArrays.ofFloats(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 2-dimensional array of floats in a new {@link FloatNdArray} - * - * @param array source array - * @return the {@code FloatNdArray} copy - */ - public static FloatNdArray ndCopyOf(float[][] array) { - FloatNdArray ndArray = NdArrays.ofFloats(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 3-dimensional array of floats in a new {@link FloatNdArray} - * - * @param array source array - * @return the {@code FloatNdArray} copy - */ - public static FloatNdArray ndCopyOf(float[][][] array) { - FloatNdArray ndArray = NdArrays.ofFloats(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 4-dimensional array of floats in a new {@link FloatNdArray} - * - * @param array source array - * @return the {@code FloatNdArray} copy - */ - public static FloatNdArray ndCopyOf(float[][][][] array) { - FloatNdArray ndArray = NdArrays.ofFloats(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 5-dimensional array of floats in a new {@link FloatNdArray} - * - * @param array source array - * @return the {@code FloatNdArray} copy - */ - public static FloatNdArray ndCopyOf(float[][][][][] array) { - FloatNdArray ndArray = NdArrays.ofFloats(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 6-dimensional array of floats in a new {@link FloatNdArray} - * - * @param array source array - * @return the {@code FloatNdArray} copy - */ - public static FloatNdArray ndCopyOf(float[][][][][][] array) { - FloatNdArray ndArray = NdArrays.ofFloats(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy an array of doubles in a new {@link DoubleNdArray} - * - * @param array source array - * @return the {@code DoubleNdArray} copy - */ - public static DoubleNdArray ndCopyOf(double[] array) { - DoubleNdArray ndArray = NdArrays.ofDoubles(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 2-dimensional array of doubles in a new {@link DoubleNdArray} - * - * @param array source array - * @return the {@code DoubleNdArray} copy - */ - public static DoubleNdArray ndCopyOf(double[][] array) { - DoubleNdArray ndArray = NdArrays.ofDoubles(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 3-dimensional array of doubles in a new {@link DoubleNdArray} - * - * @param array source array - * @return the {@code DoubleNdArray} copy - */ - public static DoubleNdArray ndCopyOf(double[][][] array) { - DoubleNdArray ndArray = NdArrays.ofDoubles(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 4-dimensional array of doubles in a new {@link DoubleNdArray} - * - * @param array source array - * @return the {@code DoubleNdArray} copy - */ - public static DoubleNdArray ndCopyOf(double[][][][] array) { - DoubleNdArray ndArray = NdArrays.ofDoubles(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 5-dimensional array of doubles in a new {@link DoubleNdArray} - * - * @param array source array - * @return the {@code DoubleNdArray} copy - */ - public static DoubleNdArray ndCopyOf(double[][][][][] array) { - DoubleNdArray ndArray = NdArrays.ofDoubles(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 6-dimensional array of doubles in a new {@link DoubleNdArray} - * - * @param array source array - * @return the {@code DoubleNdArray} copy - */ - public static DoubleNdArray ndCopyOf(double[][][][][][] array) { - DoubleNdArray ndArray = NdArrays.ofDoubles(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy an array of bytes in a new {@link ByteNdArray} - * - * @param array source array - * @return the {@code ByteNdArray} copy - */ - public static ByteNdArray ndCopyOf(byte[] array) { - ByteNdArray ndArray = NdArrays.ofBytes(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 2-dimensional array of bytes in a new {@link ByteNdArray} - * - * @param array source array - * @return the {@code ByteNdArray} copy - */ - public static ByteNdArray ndCopyOf(byte[][] array) { - ByteNdArray ndArray = NdArrays.ofBytes(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 3-dimensional array of bytes in a new {@link ByteNdArray} - * - * @param array source array - * @return the {@code ByteNdArray} copy - */ - public static ByteNdArray ndCopyOf(byte[][][] array) { - ByteNdArray ndArray = NdArrays.ofBytes(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 4-dimensional array of bytes in a new {@link ByteNdArray} - * - * @param array source array - * @return the {@code ByteNdArray} copy - */ - public static ByteNdArray ndCopyOf(byte[][][][] array) { - ByteNdArray ndArray = NdArrays.ofBytes(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 5-dimensional array of bytes in a new {@link ByteNdArray} - * - * @param array source array - * @return the {@code ByteNdArray} copy - */ - public static ByteNdArray ndCopyOf(byte[][][][][] array) { - ByteNdArray ndArray = NdArrays.ofBytes(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 6-dimensional array of bytes in a new {@link ByteNdArray} - * - * @param array source array - * @return the {@code ByteNdArray} copy - */ - public static ByteNdArray ndCopyOf(byte[][][][][][] array) { - ByteNdArray ndArray = NdArrays.ofBytes(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy an array of shorts in a new {@link ShortNdArray} - * - * @param array source array - * @return the {@code ShortNdArray} copy - */ - public static ShortNdArray ndCopyOf(short[] array) { - ShortNdArray ndArray = NdArrays.ofShorts(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 2-dimensional array of shorts in a new {@link ShortNdArray} - * - * @param array source array - * @return the {@code ShortNdArray} copy - */ - public static ShortNdArray ndCopyOf(short[][] array) { - ShortNdArray ndArray = NdArrays.ofShorts(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 3-dimensional array of shorts in a new {@link ShortNdArray} - * - * @param array source array - * @return the {@code ShortNdArray} copy - */ - public static ShortNdArray ndCopyOf(short[][][] array) { - ShortNdArray ndArray = NdArrays.ofShorts(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 4-dimensional array of shorts in a new {@link ShortNdArray} - * - * @param array source array - * @return the {@code ShortNdArray} copy - */ - public static ShortNdArray ndCopyOf(short[][][][] array) { - ShortNdArray ndArray = NdArrays.ofShorts(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 5-dimensional array of shorts in a new {@link ShortNdArray} - * - * @param array source array - * @return the {@code ShortNdArray} copy - */ - public static ShortNdArray ndCopyOf(short[][][][][] array) { - ShortNdArray ndArray = NdArrays.ofShorts(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 6-dimensional array of shorts in a new {@link ShortNdArray} - * - * @param array source array - * @return the {@code ShortNdArray} copy - */ - public static ShortNdArray ndCopyOf(short[][][][][][] array) { - ShortNdArray ndArray = NdArrays.ofShorts(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy an array of booleans in a new {@link BooleanNdArray} - * - * @param array source array - * @return the {@code BooleanNdArray} copy - */ - public static BooleanNdArray ndCopyOf(boolean[] array) { - BooleanNdArray ndArray = NdArrays.ofBooleans(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 2-dimensional array of booleans in a new {@link BooleanNdArray} - * - * @param array source array - * @return the {@code BooleanNdArray} copy - */ - public static BooleanNdArray ndCopyOf(boolean[][] array) { - BooleanNdArray ndArray = NdArrays.ofBooleans(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 3-dimensional array of booleans in a new {@link BooleanNdArray} - * - * @param array source array - * @return the {@code BooleanNdArray} copy - */ - public static BooleanNdArray ndCopyOf(boolean[][][] array) { - BooleanNdArray ndArray = NdArrays.ofBooleans(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 4-dimensional array of booleans in a new {@link BooleanNdArray} - * - * @param array source array - * @return the {@code BooleanNdArray} copy - */ - public static BooleanNdArray ndCopyOf(boolean[][][][] array) { - BooleanNdArray ndArray = NdArrays.ofBooleans(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 5-dimensional array of booleans in a new {@link BooleanNdArray} - * - * @param array source array - * @return the {@code BooleanNdArray} copy - */ - public static BooleanNdArray ndCopyOf(boolean[][][][][] array) { - BooleanNdArray ndArray = NdArrays.ofBooleans(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 6-dimensional array of booleans in a new {@link BooleanNdArray} - * - * @param array source array - * @return the {@code BooleanNdArray} copy - */ - public static BooleanNdArray ndCopyOf(boolean[][][][][][] array) { - BooleanNdArray ndArray = NdArrays.ofBooleans(shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy an array of objects in a new {@link NdArray} - * - * @param array source array - * @param data type - * @return the {@code NdArray} copy - */ - public static NdArray ndCopyOf(T[] array) { - @SuppressWarnings("unchecked") - NdArray ndArray = NdArrays.ofObjects(componentTypeOf(array), shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 2-dimensional array of objects in a new {@link NdArray} - * - * @param array source array - * @param data type - * @return the {@code NdArray} copy - */ - public static NdArray ndCopyOf(T[][] array) { - @SuppressWarnings("unchecked") - NdArrayndArray = NdArrays.ofObjects(componentTypeOf(array), shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 3-dimensional array of objects in a new {@link NdArray} - * - * @param array source array - * @param data type - * @return the {@code NdArray} copy - */ - public static NdArray ndCopyOf(T[][][] array) { - @SuppressWarnings("unchecked") - NdArrayndArray = NdArrays.ofObjects(componentTypeOf(array), shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 4-dimensional array of objects in a new {@link NdArray} - * - * @param array source array - * @param data type - * @return the {@code NdArray} copy - */ - public static NdArray ndCopyOf(T[][][][] array) { - @SuppressWarnings("unchecked") - NdArrayndArray = NdArrays.ofObjects(componentTypeOf(array), shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 5-dimensional array of objects in a new {@link NdArray} - * - * @param array source array - * @param data type - * @return the {@code NdArray} copy - */ - public static NdArray ndCopyOf(T[][][][][] array) { - @SuppressWarnings("unchecked") - NdArrayndArray = NdArrays.ofObjects(componentTypeOf(array), shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a 6-dimensional array of objects in a new {@link NdArray} - * - * @param array source array - * @param data type - * @return the {@code NdArray} copy - */ - public static NdArray ndCopyOf(T[][][][][][] array) { - @SuppressWarnings("unchecked") - NdArrayndArray = NdArrays.ofObjects(componentTypeOf(array), shapeOf(array)); - copyTo(array, ndArray); - return ndArray; - } - - /** - * Copy a {@link IntNdArray} in a new 1-dimension standard array of ints - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-1 or has a shape that - * exceeds standard arrays limits - */ - public static int[] array1dCopyOf(IntNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 1); - int[] array = new int[dims[0]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link IntNdArray} in a new 2-dimension standard array of ints - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-2 or has a shape that - * exceeds standard arrays limits - */ - public static int[][] array2dCopyOf(IntNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 2); - int[][] array = new int[dims[0]][dims[1]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link IntNdArray} in a new 3-dimension standard array of ints - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-3 or has a shape that - * exceeds standard arrays limits - */ - public static int[][][] array3dCopyOf(IntNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 3); - int[][][] array = new int[dims[0]][dims[1]][dims[2]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link IntNdArray} in a new 4-dimension standard array of ints - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-4 or has a shape that - * exceeds standard arrays limits - */ - public static int[][][][] array4dCopyOf(IntNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 4); - int[][][][] array = new int[dims[0]][dims[1]][dims[2]][dims[3]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link IntNdArray} in a new 5-dimension standard array of ints - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-5 or has a shape that - * exceeds standard arrays limits - */ - public static int[][][][][] array5dCopyOf(IntNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 5); - int[][][][][] array = new int[dims[0]][dims[1]][dims[2]][dims[3]][dims[4]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link IntNdArray} in a new 6-dimension standard array of ints - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-6 or has a shape that - * exceeds standard arrays limits - */ - public static int[][][][][][] array6dCopyOf(IntNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 6); - int[][][][][][] array = new int[dims[0]][dims[1]][dims[2]][dims[3]][dims[4]][dims[5]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link LongNdArray} in a new 1-dimension standard array of longs - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-1 or has a shape that - * exceeds standard arrays limits - */ - public static long[] array1dCopyOf(LongNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 1); - long[] array = new long[dims[0]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link LongNdArray} in a new 2-dimension standard array of longs - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-2 or has a shape that - * exceeds standard arrays limits - */ - public static long[][] array2dCopyOf(LongNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 2); - long[][] array = new long[dims[0]][dims[1]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link LongNdArray} in a new 3-dimension standard array of longs - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-3 or has a shape that - * exceeds standard arrays limits - */ - public static long[][][] array3dCopyOf(LongNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 3); - long[][][] array = new long[dims[0]][dims[1]][dims[2]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link LongNdArray} in a new 4-dimension standard array of longs - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-4 or has a shape that - * exceeds standard arrays limits - */ - public static long[][][][] array4dCopyOf(LongNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 4); - long[][][][] array = new long[dims[0]][dims[1]][dims[2]][dims[3]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link LongNdArray} in a new 5-dimension standard array of longs - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-5 or has a shape that - * exceeds standard arrays limits - */ - public static long[][][][][] array5dCopyOf(LongNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 5); - long[][][][][] array = new long[dims[0]][dims[1]][dims[2]][dims[3]][dims[4]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link LongNdArray} in a new 6-dimension standard array of longs - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-6 or has a shape that - * exceeds standard arrays limits - */ - public static long[][][][][][] array6dCopyOf(LongNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 6); - long[][][][][][] array = new long[dims[0]][dims[1]][dims[2]][dims[3]][dims[4]][dims[5]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link FloatNdArray} in a new 1-dimension standard array of floats - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-1 or has a shape that - * exceeds standard arrays limits - */ - public static float[] array1dCopyOf(FloatNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 1); - float[] array = new float[dims[0]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link FloatNdArray} in a new 2-dimension standard array of floats - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-2 or has a shape that - * exceeds standard arrays limits - */ - public static float[][] array2dCopyOf(FloatNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 2); - float[][] array = new float[dims[0]][dims[1]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link FloatNdArray} in a new 3-dimension standard array of floats - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-3 or has a shape that - * exceeds standard arrays limits - */ - public static float[][][] array3dCopyOf(FloatNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 3); - float[][][] array = new float[dims[0]][dims[1]][dims[2]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link FloatNdArray} in a new 4-dimension standard array of floats - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-4 or has a shape that - * exceeds standard arrays limits - */ - public static float[][][][] array4dCopyOf(FloatNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 4); - float[][][][] array = new float[dims[0]][dims[1]][dims[2]][dims[3]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link FloatNdArray} in a new 5-dimension standard array of floats - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-5 or has a shape that - * exceeds standard arrays limits - */ - public static float[][][][][] array5dCopyOf(FloatNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 5); - float[][][][][] array = new float[dims[0]][dims[1]][dims[2]][dims[3]][dims[4]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link FloatNdArray} in a new 6-dimension standard array of floats - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-6 or has a shape that - * exceeds standard arrays limits - */ - public static float[][][][][][] array6dCopyOf(FloatNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 6); - float[][][][][][] array = new float[dims[0]][dims[1]][dims[2]][dims[3]][dims[4]][dims[5]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link DoubleNdArray} in a new 1-dimension standard array of doubles - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-1 or has a shape that - * exceeds standard arrays limits - */ - public static double[] array1dCopyOf(DoubleNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 1); - double[] array = new double[dims[0]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link DoubleNdArray} in a new 2-dimension standard array of doubles - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-2 or has a shape that - * exceeds standard arrays limits - */ - public static double[][] array2dCopyOf(DoubleNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 2); - double[][] array = new double[dims[0]][dims[1]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link DoubleNdArray} in a new 3-dimension standard array of doubles - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-3 or has a shape that - * exceeds standard arrays limits - */ - public static double[][][] array3dCopyOf(DoubleNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 3); - double[][][] array = new double[dims[0]][dims[1]][dims[2]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link DoubleNdArray} in a new 4-dimension standard array of doubles - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-4 or has a shape that - * exceeds standard arrays limits - */ - public static double[][][][] array4dCopyOf(DoubleNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 4); - double[][][][] array = new double[dims[0]][dims[1]][dims[2]][dims[3]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link DoubleNdArray} in a new 5-dimension standard array of doubles - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-5 or has a shape that - * exceeds standard arrays limits - */ - public static double[][][][][] array5dCopyOf(DoubleNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 5); - double[][][][][] array = new double[dims[0]][dims[1]][dims[2]][dims[3]][dims[4]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link DoubleNdArray} in a new 6-dimension standard array of doubles - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-6 or has a shape that - * exceeds standard arrays limits - */ - public static double[][][][][][] array6dCopyOf(DoubleNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 6); - double[][][][][][] array = new double[dims[0]][dims[1]][dims[2]][dims[3]][dims[4]][dims[5]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link ByteNdArray} in a new 1-dimension standard array of bytes - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-1 or has a shape that - * exceeds standard arrays limits - */ - public static byte[] array1dCopyOf(ByteNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 1); - byte[] array = new byte[dims[0]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link ByteNdArray} in a new 2-dimension standard array of bytes - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-2 or has a shape that - * exceeds standard arrays limits - */ - public static byte[][] array2dCopyOf(ByteNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 2); - byte[][] array = new byte[dims[0]][dims[1]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link ByteNdArray} in a new 3-dimension standard array of bytes - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-3 or has a shape that - * exceeds standard arrays limits - */ - public static byte[][][] array3dCopyOf(ByteNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 3); - byte[][][] array = new byte[dims[0]][dims[1]][dims[2]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link ByteNdArray} in a new 4-dimension standard array of bytes - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-4 or has a shape that - * exceeds standard arrays limits - */ - public static byte[][][][] array4dCopyOf(ByteNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 4); - byte[][][][] array = new byte[dims[0]][dims[1]][dims[2]][dims[3]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link ByteNdArray} in a new 5-dimension standard array of bytes - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-5 or has a shape that - * exceeds standard arrays limits - */ - public static byte[][][][][] array5dCopyOf(ByteNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 5); - byte[][][][][] array = new byte[dims[0]][dims[1]][dims[2]][dims[3]][dims[4]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link ByteNdArray} in a new 6-dimension standard array of bytes - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-6 or has a shape that - * exceeds standard arrays limits - */ - public static byte[][][][][][] array6dCopyOf(ByteNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 6); - byte[][][][][][] array = new byte[dims[0]][dims[1]][dims[2]][dims[3]][dims[4]][dims[5]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link ShortNdArray} in a new 1-dimension standard array of shorts - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-1 or has a shape that - * exceeds standard arrays limits - */ - public static short[] array1dCopyOf(ShortNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 1); - short[] array = new short[dims[0]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link ShortNdArray} in a new 2-dimension standard array of shorts - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-2 or has a shape that - * exceeds standard arrays limits - */ - public static short[][] array2dCopyOf(ShortNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 2); - short[][] array = new short[dims[0]][dims[1]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link ShortNdArray} in a new 3-dimension standard array of shorts - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-3 or has a shape that - * exceeds standard arrays limits - */ - public static short[][][] array3dCopyOf(ShortNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 3); - short[][][] array = new short[dims[0]][dims[1]][dims[2]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link ShortNdArray} in a new 4-dimension standard array of shorts - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-4 or has a shape that - * exceeds standard arrays limits - */ - public static short[][][][] array4dCopyOf(ShortNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 4); - short[][][][] array = new short[dims[0]][dims[1]][dims[2]][dims[3]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link ShortNdArray} in a new 5-dimension standard array of shorts - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-5 or has a shape that - * exceeds standard arrays limits - */ - public static short[][][][][] array5dCopyOf(ShortNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 5); - short[][][][][] array = new short[dims[0]][dims[1]][dims[2]][dims[3]][dims[4]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link ShortNdArray} in a new 6-dimension standard array of shorts - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-6 or has a shape that - * exceeds standard arrays limits - */ - public static short[][][][][][] array6dCopyOf(ShortNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 6); - short[][][][][][] array = new short[dims[0]][dims[1]][dims[2]][dims[3]][dims[4]][dims[5]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link BooleanNdArray} in a new 1-dimension standard array of booleans - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-1 or has a shape that - * exceeds standard arrays limits - */ - public static boolean[] array1dCopyOf(BooleanNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 1); - boolean[] array = new boolean[dims[0]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link BooleanNdArray} in a new 2-dimension standard array of booleans - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-2 or has a shape that - * exceeds standard arrays limits - */ - public static boolean[][] array2dCopyOf(BooleanNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 2); - boolean[][] array = new boolean[dims[0]][dims[1]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link BooleanNdArray} in a new 3-dimension standard array of booleans - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-3 or has a shape that - * exceeds standard arrays limits - */ - public static boolean[][][] array3dCopyOf(BooleanNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 3); - boolean[][][] array = new boolean[dims[0]][dims[1]][dims[2]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link BooleanNdArray} in a new 4-dimension standard array of booleans - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-4 or has a shape that - * exceeds standard arrays limits - */ - public static boolean[][][][] array4dCopyOf(BooleanNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 4); - boolean[][][][] array = new boolean[dims[0]][dims[1]][dims[2]][dims[3]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link BooleanNdArray} in a new 5-dimension standard array of booleans - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-5 or has a shape that - * exceeds standard arrays limits - */ - public static boolean[][][][][] array5dCopyOf(BooleanNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 5); - boolean[][][][][] array = new boolean[dims[0]][dims[1]][dims[2]][dims[3]][dims[4]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link BooleanNdArray} in a new 6-dimension standard array of booleans - * - * @param ndArray source array - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-6 or has a shape that - * exceeds standard arrays limits - */ - public static boolean[][][][][][] array6dCopyOf(BooleanNdArray ndArray) { - int[] dims = computeArrayDims(ndArray, 6); - boolean[][][][][][] array = new boolean[dims[0]][dims[1]][dims[2]][dims[3]][dims[4]][dims[5]]; - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link NdArray NdArray<T>} in a new 1-dimension standard array of objects - * - * @param ndArray source array - * @param objectType type of object - * @param data type - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-1 or has a shape that - * exceeds standard arrays limits - */ - public static T[] array1dCopyOf(NdArray ndArray, Class objectType) { - int[] dims = computeArrayDims(ndArray, 1); - T[] array = (T[])Array.newInstance(objectType, dims[0]); - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link NdArray NdArray<T>} in a new 2-dimension standard array of objects - * - * @param ndArray source array - * @param objectType type of object - * @param data type - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-2 or has a shape that - * exceeds standard arrays limits - */ - public static T[][] array2dCopyOf(NdArray ndArray, Class objectType) { - int[] dims = computeArrayDims(ndArray, 2); - T[][] array = (T[][])Array.newInstance(objectType, dims[0], dims[1]); - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link NdArray NdArray<T>} in a new 3-dimension standard array of objects - * - * @param ndArray source array - * @param objectType type of object - * @param data type - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-3 or has a shape that - * exceeds standard arrays limits - */ - public static T[][][] array3dCopyOf(NdArray ndArray, Class objectType) { - int[] dims = computeArrayDims(ndArray, 3); - T[][][] array = (T[][][])Array.newInstance(objectType, dims[0], dims[1], dims[2]); - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link NdArray NdArray<T>} in a new 4-dimension standard array of objects - * - * @param ndArray source array - * @param objectType type of object - * @param data type - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-4 or has a shape that - * exceeds standard arrays limits - */ - public static T[][][][] array4dCopyOf(NdArray ndArray, Class objectType) { - int[] dims = computeArrayDims(ndArray, 4); - T[][][][] array = (T[][][][])Array.newInstance(objectType, dims[0], dims[1], dims[2], dims[3]); - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link NdArray NdArray<T>} in a new 5-dimension standard array of objects - * - * @param ndArray source array - * @param objectType type of object - * @param data type - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-5 or has a shape that - * exceeds standard arrays limits - */ - public static T[][][][][] array5dCopyOf(NdArray ndArray, Class objectType) { - int[] dims = computeArrayDims(ndArray, 5); - T[][][][][] array = - (T[][][][][])Array.newInstance(objectType, dims[0], dims[1], dims[2], dims[3], dims[4]); - copyFrom(ndArray, array); - return array; - } - - /** - * Copy a {@link NdArray NdArray<T>} in a new 6-dimension standard array of objects - * - * @param ndArray source array - * @param objectType type of object - * @param data type - * @return the array copy - * @throws IllegalArgumentException if {@code ndArray} is not of rank-6 or has a shape that - * exceeds standard arrays limits - */ - public static T[][][][][][] array6dCopyOf(NdArray ndArray, Class objectType) { - int[] dims = computeArrayDims(ndArray, 6); - T[][][][][][] array = - (T[][][][][][])Array.newInstance(objectType, dims[0], dims[1], dims[2], dims[3], dims[4], dims[5]); - copyFrom(ndArray, array); - return array; - } - - /** - * Copy an array of ints into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-1 array - * @throws IllegalArgumentException if {@code dst} is not of rank-1 or has an incompatible shape - * with the source array - */ - public static void copyTo(int[] src, IntNdArray dst) { - NdArrays.vectorOf(src).copyTo(dst); - } - - /** - * Copy a 2-dimensional array of ints into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-2 array - * @throws IllegalArgumentException if {@code dst} is not of rank-2 or has an incompatible shape - * with the source array - */ - public static void copyTo(int[][] src, IntNdArray dst) { - dst.elements(0).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]]).copyTo(e) - ); - } - - /** - * Copy a 3-dimensional array of ints into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-3 array - * @throws IllegalArgumentException if {@code dst} is not of rank-3 or has an incompatible shape - * with the source array - */ - public static void copyTo(int[][][] src, IntNdArray dst) { - dst.elements(1).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]]).copyTo(e) - ); - } - - /** - * Copy a 4-dimensional array of ints into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-4 array - * @throws IllegalArgumentException if {@code dst} is not of rank-4 or has an incompatible shape - * with the source array - */ - public static void copyTo(int[][][][] src, IntNdArray dst) { - dst.elements(2).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]]).copyTo(e) - ); - } - - /** - * Copy a 5-dimensional array of ints into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-5 array - * @throws IllegalArgumentException if {@code dst} is not of rank-5 or has an incompatible shape - * with the source array - */ - public static void copyTo(int[][][][][] src, IntNdArray dst) { - dst.elements(3).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]).copyTo(e) - ); - } - - /** - * Copy a 6-dimensional array of ints into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-6 array - * @throws IllegalArgumentException if {@code dst} is not of rank-6 or has an incompatible shape - * with the source array - */ - public static void copyTo(int[][][][][][] src, IntNdArray dst) { - dst.elements(4).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]).copyTo(e) - ); - } - - /** - * Copy an array of longs into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-1 array - * @throws IllegalArgumentException if {@code dst} is not of rank-1 or has an incompatible shape - * with the source array - */ - public static void copyTo(long[] src, LongNdArray dst) { - NdArrays.vectorOf(src).copyTo(dst); - } - - /** - * Copy a 2-dimensional array of longs into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-2 array - * @throws IllegalArgumentException if {@code dst} is not of rank-2 or has an incompatible shape - * with the source array - */ - public static void copyTo(long[][] src, LongNdArray dst) { - dst.elements(0).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]]).copyTo(e) - ); - } - - /** - * Copy a 3-dimensional array of longs into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-3 array - * @throws IllegalArgumentException if {@code dst} is not of rank-3 or has an incompatible shape - * with the source array - */ - public static void copyTo(long[][][] src, LongNdArray dst) { - dst.elements(1).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]]).copyTo(e) - ); - } - - /** - * Copy a 4-dimensional array of longs into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-4 array - * @throws IllegalArgumentException if {@code dst} is not of rank-4 or has an incompatible shape - * with the source array - */ - public static void copyTo(long[][][][] src, LongNdArray dst) { - dst.elements(2).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]]).copyTo(e) - ); - } - - /** - * Copy a 5-dimensional array of longs into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-5 array - * @throws IllegalArgumentException if {@code dst} is not of rank-5 or has an incompatible shape - * with the source array - */ - public static void copyTo(long[][][][][] src, LongNdArray dst) { - dst.elements(3).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]).copyTo(e) - ); - } - - /** - * Copy a 6-dimensional array of longs into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-6 array - * @throws IllegalArgumentException if {@code dst} is not of rank-6 or has an incompatible shape - * with the source array - */ - public static void copyTo(long[][][][][][] src, LongNdArray dst) { - dst.elements(4).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]).copyTo(e) - ); - } - - /** - * Copy an array of floats into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-1 array - * @throws IllegalArgumentException if {@code dst} is not of rank-1 or has an incompatible shape - * with the source array - */ - public static void copyTo(float[] src, FloatNdArray dst) { - NdArrays.vectorOf(src).copyTo(dst); - } - - /** - * Copy a 2-dimensional array of floats into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-2 array - * @throws IllegalArgumentException if {@code dst} is not of rank-2 or has an incompatible shape - * with the source array - */ - public static void copyTo(float[][] src, FloatNdArray dst) { - dst.elements(0).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]]).copyTo(e) - ); - } - - /** - * Copy a 3-dimensional array of floats into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-3 array - * @throws IllegalArgumentException if {@code dst} is not of rank-3 or has an incompatible shape - * with the source array - */ - public static void copyTo(float[][][] src, FloatNdArray dst) { - dst.elements(1).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]]).copyTo(e) - ); - } - - /** - * Copy a 4-dimensional array of floats into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-4 array - * @throws IllegalArgumentException if {@code dst} is not of rank-4 or has an incompatible shape - * with the source array - */ - public static void copyTo(float[][][][] src, FloatNdArray dst) { - dst.elements(2).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]]).copyTo(e) - ); - } - - /** - * Copy a 5-dimensional array of floats into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-5 array - * @throws IllegalArgumentException if {@code dst} is not of rank-5 or has an incompatible shape - * with the source array - */ - public static void copyTo(float[][][][][] src, FloatNdArray dst) { - dst.elements(3).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]).copyTo(e) - ); - } - - /** - * Copy a 6-dimensional array of floats into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-6 array - * @throws IllegalArgumentException if {@code dst} is not of rank-6 or has an incompatible shape - * with the source array - */ - public static void copyTo(float[][][][][][] src, FloatNdArray dst) { - dst.elements(4).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]).copyTo(e) - ); - } - - /** - * Copy an array of doubles into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-1 array - * @throws IllegalArgumentException if {@code dst} is not of rank-1 or has an incompatible shape - * with the source array - */ - public static void copyTo(double[] src, DoubleNdArray dst) { - NdArrays.vectorOf(src).copyTo(dst); - } - - /** - * Copy a 2-dimensional array of doubles into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-2 array - * @throws IllegalArgumentException if {@code dst} is not of rank-2 or has an incompatible shape - * with the source array - */ - public static void copyTo(double[][] src, DoubleNdArray dst) { - dst.elements(0).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]]).copyTo(e) - ); - } - - /** - * Copy a 3-dimensional array of doubles into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-3 array - * @throws IllegalArgumentException if {@code dst} is not of rank-3 or has an incompatible shape - * with the source array - */ - public static void copyTo(double[][][] src, DoubleNdArray dst) { - dst.elements(1).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]]).copyTo(e) - ); - } - - /** - * Copy a 4-dimensional array of doubles into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-4 array - * @throws IllegalArgumentException if {@code dst} is not of rank-4 or has an incompatible shape - * with the source array - */ - public static void copyTo(double[][][][] src, DoubleNdArray dst) { - dst.elements(2).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]]).copyTo(e) - ); - } - - /** - * Copy a 5-dimensional array of doubles into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-5 array - * @throws IllegalArgumentException if {@code dst} is not of rank-5 or has an incompatible shape - * with the source array - */ - public static void copyTo(double[][][][][] src, DoubleNdArray dst) { - dst.elements(3).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]).copyTo(e) - ); - } - - /** - * Copy a 6-dimensional array of doubles into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-6 array - * @throws IllegalArgumentException if {@code dst} is not of rank-6 or has an incompatible shape - * with the source array - */ - public static void copyTo(double[][][][][][] src, DoubleNdArray dst) { - dst.elements(4).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]).copyTo(e) - ); - } - - /** - * Copy an array of bytes into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-1 array - * @throws IllegalArgumentException if {@code dst} is not of rank-1 or has an incompatible shape - * with the source array - */ - public static void copyTo(byte[] src, ByteNdArray dst) { - NdArrays.vectorOf(src).copyTo(dst); - } - - /** - * Copy a 2-dimensional array of bytes into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-2 array - * @throws IllegalArgumentException if {@code dst} is not of rank-2 or has an incompatible shape - * with the source array - */ - public static void copyTo(byte[][] src, ByteNdArray dst) { - dst.elements(0).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]]).copyTo(e) - ); - } - - /** - * Copy a 3-dimensional array of bytes into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-3 array - * @throws IllegalArgumentException if {@code dst} is not of rank-3 or has an incompatible shape - * with the source array - */ - public static void copyTo(byte[][][] src, ByteNdArray dst) { - dst.elements(1).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]]).copyTo(e) - ); - } - - /** - * Copy a 4-dimensional array of bytes into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-4 array - * @throws IllegalArgumentException if {@code dst} is not of rank-4 or has an incompatible shape - * with the source array - */ - public static void copyTo(byte[][][][] src, ByteNdArray dst) { - dst.elements(2).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]]).copyTo(e) - ); - } - - /** - * Copy a 5-dimensional array of bytes into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-5 array - * @throws IllegalArgumentException if {@code dst} is not of rank-5 or has an incompatible shape - * with the source array - */ - public static void copyTo(byte[][][][][] src, ByteNdArray dst) { - dst.elements(3).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]).copyTo(e) - ); - } - - /** - * Copy a 6-dimensional array of bytes into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-6 array - * @throws IllegalArgumentException if {@code dst} is not of rank-6 or has an incompatible shape - * with the source array - */ - public static void copyTo(byte[][][][][][] src, ByteNdArray dst) { - dst.elements(4).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]).copyTo(e) - ); - } - - /** - * Copy an array of shorts into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-1 array - * @throws IllegalArgumentException if {@code dst} is not of rank-1 or has an incompatible shape - * with the source array - */ - public static void copyTo(short[] src, ShortNdArray dst) { - NdArrays.vectorOf(src).copyTo(dst); - } - - /** - * Copy a 2-dimensional array of shorts into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-2 array - * @throws IllegalArgumentException if {@code dst} is not of rank-2 or has an incompatible shape - * with the source array - */ - public static void copyTo(short[][] src, ShortNdArray dst) { - dst.elements(0).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]]).copyTo(e) - ); - } - - /** - * Copy a 3-dimensional array of shorts into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-3 array - * @throws IllegalArgumentException if {@code dst} is not of rank-3 or has an incompatible shape - * with the source array - */ - public static void copyTo(short[][][] src, ShortNdArray dst) { - dst.elements(1).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]]).copyTo(e) - ); - } - - /** - * Copy a 4-dimensional array of shorts into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-4 array - * @throws IllegalArgumentException if {@code dst} is not of rank-4 or has an incompatible shape - * with the source array - */ - public static void copyTo(short[][][][] src, ShortNdArray dst) { - dst.elements(2).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]]).copyTo(e) - ); - } - - /** - * Copy a 5-dimensional array of shorts into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-5 array - * @throws IllegalArgumentException if {@code dst} is not of rank-5 or has an incompatible shape - * with the source array - */ - public static void copyTo(short[][][][][] src, ShortNdArray dst) { - dst.elements(3).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]).copyTo(e) - ); - } - - /** - * Copy a 6-dimensional array of shorts into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-6 array - * @throws IllegalArgumentException if {@code dst} is not of rank-6 or has an incompatible shape - * with the source array - */ - public static void copyTo(short[][][][][][] src, ShortNdArray dst) { - dst.elements(4).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]).copyTo(e) - ); - } - - /** - * Copy an array of booleans into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-1 array - * @throws IllegalArgumentException if {@code dst} is not of rank-1 or has an incompatible shape - * with the source array - */ - public static void copyTo(boolean[] src, BooleanNdArray dst) { - NdArrays.vectorOf(src).copyTo(dst); - } - - /** - * Copy a 2-dimensional array of booleans into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-2 array - * @throws IllegalArgumentException if {@code dst} is not of rank-2 or has an incompatible shape - * with the source array - */ - public static void copyTo(boolean[][] src, BooleanNdArray dst) { - dst.elements(0).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]]).copyTo(e) - ); - } - - /** - * Copy a 3-dimensional array of booleans into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-3 array - * @throws IllegalArgumentException if {@code dst} is not of rank-3 or has an incompatible shape - * with the source array - */ - public static void copyTo(boolean[][][] src, BooleanNdArray dst) { - dst.elements(1).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]]).copyTo(e) - ); - } - - /** - * Copy a 4-dimensional array of booleans into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-4 array - * @throws IllegalArgumentException if {@code dst} is not of rank-4 or has an incompatible shape - * with the source array - */ - public static void copyTo(boolean[][][][] src, BooleanNdArray dst) { - dst.elements(2).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]]).copyTo(e) - ); - } - - /** - * Copy a 5-dimensional array of booleans into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-5 array - * @throws IllegalArgumentException if {@code dst} is not of rank-5 or has an incompatible shape - * with the source array - */ - public static void copyTo(boolean[][][][][] src, BooleanNdArray dst) { - dst.elements(3).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]).copyTo(e) - ); - } - - /** - * Copy a 6-dimensional array of booleans into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-6 array - * @throws IllegalArgumentException if {@code dst} is not of rank-6 or has an incompatible shape - * with the source array - */ - public static void copyTo(boolean[][][][][][] src, BooleanNdArray dst) { - dst.elements(4).forEachIndexed((idx, e) -> - NdArrays.vectorOf(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]).copyTo(e) - ); - } - - /** - * Copy an array of objects into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-1 array - * @param data type - * @throws IllegalArgumentException if {@code dst} is not of rank-1 or has an incompatible shape - * with the source array - */ - public static void copyTo(T[] src, NdArray dst) { - NdArrays.vectorOfObjects(src).copyTo(dst); - } - - /** - * Copy a 2-dimensional array of objects into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-2 array - * @param data type - * @throws IllegalArgumentException if {@code dst} is not of rank-2 or has an incompatible shape - * with the source array - */ - public static void copyTo(T[][] src, NdArray dst) { - dst.elements(0).forEachIndexed((idx, e) -> - NdArrays.vectorOfObjects(src[(int)idx[0]]).copyTo(e) - ); - } - - /** - * Copy a 3-dimensional array of objects into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-3 array - * @param data type - * @throws IllegalArgumentException if {@code dst} is not of rank-3 or has an incompatible shape - * with the source array - */ - public static void copyTo(T[][][] src, NdArray dst) { - dst.elements(1).forEachIndexed((idx, e) -> - NdArrays.vectorOfObjects(src[(int)idx[0]][(int)idx[1]]).copyTo(e) - ); - } - - /** - * Copy a 4-dimensional array of objects into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-4 array - * @param data type - * @throws IllegalArgumentException if {@code dst} is not of rank-4 or has an incompatible shape - * with the source array - */ - public static void copyTo(T[][][][] src, NdArray dst) { - dst.elements(2).forEachIndexed((idx, e) -> - NdArrays.vectorOfObjects(src[(int)idx[0]][(int)idx[1]][(int)idx[2]]).copyTo(e) - ); - } - - /** - * Copy a 5-dimensional array of objects into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-5 array - * @param data type - * @throws IllegalArgumentException if {@code dst} is not of rank-5 or has an incompatible shape - * with the source array - */ - public static void copyTo(T[][][][][] src, NdArray dst) { - dst.elements(3).forEachIndexed((idx, e) -> - NdArrays.vectorOfObjects(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]).copyTo(e) - ); - } - - /** - * Copy a 6-dimensional array of objects into the {@code dst} {@link NdArray} - * - * @param src source array - * @param dst destination rank-6 array - * @param data type - * @throws IllegalArgumentException if {@code dst} is not of rank-6 or has an incompatible shape - * with the source array - */ - public static void copyTo(T[][][][][][] src, NdArray dst) { - dst.elements(4).forEachIndexed((idx, e) -> - NdArrays.vectorOfObjects(src[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]).copyTo(e) - ); - } - - - /** - * Copy a {@link NdArray} to an array of ints - * - * @param src source rank-1 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-1 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(IntNdArray src, int[] dst) { - if (src.rank() != 1) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - if (src.size() > dst.length) { - throw new ArrayIndexOutOfBoundsException(String.valueOf(src.size()) + " > " + dst.length); - } - src.read(DataBuffers.of(dst, false, false)); - } - - /** - * Copy a {@link NdArray} to a 2-dimensional array of ints - * - * @param src source rank-2 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-2 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(IntNdArray src, int[][] dst) { - if (src.rank() != 2) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(0).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]]) - ); - } - - /** - * Copy a {@link NdArray} to a 3-dimensional array of ints - * - * @param src source rank-3 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-3 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(IntNdArray src, int[][][] dst) { - if (src.rank() != 3) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(1).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]]) - ); - } - - /** - * Copy a {@link NdArray} to a 4-dimensional array of ints - * - * @param src source rank-4 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-4 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(IntNdArray src, int[][][][] dst) { - if (src.rank() != 4) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(2).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]]) - ); - } - - /** - * Copy a {@link NdArray} to a 5-dimensional array of ints - * - * @param src source rank-5 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-5 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(IntNdArray src, int[][][][][] dst) { - if (src.rank() != 5) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(3).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]) - ); - } - - /** - * Copy a {@link NdArray} to a 6-dimensional array of ints - * - * @param src source rank-6 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-6 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(IntNdArray src, int[][][][][][] dst) { - if (src.rank() != 6) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(4).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]) - ); - } - - /** - * Copy a {@link NdArray} to an array of longs - * - * @param src source rank-1 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-1 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(LongNdArray src, long[] dst) { - if (src.rank() != 1) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - if (src.size() > dst.length) { - throw new ArrayIndexOutOfBoundsException(String.valueOf(src.size()) + " > " + dst.length); - } - src.read(DataBuffers.of(dst, false, false)); - } - - /** - * Copy a {@link NdArray} to a 2-dimensional array of longs - * - * @param src source rank-2 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-2 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(LongNdArray src, long[][] dst) { - if (src.rank() != 2) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(0).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]]) - ); - } - - /** - * Copy a {@link NdArray} to a 3-dimensional array of longs - * - * @param src source rank-3 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-3 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(LongNdArray src, long[][][] dst) { - if (src.rank() != 3) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(1).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]]) - ); - } - - /** - * Copy a {@link NdArray} to a 4-dimensional array of longs - * - * @param src source rank-4 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-4 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(LongNdArray src, long[][][][] dst) { - if (src.rank() != 4) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(2).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]]) - ); - } - - /** - * Copy a {@link NdArray} to a 5-dimensional array of longs - * - * @param src source rank-5 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-5 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(LongNdArray src, long[][][][][] dst) { - if (src.rank() != 5) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(3).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]) - ); - } - - /** - * Copy a {@link NdArray} to a 6-dimensional array of longs - * - * @param src source rank-6 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-6 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(LongNdArray src, long[][][][][][] dst) { - if (src.rank() != 6) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(4).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]) - ); - } - - /** - * Copy a {@link NdArray} to an array of floats - * - * @param src source rank-1 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-1 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(FloatNdArray src, float[] dst) { - if (src.rank() != 1) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - if (src.size() > dst.length) { - throw new ArrayIndexOutOfBoundsException(String.valueOf(src.size()) + " > " + dst.length); - } - src.read(DataBuffers.of(dst, false, false)); - } - - /** - * Copy a {@link NdArray} to a 2-dimensional array of floats - * - * @param src source rank-2 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-2 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(FloatNdArray src, float[][] dst) { - if (src.rank() != 2) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(0).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]]) - ); - } - - /** - * Copy a {@link NdArray} to a 3-dimensional array of floats - * - * @param src source rank-3 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-3 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(FloatNdArray src, float[][][] dst) { - if (src.rank() != 3) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(1).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]]) - ); - } - - /** - * Copy a {@link NdArray} to a 4-dimensional array of floats - * - * @param src source rank-4 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-4 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(FloatNdArray src, float[][][][] dst) { - if (src.rank() != 4) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(2).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]]) - ); - } - - /** - * Copy a {@link NdArray} to a 5-dimensional array of floats - * - * @param src source rank-5 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-5 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(FloatNdArray src, float[][][][][] dst) { - if (src.rank() != 5) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(3).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]) - ); - } - - /** - * Copy a {@link NdArray} to a 6-dimensional array of floats - * - * @param src source rank-6 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-6 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(FloatNdArray src, float[][][][][][] dst) { - if (src.rank() != 6) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(4).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]) - ); - } - - /** - * Copy a {@link NdArray} to an array of doubles - * - * @param src source rank-1 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-1 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(DoubleNdArray src, double[] dst) { - if (src.rank() != 1) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - if (src.size() > dst.length) { - throw new ArrayIndexOutOfBoundsException(String.valueOf(src.size()) + " > " + dst.length); - } - src.read(DataBuffers.of(dst, false, false)); - } - - /** - * Copy a {@link NdArray} to a 2-dimensional array of doubles - * - * @param src source rank-2 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-2 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(DoubleNdArray src, double[][] dst) { - if (src.rank() != 2) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(0).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]]) - ); - } - - /** - * Copy a {@link NdArray} to a 3-dimensional array of doubles - * - * @param src source rank-3 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-3 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(DoubleNdArray src, double[][][] dst) { - if (src.rank() != 3) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(1).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]]) - ); - } - - /** - * Copy a {@link NdArray} to a 4-dimensional array of doubles - * - * @param src source rank-4 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-4 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(DoubleNdArray src, double[][][][] dst) { - if (src.rank() != 4) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(2).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]]) - ); - } - - /** - * Copy a {@link NdArray} to a 5-dimensional array of doubles - * - * @param src source rank-5 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-5 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(DoubleNdArray src, double[][][][][] dst) { - if (src.rank() != 5) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(3).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]) - ); - } - - /** - * Copy a {@link NdArray} to a 6-dimensional array of doubles - * - * @param src source rank-6 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-6 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(DoubleNdArray src, double[][][][][][] dst) { - if (src.rank() != 6) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(4).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]) - ); - } - - /** - * Copy a {@link NdArray} to an array of bytes - * - * @param src source rank-1 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-1 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(ByteNdArray src, byte[] dst) { - if (src.rank() != 1) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - if (src.size() > dst.length) { - throw new ArrayIndexOutOfBoundsException(String.valueOf(src.size()) + " > " + dst.length); - } - src.read(DataBuffers.of(dst, false, false)); - } - - /** - * Copy a {@link NdArray} to a 2-dimensional array of bytes - * - * @param src source rank-2 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-2 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(ByteNdArray src, byte[][] dst) { - if (src.rank() != 2) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(0).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]]) - ); - } - - /** - * Copy a {@link NdArray} to a 3-dimensional array of bytes - * - * @param src source rank-3 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-3 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(ByteNdArray src, byte[][][] dst) { - if (src.rank() != 3) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(1).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]]) - ); - } - - /** - * Copy a {@link NdArray} to a 4-dimensional array of bytes - * - * @param src source rank-4 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-4 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(ByteNdArray src, byte[][][][] dst) { - if (src.rank() != 4) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(2).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]]) - ); - } - - /** - * Copy a {@link NdArray} to a 5-dimensional array of bytes - * - * @param src source rank-5 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-5 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(ByteNdArray src, byte[][][][][] dst) { - if (src.rank() != 5) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(3).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]) - ); - } - - /** - * Copy a {@link NdArray} to a 6-dimensional array of bytes - * - * @param src source rank-6 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-6 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(ByteNdArray src, byte[][][][][][] dst) { - if (src.rank() != 6) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(4).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]) - ); - } - - /** - * Copy a {@link NdArray} to an array of shorts - * - * @param src source rank-1 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-1 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(ShortNdArray src, short[] dst) { - if (src.rank() != 1) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - if (src.size() > dst.length) { - throw new ArrayIndexOutOfBoundsException(String.valueOf(src.size()) + " > " + dst.length); - } - src.read(DataBuffers.of(dst, false, false)); - } - - /** - * Copy a {@link NdArray} to a 2-dimensional array of shorts - * - * @param src source rank-2 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-2 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(ShortNdArray src, short[][] dst) { - if (src.rank() != 2) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(0).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]]) - ); - } - - /** - * Copy a {@link NdArray} to a 3-dimensional array of shorts - * - * @param src source rank-3 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-3 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(ShortNdArray src, short[][][] dst) { - if (src.rank() != 3) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(1).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]]) - ); - } - - /** - * Copy a {@link NdArray} to a 4-dimensional array of shorts - * - * @param src source rank-4 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-4 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(ShortNdArray src, short[][][][] dst) { - if (src.rank() != 4) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(2).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]]) - ); - } - - /** - * Copy a {@link NdArray} to a 5-dimensional array of shorts - * - * @param src source rank-5 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-5 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(ShortNdArray src, short[][][][][] dst) { - if (src.rank() != 5) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(3).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]) - ); - } - - /** - * Copy a {@link NdArray} to a 6-dimensional array of shorts - * - * @param src source rank-6 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-6 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(ShortNdArray src, short[][][][][][] dst) { - if (src.rank() != 6) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(4).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]) - ); - } - - /** - * Copy a {@link NdArray} to an array of booleans. - * - * @param src source rank-1 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-1 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(BooleanNdArray src, boolean[] dst) { - if (src.rank() != 1) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - if (src.size() > dst.length) { - throw new ArrayIndexOutOfBoundsException(String.valueOf(src.size()) + " > " + dst.length); - } - src.read(DataBuffers.of(dst, false, false)); - } - - /** - * Copy a {@link NdArray} to a 2-dimensional array of booleans - * - * @param src source rank-2 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-2 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(BooleanNdArray src, boolean[][] dst) { - if (src.rank() != 2) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(0).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]]) - ); - } - - /** - * Copy a {@link NdArray} to a 3-dimensional array of booleans - * - * @param src source rank-3 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-3 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(BooleanNdArray src, boolean[][][] dst) { - if (src.rank() != 3) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(1).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]]) - ); - } - - /** - * Copy a {@link NdArray} to a 4-dimensional array of booleans - * - * @param src source rank-4 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-4 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(BooleanNdArray src, boolean[][][][] dst) { - if (src.rank() != 4) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(2).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]]) - ); - } - - /** - * Copy a {@link NdArray} to a 5-dimensional array of booleans - * - * @param src source rank-5 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-5 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(BooleanNdArray src, boolean[][][][][] dst) { - if (src.rank() != 5) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(3).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]) - ); - } - - /** - * Copy a {@link NdArray} to a 6-dimensional array of booleans - * - * @param src source rank-6 array - * @param dst destination array - * @throws IllegalArgumentException if {@code src} is not of rank-6 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(BooleanNdArray src, boolean[][][][][][] dst) { - if (src.rank() != 6) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(4).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]) - ); - } - - /** - * Copy a {@link NdArray} to an array of objects - * - * @param src source rank-1 array - * @param dst destination array - * @param data type - * @throws IllegalArgumentException if {@code src} is not of rank-1 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(NdArray src, T[] dst) { - if (src.rank() != 1) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - if (src.size() > dst.length) { - throw new ArrayIndexOutOfBoundsException(String.valueOf(src.size()) + " > " + dst.length); - } - src.read(DataBuffers.of(dst, false, false)); - } - - /** - * Copy a {@link NdArray} to a 2-dimensional array of objects - * - * @param src source rank-2 array - * @param dst destination array - * @param data type - * @throws IllegalArgumentException if {@code src} is not of rank-2 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(NdArray src, T[][] dst) { - if (src.rank() != 2) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(0).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]]) - ); - } - - /** - * Copy a {@link NdArray} to a 3-dimensional array of objects - * - * @param src source rank-3 array - * @param dst destination array - * @param data type - * @throws IllegalArgumentException if {@code src} is not of rank-3 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(NdArray src, T[][][] dst) { - if (src.rank() != 3) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(1).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]]) - ); - } - - /** - * Copy a {@link NdArray} to a 4-dimensional array of objects - * - * @param src source rank-4 array - * @param dst destination array - * @param data type - * @throws IllegalArgumentException if {@code src} is not of rank-4 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(NdArray src, T[][][][] dst) { - if (src.rank() != 4) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(2).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]]) - ); - } - - /** - * Copy a {@link NdArray} to a 5-dimensional array of objects - * - * @param src source rank-5 array - * @param dst destination array - * @param data type - * @throws IllegalArgumentException if {@code src} is not of rank-5 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(NdArray src, T[][][][][] dst) { - if (src.rank() != 5) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(3).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]]) - ); - } - - /** - * Copy a {@link NdArray} to a 6-dimensional array of objects - * - * @param src source rank-6 array - * @param dst destination array - * @param data type - * @throws IllegalArgumentException if {@code src} is not of rank-6 - * @throws ArrayIndexOutOfBoundsException if not all elements of {@code src} can fit it the destination array - */ - public static void copyFrom(NdArray src, T[][][][][][] dst) { - if (src.rank() != 6) { - throw new IllegalArgumentException("Array cannot be copied from NdArray of rank " + src.rank()); - } - src.elements(4).forEachIndexed((idx, e) -> - copyFrom(e, dst[(int)idx[0]][(int)idx[1]][(int)idx[2]][(int)idx[3]][(int)idx[4]]) - ); - } - - /** - * Compute the shape of an int array. - * - * @param array 1D array - * @return shape of the array - */ - public static Shape shapeOf(int[] array) { - return Shape.of(array.length); - } - - /** - * Compute the shape of a 2-dimensional int array. - * - * @param array 2D array - * @return shape of the array - */ - public static Shape shapeOf(int[][] array) { - return Shape.of(computeShape(array, new long[2])); - } - - /** - * Compute the shape of a 3-dimensional int array. - * - * @param array 3D array - * @return shape of the array - */ - public static Shape shapeOf(int[][][] array) { - return Shape.of(computeShape(array, new long[3])); - } - - /** - * Compute the shape of a 4-dimensional int array. - * - * @param array 4D array - * @return shape of the array - */ - public static Shape shapeOf(int[][][][] array) { - return Shape.of(computeShape(array, new long[4])); - } - - /** - * Compute the shape of a 5-dimensional int array. - * - * @param array 5D array - * @return shape of the array - */ - public static Shape shapeOf(int[][][][][] array) { - return Shape.of(computeShape(array, new long[5])); - } - - /** - * Compute the shape of a 6-dimensional int array. - * - * @param array 6D array - * @return shape of the array - */ - public static Shape shapeOf(int[][][][][][] array) { - return Shape.of(computeShape(array, new long[6])); - } - - /** - * Compute the shape of a long array. - * - * @param array 1D array - * @return shape of the array - */ - public static Shape shapeOf(long[] array) { - return Shape.of(array.length); - } - - /** - * Compute the shape of a 2-dimensional long array. - * - * @param array 2D array - * @return shape of the array - */ - public static Shape shapeOf(long[][] array) { - return Shape.of(computeShape(array, new long[2])); - } - - /** - * Compute the shape of a 3-dimensional long array. - * - * @param array 3D array - * @return shape of the array - */ - public static Shape shapeOf(long[][][] array) { - return Shape.of(computeShape(array, new long[3])); - } - - /** - * Compute the shape of a 4-dimensional long array. - * - * @param array 4D array - * @return shape of the array - */ - public static Shape shapeOf(long[][][][] array) { - return Shape.of(computeShape(array, new long[4])); - } - - /** - * Compute the shape of a 5-dimensional long array. - * - * @param array 5D array - * @return shape of the array - */ - public static Shape shapeOf(long[][][][][] array) { - return Shape.of(computeShape(array, new long[5])); - } - - /** - * Compute the shape of a 6-dimensional long array. - * - * @param array 6D array - * @return shape of the array - */ - public static Shape shapeOf(long[][][][][][] array) { - return Shape.of(computeShape(array, new long[6])); - } - - /** - * Compute the shape of a float array. - * - * @param array 1D array - * @return shape of the array - */ - public static Shape shapeOf(float[] array) { - return Shape.of(array.length); - } - - /** - * Compute the shape of a 2-dimensional float array. - * - * @param array 2D array - * @return shape of the array - */ - public static Shape shapeOf(float[][] array) { - return Shape.of(computeShape(array, new long[2])); - } - - /** - * Compute the shape of a 3-dimensional float array. - * - * @param array 3D array - * @return shape of the array - */ - public static Shape shapeOf(float[][][] array) { - return Shape.of(computeShape(array, new long[3])); - } - - /** - * Compute the shape of a 4-dimensional float array. - * - * @param array 4D array - * @return shape of the array - */ - public static Shape shapeOf(float[][][][] array) { - return Shape.of(computeShape(array, new long[4])); - } - - /** - * Compute the shape of a 5-dimensional float array. - * - * @param array 5D array - * @return shape of the array - */ - public static Shape shapeOf(float[][][][][] array) { - return Shape.of(computeShape(array, new long[5])); - } - - /** - * Compute the shape of a 6-dimensional float array. - * - * @param array 6D array - * @return shape of the array - */ - public static Shape shapeOf(float[][][][][][] array) { - return Shape.of(computeShape(array, new long[6])); - } - - /** - * Compute the shape of a double array. - * - * @param array 1D array - * @return shape of the array - */ - public static Shape shapeOf(double[] array) { - return Shape.of(array.length); - } - - /** - * Compute the shape of a 2-dimensional double array. - * - * @param array 2D array - * @return shape of the array - */ - public static Shape shapeOf(double[][] array) { - return Shape.of(computeShape(array, new long[2])); - } - - /** - * Compute the shape of a 3-dimensional double array. - * - * @param array 3D array - * @return shape of the array - */ - public static Shape shapeOf(double[][][] array) { - return Shape.of(computeShape(array, new long[3])); - } - - /** - * Compute the shape of a 4-dimensional double array. - * - * @param array 4D array - * @return shape of the array - */ - public static Shape shapeOf(double[][][][] array) { - return Shape.of(computeShape(array, new long[4])); - } - - /** - * Compute the shape of a 5-dimensional double array. - * - * @param array 5D array - * @return shape of the array - */ - public static Shape shapeOf(double[][][][][] array) { - return Shape.of(computeShape(array, new long[5])); - } - - /** - * Compute the shape of a 6-dimensional double array. - * - * @param array 6D array - * @return shape of the array - */ - public static Shape shapeOf(double[][][][][][] array) { - return Shape.of(computeShape(array, new long[6])); - } - - /** - * Compute the shape of a byte array. - * - * @param array 1D array - * @return shape of the array - */ - public static Shape shapeOf(byte[] array) { - return Shape.of(array.length); - } - - /** - * Compute the shape of a 2-dimensional byte array. - * - * @param array 2D array - * @return shape of the array - */ - public static Shape shapeOf(byte[][] array) { - return Shape.of(computeShape(array, new long[2])); - } - - /** - * Compute the shape of a 3-dimensional byte array. - * - * @param array 3D array - * @return shape of the array - */ - public static Shape shapeOf(byte[][][] array) { - return Shape.of(computeShape(array, new long[3])); - } - - /** - * Compute the shape of a 4-dimensional byte array. - * - * @param array 4D array - * @return shape of the array - */ - public static Shape shapeOf(byte[][][][] array) { - return Shape.of(computeShape(array, new long[4])); - } - - /** - * Compute the shape of a 5-dimensional byte array. - * - * @param array 5D array - * @return shape of the array - */ - public static Shape shapeOf(byte[][][][][] array) { - return Shape.of(computeShape(array, new long[5])); - } - - /** - * Compute the shape of a 6-dimensional byte array. - * - * @param array 6D array - * @return shape of the array - */ - public static Shape shapeOf(byte[][][][][][] array) { - return Shape.of(computeShape(array, new long[6])); - } - - /** - * Compute the shape of a short array. - * - * @param array 1D array - * @return shape of the array - */ - public static Shape shapeOf(short[] array) { - return Shape.of(array.length); - } - - /** - * Compute the shape of a 2-dimensional short array. - * - * @param array 2D array - * @return shape of the array - */ - public static Shape shapeOf(short[][] array) { - return Shape.of(computeShape(array, new long[2])); - } - - /** - * Compute the shape of a 3-dimensional short array. - * - * @param array 3D array - * @return shape of the array - */ - public static Shape shapeOf(short[][][] array) { - return Shape.of(computeShape(array, new long[3])); - } - - /** - * Compute the shape of a 4-dimensional short array. - * - * @param array 4D array - * @return shape of the array - */ - public static Shape shapeOf(short[][][][] array) { - return Shape.of(computeShape(array, new long[4])); - } - - /** - * Compute the shape of a 5-dimensional short array. - * - * @param array 5D array - * @return shape of the array - */ - public static Shape shapeOf(short[][][][][] array) { - return Shape.of(computeShape(array, new long[5])); - } - - /** - * Compute the shape of a 6-dimensional short array. - * - * @param array 6D array - * @return shape of the array - */ - public static Shape shapeOf(short[][][][][][] array) { - return Shape.of(computeShape(array, new long[6])); - } - - /** - * Compute the shape of a boolean array. - * - * @param array 1D array - * @return shape of the array - */ - public static Shape shapeOf(boolean[] array) { - return Shape.of(array.length); - } - - /** - * Compute the shape of a 2-dimensional boolean array. - * - * @param array 2D array - * @return shape of the array - */ - public static Shape shapeOf(boolean[][] array) { - return Shape.of(computeShape(array, new long[2])); - } - - /** - * Compute the shape of a 3-dimensional boolean array. - * - * @param array 3D array - * @return shape of the array - */ - public static Shape shapeOf(boolean[][][] array) { - return Shape.of(computeShape(array, new long[3])); - } - - /** - * Compute the shape of a 4-dimensional boolean array. - * - * @param array 4D array - * @return shape of the array - */ - public static Shape shapeOf(boolean[][][][] array) { - return Shape.of(computeShape(array, new long[4])); - } - - /** - * Compute the shape of a 5-dimensional boolean array. - * - * @param array 5D array - * @return shape of the array - */ - public static Shape shapeOf(boolean[][][][][] array) { - return Shape.of(computeShape(array, new long[5])); - } - - /** - * Compute the shape of a 6-dimensional boolean array. - * - * @param array 6D array - * @return shape of the array - */ - public static Shape shapeOf(boolean[][][][][][] array) { - return Shape.of(computeShape(array, new long[6])); - } - - /** - * Compute the shape of an object array. - * - * @param array 1D array - * @param data type - * @return shape of the array - */ - public static Shape shapeOf(T[] array) { - return Shape.of(array.length); - } - - /** - * Compute the shape of a 2-dimensional object array. - * - * @param array 2D array - * @param data type - * @return shape of the array - */ - public static Shape shapeOf(T[][] array) { - return Shape.of(computeShape(array, new long[2])); - } - - /** - * Compute the shape of a 3-dimensional object array. - * - * @param array 3D array - * @param data type - * @return shape of the array - */ - public static Shape shapeOf(T[][][] array) { - return Shape.of(computeShape(array, new long[3])); - } - - /** - * Compute the shape of a 4-dimensional object array. - * - * @param array 4D array - * @param data type - * @return shape of the array - */ - public static Shape shapeOf(T[][][][] array) { - return Shape.of(computeShape(array, new long[4])); - } - - /** - * Compute the shape of a 5-dimensional object array. - * - * @param array 5D array - * @param data type - * @return shape of the array - */ - public static Shape shapeOf(T[][][][][] array) { - return Shape.of(computeShape(array, new long[5])); - } - - /** - * Compute the shape of a 6-dimensional object array. - * - * @param array 6D array - * @param data type - * @return shape of the array - */ - public static Shape shapeOf(T[][][][][][] array) { - return Shape.of(computeShape(array, new long[6])); - } - - private static void dimSize(int arrayLength, long[] shape, int dimIdx) { - if (shape[dimIdx] == 0) { - shape[dimIdx] = arrayLength; - } else if (shape[dimIdx] != arrayLength) { - shape[dimIdx] = Shape.UNKNOWN_SIZE; - } - } - - private static long[] computeShape(int[][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 2); - for (int i = 0; i < array.length; ++i) { - if (array[i] == null) { - throw new IllegalStateException("One of the subarray is null"); - } - dimSize(array[i].length, shape, shape.length - 1); - } - return shape; - } - - private static long[] computeShape(int[][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 3); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(int[][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 4); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(int[][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 5); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(int[][][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 6); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(long[][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 2); - for (int i = 0; i < array.length; ++i) { - if (array[i] == null) { - throw new IllegalStateException("One of the subarray is null"); - } - dimSize(array[i].length, shape, shape.length - 1); - } - return shape; - } - - private static long[] computeShape(long[][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 3); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(long[][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 4); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(long[][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 5); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(long[][][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 6); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(float[][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 2); - for (int i = 0; i < array.length; ++i) { - if (array[i] == null) { - throw new IllegalStateException("One of the subarray is null"); - } - dimSize(array[i].length, shape, shape.length - 1); - } - return shape; - } - - private static long[] computeShape(float[][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 3); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(float[][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 4); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(float[][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 5); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(float[][][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 6); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(double[][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 2); - for (int i = 0; i < array.length; ++i) { - if (array[i] == null) { - throw new IllegalStateException("One of the subarray is null"); - } - dimSize(array[i].length, shape, shape.length - 1); - } - return shape; - } - - private static long[] computeShape(double[][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 3); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(double[][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 4); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(double[][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 5); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(double[][][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 6); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(byte[][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 2); - for (int i = 0; i < array.length; ++i) { - if (array[i] == null) { - throw new IllegalStateException("One of the subarray is null"); - } - dimSize(array[i].length, shape, shape.length - 1); - } - return shape; - } - - private static long[] computeShape(byte[][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 3); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(byte[][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 4); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(byte[][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 5); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(byte[][][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 6); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(short[][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 2); - for (int i = 0; i < array.length; ++i) { - if (array[i] == null) { - throw new IllegalStateException("One of the subarray is null"); - } - dimSize(array[i].length, shape, shape.length - 1); - } - return shape; - } - - private static long[] computeShape(short[][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 3); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(short[][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 4); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(short[][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 5); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(short[][][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 6); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(boolean[][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 2); - for (int i = 0; i < array.length; ++i) { - if (array[i] == null) { - throw new IllegalStateException("One of the subarray is null"); - } - dimSize(array[i].length, shape, shape.length - 1); - } - return shape; - } - - private static long[] computeShape(boolean[][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 3); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(boolean[][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 4); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(boolean[][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 5); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(boolean[][][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 6); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(T[][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 2); - for (int i = 0; i < array.length; ++i) { - if (array[i] == null) { - throw new IllegalStateException("One of the subarray is null"); - } - dimSize(array[i].length, shape, shape.length - 1); - } - return shape; - } - - private static long[] computeShape(T[][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 3); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(T[][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 4); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(T[][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 5); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static long[] computeShape(T[][][][][][] array, long[] shape) { - if (array == null) { - throw new IllegalStateException("The array or one of its subarray is null"); - } - dimSize(array.length, shape, shape.length - 6); - for (int i = 0; i < array.length; ++i) { - computeShape(array[i], shape); - } - return shape; - } - - private static Class componentTypeOf(Object array) { - Class componentType = array.getClass().getComponentType(); - while (componentType.isArray()) { - componentType = componentType.getComponentType(); - } - return (Class)componentType; - } - - private static int[] computeArrayDims(NdArray ndArray, int expectedRank) { - Shape shape = ndArray.shape(); - if (shape.numDimensions() != expectedRank) { - throw new IllegalArgumentException("NdArray must be of rank " + expectedRank); - } - int[] arrayShape = new int[expectedRank]; - for (int i = 0; i < expectedRank; ++i) { - long dimSize = shape.size(i); - if (dimSize > Integer.MAX_VALUE) { - throw new IllegalArgumentException("Dimension " + i + " is too large to fit in a standard array (" + shape.size(i) + ")"); - } - arrayShape[i] = (int)dimSize; - } - return arrayShape; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/BooleanDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/BooleanDataBuffer.java deleted file mode 100644 index 73a570d4fe8..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/BooleanDataBuffer.java +++ /dev/null @@ -1,165 +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.ndarray.buffer; - -import java.nio.BufferOverflowException; -import java.nio.BufferUnderflowException; -import java.nio.ReadOnlyBufferException; - -/** - * A {@link DataBuffer} of booleans. - */ -public interface BooleanDataBuffer extends DataBuffer { - - /** - * Reads the boolean at the given index. - * - * @param index the index from which the float will be read - * @return the boolean at the given index - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - */ - boolean getBoolean(long index); - - /** - * Writes the given boolean into this buffer at the given index. - * - * @param value the boolean to be written - * @param index the index at which the value will be written - * @return this buffer - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - * @throws ReadOnlyBufferException if this buffer is read-only - */ - BooleanDataBuffer setBoolean(boolean value, long index); - - /** - * Bulk get method, using boolean arrays. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code dst.length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = dst.length} values from this buffer into the given - * array. - * - * @param dst the array into which values are to be written - * @return this buffer - * @throws BufferUnderflowException if there are not enough values to copy from this buffer - */ - default BooleanDataBuffer read(boolean[] dst) { - return read(dst, 0, dst.length); - } - - /** - * Bulk get method, using boolean arrays. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from this buffer into the given array - * starting at the given offset. - * - * @param dst the array into which values are to be written - * @param offset the offset within the array of the first value to be written; must be - * non-negative and no larger than {@code dst.length} - * @param length the maximum number of values to be written to the given array; must be - * non-negative and no larger than {@code dst.length - offset} - * @return this buffer - * @throws BufferUnderflowException if there are fewer than length values remaining in this buffer - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - */ - BooleanDataBuffer read(boolean[] dst, int offset, int length); - - /** - * Bulk put method, using boolean arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code src.length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = src.length} values from the given array. - * - * @param src the source array from which values are to be read - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws ReadOnlyBufferException if this buffer is read-only - */ - default BooleanDataBuffer write(boolean[] src) { - return write(src, 0, src.length); - } - - /** - * Bulk put method, using boolean arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from the given array into this buffer, - * starting at the given offset. - * - * @param src the source array from which values are to be read - * @param offset the offset within the array of the first value to be read; must be non-negative - * and no larger than {@code src.length} - * @param length the number of values to be read from the given array; must be non-negative and no - * larger than {@code src.length - offset} - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - * @throws ReadOnlyBufferException if this buffer is read-only - */ - BooleanDataBuffer write(boolean[] src, int offset, int length); - - @Override - default Boolean getObject(long index) { - return getBoolean(index); - } - - @Override - default BooleanDataBuffer setObject(Boolean value, long index) { - return setBoolean(value, index); - } - - @Override - BooleanDataBuffer copyTo(DataBuffer dst, long size); - - @Override - default BooleanDataBuffer offset(long index) { - return slice(index, size() - index); - } - - @Override - default BooleanDataBuffer narrow(long size) { - return slice(0, size); - } - - @Override - BooleanDataBuffer slice(long index, long size); - - @Override - default DataBufferWindow window(long size) { - throw new UnsupportedOperationException(); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/ByteDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/ByteDataBuffer.java deleted file mode 100644 index b1cce441b13..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/ByteDataBuffer.java +++ /dev/null @@ -1,232 +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.ndarray.buffer; - -import java.nio.BufferOverflowException; -import java.nio.BufferUnderflowException; -import java.nio.ReadOnlyBufferException; - -/** - * A {@link DataBuffer} of bytes. - */ -public interface ByteDataBuffer extends DataBuffer { - - /** - * Reads the byte at the given index. - * - * @param index the index from which the float will be read - * @return the byte at the given index - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - */ - byte getByte(long index); - - /** - * Writes the given byte into this buffer at the given index. - * - * @param value the byte to be written - * @param index the index at which the value will be written - * @return this buffer - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - * @throws ReadOnlyBufferException if this buffer is read-only - */ - ByteDataBuffer setByte(byte value, long index); - - /** - * Bulk get method, using byte arrays. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code dst.length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = dst.length} values from this buffer into the given - * array. - * - * @param dst the array into which values are to be written - * @return this buffer - * @throws BufferUnderflowException if there are not enough values to copy from this buffer - */ - default ByteDataBuffer read(byte[] dst) { - return read(dst, 0, dst.length); - } - - /** - * Bulk get method, using byte arrays. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from this buffer into the given array - * starting at the given offset. - * - * @param dst the array into which values are to be written - * @param offset the offset within the array of the first value to be written; must be - * non-negative and no larger than {@code dst.length} - * @param length the maximum number of values to be written to the given array; must be - * non-negative and no larger than {@code dst.length - offset} - * @return this buffer - * @throws BufferUnderflowException if there are fewer than length values remaining in this buffer - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - */ - ByteDataBuffer read(byte[] dst, int offset, int length); - - /** - * Bulk put method, using byte arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code src.length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = src.length} values from the given array. - * - * @param src the source array from which values are to be read - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws ReadOnlyBufferException if this buffer is read-only - */ - default ByteDataBuffer write(byte[] src) { - return write(src, 0, src.length); - } - - /** - * Bulk put method, using byte arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from the given array into this buffer, - * starting at the given offset. - * - * @param src the source array from which values are to be read - * @param offset the offset within the array of the first value to be read; must be non-negative - * and no larger than {@code src.length} - * @param length the number of values to be read from the given array; must be non-negative and no - * larger than {@code src.length - offset} - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - * @throws ReadOnlyBufferException if this buffer is read-only - */ - ByteDataBuffer write(byte[] src, int offset, int length); - - /** - * Return this byte buffer as a buffer of ints. - * - *

The returned buffer provides a different view on the same memory as the original byte buffer, - * meaning that changing a value in one will affect the other. - * - * @return this buffer as a {@link IntDataBuffer} - * @throws IllegalStateException if this buffer cannot be converted - */ - IntDataBuffer asInts(); - - /** - * Return this byte buffer as a buffer of shorts. - * - *

The returned buffer provides a different view on the same memory as the original byte buffer, - * meaning that changing a value in one will affect the other. - * - * @return this buffer as a {@link ShortDataBuffer} - * @throws IllegalStateException if this buffer cannot be converted - */ - ShortDataBuffer asShorts(); - - /** - * Return this byte buffer as a buffer of longs. - * - *

The returned buffer provides a different view on the same memory as the original byte buffer, - * meaning that changing a value in one will affect the other. - * - * @return this buffer as a {@link LongDataBuffer} - * @throws IllegalStateException if this buffer cannot be converted - */ - LongDataBuffer asLongs(); - - /** - * Return this byte buffer as a buffer of floats. - * - *

The returned buffer provides a different view on the same memory as the original byte buffer, - * meaning that changing a value in one will affect the other. - * - * @return this buffer as a {@link FloatDataBuffer} - * @throws IllegalStateException if this buffer cannot be converted - */ - FloatDataBuffer asFloats(); - - /** - * Return this byte buffer as a buffer of doubles. - * - *

The returned buffer provides a different view on the same memory as the original byte buffer, - * meaning that changing a value in one will affect the other. - * - * @return this buffer as a {@link DoubleDataBuffer} - * @throws IllegalStateException if this buffer cannot be converted - */ - DoubleDataBuffer asDoubles(); - - /** - * Return this byte buffer as a buffer of booleans. - * - *

The returned buffer provides a different view on the same memory as the original byte buffer, - * meaning that changing a value in one will affect the other. - * - * @return this buffer as a {@link BooleanDataBuffer} - * @throws IllegalStateException if this buffer cannot be converted - */ - BooleanDataBuffer asBooleans(); - - @Override - default Byte getObject(long index) { - return getByte(index); - } - - @Override - default ByteDataBuffer setObject(Byte value, long index) { - return setByte(value, index); - } - - @Override - ByteDataBuffer copyTo(DataBuffer dst, long size); - - - @Override - default ByteDataBuffer offset(long index) { - return slice(index, size() - index); - } - - @Override - default ByteDataBuffer narrow(long size) { - return slice(0, size); - } - - @Override - ByteDataBuffer slice(long index, long size); - - @Override - default DataBufferWindow window(long size) { - throw new UnsupportedOperationException(); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DataBuffer.java deleted file mode 100644 index e62ba87ce6e..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DataBuffer.java +++ /dev/null @@ -1,324 +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.ndarray.buffer; - -import java.nio.BufferOverflowException; -import java.nio.BufferUnderflowException; -import java.nio.ReadOnlyBufferException; - -/** - * A container of data of a specific type. - * - *

Instances of {@code DataBuffer} map native or heap memory segments to a linear view that - * supports: - *

    - *
  • 64-bits indexing, allowing to work with buffer larger than 231 bytes
    • - *
  • Storage of object of any types and not only primitives
    • - *
  • Generic types allows to work directly with boxed types as well, which does not require - * explicit buffer types as with the standard JDK buffers. - *
- * It is important to note that there is no guarantee the memory managed by a {@code DataBuffer} - * is linear, specially when dealing with non-primitive types or large buffers. - * - * @param type of data stored in this buffer - */ -public interface DataBuffer { - - /** - * Size of the buffer, in elements. - *

- * For exemple, in case of a byte buffer, this value is equal to the number of bytes this buffer - * can hold. For an integer buffer, it is equal to the number of integers, therefore the size - * in bytes of this buffer is {@code size() * Integer.BYTES}. - * - * @return the buffer size - */ - long size(); - - /** - * Tells whether or not this buffer is backed by an accessible array. - * - * @return true if, and only if, this buffer is read-only - */ - boolean isReadOnly(); - - /** - * Reads the value at the given index. - * - * Important: Usage of this method should be limited to buffers of non-primitive types or - * when the data type is not deterministically known by the caller. In any other case, prefer - * the usage of its primitive variant which will significantly improve performances - * (e.g. {@code IntDataBuffer.getInt(idx)} - * - * @param index the index from which the float will be read - * @return the value at the given index - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - */ - T getObject(long index); - - /** - * Writes the given value into this buffer at the given index. - * - * Important: Usage of this method should be limited to buffers of non-primitive types or - * when the data type is not deterministically known by the caller. In any other case, prefer - * the usage of its primitive variant which will significantly improve performances - * (e.g. {@code IntDataBuffer.setInt(idx)} - * - * @param value the value to be written - * @param index the index at which the value will be written - * @return this buffer - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - * @throws ReadOnlyBufferException if this buffer is read-only - */ - DataBuffer setObject(T value, long index); - - /** - * Read the references of the objects in this buffer into the destination array. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code dst.length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = dst.length} values from this buffer into the given - * array. - * - * @param dst the array into which values are to be written - * @return this buffer - * @throws BufferUnderflowException if there are not enough values to copy from this buffer - */ - default DataBuffer read(T[] dst) { - return read(dst, 0, dst.length); - } - - /** - * Read the references of the objects in this buffer into the destination array. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from this buffer into the given array - * starting at the given offset. - * - * @param dst the array into which values are to be written - * @param offset the offset within the array of the first value to be written; must be - * non-negative and no larger than {@code dst.length} - * @param length the maximum number of values to be written to the given array; must be - * non-negative and no larger than {@code dst.length - offset} - * @return this buffer - * @throws BufferUnderflowException if there are fewer than length values remaining in this buffer - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - */ - DataBuffer read(T[] dst, int offset, int length); - - /** - * Write the references of the objects in the source array into this buffer. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code src.length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = src.length} values from the given array. - * - * @param src the source array from which values are to be read - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws ReadOnlyBufferException if this buffer is read-only - */ - default DataBuffer write(T[] src) { - return write(src, 0, src.length); - } - - /** - * Bulk put method, using int arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from the given array into this buffer, - * starting at the given offset. - * - * @param src the source array from which values are to be read - * @param offset the offset within the array of the first value to be read; must be non-negative - * and no larger than {@code src.length} - * @param length the number of values to be read from the given array; must be non-negative and no - * larger than {@code src.length - offset} - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - * @throws ReadOnlyBufferException if this buffer is read-only - */ - DataBuffer write(T[] src, int offset, int length); - - /** - * Write the references of the objects in the source array into this buffer. - *

- * If there are more values to copy than the destination buffer size, i.e. - * {@code size > dst.size()}, then no values are transferred and a - * BufferOverflowException is thrown. On the other hand, if there are more values to copy that - * the source buffer size, i.e. {@code > src.size()}, then a BufferUnderfloatException is thrown. - *

- * Otherwise, this method copies {@code n = size} values from this buffer into - * the destination buffer. - * - * @param dst the destination buffer into which values are copied; must not be this buffer - * @param size number of values to copy to the destination buffer - * @return this buffer - * @throws IllegalArgumentException if the destination buffer is this buffer - * @throws ReadOnlyBufferException if the destination buffer is read-only - * @throws java.nio.BufferOverflowException if there is not enough space in destination buffer - * @throws java.nio.BufferUnderflowException if there are not enough values in the source buffer - */ - DataBuffer copyTo(DataBuffer dst, long size); - - /** - * Creates a new buffer whose content is a shared subsequence of this buffer's content, starting - * at the given index. - *

- * The index must not be greater than this buffer size. Changes to this buffer's content will - * be visible in the new buffer and vice versa. The new buffer will be read-only if, and only if, - * this buffer is read-only. - *

- * This call is equivalent to {@link #slice(long, long) slice(index, size() - index)} - * - * @param index index of the first value of the new buffer created, must not be greater than - * {@code size()} - * @return the new buffer - * @throws IllegalArgumentException if index do not pass validation checks - */ - default DataBuffer offset(long index) { - return slice(index, size() - index); - } - - /** - * Creates a new buffer whose content is a shared subsequence of this buffer's content, whose - * size is set to the given value. - *

- * The new size must not be greater than this buffer size. Changes to this buffer's - * content will be visible in the new buffer and vice versa. The new buffer will be read-only if, - * and only if, this buffer is read-only. - *

- * This call is equivalent to {@link #slice(long, long) slice(0, size)} - * - * @param size size of this new buffer - * @return the new buffer - * @throws IllegalArgumentException if index and/or size values do not pass validation checks - */ - default DataBuffer narrow(long size) { - return slice(0, size); - } - - /** - * Creates a new buffer whose content is a shared subsequence of this buffer's content, starting - * at the given index and of the given size. - *

- * The index plus the new size must not be greater than this buffer size. Changes to this - * buffer's content will be visible in the new buffer and vice versa. The new buffer will be - * read-only if, and only if, this buffer is read-only. - * - * @param index index of the first value of the new buffer created - * @param size size of this new buffer, must not be greater than {@code size()} - * @return the new buffer - * @throws IllegalArgumentException if size value do not pass validation checks - */ - DataBuffer slice(long index, long size); - - /** - * Creates a {@link DataBufferWindow} that provides a partial view of this buffer. - * - *

The created window has a fixed size and can {@link DataBufferWindow#slide(long) "slide"} - * along this buffer to provide different views of the data without allocating a new buffer - * instance, like {@link #offset(long)} does. This improves overall performance when this - * operation is repeated frequently. For example: - * - * 

{@code
-   * IntDataBuffer bufferA = DataBuffers.ofInts(1024);
-   * // ... init buffer data
-   * IntDataBuffer bufferB = DataBuffers.ofInts(1, 2, 3, 4);
-   *
-   * // Return the index of the first occurrence of bufferB in bufferA using a sliding window
-   * DataBufferWindow windowA = bufferA.window(4);
-   * for (int i = 0; i < bufferA.size() - bufferB.size(); ++i) {
-   *     if (windowA.slideTo(i).buffer().equals(bufferB)) {
-   *         return i;
-   *     }
-   * }
-   * }
- * - *

The returned object is stateful and is not thread-safe. - * - * @param size size of the window - * @return a new window that starts at the index 0 of this buffer - * @throws UnsupportedOperationException if this type of buffer does not support buffer windows - */ - default DataBufferWindow> window(long size) { - throw new UnsupportedOperationException(); - } - - /** - * Visits the backing storage of this buffer. - * - *

The buffer implementation is responsible of passing back a reference to the actual data - * storage to the provided visitor. The visitor does not have to handle all possible types of - * data storage and can override only methods for storage it is actually interested in. For any - * other type of storage, this call will fallback to {@link DataStorageVisitor#fallback()} so the - * visitor can execute some generic routine if needed. - * - * @param visitor visits the data storage of this buffer - * @param type of value returned by the visitor - * @return the same value returned by the visitor - */ - default R accept(DataStorageVisitor visitor) { - return visitor.fallback(); - } - - /** - * Checks equality between data buffers. - * - *

A data buffer is equal to another object if this object is another {@link DataBuffer} of the - * same size, type and the elements are equal and in the same order. For example: - * - * 

{@code
-   * IntDataBuffer buffer = DataBuffers.of(1, 2, 3);
-   *
-   * assertEquals(buffer, DataBuffers.of(1, 2, 3));  // true
-   * assertEquals(buffer, DataBuffers.ofObjects(1, 2, 3));  // true, as Integers are equal to ints
-   * assertNotEquals(buffer, DataBuffers.of(1, 2, 3, 0));  // false, different sizes
-   * assertNotEquals(buffer, DataBuffers.of(1, 3, 2));  // false, different order
-   * assertNotEquals(buffer, DataBuffers.of(1L, 2L, 3L));  // false, different types
-   * }
- * - *

Note that the computation required to verify equality between two buffers can be expensive - * in some cases and therefore, it is recommended to not use this method in a critical path - * where performances matter. - * - * @param obj object to compare this buffer with - * @return true if this buffer is equal to the provided object - */ - @Override - boolean equals(Object obj); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DataBufferWindow.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DataBufferWindow.java deleted file mode 100644 index 85fc8c43d05..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DataBufferWindow.java +++ /dev/null @@ -1,93 +0,0 @@ -package org.tensorflow.ndarray.buffer; - -/** - * A mutable container for viewing part of a {@link DataBuffer}. - * - *

Data buffer windows have a fixed size and can {@link DataBufferWindow#slide(long) "slide"} - * along a buffer to provide different views of the data without allocating a new buffer instance, - * like {@link DataBuffer#offset(long)} does. This improves overall performance when this operation - * is repeated frequently. For example: - * - * 

{@code
- * IntDataBuffer bufferA = DataBuffers.ofInts(1024);
- * // ... init buffer data
- * IntDataBuffer bufferB = DataBuffers.ofInts(1, 2, 3, 4);
- *
- * // Return the index of the first occurrence of bufferB in bufferA using a sliding window
- * DataBufferWindow windowA = bufferA.window(4);
- * for (int i = 0; i < bufferA.size() - bufferB.size(); ++i) {
- *     if (windowA.slideTo(i).buffer().equals(bufferB)) {
- *         return i;
- *     }
- * }
- * }
- * - *

{@code DataBufferWindow} instances are stateful and not thread-safe. - * - * @param the type of buffer being viewed - */ -public interface DataBufferWindow> { - - /** - * Returns the current offset of this window in the original buffer. - */ - long offset(); - - /** - * Returns the size of this buffer window. - */ - long size(); - - /** - * Moves the window at the given position in the original buffer. - * - *

The size of the window remains the same and its offset is set to {@code index}, so that - * accessing the value of {@link #buffer()} at index {@code x} will return the value at - * {@code index + x} in the original buffer. - * - * @param index new offset for this window - * @return this instance - * @throws IndexOutOfBoundsException if the window cannot be slid because it goes beyond - * the original buffer limits - */ - DataBufferWindow slideTo(long index); - - /** - * Moves the window of {@code step} elements in the original buffer. - * - *

The size of the window remains the same and its offset is set to {@code offset() + step}. - * If {@code step} is positive, then the window will slide forward. If it is negative, it will - * slide backward. - * - * @param step value to add to the current offset of this window - * @return this instance - * @throws IndexOutOfBoundsException if the window cannot be slid because it goes beyond - * the original buffer limits - */ - DataBufferWindow slide(long step); - - /** - * Returns the buffer backing this window. - * - *

Each window instance has it's own buffer providing a view onto the original - * {@link DataBuffer}. The buffers are mutated when the window slides to different offsets. - * For example: - * - * 

{@code
-   * IntDataBuffer buffer = DataBuffers.of(0, 1, 2, 3);
-   * DataBufferWindow window = buffer.window(0, 2);
-   *
-   * IntDataBuffer windowBuffer = window.buffer();
-   * assertEquals(0, windowBuffer.getInt(0));
-   * assertEquals(1, windowBuffer.getInt(1));
-   *
-   * window.slideTo(2);
-   * assertEquals(2, windowBuffer.getInt(0));
-   * assertEquals(3, windowBuffer.getInt(1));
-   * assertSame(windowBuffer, window.buffer());
-   * }
- * - * @return this window's buffer - */ - B buffer(); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DataBuffers.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DataBuffers.java deleted file mode 100644 index a5feb2599d0..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DataBuffers.java +++ /dev/null @@ -1,457 +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.ndarray.buffer; - -import java.lang.reflect.Array; -import java.nio.ByteBuffer; -import java.nio.DoubleBuffer; -import java.nio.FloatBuffer; -import java.nio.IntBuffer; -import java.nio.LongBuffer; -import java.nio.ShortBuffer; -import java.util.Arrays; -import java.util.BitSet; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.impl.buffer.misc.MiscDataBufferFactory; -import org.tensorflow.ndarray.impl.buffer.nio.NioDataBufferFactory; -import org.tensorflow.ndarray.impl.buffer.raw.RawDataBufferFactory; - -/** - * Helper class for creating {@code DataBuffer} instances. - */ -public final class DataBuffers { - - /** - * Creates a buffer of bytes that can store up to {@code size} values - * - * @param size size of the buffer to allocate - * @return a new buffer - */ - public static ByteDataBuffer ofBytes(long size) { - Validator.createArgs(size, MAX_32BITS); - if (RawDataBufferFactory.canBeUsed()) { - return RawDataBufferFactory.create(new byte[(int)size], false); - } - return NioDataBufferFactory.create(ByteBuffer.allocate((int)size)); - } - - /** - * Creates a buffer of longs that can store up to {@code size} values - * - * @param size size of the buffer to allocate - * @return a new buffer - */ - public static LongDataBuffer ofLongs(long size) { - Validator.createArgs(size, MAX_32BITS); - if (RawDataBufferFactory.canBeUsed()) { - return RawDataBufferFactory.create(new long[(int)size], false); - } - return NioDataBufferFactory.create(LongBuffer.allocate((int)size)); - } - - /** - * Creates a buffer of integers that can store up to {@code size} values - * - * @param size size of the buffer to allocate - * @return a new buffer - */ - public static IntDataBuffer ofInts(long size) { - Validator.createArgs(size, MAX_32BITS); - if (RawDataBufferFactory.canBeUsed()) { - return RawDataBufferFactory.create(new int[(int)size], false); - } - return NioDataBufferFactory.create(IntBuffer.allocate((int)size)); - } - - /** - * Creates a buffer of shorts that can store up to {@code size} values - * - * @param size size of the buffer to allocate - * @return a new buffer - */ - public static ShortDataBuffer ofShorts(long size) { - Validator.createArgs(size, MAX_32BITS); - if (RawDataBufferFactory.canBeUsed()) { - return RawDataBufferFactory.create(new short[(int)size], false); - } - return NioDataBufferFactory.create(ShortBuffer.allocate((int)size)); - } - - /** - * Creates a buffer of doubles that can store up to {@code size} values - * - * @param size size of the buffer to allocate - * @return a new buffer - */ - public static DoubleDataBuffer ofDoubles(long size) { - Validator.createArgs(size, MAX_32BITS); - if (RawDataBufferFactory.canBeUsed()) { - return RawDataBufferFactory.create(new double[(int)size], false); - } - return NioDataBufferFactory.create(DoubleBuffer.allocate((int)size)); - } - - /** - * Creates a buffer of floats that can store up to {@code size} values - * - * @param size size of the buffer to allocate - * @return a new buffer - */ - public static FloatDataBuffer ofFloats(long size) { - Validator.createArgs(size, MAX_32BITS); - if (RawDataBufferFactory.canBeUsed()) { - return RawDataBufferFactory.create(new float[(int)size], false); - } - return NioDataBufferFactory.create(FloatBuffer.allocate((int)size)); - } - - /** - * Creates a buffer of booleans that can store up to {@code size} values - * - * @param size size of the buffer to allocate - * @return a new buffer - */ - public static BooleanDataBuffer ofBooleans(long size) { - Validator.createArgs(size, MAX_32BITS); - if (RawDataBufferFactory.canBeUsed()) { - return RawDataBufferFactory.create(new boolean[(int)size], false); - } - return MiscDataBufferFactory.create(new BitSet((int)size), size, false); - } - - /** - * Creates a buffer of references to objects of type {@code clazz` that can store up to `size} - * values. - * - * @param type the type of object stored in this buffer - * @param size size of the buffer to allocate - * @param data type - * @return a new buffer - */ - public static DataBuffer ofObjects(Class type, long size) { - Validator.createArgs(size, MAX_32BITS); - @SuppressWarnings("unchecked") - T[] array = (T[])Array.newInstance(type, (int)size); - return MiscDataBufferFactory.create(array, false); - } - - /** - * Create a buffer from an array of floats into a data buffer. - * - *

The returned buffer allows read and write operations and share the memory of the source - * array, which is equivalent to call {@link #of(float[], boolean, boolean) of(values, false, false}} - * - * @param values float values - * @return a new buffer - */ - public static FloatDataBuffer of(float... values) { - return of(values, false, false); - } - - /** - * Create a buffer from an array of bytes into a data buffer. - * - *

The returned buffer allows read and write operations and share the memory of the source - * array, which is equivalent to call {@link #of(byte[], boolean, boolean) of(values, false, false}} - * - * @param values byte values - * @return a new buffer - */ - public static ByteDataBuffer of(byte... values) { - return of(values, false, false); - } - - /** - * Create a buffer from an array of longs into a data buffer. - * - *

The returned buffer allows read and write operations and share the memory of the source - * array, which is equivalent to call {@link #of(long[], boolean, boolean) of(values, false, false}} - * - * @param values long values - * @return a new buffer - */ - public static LongDataBuffer of(long... values) { - return of(values, false, false); - } - - /** - * Create a buffer from an array of ints into a data buffer. - * - *

The returned buffer allows read and write operations and share the memory of the source - * array, which is equivalent to call {@link #of(int[], boolean, boolean) of(values, false, false}} - * - * @param values int values - * @return a new buffer - */ - public static IntDataBuffer of(int... values) { - return of(values, false, false); - } - - /** - * Create a buffer from an array of shorts into a data buffer. - * - *

The returned buffer allows read and write operations and share the memory of the source - * array, which is equivalent to call {@link #of(short[], boolean, boolean) of(values, false, false}} - * - * @param values short values - * @return a new buffer - */ - public static ShortDataBuffer of(short... values) { - return of(values, false, false); - } - - /** - * Create a buffer from an array of doubles into a data buffer. - * - *

The returned buffer allows read and write operations and share the memory of the source - * array, which is equivalent to call {@link #of(double[], boolean, boolean) of(array, false, false}} - * - * @param values double values - * @return a new buffer - */ - public static DoubleDataBuffer of(double... values) { - return of(values, false, false); - } - - /** - * Create a buffer from an array of booleans into a data buffer. - * - *

The returned buffer allows read and write operations and share the memory of the source - * array, which is equivalent to call {@link #of(boolean[], boolean, boolean) of(values, false, false}} - * - * @param values booleans values - * @return a new buffer - */ - public static BooleanDataBuffer of(boolean... values) { - return of(values, false, false); - } - - /** - * Create a buffer from an array of objects into a data buffer. - * - *

The returned buffer allows read and write operations and share the memory of the source - * array, which is equivalent to call {@link #of(Object[], boolean, boolean) of(values, false, false}} - * - * @param values objects values - * @param data type - * @return a new buffer - */ - @SafeVarargs - public static DataBuffer ofObjects(T... values) { - return of(values, false, false); - } - - /** - * Create a buffer from an array of floats into a data buffer. - * - * @param array array of floats - * @param readOnly true if the buffer created must be read-only - * @param makeCopy true if the array must be copied, false will wrap the provided array - * @return a new buffer - */ - public static FloatDataBuffer of(float[] array, boolean readOnly, boolean makeCopy) { - float[] bufferArray = makeCopy ? Arrays.copyOf(array, array.length) : array; - if (RawDataBufferFactory.canBeUsed()) { - return RawDataBufferFactory.create(bufferArray, readOnly); - } - FloatBuffer buf = FloatBuffer.wrap(bufferArray); - return NioDataBufferFactory.create(readOnly ? buf.asReadOnlyBuffer() : buf); - } - - /** - * Create a buffer from an array of bytes into a data buffer. - * - * @param array array of bytes - * @param readOnly true if the buffer created must be read-only - * @param makeCopy true if the array must be copied, false will wrap the provided array - * @return a new buffer - */ - public static ByteDataBuffer of(byte[] array, boolean readOnly, boolean makeCopy) { - byte[] bufferArray = makeCopy ? Arrays.copyOf(array, array.length) : array; - if (RawDataBufferFactory.canBeUsed()) { - return RawDataBufferFactory.create(bufferArray, readOnly); - } - ByteBuffer buf = ByteBuffer.wrap(bufferArray); - return NioDataBufferFactory.create(readOnly ? buf.asReadOnlyBuffer() : buf); - } - - /** - * Create a buffer from an array of longs into a data buffer. - * - * @param array array of longs - * @param readOnly true if the buffer created must be read-only - * @param makeCopy true if the array must be copied, false will wrap the provided array - * @return a new buffer - */ - public static LongDataBuffer of(long[] array, boolean readOnly, boolean makeCopy) { - long[] bufferArray = makeCopy ? Arrays.copyOf(array, array.length) : array; - if (RawDataBufferFactory.canBeUsed()) { - return RawDataBufferFactory.create(bufferArray, readOnly); - } - LongBuffer buf = LongBuffer.wrap(bufferArray); - return NioDataBufferFactory.create(readOnly ? buf.asReadOnlyBuffer() : buf); - } - - /** - * Create a buffer from an array of ints into a data buffer. - * - * @param array array of ints - * @param readOnly true if the buffer created must be read-only - * @param makeCopy true if the array must be copied, false will wrap the provided array - * @return a new buffer - */ - public static IntDataBuffer of(int[] array, boolean readOnly, boolean makeCopy) { - int[] bufferArray = makeCopy ? Arrays.copyOf(array, array.length) : array; - if (RawDataBufferFactory.canBeUsed()) { - return RawDataBufferFactory.create(bufferArray, readOnly); - } - IntBuffer buf = IntBuffer.wrap(bufferArray); - return NioDataBufferFactory.create(readOnly ? buf.asReadOnlyBuffer() : buf); - } - - /** - * Create a buffer from an array of shorts into a data buffer. - * - * @param array array of shorts - * @param readOnly true if the buffer created must be read-only - * @param makeCopy true if the array must be copied, false will wrap the provided array - * @return a new buffer - */ - public static ShortDataBuffer of(short[] array, boolean readOnly, boolean makeCopy) { - short[] bufferArray = makeCopy ? Arrays.copyOf(array, array.length) : array; - if (RawDataBufferFactory.canBeUsed()) { - return RawDataBufferFactory.create(bufferArray, readOnly); - } - ShortBuffer buf = ShortBuffer.wrap(bufferArray); - return NioDataBufferFactory.create(readOnly ? buf.asReadOnlyBuffer() : buf); - } - - /** - * Create a buffer from an array of doubles into a data buffer. - * - * @param array array of doubles - * @param readOnly true if the buffer created must be read-only - * @param makeCopy true if the array must be copied, false will wrap the provided array - * @return a new buffer - */ - public static DoubleDataBuffer of(double[] array, boolean readOnly, boolean makeCopy) { - double[] bufferArray = makeCopy ? Arrays.copyOf(array, array.length) : array; - if (RawDataBufferFactory.canBeUsed()) { - return RawDataBufferFactory.create(bufferArray, readOnly); - } - DoubleBuffer buf = DoubleBuffer.wrap(bufferArray); - return NioDataBufferFactory.create(readOnly ? buf.asReadOnlyBuffer() : buf); - } - - /** - * Create a buffer from an array of booleans into a data buffer. - * - * @param array array of booleans - * @param readOnly true if the buffer created must be read-only - * @param makeCopy true if the array must be copied, false will wrap the provided array - * @return a new buffer - */ - public static BooleanDataBuffer of(boolean[] array, boolean readOnly, boolean makeCopy) { - boolean[] bufferArray = makeCopy ? Arrays.copyOf(array, array.length) : array; - if (RawDataBufferFactory.canBeUsed()) { - return RawDataBufferFactory.create(bufferArray, readOnly); - } - return MiscDataBufferFactory.create(bufferArray, readOnly); - } - - /** - * Create a buffer from an array of objects into a data buffer. - * - * @param array array of objects - * @param readOnly true if the buffer created must be read-only - * @param makeCopy true if the array must be copied, false will wrap the provided array - * @param data type - * @return a new buffer - */ - public static DataBuffer of(T[] array, boolean readOnly, boolean makeCopy) { - T[] bufferArray = makeCopy ? Arrays.copyOf(array, array.length) : array; - return MiscDataBufferFactory.create(bufferArray, readOnly); - } - - /** - * Wraps a JDK NIO {@link ByteBuffer} into a data buffer. - * - * @param buf buffer to wrap - * @return a new buffer - */ - public static ByteDataBuffer of(ByteBuffer buf) { - return NioDataBufferFactory.create(buf.duplicate()); - } - - /** - * Wraps a JDK NIO {@link IntBuffer} into a data buffer. - * - * @param buf buffer to wrap - * @return a new buffer - */ - public static IntDataBuffer of(IntBuffer buf) { - return NioDataBufferFactory.create(buf.duplicate()); - } - - /** - * Wraps a JDK NIO {@link ShortBuffer} into a data buffer. - * - * @param buf buffer to wrap - * @return a new buffer - */ - public static ShortDataBuffer of(ShortBuffer buf) { - return NioDataBufferFactory.create(buf.duplicate()); - } - - /** - * Wraps a JDK NIO {@link LongBuffer} into a data buffer. - * - * @param buf buffer to wrap - * @return a new buffer - */ - public static LongDataBuffer of(LongBuffer buf) { - return NioDataBufferFactory.create(buf.duplicate()); - } - - /** - * Wraps a JDK NIO {@link FloatBuffer} into a data buffer. - * - * @param buf buffer to wrap - * @return a new buffer - */ - public static FloatDataBuffer of(FloatBuffer buf) { - return NioDataBufferFactory.create(buf.duplicate()); - } - - /** - * Wraps a JDK NIO {@link DoubleBuffer} into a data buffer. - * - * @param buf buffer to wrap - * @return a new buffer - */ - public static DoubleDataBuffer of(DoubleBuffer buf) { - return NioDataBufferFactory.create(buf.duplicate()); - } - - /* - * The maximum size for a buffer of this type, i.e. the maximum number of bytes it can store. - *

- * As the maximum size may vary depending on the JVM implementation and on the platform, this - * property returns a value that is safe for most of them. - */ - static long MAX_32BITS = Integer.MAX_VALUE - 10; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DataStorageVisitor.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DataStorageVisitor.java deleted file mode 100644 index 560320cd7eb..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DataStorageVisitor.java +++ /dev/null @@ -1,147 +0,0 @@ -package org.tensorflow.ndarray.buffer; - -import java.nio.ByteBuffer; -import java.nio.DoubleBuffer; -import java.nio.FloatBuffer; -import java.nio.IntBuffer; -import java.nio.LongBuffer; -import java.nio.ShortBuffer; -import java.util.BitSet; - -/** - * Visit the backing storage of {@link DataBuffer} instances. - * - * @param value type returned by the visitor - */ -public interface DataStorageVisitor { - - /** - * Visit the {@link ByteBuffer} backing a given instance of a {@link DataBuffer} - * - * @param buffer underlying buffer - * @return any value - * @see DataBuffer#accept(DataStorageVisitor) - */ - default R visit(ByteBuffer buffer) { - return fallback(); - } - - /** - * Visit the {@link ShortBuffer} backing a given instance of a {@link DataBuffer} - * - * @param buffer underlying buffer - * @return any value - * @see DataBuffer#accept(DataStorageVisitor) - */ - default R visit(ShortBuffer buffer) { - return fallback(); - } - - /** - * Visit the {@link IntBuffer} backing a given instance of a {@link DataBuffer} - * - * @param buffer underlying buffer - * @return any value - * @see DataBuffer#accept(DataStorageVisitor) - */ - default R visit(IntBuffer buffer) { - return fallback(); - } - - /** - * Visit the {@link LongBuffer} backing a given instance of a {@link DataBuffer} - * - * @param buffer underlying buffer - * @return any value - * @see DataBuffer#accept(DataStorageVisitor) - */ - default R visit(LongBuffer buffer) { - return fallback(); - } - - /** - * Visit the {@link FloatBuffer} backing a given instance of a {@link DataBuffer} - * - * @param buffer underlying buffer - * @return any value - * @see DataBuffer#accept(DataStorageVisitor) - */ - default R visit(FloatBuffer buffer) { - return fallback(); - } - - /** - * Visit the {@link DoubleBuffer} backing a given instance of a {@link DataBuffer} - * - * @param buffer underlying buffer - * @return any value - * @see DataBuffer#accept(DataStorageVisitor) - */ - default R visit(DoubleBuffer buffer) { - return fallback(); - } - - /** - * Visit the boolean array backing a given instance of a {@link DataBuffer} - * - * @param array underlying array - * @param offset offset of the buffer within the array - * @param length length of the buffer within the array - * @return any value - * @see DataBuffer#accept(DataStorageVisitor) - */ - default R visit(boolean[] array, int offset, int length) { - return fallback(); - } - - /** - * Visit the bit set backing a given instance of a {@link DataBuffer} - * - * @param bitSet underlying bit set - * @param offset offset of the buffer within the bit set - * @param numBits number of bits used to represent the buffer within the bit set - * @return any value - * @see DataBuffer#accept(DataStorageVisitor) - */ - default R visit(BitSet bitSet, int offset, long numBits) { - return fallback(); - } - - /** - * Visit the object array backing a given instance of a {@link DataBuffer} - * - * @param array underlying array - * @param offset offset of the buffer within the array - * @param length length of the buffer within the array - * @return any value - * @see DataBuffer#accept(DataStorageVisitor) - */ - default R visit(Object[] array, int offset, int length) { - return fallback(); - } - - /** - * Visit the raw memory segment of a given instance of a {@link DataBuffer} - * - * @param address native address of the buffer - * @param length length of the buffer - * @param scale number of bytes required to store a single value of this buffer - * @return any value - * @see DataBuffer#accept(DataStorageVisitor) - */ - default R visit(long address, long length, long scale) { - return fallback(); - } - - /** - * Fallback method called if the visitor implementation does not support the type of backing storage - * for a given {@link DataBuffer} - * - *

The implementor of this interface must override the {@code visit} methods for type of storage - * it supports. If {@link DataBuffer#accept(DataStorageVisitor)} is called on a buffer - * using a different type of storage, the invocation will fallback to this method. - * - * @return any value - */ - R fallback(); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DoubleDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DoubleDataBuffer.java deleted file mode 100644 index f2db925eb78..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/DoubleDataBuffer.java +++ /dev/null @@ -1,165 +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.ndarray.buffer; - -import java.nio.BufferOverflowException; -import java.nio.BufferUnderflowException; -import java.nio.ReadOnlyBufferException; - -/** - * A {@link DataBuffer} of doubles. - */ -public interface DoubleDataBuffer extends DataBuffer { - - /** - * Reads the double at the given index. - * - * @param index the index from which the float will be read - * @return the double at the given index - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - */ - double getDouble(long index); - - /** - * Writes the given double into this buffer at the given index. - * - * @param value the double to be written - * @param index the index at which the value will be written - * @return this buffer - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - * @throws ReadOnlyBufferException if this buffer is read-only - */ - DoubleDataBuffer setDouble(double value, long index); - - /** - * Bulk get method, using double arrays. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code dst.length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = dst.length} values from this buffer into the given - * array. - * - * @param dst the array into which values are to be written - * @return this buffer - * @throws BufferUnderflowException if there are not enough values to copy from this buffer - */ - default DoubleDataBuffer read(double[] dst) { - return read(dst, 0, dst.length); - } - - /** - * Bulk get method, using double arrays. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from this buffer into the given array - * starting at the given offset. - * - * @param dst the array into which values are to be written - * @param offset the offset within the array of the first value to be written; must be - * non-negative and no larger than {@code dst.length} - * @param length the maximum number of values to be written to the given array; must be - * non-negative and no larger than {@code dst.length - offset} - * @return this buffer - * @throws BufferUnderflowException if there are fewer than length values remaining in this buffer - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - */ - DoubleDataBuffer read(double[] dst, int offset, int length); - - /** - * Bulk put method, using double arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code src.length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = src.length} values from the given array. - * - * @param src the source array from which values are to be read - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws ReadOnlyBufferException if this buffer is read-only - */ - default DoubleDataBuffer write(double[] src) { - return write(src, 0, src.length); - } - - /** - * Bulk put method, using double arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from the given array into this buffer, - * starting at the given offset. - * - * @param src the source array from which values are to be read - * @param offset the offset within the array of the first value to be read; must be non-negative - * and no larger than {@code src.length} - * @param length the number of values to be read from the given array; must be non-negative and no - * larger than {@code src.length - offset} - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - * @throws ReadOnlyBufferException if this buffer is read-only - */ - DoubleDataBuffer write(double[] src, int offset, int length); - - @Override - default Double getObject(long index) { - return getDouble(index); - } - - @Override - default DoubleDataBuffer setObject(Double value, long index) { - return setDouble(value, index); - } - - @Override - DoubleDataBuffer copyTo(DataBuffer dst, long size); - - @Override - default DoubleDataBuffer offset(long index) { - return slice(index, size() - index); - } - - @Override - default DoubleDataBuffer narrow(long size) { - return slice(0, size); - } - - @Override - DoubleDataBuffer slice(long index, long size); - - @Override - default DataBufferWindow window(long size) { - throw new UnsupportedOperationException(); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/FloatDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/FloatDataBuffer.java deleted file mode 100644 index 4961c1b3445..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/FloatDataBuffer.java +++ /dev/null @@ -1,165 +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.ndarray.buffer; - -import java.nio.BufferOverflowException; -import java.nio.BufferUnderflowException; -import java.nio.ReadOnlyBufferException; - -/** - * A {@link DataBuffer} of floats. - */ -public interface FloatDataBuffer extends DataBuffer { - - /** - * Reads the float at the given index. - * - * @param index the index from which the float will be read - * @return the float at the given index - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - */ - float getFloat(long index); - - /** - * Writes the given float into this buffer at the given index. - * - * @param value the float to be written - * @param index the index at which the value will be written - * @return this buffer - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - * @throws ReadOnlyBufferException if this buffer is read-only - */ - FloatDataBuffer setFloat(float value, long index); - - /** - * Bulk get method, using float arrays. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code dst.length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = dst.length} values from this buffer into the given - * array. - * - * @param dst the array into which values are to be written - * @return this buffer - * @throws BufferUnderflowException if there are not enough values to copy from this buffer - */ - default FloatDataBuffer read(float[] dst) { - return read(dst, 0, dst.length); - } - - /** - * Bulk get method, using float arrays. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from this buffer into the given array - * starting at the given offset. - * - * @param dst the array into which values are to be written - * @param offset the offset within the array of the first value to be written; must be - * non-negative and no larger than {@code dst.length} - * @param length the maximum number of values to be written to the given array; must be - * non-negative and no larger than {@code dst.length - offset} - * @return this buffer - * @throws BufferUnderflowException if there are fewer than length values remaining in this buffer - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - */ - FloatDataBuffer read(float[] dst, int offset, int length); - - /** - * Bulk put method, using float arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code src.length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = src.length} values from the given array. - * - * @param src the source array from which values are to be read - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws ReadOnlyBufferException if this buffer is read-only - */ - default FloatDataBuffer write(float[] src) { - return write(src, 0, src.length); - } - - /** - * Bulk put method, using float arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from the given array into this buffer, - * starting at the given offset. - * - * @param src the source array from which values are to be read - * @param offset the offset within the array of the first value to be read; must be non-negative - * and no larger than {@code src.length} - * @param length the number of values to be read from the given array; must be non-negative and no - * larger than {@code src.length - offset} - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - * @throws ReadOnlyBufferException if this buffer is read-only - */ - FloatDataBuffer write(float[] src, int offset, int length); - - @Override - default Float getObject(long index) { - return getFloat(index); - } - - @Override - default FloatDataBuffer setObject(Float value, long index) { - return setFloat(value, index); - } - - @Override - FloatDataBuffer copyTo(DataBuffer dst, long size); - - @Override - default FloatDataBuffer offset(long index) { - return slice(index, size() - index); - } - - @Override - default FloatDataBuffer narrow(long size) { - return slice(0, size); - } - - @Override - FloatDataBuffer slice(long index, long size); - - @Override - default DataBufferWindow window(long size) { - throw new UnsupportedOperationException(); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/IntDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/IntDataBuffer.java deleted file mode 100644 index 2d660756e09..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/IntDataBuffer.java +++ /dev/null @@ -1,165 +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.ndarray.buffer; - -import java.nio.BufferOverflowException; -import java.nio.BufferUnderflowException; -import java.nio.ReadOnlyBufferException; - -/** - * A {@link DataBuffer} of ints. - */ -public interface IntDataBuffer extends DataBuffer { - - /** - * Reads the int at the given index. - * - * @param index the index from which the float will be read - * @return the int at the given index - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - */ - int getInt(long index); - - /** - * Writes the given int into this buffer at the given index. - * - * @param value the int to be written - * @param index the index at which the value will be written - * @return this buffer - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - * @throws ReadOnlyBufferException if this buffer is read-only - */ - IntDataBuffer setInt(int value, long index); - - /** - * Bulk get method, using int arrays. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code dst.length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = dst.length} values from this buffer into the given - * array. - * - * @param dst the array into which values are to be written - * @return this buffer - * @throws BufferUnderflowException if there are not enough values to copy from this buffer - */ - default IntDataBuffer read(int[] dst) { - return read(dst, 0, dst.length); - } - - /** - * Bulk get method, using int arrays. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from this buffer into the given array - * starting at the given offset. - * - * @param dst the array into which values are to be written - * @param offset the offset within the array of the first value to be written; must be - * non-negative and no larger than {@code dst.length} - * @param length the maximum number of values to be written to the given array; must be - * non-negative and no larger than {@code dst.length - offset} - * @return this buffer - * @throws BufferUnderflowException if there are fewer than length values remaining in this buffer - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - */ - IntDataBuffer read(int[] dst, int offset, int length); - - /** - * Bulk put method, using int arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code src.length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = src.length} values from the given array. - * - * @param src the source array from which values are to be read - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws ReadOnlyBufferException if this buffer is read-only - */ - default IntDataBuffer write(int[] src) { - return write(src, 0, src.length); - } - - /** - * Bulk put method, using int arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from the given array into this buffer, - * starting at the given offset. - * - * @param src the source array from which values are to be read - * @param offset the offset within the array of the first value to be read; must be non-negative - * and no larger than {@code src.length} - * @param length the number of values to be read from the given array; must be non-negative and no - * larger than {@code src.length - offset} - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - * @throws ReadOnlyBufferException if this buffer is read-only - */ - IntDataBuffer write(int[] src, int offset, int length); - - @Override - default Integer getObject(long index) { - return getInt(index); - } - - @Override - default IntDataBuffer setObject(Integer value, long index) { - return setInt(value, index); - } - - @Override - IntDataBuffer copyTo(DataBuffer dst, long size); - - @Override - default IntDataBuffer offset(long index) { - return slice(index, size() - index); - } - - @Override - default IntDataBuffer narrow(long size) { - return slice(0, size); - } - - @Override - IntDataBuffer slice(long index, long size); - - @Override - default DataBufferWindow window(long size) { - throw new UnsupportedOperationException(); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/LongDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/LongDataBuffer.java deleted file mode 100644 index f88ae4a80b4..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/LongDataBuffer.java +++ /dev/null @@ -1,165 +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.ndarray.buffer; - -import java.nio.BufferOverflowException; -import java.nio.BufferUnderflowException; -import java.nio.ReadOnlyBufferException; - -/** - * A {@link DataBuffer} of longs. - */ -public interface LongDataBuffer extends DataBuffer { - - /** - * Reads the long at the given index. - * - * @param index the index from which the float will be read - * @return the long at the given index - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - */ - long getLong(long index); - - /** - * Writes the given long into this buffer at the given index. - * - * @param value the long to be written - * @param index the index at which the value will be written - * @return this buffer - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - * @throws ReadOnlyBufferException if this buffer is read-only - */ - LongDataBuffer setLong(long value, long index); - - /** - * Bulk get method, using long arrays. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code dst.length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = dst.length} values from this buffer into the given - * array. - * - * @param dst the array into which values are to be written - * @return this buffer - * @throws BufferUnderflowException if there are not enough values to copy from this buffer - */ - default LongDataBuffer read(long[] dst) { - return read(dst, 0, dst.length); - } - - /** - * Bulk get method, using long arrays. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from this buffer into the given array - * starting at the given offset. - * - * @param dst the array into which values are to be written - * @param offset the offset within the array of the first value to be written; must be - * non-negative and no larger than {@code dst.length} - * @param length the maximum number of values to be written to the given array; must be - * non-negative and no larger than {@code dst.length - offset} - * @return this buffer - * @throws BufferUnderflowException if there are fewer than length values remaining in this buffer - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - */ - LongDataBuffer read(long[] dst, int offset, int length); - - /** - * Bulk put method, using long arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code src.length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = src.length} values from the given array. - * - * @param src the source array from which values are to be read - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws ReadOnlyBufferException if this buffer is read-only - */ - default LongDataBuffer write(long[] src) { - return write(src, 0, src.length); - } - - /** - * Bulk put method, using long arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from the given array into this buffer, - * starting at the given offset. - * - * @param src the source array from which values are to be read - * @param offset the offset within the array of the first value to be read; must be non-negative - * and no larger than {@code src.length} - * @param length the number of values to be read from the given array; must be non-negative and no - * larger than {@code src.length - offset} - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - * @throws ReadOnlyBufferException if this buffer is read-only - */ - LongDataBuffer write(long[] src, int offset, int length); - - @Override - default Long getObject(long index) { - return getLong(index); - } - - @Override - default LongDataBuffer setObject(Long value, long index) { - return setLong(value, index); - } - - @Override - LongDataBuffer copyTo(DataBuffer dst, long size); - - @Override - default LongDataBuffer offset(long index) { - return slice(index, size() - index); - } - - @Override - default LongDataBuffer narrow(long size) { - return slice(0, size); - } - - @Override - LongDataBuffer slice(long index, long size); - - @Override - default DataBufferWindow window(long size) { - throw new UnsupportedOperationException(); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/ShortDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/ShortDataBuffer.java deleted file mode 100644 index 290e2d57619..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/ShortDataBuffer.java +++ /dev/null @@ -1,165 +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.ndarray.buffer; - -import java.nio.BufferOverflowException; -import java.nio.BufferUnderflowException; -import java.nio.ReadOnlyBufferException; - -/** - * A {@link DataBuffer} of shorts. - */ -public interface ShortDataBuffer extends DataBuffer { - - /** - * Reads the short at the given index. - * - * @param index the index from which the float will be read - * @return the short at the given index - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - */ - short getShort(long index); - - /** - * Writes the given short into this buffer at the given index. - * - * @param value the short to be written - * @param index the index at which the value will be written - * @return this buffer - * @throws IndexOutOfBoundsException if index is negative or not smaller than the buffer size - * @throws ReadOnlyBufferException if this buffer is read-only - */ - ShortDataBuffer setShort(short value, long index); - - /** - * Bulk get method, using short arrays. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code dst.length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = dst.length} values from this buffer into the given - * array. - * - * @param dst the array into which values are to be written - * @return this buffer - * @throws BufferUnderflowException if there are not enough values to copy from this buffer - */ - default ShortDataBuffer read(short[] dst) { - return read(dst, 0, dst.length); - } - - /** - * Bulk get method, using short arrays. - *

- * This method transfers values from this buffer into the given destination array. If there are - * fewer values in the buffer than are required to satisfy the request, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferUnderflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from this buffer into the given array - * starting at the given offset. - * - * @param dst the array into which values are to be written - * @param offset the offset within the array of the first value to be written; must be - * non-negative and no larger than {@code dst.length} - * @param length the maximum number of values to be written to the given array; must be - * non-negative and no larger than {@code dst.length - offset} - * @return this buffer - * @throws BufferUnderflowException if there are fewer than length values remaining in this buffer - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - */ - ShortDataBuffer read(short[] dst, int offset, int length); - - /** - * Bulk put method, using short arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code src.length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = src.length} values from the given array. - * - * @param src the source array from which values are to be read - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws ReadOnlyBufferException if this buffer is read-only - */ - default ShortDataBuffer write(short[] src) { - return write(src, 0, src.length); - } - - /** - * Bulk put method, using short arrays. - *

- * This method transfers the values in the given source array into this buffer. If there are - * more values in the source array than in this buffer, that is, if - * {@code length > size()}, then no values are transferred and a - * BufferOverflowException is thrown. - *

- * Otherwise, this method copies {@code n = length} values from the given array into this buffer, - * starting at the given offset. - * - * @param src the source array from which values are to be read - * @param offset the offset within the array of the first value to be read; must be non-negative - * and no larger than {@code src.length} - * @param length the number of values to be read from the given array; must be non-negative and no - * larger than {@code src.length - offset} - * @return this buffer - * @throws BufferOverflowException if there is insufficient space in this buffer for the values in - * the source array - * @throws IndexOutOfBoundsException if the preconditions on the offset and length parameters do - * not hold - * @throws ReadOnlyBufferException if this buffer is read-only - */ - ShortDataBuffer write(short[] src, int offset, int length); - - @Override - default Short getObject(long index) { - return getShort(index); - } - - @Override - default ShortDataBuffer setObject(Short value, long index) { - return setShort(value, index); - } - - @Override - ShortDataBuffer copyTo(DataBuffer dst, long size); - - @Override - default ShortDataBuffer offset(long index) { - return slice(index, size() - index); - } - - @Override - default ShortDataBuffer narrow(long size) { - return slice(0, size); - } - - @Override - ShortDataBuffer slice(long index, long size); - - @Override - default DataBufferWindow window(long size) { - throw new UnsupportedOperationException(); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/BooleanDataLayout.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/BooleanDataLayout.java deleted file mode 100644 index c7092c8720d..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/BooleanDataLayout.java +++ /dev/null @@ -1,65 +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.ndarray.buffer.layout; - -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.impl.buffer.adapter.DataBufferAdapterFactory; - -/** - * A {@link DataLayout} that converts data stored in a buffer to booleans. - * - * @param type of buffer this layout can be applied to - * @see DataLayout - */ -public interface BooleanDataLayout> extends DataLayout { - - @Override - default BooleanDataBuffer applyTo(S buffer) { - return DataBufferAdapterFactory.create(buffer, this); - } - - /** - * Writes a boolean into the buffer at the given index after converting it to the buffer type. - * - * @param buffer the buffer to write to - * @param value the boolean to convert and write - * @param index index in the buffer where the converted value should be written - * @see #writeObject(DataBuffer, Boolean, long) - */ - void writeBoolean(S buffer, boolean value, long index); - - /** - * Reads {@code n = scale()} values from the buffer at the given index and return them as a boolean. - * - * @param buffer the buffer to read from - * @param index position of the buffer to read in the buffer - * @return the boolean value - * @see #readObject(DataBuffer, long) - */ - boolean readBoolean(S buffer, long index); - - @Override - default void writeObject(S buffer, Boolean value, long index) { - writeBoolean(buffer, value, index); - } - - @Override - default Boolean readObject(S buffer, long index) { - return readBoolean(buffer, index); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/ByteDataLayout.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/ByteDataLayout.java deleted file mode 100644 index e4d4bf9c8cf..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/ByteDataLayout.java +++ /dev/null @@ -1,65 +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.ndarray.buffer.layout; - -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.impl.buffer.adapter.DataBufferAdapterFactory; - -/** - * A {@link DataLayout} that converts data stored in a buffer to bytes. - * - * @param type of buffer this layout can be applied to - * @see DataLayout - */ -public interface ByteDataLayout> extends DataLayout { - - @Override - default ByteDataBuffer applyTo(S buffer) { - return DataBufferAdapterFactory.create(buffer, this); - } - - /** - * Writes a byte into the buffer at the given index after converting it to the buffer type. - * - * @param buffer the buffer to write to - * @param value the byte to convert and write - * @param index index in the buffer where the converted value should be written - * @see #writeObject(DataBuffer, Byte, long) - */ - void writeByte(S buffer, byte value, long index); - - /** - * Reads {@code n = scale()} values from the buffer at the given index and return them as a byte. - * - * @param buffer the buffer to read from - * @param index position of the buffer to read in the buffer - * @return the byte value - * @see #readObject(DataBuffer, long) - */ - byte readByte(S buffer, long index); - - @Override - default void writeObject(S buffer, Byte value, long index) { - writeByte(buffer, value, index); - } - - @Override - default Byte readObject(S buffer, long index) { - return readByte(buffer, index); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/DataLayout.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/DataLayout.java deleted file mode 100644 index 93cc542e07a..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/DataLayout.java +++ /dev/null @@ -1,129 +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.ndarray.buffer.layout; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.impl.buffer.adapter.DataBufferAdapterFactory; - -/** - * Converts data stored in a buffer to a given type. - * - *

{@code DataLayout} instances are used to define a custom format for storing and reading data - * of a {@link DataBuffer}. They provide a segregation layer between the type of data stored in the - * buffer (the buffer type) and the type of data manipulated by the end user (the - * user type). - * - *

Since the conversion methods are invoked for every value that is written or read, working - * with data layouts may have a negative impact on the performances so using primitive types directly - * should be preferred whenever possible. - * - *

It is also recommended to implement immutable data layouts so they can be reapplied to multiple - * buffers without reallocating a new instance for each of them. For example: - * - * 

- * class BigIntegerBufferAllocator {
- *
- *     public DataBuffer<BigInteger> allocate(long size) {
- *         return LAYOUT.applyTo(DataBuffers.ofLongs(size * LAYOUT.scale()));  // scale is 1 by default
- *     }
- *
- *     private static final DataLayout<LongDataBuffer, BigInteger> LAYOUT = new DataLayout<LongDataBuffer, BigInteger>() {
- *
- *         @Override
- *         public void writeObject(LongDataBuffer buffer, BigInteger value, long index) {
- *             buffer.setLong(value.longValue(), index);
- *         }
- *
- *         @Override
- *         public BigInteger readObject(LongDataBuffer buffer, long index) {
- *             return BigInteger.valueOf(buffer.getLong(index));
- *         }
- *     };
- * }
- *
- * - * @param type of buffer this layout can be applied to - * @param user data type of this layout - */ -public interface DataLayout, T> { - - /** - * Apply this layout to the provided buffer. - * - *

The returned {@link DataBuffer} instance is simply a wrapper to the original buffer and does - * not have a backing storage of his own. - * - * @param buffer the target buffer to apply this layout to - * @return a buffer with this layout - */ - default DataBuffer applyTo(S buffer) { - return DataBufferAdapterFactory.create(buffer, this); - } - - /** - * Writes a user value into the buffer at the given index after converting it to the buffer type. - * - *

It is the responsibility of the implementors of this interface to write the converted value - * to the given buffer before this call returns, using the most appropriate method. For example, - * for a layout converting a {@code BigInteger} to a single {@code long}, - * 

-   * @Override
-   * public void writeObject(LongDataBuffer buffer, BigInteger value, long index) {
-   *   buffer.setLong(value.longValue(), index);
-   * }
-   *
- * If a single user value scales over more than one buffer values, {@code index} indicates the - * starting position of the sequence to be written to the buffer. - * - * @param buffer the buffer to write to - * @param value the value in the user type to convert and write - * @param index index in the buffer where the converted value should be written - */ - void writeObject(S buffer, T value, long index); - - /** - * Reads {@code n = scale()} values from the buffer at the given index and return them as a single - * value in the user type. - * - *

It is the responsibility of the implementors of this interface to read the value to be - * converted from the given buffer, using the most appropriate method. For example, for a layout - * that converting a single {@code long} to a {@code BigInteger}, - * 

-   * @Override
-   * public BigInteger readObject(LongDataBuffer buffer, long index) {
-   *   return BigInteger.valueOf(buffer.getLong(index));
-   * }
-   *
- * If a single user value scales over more than one buffer values, {@code index} indicates the - * starting position of the sequence to be read from the buffer. - * - * @param buffer the buffer to read from - * @param index position of the buffer to read in the buffer - * @return the converted value - */ - T readObject(S buffer, long index); - - /** - * Indicates the number of buffer values are required to represent a single user value, default is 1. - * - *

Scale must be positive and must be an integer, meaning that a single buffer value in a buffer cannot - * be used to represent more than one user value. - */ - default int scale() { - return 1; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/DataLayouts.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/DataLayouts.java deleted file mode 100644 index 8f69168930c..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/DataLayouts.java +++ /dev/null @@ -1,96 +0,0 @@ -/* - * 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.ndarray.buffer.layout; - -import java.nio.charset.Charset; -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.impl.buffer.layout.Bfloat16Layout; -import org.tensorflow.ndarray.impl.buffer.layout.BoolLayout; -import org.tensorflow.ndarray.impl.buffer.layout.Float16Layout; -import org.tensorflow.ndarray.impl.buffer.layout.StringLayout; - -/** - * Exposes {@link DataLayout} instances of data formats frequently used in linear algebra computation. - * - *

Example of usage: - * 

{@code
- * // Storing boolean values in a ByteDataBuffer
- * BooleanDataBuffer boolBuffer = DataLayouts.BOOL.applyTo(byteDataBuffer);
- *
- * // Allocating a new buffer of 256 half floats
- * FloatDataBuffer halfBuffer = DataLayouts.FLOAT16.applyTo(DataBuffers.ofShorts(256 * DataLayouts.FLOAT16.scale());
- * }
- */ -public final class DataLayouts { - - /** - * Data layout for converting 16-bit bfloats to/from short values. - * - *

This format used to be specific to TensorFlow but has now been adopted more broadly in the - * machine learning field. It is optimized for fast conversion with single-precision 32-bit - * floating points by simply shifting their value and truncating the mantissa to only 7 bits. - * - *

Therefore, this is a lost of precision in the fraction part compared to the IEEE-754 - * half-precision floating point specification (see {@link #FLOAT16} but it has a larger range of - * possible values in the whole part as it preserves the 8-bit exponent and uses the same bias, - * (i.e. an absolute range above 0 of approximately [10-40, 3.39 × 1038] - * - *

Some CPUs support the bfloat16 format natively for better performances. - */ - public static final FloatDataLayout BFLOAT16 = new Bfloat16Layout(); - - /** - * Data layout for converting 16-bit half floats to/from short values. - * - *

Half floats are stored in memory accordingly to the IEEE-754 half-precision floating point - * specification, and are converted to/from 32-bit floats in the user space. - * - *

There is a potential loss of precision when converting a single float (32-bit) to a half - * float (16-bit). Absolute range of values above 0 for a half float is approximately - * [5.96 × 10-8, 6.55 × 104] and their decimal part is rounded up - * to a 10 bits mantissa. - * - *

In general, half float computation perform better on GPUs since, in general, CPUs do not - * support this format natively.

- */ - public static final FloatDataLayout FLOAT16 = new Float16Layout(); - - /** - * Data layout for converting booleans to/from byte values. - * - *

Since there is no Java NIO boolean buffer, this layout is particularly useful for mapping - * booleans values to standard byte buffers. The conversion between a boolean and a byte requires - * explicit type casting. - */ - public static final BooleanDataLayout BOOL = new BoolLayout(); - - /** - * Creates a data layout for converting strings to/from byte sequences. - * - *

This layout requires a {@code charset} in parameter to specify how the strings must be - * encoded/decoded as byte sequences. So a new layout instance is always returned. - * - * @param charset charset to use - * @return a new string layout - */ - public static DataLayout, String> ofStrings(Charset charset) { - return StringLayout.of(charset); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/DoubleDataLayout.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/DoubleDataLayout.java deleted file mode 100644 index efd1e461802..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/DoubleDataLayout.java +++ /dev/null @@ -1,65 +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.ndarray.buffer.layout; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.impl.buffer.adapter.DataBufferAdapterFactory; - -/** - * A {@link DataLayout} that converts data stored in a buffer to doubles. - * - * @param type of buffer this layout can be applied to - * @see DataLayout - */ -public interface DoubleDataLayout> extends DataLayout { - - @Override - default DoubleDataBuffer applyTo(S buffer) { - return DataBufferAdapterFactory.create(buffer, this); - } - - /** - * Writes a double into the buffer at the given index after converting it to the buffer type. - * - * @param buffer the buffer to write to - * @param value the double to convert and write - * @param index index in the buffer where the converted value should be written - * @see #writeObject(DataBuffer, Double, long) - */ - void writeDouble(S buffer, double value, long index); - - /** - * Reads {@code n = scale()} buffer values at the given index and return them as a double. - * - * @param buffer the buffer to read from - * @param index position of the buffer to read in the buffer - * @return the double value - * @see #readObject(DataBuffer, long) - */ - double readDouble(S buffer, long index); - - @Override - default void writeObject(S buffer, Double value, long index) { - writeDouble(buffer, value, index); - } - - @Override - default Double readObject(S buffer, long index) { - return readDouble(buffer, index); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/FloatDataLayout.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/FloatDataLayout.java deleted file mode 100644 index a57f525d69f..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/FloatDataLayout.java +++ /dev/null @@ -1,65 +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.ndarray.buffer.layout; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.impl.buffer.adapter.DataBufferAdapterFactory; - -/** - * A {@link DataLayout} that converts data stored in a buffer to floats. - * - * @param type of buffer this layout can be applied to - * @see DataLayout - */ -public interface FloatDataLayout> extends DataLayout { - - @Override - default FloatDataBuffer applyTo(S buffer) { - return DataBufferAdapterFactory.create(buffer, this); - } - - /** - * Writes a float into the buffer at the given index after converting it to the buffer type. - * - * @param buffer the buffer to write to - * @param value the float to convert and write - * @param index index in the buffer where the converted value should be written - * @see #writeObject(DataBuffer, Float, long) - */ - void writeFloat(S buffer, float value, long index); - - /** - * Reads {@code n = scale()} values from the buffer at the given index and return them as a float. - * - * @param buffer the buffer to read from - * @param index position of the buffer to read in the buffer - * @return the float value - * @see #readObject(DataBuffer, long) - */ - float readFloat(S buffer, long index); - - @Override - default void writeObject(S buffer, Float value, long index) { - writeFloat(buffer, value, index); - } - - @Override - default Float readObject(S buffer, long index) { - return readFloat(buffer, index); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/IntDataLayout.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/IntDataLayout.java deleted file mode 100644 index 718deac9b9f..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/IntDataLayout.java +++ /dev/null @@ -1,66 +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.ndarray.buffer.layout; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.impl.buffer.adapter.DataBufferAdapterFactory; - -/** - * A {@link DataLayout} that converts data stored in a buffer to ints. - * - * @param type of buffer this layout can be applied to - * @see DataLayout - */ -public interface IntDataLayout> extends DataLayout { - - @Override - default IntDataBuffer applyTo(S buffer) { - return DataBufferAdapterFactory.create(buffer, this); - } - - /** - * Writes a int into the buffer at the given index after converting it to the buffer type. - * - * @param buffer the buffer to write to - * @param value the int to convert and write - * @param index index in the buffer where the converted value should be written - * @see #writeObject(DataBuffer, Integer, long) - */ - void writeInt(S buffer, int value, long index); - - /** - * Reads {@code n = scale()} values from the buffer at the given index and return them as an int. - * - * @param buffer the buffer to read from - * @param index position of the buffer to read in the buffer - * @return the int value - * @see #readObject(DataBuffer, long) - */ - int readInt(S buffer, long index); - - @Override - default void writeObject(S buffer, Integer value, long index) { - writeInt(buffer, value, index); - } - - @Override - default Integer readObject(S buffer, long index) { - return readInt(buffer, index); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/LongDataLayout.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/LongDataLayout.java deleted file mode 100644 index f5c86ddd378..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/LongDataLayout.java +++ /dev/null @@ -1,65 +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.ndarray.buffer.layout; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.impl.buffer.adapter.DataBufferAdapterFactory; - -/** - * A {@link DataLayout} that converts data stored in a buffer to longs. - * - * @param type of buffer this layout can be applied to - * @see DataLayout - */ -public interface LongDataLayout> extends DataLayout { - - @Override - default LongDataBuffer applyTo(S buffer) { - return DataBufferAdapterFactory.create(buffer, this); - } - - /** - * Writes a long into the buffer at the given index after converting it to the buffer type. - * - * @param buffer the buffer to write to - * @param value the long to convert and write - * @param index index in the buffer where the converted value should be written - * @see #writeObject(DataBuffer, Long, long) - */ - void writeLong(S buffer, long value, long index); - - /** - * Reads {@code n = scale()} values from the buffer at the given index and return them as a long. - * - * @param buffer the buffer to read from - * @param index position of the buffer to read in the buffer - * @return the long value - * @see #readObject(DataBuffer, long) - */ - long readLong(S buffer, long index); - - @Override - default void writeObject(S buffer, Long value, long index) { - writeLong(buffer, value, index); - } - - @Override - default Long readObject(S buffer, long index) { - return readLong(buffer, index); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/ShortDataLayout.java b/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/ShortDataLayout.java deleted file mode 100644 index 89c1fd0dec4..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/buffer/layout/ShortDataLayout.java +++ /dev/null @@ -1,65 +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.ndarray.buffer.layout; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.impl.buffer.adapter.DataBufferAdapterFactory; - -/** - * A {@link DataLayout} that converts data stored in a buffer to shorts. - * - * @param type of buffer this layout can be applied to - * @see DataLayout - */ -public interface ShortDataLayout> extends DataLayout { - - @Override - default ShortDataBuffer applyTo(S buffer) { - return DataBufferAdapterFactory.create(buffer, this); - } - - /** - * Writes a short into the buffer at the given index after converting it to the buffer type. - * - * @param buffer the buffer to write to - * @param value the short to convert and write - * @param index index in the buffer where the converted value should be written - * @see #writeObject(DataBuffer, Short, long) - */ - void writeShort(S buffer, short value, long index); - - /** - * Reads {@code n = scale()} buffer values at the given index and return them as a short. - * - * @param buffer the buffer to read from - * @param index position of the value to read in the buffer - * @return the short value - * @see #readObject(DataBuffer, long) - */ - short readShort(S buffer, long index); - - @Override - default void writeObject(S buffer, Short value, long index) { - writeShort(buffer, value, index); - } - - @Override - default Short readObject(S buffer, long index) { - return readShort(buffer, index); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/AbstractNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/AbstractNdArray.java deleted file mode 100644 index 690dedc2042..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/AbstractNdArray.java +++ /dev/null @@ -1,92 +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.ndarray.impl; - -import java.util.Iterator; -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.NdArraySequence; -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -@SuppressWarnings("unchecked") -public abstract class AbstractNdArray> implements NdArray { - - public abstract U slice(long position, DimensionalSpace dimensions); - - public DimensionalSpace dimensions() { - return dimensions; - } - - @Override - public Shape shape() { - return dimensions.shape(); - } - - @Override - public NdArraySequence scalars() { - // negative if this array is a scalar, should be handled in `elements(dimIdx)` - return (NdArraySequence)elements(shape().numDimensions() - 1); - } - - @Override - public int hashCode() { - return slowHashCode(); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof NdArray)) { - return false; - } - return slowEquals((NdArray)obj); - } - - protected AbstractNdArray(DimensionalSpace dimensions) { - this.dimensions = dimensions; - } - - protected void slowCopyTo(NdArray array) { - scalars().forEachIndexed((coords, e) -> array.setObject(e.getObject(), coords)); - } - - protected int slowHashCode() { - final int prime = 31; - int result = 1; - for (NdArray scalar : scalars()) { - result = prime * result + scalar.getObject().hashCode(); - } - result = prime * result + shape().hashCode(); - return result; - } - - protected boolean slowEquals(NdArray array) { - if (!shape().equals(array.shape())) { // this guarantees also that we have the same number of scalar values - return false; - } - for (Iterator> thisIter = scalars().iterator(), otherIter = array.scalars().iterator(); thisIter.hasNext();) { - if (!thisIter.next().getObject().equals(otherIter.next().getObject())) { - return false; - } - } - return true; - } - - protected final DimensionalSpace dimensions; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/Validator.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/Validator.java deleted file mode 100644 index 285d09966de..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/Validator.java +++ /dev/null @@ -1,55 +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.ndarray.impl; - -import java.nio.BufferOverflowException; -import java.nio.BufferUnderflowException; -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.buffer.DataBuffer; - -public class Validator { - - public static void copyToNdArrayArgs(NdArray ndArray, NdArray otherNdArray) { - if (!ndArray.shape().equals(otherNdArray.shape())) { - throw new IllegalArgumentException("Can only copy to arrays of the same shape (" + - ndArray.shape() + " != " + otherNdArray.shape() + ")"); - } - } - - public static void readToBufferArgs(NdArray ndArray, DataBuffer dst) { - if (dst.size() < ndArray.size()) { - throw new BufferOverflowException(); - } - } - - public static void writeFromBufferArgs(NdArray ndArray, DataBuffer src) { - if (src.size() < ndArray.size()) { - throw new BufferUnderflowException(); - } - } - - private static void copyArrayArgs(int arrayLength, int arrayOffset) { - if (arrayOffset < 0) { - throw new IndexOutOfBoundsException("Offset must be non-negative"); - } - if (arrayOffset > arrayLength) { - throw new IndexOutOfBoundsException("Offset must be no larger than array length"); - } - } - - protected Validator() {} -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/AbstractDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/AbstractDataBuffer.java deleted file mode 100644 index e5103a2c17a..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/AbstractDataBuffer.java +++ /dev/null @@ -1,182 +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.ndarray.impl.buffer; - -import java.util.Arrays; -import java.util.HashMap; -import java.util.Map; -import java.util.Objects; -import org.tensorflow.ndarray.buffer.DataBuffer; - -public abstract class AbstractDataBuffer implements DataBuffer { - - @Override - public DataBuffer read(T[] dst, int offset, int length) { - Validator.readArgs(this, dst.length, offset, length); - for (int i = 0; i < length; ++i) { - dst[i + offset] = getObject(i); - } - return this; - } - - @Override - public DataBuffer write(T[] src, int offset, int length) { - Validator.writeArgs(this, src.length, offset, length); - for (int i = 0; i < length; ++i) { - setObject(src[i + offset], i); - } - return this; - } - - @Override - public DataBuffer copyTo(DataBuffer dst, long size) { - return slowCopyTo(dst, size); - } - - @Override - public int hashCode() { - // This hash code computation is generic to all types of data buffers and accurate but not optimized - // for performances, it needs to be improved if there is a present use case for such hash codes. - return slowHashCode(); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof DataBuffer)) { - return false; - } - return slowEquals((DataBuffer)obj); - } - - @SuppressWarnings("unchecked") - protected > U slowCopyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - for (long idx = 0L; idx < size; ++idx) { - dst.setObject(getObject(idx), idx); - } - return (U)this; - } - - protected int slowHashCode() { - final int prime = 31; - int result = 1; - - // First check from the first non-null element if we are dealing with a buffer of arrays - long idx = 0L; - for (; idx < size(); ++idx) { - T o = getObject(idx); - if (o != null) { - if (o.getClass().isArray()) { - result = prime * result + arrayHashCode(idx, o.getClass()); // compute hash codes based on array elements - return result; - } - result = prime * result + o.hashCode(); - break; // continue hash code computation without array type check - } - result = prime * result; - } - while (++idx < size()) { - result = prime * result + Objects.hashCode(getObject(idx)); - } - return result; - } - - protected boolean slowEquals(DataBuffer other) { - if (other.size() != size()) { - return false; - } - long idx = 0L; - for (; idx < size(); ++idx) { - Object thisObject = getObject(idx); - if (thisObject != null) { - if (thisObject.getClass().isArray()) { - return arrayEquals(idx, thisObject.getClass(), other); - } - if (!Objects.equals(other.getObject(idx), thisObject)) { - return false; - } - break; // continue equality comparison without array type check - } - if (other.getObject(idx) != null) { - return false; - } - } - while (++idx < size()) { - if (!Objects.equals(other.getObject(idx), getObject(idx))) { - return false; - } - } - return true; - } - - private int arrayHashCode(long startIdx, Class arrayClass) { - ArrayHashCoder hashCoder = ARRAY_HASH_CODERS.getOrDefault(arrayClass, DEFAULT_ARRAY_HASH_CODER); - final int prime = 31; - int result = 1; - for (long idx = startIdx; idx < size(); ++idx) { - result = prime * result + hashCoder.hashCode(this, idx); - } - return result; - } - - private boolean arrayEquals(long startIdx, Class arrayClass, DataBuffer other) { - ArrayComparator comparator = ARRAY_COMPARATORS.getOrDefault(arrayClass, DEFAULT_ARRAY_COMPARATOR); - for (long idx = startIdx; idx < size(); ++idx) { - if (!comparator.equals(this, other, idx)) { - return false; - } - } - return true; - } - - @FunctionalInterface - private static interface ArrayHashCoder { - int hashCode(DataBuffer buffer, long index); - } - private static final Map, ArrayHashCoder> ARRAY_HASH_CODERS = new HashMap<>(); - private static final ArrayHashCoder DEFAULT_ARRAY_HASH_CODER; - - @FunctionalInterface - private static interface ArrayComparator { - boolean equals(DataBuffer buffer, DataBuffer otherBuffer, long index); - } - private static final Map, ArrayComparator> ARRAY_COMPARATORS = new HashMap<>(); - private static final ArrayComparator DEFAULT_ARRAY_COMPARATOR; - - static { - ARRAY_HASH_CODERS.put(byte[].class, (b, idx) -> Arrays.hashCode((byte[])b.getObject(idx))); - ARRAY_HASH_CODERS.put(int[].class, (b, idx) -> Arrays.hashCode((int[])b.getObject(idx))); - ARRAY_HASH_CODERS.put(short[].class, (b, idx) -> Arrays.hashCode((short[])b.getObject(idx))); - ARRAY_HASH_CODERS.put(long[].class, (b, idx) -> Arrays.hashCode((long[])b.getObject(idx))); - ARRAY_HASH_CODERS.put(float[].class, (b, idx) -> Arrays.hashCode((float[])b.getObject(idx))); - ARRAY_HASH_CODERS.put(double[].class, (b, idx) -> Arrays.hashCode((double[])b.getObject(idx))); - ARRAY_HASH_CODERS.put(boolean[].class, (b, idx) -> Arrays.hashCode((boolean[])b.getObject(idx))); - DEFAULT_ARRAY_HASH_CODER = (b, idx) -> Arrays.deepHashCode((Object[])b.getObject(idx)); - - ARRAY_COMPARATORS.put(byte[].class, (b1, b2, idx) -> Arrays.equals((byte[])b1.getObject(idx), (byte[])b2.getObject(idx))); - ARRAY_COMPARATORS.put(int[].class, (b1, b2, idx) -> Arrays.equals((int[])b1.getObject(idx), (int[])b2.getObject(idx))); - ARRAY_COMPARATORS.put(short[].class, (b1, b2, idx) -> Arrays.equals((short[])b1.getObject(idx), (short[])b2.getObject(idx))); - ARRAY_COMPARATORS.put(long[].class, (b1, b2, idx) -> Arrays.equals((long[])b1.getObject(idx), (long[])b2.getObject(idx))); - ARRAY_COMPARATORS.put(float[].class, (b1, b2, idx) -> Arrays.equals((float[])b1.getObject(idx), (float[])b2.getObject(idx))); - ARRAY_COMPARATORS.put(double[].class, (b1, b2, idx) -> Arrays.equals((double[])b1.getObject(idx), (double[])b2.getObject(idx))); - ARRAY_COMPARATORS.put(boolean[].class, (b1, b2, idx) -> Arrays.equals((boolean[])b1.getObject(idx), (boolean[])b2.getObject(idx))); - DEFAULT_ARRAY_COMPARATOR = (b1, b2, idx) -> Arrays.deepEquals((Object[])b1.getObject(idx), (Object[])b2.getObject(idx)); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/AbstractDataBufferWindow.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/AbstractDataBufferWindow.java deleted file mode 100644 index 55d4fd56021..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/AbstractDataBufferWindow.java +++ /dev/null @@ -1,48 +0,0 @@ -package org.tensorflow.ndarray.impl.buffer; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBufferWindow; - -public abstract class AbstractDataBufferWindow> implements DataBufferWindow { - - @Override - public final long offset() { - return offset; - } - - @Override - public final long size() { - return windowBuffer.size(); - } - - @Override - public final DataBufferWindow slideTo(long index) { - if (index < 0 || index > maxOffset) { - throw new IndexOutOfBoundsException(); - } - offset(index); - offset = index; - return this; - } - - @Override - public final DataBufferWindow slide(long step) { - return slideTo(offset + step); - } - - @Override - public final B buffer() { - return windowBuffer; - } - - protected abstract void offset(long offset); - - protected AbstractDataBufferWindow(B windowBuffer, long bufferLimit) { - this.windowBuffer = windowBuffer; - maxOffset = bufferLimit - windowBuffer.size(); - } - - private final B windowBuffer; - private final long maxOffset; - private long offset = 0; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/Validator.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/Validator.java deleted file mode 100644 index 8f18e620b90..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/Validator.java +++ /dev/null @@ -1,132 +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.ndarray.impl.buffer; - -import java.nio.BufferOverflowException; -import java.nio.BufferUnderflowException; -import java.nio.ReadOnlyBufferException; -import org.tensorflow.ndarray.buffer.DataBuffer; - -public class Validator { - - public static void createArgs(long size, long maxSize) { - if (size < 0) { - throw new IllegalArgumentException("Size must be non-negative"); - } - if (size > maxSize) { - throw new IllegalArgumentException("Buffer size must be no greater than maximum size allowed (" + maxSize + ")"); - } - } - - public static void getArgs(DataBuffer buffer, long index) { - if (index < 0) { - throw new IndexOutOfBoundsException("Index must be non-negative"); - } - if (index >= buffer.size()) { - throw new IndexOutOfBoundsException("Index must be smaller than the buffer size"); - } - } - - public static void setArgs(DataBuffer buffer, long index) { - if (index < 0) { - throw new IndexOutOfBoundsException("Index must be non-negative"); - } - if (index >= buffer.size()) { - throw new IndexOutOfBoundsException("Index must be smaller than the buffer size"); - } - if (buffer.isReadOnly()) { - throw new ReadOnlyBufferException(); - } - } - - public static void copyToArgs(DataBuffer src, DataBuffer dst, long size) { - if (dst == src) { - throw new IllegalArgumentException("Source cannot be the same buffer as destination"); - } - if (size > dst.size()) { - throw new BufferOverflowException(); - } - if (size > src.size()) { - throw new BufferUnderflowException(); - } - if (dst.isReadOnly()) { - throw new ReadOnlyBufferException(); - } - } - - public static void readArgs(DataBuffer buffer, int arrayLength, int offset, int length) { - if (length > buffer.size()) { - throw new BufferUnderflowException(); - } - arrayArgs(arrayLength, offset, length); - } - - public static void writeArgs(DataBuffer buffer, int arrayLength, int offset, int length) { - if (length > buffer.size()) { - throw new BufferOverflowException(); - } - if (buffer.isReadOnly()) { - throw new ReadOnlyBufferException(); - } - arrayArgs(arrayLength, offset, length); - } - - public static void offsetArgs(DataBuffer buffer, long index) { - if (index < 0) { - throw new IllegalArgumentException("Index must be non-negative"); - } - if (index > buffer.size()) { - throw new IllegalArgumentException("Index must not exceed buffer size"); - } - } - - public static void narrowArgs(DataBuffer buffer, long size) { - if (size < 0) { - throw new IllegalArgumentException("Size must be non-negative"); - } - if (size > buffer.size()) { - throw new IllegalArgumentException("Cannot narrow a buffer of size " + buffer.size() + " to " + size); - } - } - - public static void sliceArgs(DataBuffer buffer, long index, long size) { - if (index < 0) { - throw new IllegalArgumentException("Index must be non-negative"); - } - if (size < 0) { - throw new IllegalArgumentException("Size must be non-negative"); - } - if (index + size > buffer.size()) { - throw new IllegalArgumentException("Buffer view must not exceed original buffer limits"); - } - } - - private static void arrayArgs(int arrayLength, int offset, int length) { - if (offset < 0) { - throw new IndexOutOfBoundsException("Offset must be non-negative"); - } - if (offset > arrayLength) { - throw new IndexOutOfBoundsException("Offset must be no larger than array length"); - } - if (length < 0) { - throw new IndexOutOfBoundsException("Length must be non-negative"); - } - if (length > arrayLength - offset) { - throw new IndexOutOfBoundsException("Length must be no larger than array length minus the offset"); - } - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/AbstractDataBufferAdapter.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/AbstractDataBufferAdapter.java deleted file mode 100644 index 3c9b6df1e93..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/AbstractDataBufferAdapter.java +++ /dev/null @@ -1,68 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.impl.buffer.AbstractDataBuffer; -import org.tensorflow.ndarray.buffer.layout.DataLayout; - -@SuppressWarnings("unchecked") -abstract class AbstractDataBufferAdapter, T, U extends DataBuffer> extends AbstractDataBuffer { - - @Override - public long size() { - return size; - } - - @Override - public boolean isReadOnly() { - return buffer.isReadOnly(); - } - - @Override - public T getObject(long index) { - Validator.getArgs(this, index); - return layout.readObject(buffer, index * layout.scale()); - } - - @Override - public U setObject(T value, long index) { - Validator.setArgs(this, index); - layout.writeObject(buffer, value, index * layout.scale()); - return (U)this; - } - - AbstractDataBufferAdapter(S buffer, DataLayout layout) { - this.buffer = buffer; - this.layout = layout; - size = buffer.size() / layout.scale(); - } - - DataLayout layout() { - return layout; - } - - S buffer() { - return buffer; - } - - private final S buffer; - private final DataLayout layout; - private final long size; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/BooleanDataBufferAdapter.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/BooleanDataBufferAdapter.java deleted file mode 100644 index 40217b57d6a..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/BooleanDataBufferAdapter.java +++ /dev/null @@ -1,116 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.layout.BooleanDataLayout; - -class BooleanDataBufferAdapter> extends AbstractDataBufferAdapter - implements BooleanDataBuffer { - - @Override - public boolean getBoolean(long index) { - Validator.getArgs(this, index); - return layout.readBoolean(buffer(), index * layout.scale()); - } - - @Override - public BooleanDataBuffer setBoolean(boolean value, long index) { - Validator.setArgs(this, index); - layout.writeBoolean(buffer(), value, index * layout.scale()); - return this; - } - - @Override - public BooleanDataBuffer read(boolean[] dst, int offset, int length) { - Validator.readArgs(this, dst.length, offset, length); - for (int i = 0, j = offset; i < length; ++i, ++j) { - dst[j] = layout.readBoolean(buffer(), i * layout.scale()); - } - return this; - } - - @Override - public BooleanDataBuffer write(boolean[] src, int offset, int length) { - Validator.writeArgs(this, src.length, offset, length); - for (int i = 0, j = offset; i < length; ++i, ++j) { - layout.writeBoolean(buffer(), src[j], i * layout.scale()); - } - return this; - } - - @Override - public BooleanDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - if (dst instanceof BooleanDataBuffer) { - BooleanDataBuffer booleanDst = (BooleanDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - booleanDst.setBoolean(getBoolean(idx), idx); - } - return this; - } - return slowCopyTo(dst, size); - } - - @Override - @SuppressWarnings("unchecked") - public BooleanDataBuffer offset(long index) { - return new BooleanDataBufferAdapter<>((S)buffer().offset(index * layout.scale()), layout); - } - - @Override - @SuppressWarnings("unchecked") - public BooleanDataBuffer narrow(long size) { - return new BooleanDataBufferAdapter<>((S)buffer().narrow(size * layout.scale()), layout); - } - - @Override - @SuppressWarnings("unchecked") - public BooleanDataBuffer slice(long index, long size) { - return new BooleanDataBufferAdapter<>((S)buffer().slice(index * layout.scale(), size * layout.scale()), layout); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof BooleanDataBuffer)) { - return super.equals(obj); - } - BooleanDataBuffer other = (BooleanDataBuffer)obj; - if (other.size() != size()) { - return false; - } - for (long idx = 0L; idx < size(); ++idx) { - if (other.getBoolean(idx) != getBoolean(idx)) { - return false; - } - } - return true; - } - - BooleanDataBufferAdapter(S buffer, BooleanDataLayout layout) { - super(buffer, layout); - this.layout = layout; - } - - private BooleanDataLayout layout; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/ByteDataBufferAdapter.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/ByteDataBufferAdapter.java deleted file mode 100644 index c120a3ba810..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/ByteDataBufferAdapter.java +++ /dev/null @@ -1,135 +0,0 @@ -package org.tensorflow.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.buffer.layout.ByteDataLayout; - -class ByteDataBufferAdapter> extends AbstractDataBufferAdapter - implements ByteDataBuffer { - - @Override - public byte getByte(long index) { - Validator.getArgs(this, index); - return layout.readByte(buffer(), index * layout.scale()); - } - - @Override - public ByteDataBuffer setByte(byte value, long index) { - Validator.setArgs(this, index); - layout.writeByte(buffer(), value, index * layout.scale()); - return this; - } - - @Override - public ByteDataBuffer read(byte[] dst, int offset, int length) { - Validator.readArgs(this, dst.length, offset, length); - for (int i = 0, j = offset; i < length; ++i, ++j) { - dst[j] = layout.readByte(buffer(), i * layout.scale()); - } - return this; - } - - @Override - public ByteDataBuffer write(byte[] src, int offset, int length) { - Validator.writeArgs(this, src.length, offset, length); - for (int i = 0, j = offset; i < length; ++i, ++j) { - layout.writeByte(buffer(), src[j], i * layout.scale()); - } - return this; - } - - @Override - public ByteDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - if (dst instanceof ByteDataBuffer) { - ByteDataBuffer byteDst = (ByteDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - byteDst.setByte(getByte(idx), idx); - } - return this; - } - return slowCopyTo(dst, size); - } - - @Override - public IntDataBuffer asInts() { - throw new IllegalStateException("Byte buffers with layout cannot be converted"); - } - - @Override - public ShortDataBuffer asShorts() { - throw new IllegalStateException("Byte buffers with layout cannot be converted"); - } - - @Override - public LongDataBuffer asLongs() { - throw new IllegalStateException("Byte buffers with layout cannot be converted"); - } - - @Override - public FloatDataBuffer asFloats() { - throw new IllegalStateException("Byte buffers with layout cannot be converted"); - } - - @Override - public DoubleDataBuffer asDoubles() { - throw new IllegalStateException("Byte buffers with layout cannot be converted"); - } - - @Override - public BooleanDataBuffer asBooleans() { - throw new IllegalStateException("Byte buffers with layout cannot be converted"); - } - - @Override - @SuppressWarnings("unchecked") - public ByteDataBuffer offset(long index) { - return new ByteDataBufferAdapter<>((S)buffer().offset(index * layout.scale()), layout); - } - - @Override - @SuppressWarnings("unchecked") - public ByteDataBuffer narrow(long size) { - return new ByteDataBufferAdapter<>((S)buffer().narrow(size * layout.scale()), layout); - } - - @Override - @SuppressWarnings("unchecked") - public ByteDataBuffer slice(long index, long size) { - return new ByteDataBufferAdapter<>((S)buffer().slice(index * layout.scale(), size * layout.scale()), layout); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof ByteDataBuffer)) { - return super.equals(obj); - } - ByteDataBuffer other = (ByteDataBuffer)obj; - if (other.size() != size()) { - return false; - } - for (long idx = 0L; idx < size(); ++idx) { - if (other.getByte(idx) != getByte(idx)) { - return false; - } - } - return true; - } - - ByteDataBufferAdapter(S buffer, ByteDataLayout layout) { - super(buffer, layout); - this.layout = layout; - } - - private ByteDataLayout layout; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/DataBufferAdapter.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/DataBufferAdapter.java deleted file mode 100644 index de20ab2cfd7..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/DataBufferAdapter.java +++ /dev/null @@ -1,47 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.layout.DataLayout; - -@SuppressWarnings("unchecked") -class DataBufferAdapter, T> extends AbstractDataBufferAdapter> { - - @Override - @SuppressWarnings("unchecked") - public DataBuffer offset(long index) { - return new DataBufferAdapter<>((S)buffer().offset(index * layout().scale()), layout()); - } - - @Override - @SuppressWarnings("unchecked") - public DataBuffer narrow(long size) { - return new DataBufferAdapter<>((S)buffer().narrow(size * layout().scale()), layout()); - } - - @Override - @SuppressWarnings("unchecked") - public DataBuffer slice(long index, long size) { - return new DataBufferAdapter<>((S)buffer().slice(index * layout().scale(), size * layout().scale()), layout()); - } - - DataBufferAdapter(S buffer, DataLayout layout) { - super(buffer, layout); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/DataBufferAdapterFactory.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/DataBufferAdapterFactory.java deleted file mode 100644 index 468051e1b46..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/DataBufferAdapterFactory.java +++ /dev/null @@ -1,142 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.buffer.layout.BooleanDataLayout; -import org.tensorflow.ndarray.buffer.layout.ByteDataLayout; -import org.tensorflow.ndarray.buffer.layout.DataLayout; -import org.tensorflow.ndarray.buffer.layout.DoubleDataLayout; -import org.tensorflow.ndarray.buffer.layout.FloatDataLayout; -import org.tensorflow.ndarray.buffer.layout.IntDataLayout; -import org.tensorflow.ndarray.buffer.layout.LongDataLayout; -import org.tensorflow.ndarray.buffer.layout.ShortDataLayout; - -/** - * Factory of data buffer adapters. - * - *

Data buffer adapters are used to apply a {@link DataLayout} to a buffer. Conceptually, they act - * as a proxy that intercept each I/O call and perform the required type conversions after/before - * delegating the task to the underlying buffer. - */ -public class DataBufferAdapterFactory { - - /** - * Creates an adapter that applies a byte data layout to the given buffer. - * - * @param buffer the delegate buffer - * @param layout layout to apply - * @param the type of the buffer - * @return buffer adapter - */ - public static > ByteDataBuffer create(S buffer, ByteDataLayout layout) { - return new ByteDataBufferAdapter<>(buffer, layout); - } - - /** - * Creates an adapter that applies a boolean data layout to the given buffer. - * - * @param buffer the delegate buffer - * @param layout layout to apply - * @param the type of the buffer - * @return buffer adapter - */ - public static > BooleanDataBuffer create(S buffer, BooleanDataLayout layout) { - return new BooleanDataBufferAdapter<>(buffer, layout); - } - - /** - * Creates an adapter that applies a double data layout to the given buffer. - * - * @param buffer the delegate buffer - * @param layout layout to apply - * @param the type of the buffer - * @return buffer adapter - */ - public static > DoubleDataBuffer create(S buffer, DoubleDataLayout layout) { - return new DoubleDataBufferAdapter<>(buffer, layout); - } - - /** - * Creates an adapter that applies a float data layout to the given buffer. - * - * @param buffer the delegate buffer - * @param layout layout to apply - * @param the type of the buffer - * @return buffer adapter - */ - public static > FloatDataBuffer create(S buffer, FloatDataLayout layout) { - return new FloatDataBufferAdapter<>(buffer, layout); - } - - /** - * Creates an adapter that applies a integer data layout to the given buffer. - * - * @param buffer the delegate buffer - * @param layout layout to apply - * @param the type of the buffer - * @return buffer adapter - */ - public static > IntDataBuffer create(S buffer, IntDataLayout layout) { - return new IntDataBufferAdapter<>(buffer, layout); - } - - /** - * Creates an adapter that applies a long data layout to the given buffer. - * - * @param buffer the delegate buffer - * @param layout layout to apply - * @param the type of the buffer - * @return buffer adapter - */ - public static > LongDataBuffer create(S buffer, LongDataLayout layout) { - return new LongDataBufferAdapter<>(buffer, layout); - } - - /** - * Creates an adapter that applies a short data layout to the given buffer. - * - * @param buffer the delegate buffer - * @param layout layout to apply - * @param the type of the buffer - * @return buffer adapter - */ - public static > ShortDataBuffer create(S buffer, ShortDataLayout layout) { - return new ShortDataBufferAdapter<>(buffer, layout); - } - - /** - * Creates an adapter that applies a data layout to the given buffer. - * - * @param buffer the delegate buffer - * @param layout layout to apply - * @param the type of the buffer - * @param the type of data returned by the layout - * @return buffer adapter - */ - public static , T> DataBuffer create(S buffer, DataLayout layout) { - return new DataBufferAdapter<>(buffer, layout); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/DoubleDataBufferAdapter.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/DoubleDataBufferAdapter.java deleted file mode 100644 index 253acbac269..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/DoubleDataBufferAdapter.java +++ /dev/null @@ -1,116 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.buffer.layout.DoubleDataLayout; - -class DoubleDataBufferAdapter> extends AbstractDataBufferAdapter - implements DoubleDataBuffer { - - @Override - public double getDouble(long index) { - Validator.getArgs(this, index); - return layout.readDouble(buffer(), index * layout.scale()); - } - - @Override - public DoubleDataBuffer setDouble(double value, long index) { - Validator.setArgs(this, index); - layout.writeDouble(buffer(), value, index * layout.scale()); - return this; - } - - @Override - public DoubleDataBuffer read(double[] dst, int offset, int length) { - Validator.readArgs(this, dst.length, offset, length); - for (int i = 0, j = offset; i < length; ++i, ++j) { - dst[j] = layout.readDouble(buffer(), i * layout.scale()); - } - return this; - } - - @Override - public DoubleDataBuffer write(double[] src, int offset, int length) { - Validator.writeArgs(this, src.length, offset, length); - for (int i = 0, j = offset; i < length; ++i, ++j) { - layout.writeDouble(buffer(), src[j], i * layout.scale()); - } - return this; - } - - @Override - public DoubleDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - if (dst instanceof DoubleDataBuffer) { - DoubleDataBuffer doubleDst = (DoubleDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - doubleDst.setDouble(getDouble(idx), idx); - } - return this; - } - return slowCopyTo(dst, size); - } - - @Override - @SuppressWarnings("unchecked") - public DoubleDataBuffer offset(long index) { - return new DoubleDataBufferAdapter<>((S)buffer().offset(index * layout.scale()), layout); - } - - @Override - @SuppressWarnings("unchecked") - public DoubleDataBuffer narrow(long size) { - return new DoubleDataBufferAdapter<>((S)buffer().narrow(size * layout.scale()), layout); - } - - @Override - @SuppressWarnings("unchecked") - public DoubleDataBuffer slice(long index, long size) { - return new DoubleDataBufferAdapter<>((S)buffer().slice(index * layout.scale(), size * layout.scale()), layout); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof DoubleDataBuffer)) { - return super.equals(obj); - } - DoubleDataBuffer other = (DoubleDataBuffer)obj; - if (other.size() != size()) { - return false; - } - for (long idx = 0L; idx < size(); ++idx) { - if (other.getDouble(idx) != getDouble(idx)) { - return false; - } - } - return true; - } - - DoubleDataBufferAdapter(S buffer, DoubleDataLayout layout) { - super(buffer, layout); - this.layout = layout; - } - - private DoubleDataLayout layout; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/FloatDataBufferAdapter.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/FloatDataBufferAdapter.java deleted file mode 100644 index 69928bf0ccb..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/FloatDataBufferAdapter.java +++ /dev/null @@ -1,116 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.buffer.layout.FloatDataLayout; - -class FloatDataBufferAdapter> extends AbstractDataBufferAdapter - implements FloatDataBuffer { - - @Override - public float getFloat(long index) { - Validator.getArgs(this, index); - return layout.readFloat(buffer(), index * layout.scale()); - } - - @Override - public FloatDataBuffer setFloat(float value, long index) { - Validator.setArgs(this, index); - layout.writeFloat(buffer(), value, index * layout.scale()); - return this; - } - - @Override - public FloatDataBuffer read(float[] dst, int offset, int length) { - Validator.readArgs(this, dst.length, offset, length); - for (int i = 0, j = offset; i < length; ++i, ++j) { - dst[j] = layout.readFloat(buffer(), i * layout.scale()); - } - return this; - } - - @Override - public FloatDataBuffer write(float[] src, int offset, int length) { - Validator.writeArgs(this, src.length, offset, length); - for (int i = 0, j = offset; i < length; ++i, ++j) { - layout.writeFloat(buffer(), src[j], i * layout.scale()); - } - return this; - } - - @Override - public FloatDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - if (dst instanceof FloatDataBuffer) { - FloatDataBuffer floatDst = (FloatDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - floatDst.setFloat(getFloat(idx), idx); - } - return this; - } - return slowCopyTo(dst, size); - } - - @Override - @SuppressWarnings("unchecked") - public FloatDataBuffer offset(long index) { - return new FloatDataBufferAdapter<>((S)buffer().offset(index * layout.scale()), layout); - } - - @Override - @SuppressWarnings("unchecked") - public FloatDataBuffer narrow(long size) { - return new FloatDataBufferAdapter<>((S)buffer().narrow(size * layout.scale()), layout); - } - - @Override - @SuppressWarnings("unchecked") - public FloatDataBuffer slice(long index, long size) { - return new FloatDataBufferAdapter<>((S)buffer().slice(index * layout.scale(), size * layout.scale()), layout); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof FloatDataBuffer)) { - return super.equals(obj); - } - FloatDataBuffer other = (FloatDataBuffer)obj; - if (other.size() != size()) { - return false; - } - for (long idx = 0L; idx < size(); ++idx) { - if (other.getFloat(idx) != getFloat(idx)) { - return false; - } - } - return true; - } - - FloatDataBufferAdapter(S buffer, FloatDataLayout layout) { - super(buffer, layout); - this.layout = layout; - } - - private FloatDataLayout layout; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/IntDataBufferAdapter.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/IntDataBufferAdapter.java deleted file mode 100644 index 052b63fe0f3..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/IntDataBufferAdapter.java +++ /dev/null @@ -1,116 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.buffer.layout.IntDataLayout; - -class IntDataBufferAdapter> extends AbstractDataBufferAdapter - implements IntDataBuffer { - - @Override - public int getInt(long index) { - Validator.getArgs(this, index); - return layout.readInt(buffer(), index * layout.scale()); - } - - @Override - public IntDataBuffer setInt(int value, long index) { - Validator.setArgs(this, index); - layout.writeInt(buffer(), value, index * layout.scale()); - return this; - } - - @Override - public IntDataBuffer read(int[] dst, int offset, int length) { - Validator.readArgs(this, dst.length, offset, length); - for (int i = 0, j = offset; i < length; ++i, ++j) { - dst[j] = layout.readInt(buffer(), i * layout.scale()); - } - return this; - } - - @Override - public IntDataBuffer write(int[] src, int offset, int length) { - Validator.writeArgs(this, src.length, offset, length); - for (int i = 0, j = offset; i < length; ++i, ++j) { - layout.writeInt(buffer(), src[j], i * layout.scale()); - } - return this; - } - - @Override - public IntDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - if (dst instanceof IntDataBuffer) { - IntDataBuffer intDst = (IntDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - intDst.setInt(getInt(idx), idx); - } - return this; - } - return slowCopyTo(dst, size); - } - - @Override - @SuppressWarnings("unchecked") - public IntDataBuffer offset(long index) { - return new IntDataBufferAdapter<>((S)buffer().offset(index * layout.scale()), layout); - } - - @Override - @SuppressWarnings("unchecked") - public IntDataBuffer narrow(long size) { - return new IntDataBufferAdapter<>((S)buffer().narrow(size * layout.scale()), layout); - } - - @Override - @SuppressWarnings("unchecked") - public IntDataBuffer slice(long index, long size) { - return new IntDataBufferAdapter<>((S)buffer().slice(index * layout.scale(), size * layout.scale()), layout); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof IntDataBuffer)) { - return super.equals(obj); - } - IntDataBuffer other = (IntDataBuffer)obj; - if (other.size() != size()) { - return false; - } - for (long idx = 0L; idx < size(); ++idx) { - if (other.getInt(idx) != getInt(idx)) { - return false; - } - } - return true; - } - - IntDataBufferAdapter(S buffer, IntDataLayout layout) { - super(buffer, layout); - this.layout = layout; - } - - private IntDataLayout layout; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/LongDataBufferAdapter.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/LongDataBufferAdapter.java deleted file mode 100644 index aea154d4b9f..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/LongDataBufferAdapter.java +++ /dev/null @@ -1,116 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.buffer.layout.LongDataLayout; - -class LongDataBufferAdapter> extends AbstractDataBufferAdapter - implements LongDataBuffer { - - @Override - public long getLong(long index) { - Validator.getArgs(this, index); - return layout.readLong(buffer(), index * layout.scale()); - } - - @Override - public LongDataBuffer setLong(long value, long index) { - Validator.setArgs(this, index); - layout.writeLong(buffer(), value, index * layout.scale()); - return this; - } - - @Override - public LongDataBuffer read(long[] dst, int offset, int length) { - Validator.readArgs(this, dst.length, offset, length); - for (int i = 0, j = offset; i < length; ++i, ++j) { - dst[j] = layout.readLong(buffer(), i * layout.scale()); - } - return this; - } - - @Override - public LongDataBuffer write(long[] src, int offset, int length) { - Validator.writeArgs(this, src.length, offset, length); - for (int i = 0, j = offset; i < length; ++i, ++j) { - layout.writeLong(buffer(), src[j], i * layout.scale()); - } - return this; - } - - @Override - public LongDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - if (dst instanceof LongDataBuffer) { - LongDataBuffer longDst = (LongDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - longDst.setLong(getLong(idx), idx); - } - return this; - } - return slowCopyTo(dst, size); - } - - @Override - @SuppressWarnings("unchecked") - public LongDataBuffer offset(long index) { - return new LongDataBufferAdapter<>((S)buffer().offset(index * layout.scale()), layout); - } - - @Override - @SuppressWarnings("unchecked") - public LongDataBuffer narrow(long size) { - return new LongDataBufferAdapter<>((S)buffer().narrow(size * layout.scale()), layout); - } - - @Override - @SuppressWarnings("unchecked") - public LongDataBuffer slice(long index, long size) { - return new LongDataBufferAdapter<>((S)buffer().slice(index * layout.scale(), size * layout.scale()), layout); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof LongDataBuffer)) { - return super.equals(obj); - } - LongDataBuffer other = (LongDataBuffer)obj; - if (other.size() != size()) { - return false; - } - for (long idx = 0L; idx < size(); ++idx) { - if (other.getLong(idx) != getLong(idx)) { - return false; - } - } - return true; - } - - LongDataBufferAdapter(S buffer, LongDataLayout layout) { - super(buffer, layout); - this.layout = layout; - } - - private LongDataLayout layout; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/ShortDataBufferAdapter.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/ShortDataBufferAdapter.java deleted file mode 100644 index 6b6b1bb24b7..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/adapter/ShortDataBufferAdapter.java +++ /dev/null @@ -1,116 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.buffer.layout.ShortDataLayout; - -class ShortDataBufferAdapter> extends AbstractDataBufferAdapter - implements ShortDataBuffer { - - @Override - public short getShort(long index) { - Validator.getArgs(this, index); - return layout.readShort(buffer(), index * layout.scale()); - } - - @Override - public ShortDataBuffer setShort(short value, long index) { - Validator.setArgs(this, index); - layout.writeShort(buffer(), value, index * layout.scale()); - return this; - } - - @Override - public ShortDataBuffer read(short[] dst, int offset, int length) { - Validator.readArgs(this, dst.length, offset, length); - for (int i = 0, j = offset; i < length; ++i, ++j) { - dst[j] = layout.readShort(buffer(), i * layout.scale()); - } - return this; - } - - @Override - public ShortDataBuffer write(short[] src, int offset, int length) { - Validator.writeArgs(this, src.length, offset, length); - for (int i = 0, j = offset; i < length; ++i, ++j) { - layout.writeShort(buffer(), src[j], i * layout.scale()); - } - return this; - } - - @Override - public ShortDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - if (dst instanceof ShortDataBuffer) { - ShortDataBuffer shortDst = (ShortDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - shortDst.setShort(getShort(idx), idx); - } - return this; - } - return slowCopyTo(dst, size); - } - - @Override - @SuppressWarnings("unchecked") - public ShortDataBuffer offset(long index) { - return new ShortDataBufferAdapter<>((S)buffer().offset(index * layout.scale()), layout); - } - - @Override - @SuppressWarnings("unchecked") - public ShortDataBuffer narrow(long size) { - return new ShortDataBufferAdapter<>((S)buffer().narrow(size * layout.scale()), layout); - } - - @Override - @SuppressWarnings("unchecked") - public ShortDataBuffer slice(long index, long size) { - return new ShortDataBufferAdapter<>((S)buffer().slice(index * layout.scale(), size * layout.scale()), layout); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof ShortDataBuffer)) { - return super.equals(obj); - } - ShortDataBuffer other = (ShortDataBuffer)obj; - if (other.size() != size()) { - return false; - } - for (long idx = 0L; idx < size(); ++idx) { - if (other.getShort(idx) != getShort(idx)) { - return false; - } - } - return true; - } - - ShortDataBufferAdapter(S buffer, ShortDataLayout layout) { - super(buffer, layout); - this.layout = layout; - } - - private ShortDataLayout layout; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/layout/Bfloat16Layout.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/layout/Bfloat16Layout.java deleted file mode 100644 index 3f8171088cb..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/layout/Bfloat16Layout.java +++ /dev/null @@ -1,54 +0,0 @@ -/* - * 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.ndarray.impl.buffer.layout; - -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.buffer.layout.FloatDataLayout; - -/** - * Data layout that converts 32-bit floats from/to 16-bit, truncating their mantissa to 7 bits but - * preserving the 8-bit exponent with the same bias. - */ -public final class Bfloat16Layout implements FloatDataLayout { - - @Override - public void writeFloat(ShortDataBuffer buffer, float value, long index) { - buffer.setShort(float32to16(value), index); - } - - @Override - public float readFloat(ShortDataBuffer buffer, long index) { - return float16to32(buffer.getShort(index)); - } - - // - // FLOAT 32-bit to/from BFLOAT 16-bit conversions - // - // We simply shift the value from 32-bit to 16-bit and vice-versa. NaN special case is ignored. - // - - // VisibleForTesting - static short float32to16(float f32) { - return (short)(Float.floatToIntBits(f32) >>> 16); - } - - // Visible for testing - static float float16to32(short i16) { - return Float.intBitsToFloat((int)i16 << 16); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/layout/BoolLayout.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/layout/BoolLayout.java deleted file mode 100644 index 0358d60d662..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/layout/BoolLayout.java +++ /dev/null @@ -1,47 +0,0 @@ -/* - * 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.ndarray.impl.buffer.layout; - -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.layout.BooleanDataLayout; - -/** - * Data layout that converts booleans from/to bytes. - */ -public final class BoolLayout implements BooleanDataLayout { - - @Override - public void writeBoolean(ByteDataBuffer buffer, boolean value, long index) { - buffer.setByte(booleanToByte(value), index); - } - - @Override - public boolean readBoolean(ByteDataBuffer buffer, long index) { - return byteToBoolean(buffer.getByte(index)); - } - - // Visible for testing - static byte booleanToByte(boolean b) { - return (byte)(b ? 0x1 : 0x0); - } - - // Visible for testing - static boolean byteToBoolean(byte b) { - return b != 0x0; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/layout/Float16Layout.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/layout/Float16Layout.java deleted file mode 100644 index b19744bbd13..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/layout/Float16Layout.java +++ /dev/null @@ -1,119 +0,0 @@ -/* - * 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.ndarray.impl.buffer.layout; - -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.buffer.layout.FloatDataLayout; - -/** - * Data layout that converts 32-bit floats from/to 16-bit, accordingly to the IEEE-754 half-precision - * floating point specification. - */ -public final class Float16Layout implements FloatDataLayout { - - @Override - public void writeFloat(ShortDataBuffer buffer, float value, long index) { - buffer.setShort(float32to16(value), index); - } - - @Override - public float readFloat(ShortDataBuffer buffer, long index) { - return float16to32(buffer.getShort(index)); - } - - // - // FLOAT 32-bit to/from 16-bit conversions - // - // The following conversion algorithms are issued from the C++ implementation found in the - // Eigen library used by TensorFlow native library. - // See https://eigen.tuxfamily.org/dox-devel/Half_8h_source.html for more details. - // - - // VisibleForTesting - static short float32to16(float f32) { - int i16; - int i32 = Float.floatToIntBits(f32); - short sign16 = (short) ((i32 >>> 16) & 0x8000); - i32 &= 0x7FFFFFFF; // remove sign - - if (i32 >= (E32BIAS + E16MAX + 1) << E32SHIFT) { - // float32 value is higher than float16 max value (max16 -> 2^15 * 2 -> 2^16) - // - if float32 value is higher than infinite (i.e. s32 > 0), then it is NaN and should also - // be NaN in float16 (0x7e00) - // - else, float16 value is forced to infinite (0x7c00) - i16 = i32 > E32MASK ? 0x7E00 : 0x7C00; - - } else if (i32 < (E32BIAS + E16MIN) << E32SHIFT){ - // float32 abs value is smaller than float16 min abs value (min16 = 2^-14), could also be 0 - // - apply magic number to align significand 10 bits at the bottom on the float and subtract bias - i16 = Float.floatToIntBits(Float.intBitsToFloat(i32) + MAGIC_32_16_FLOAT) - MAGIC_32_16; - - } else { - // float32 value can be rounded up to a normalized float16 value (i.e. exp32 = [113(-14), 142(15)]) - // - rebase exponent to float16 - // - round up significand to the 13nd bit if s16 is even, on the 12nd bit if it is odd - int round = 0xFFF + ((i32 >>> 13) & 0x1); - i16 = (i32 + ((E16BIAS - E32BIAS) << E32SHIFT) + round) >>> 13; - } - return (short)(i16 | sign16); - } - - // Visible for testing - static float float16to32(short i16) { - int i32 = (i16 & 0x7FFF) << (S32BITS - S16BITS); // remove sign and align in float32 - i32 += (E32BIAS - E16BIAS) << E32SHIFT; // rebase exponent to float32 - - // Handle float16 exponent special cases - switch (i16 & E16MASK) { - case E16MASK: - // float16 value is infinite or NaN - // - adjust float32 exponent one more time - i32 += (E32BIAS - E16BIAS) << E32SHIFT; - break; - case 0x0: - // float16 value is zero or subnormal - // - adjust float32 exponent - // - renormalize using magic number - i32 = Float.floatToIntBits(Float.intBitsToFloat(i32 + (1 << E32SHIFT)) - MAGIC_16_32_FLOAT); - break; - default: - break; - } - return Float.intBitsToFloat(i32 | ((i16 & 0x8000) << 16)); // reapply sign - } - - // float32 format - private static final int E32SHIFT = 23; // position of the exponent in float32 - private static final int E32MASK = 0xFF << E32SHIFT; // mask for float32 exponent (== Infinity) - private static final int E32BIAS = 127; // exponent bias for float32 - private static final int S32BITS = 23; // number of bits in float32 significand - - // float16 format - private static final int E16SHIFT = 10; // position of the exponent in float16 - private static final int E16MASK = 0x1F << E16SHIFT; // mask for float16 exponent (== Infinity) - private static final int E16BIAS = 15; // exponent bias for float16 - private static final int E16MAX = 15; // max value for float16 exponent - private static final int E16MIN = -14; // min value for float16 exponent - private static final int S16BITS = 10; // number of bits in float16 significand - - // magic numbers used when converting denormalized values - private static final int MAGIC_32_16 = ((E32BIAS - E16BIAS) + (S32BITS - S16BITS) + 1) << E32SHIFT; - private static final float MAGIC_32_16_FLOAT = Float.intBitsToFloat(MAGIC_32_16); - private static final int MAGIC_16_32 = (E32BIAS - E16BIAS + 1) << E32SHIFT; - private static final float MAGIC_16_32_FLOAT = Float.intBitsToFloat(MAGIC_16_32); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/layout/StringLayout.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/layout/StringLayout.java deleted file mode 100644 index 51576c0100b..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/layout/StringLayout.java +++ /dev/null @@ -1,48 +0,0 @@ -/* - * 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.ndarray.impl.buffer.layout; - -import java.nio.charset.Charset; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.layout.DataLayout; - -/** - * Data layout that converts a String to/from a sequence of bytes applying a given charset. - */ -public final class StringLayout implements DataLayout, String> { - - public static StringLayout of(Charset charset) { - return new StringLayout(charset); - } - - @Override - public void writeObject(DataBuffer buffer, String value, long index) { - buffer.setObject(value.getBytes(charset), index); - } - - @Override - public String readObject(DataBuffer buffer, long index) { - return new String(buffer.getObject(index), charset); - } - - private StringLayout(Charset charset) { - this.charset = charset; - } - - private final Charset charset; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/misc/ArrayDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/misc/ArrayDataBuffer.java deleted file mode 100644 index 676e291357a..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/misc/ArrayDataBuffer.java +++ /dev/null @@ -1,126 +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.ndarray.impl.buffer.misc; - -import java.util.Arrays; -import org.tensorflow.ndarray.impl.buffer.AbstractDataBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; - -class ArrayDataBuffer extends AbstractDataBuffer { - - @Override - public long size() { - return length; - } - - @Override - public boolean isReadOnly() { - return readOnly; - } - - @Override - public T getObject(long index) { - Validator.getArgs(this, index); - return values[(int)index + offset]; - } - - @Override - public DataBuffer setObject(T value, long index) { - Validator.setArgs(this, index); - values[(int)index + offset] = value; - return this; - } - - @Override - public DataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor>() { - - @Override - public DataBuffer visit(Object[] array, int arrayOffset, int arrayLength) { - System.arraycopy(values, offset, array, arrayOffset, (int)size); - return ArrayDataBuffer.this; - } - - @Override - public DataBuffer fallback() { - for (int idx = 0; idx < size; ++idx) { - dst.setObject(values[idx + offset], idx); - } - return ArrayDataBuffer.this; - } - }); - } - - @Override - public DataBuffer slice(long index, long size) { - Validator.sliceArgs(this, index, size); - return new ArrayDataBuffer<>(values, readOnly, offset + (int)index, (int)size); - } - - @Override - public R accept(DataStorageVisitor visitor) { - return visitor.visit(values, offset, length); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof DataBuffer)) { - return false; - } - DataBuffer other = (DataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(Object[] array, int arrayOffset, int arrayLength) { - if (offset == 0 && values.length == length && arrayOffset == 0 && array.length == arrayLength) { - return Arrays.deepEquals(array, values); - } - return slowEquals(other); - } - - @Override - public Boolean fallback() { - return slowEquals(other); - } - }); - } - - ArrayDataBuffer(T[] values, boolean readOnly) { - this(values, readOnly, 0, values.length); - } - - private ArrayDataBuffer(T[] values, boolean readOnly, int offset, int length) { - this.values = values; - this.readOnly = readOnly; - this.offset = offset; - this.length = length; - } - - private final T[] values; - private final boolean readOnly; - private final int offset; - private final int length; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/misc/BitSetDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/misc/BitSetDataBuffer.java deleted file mode 100644 index 5b5ec15294b..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/misc/BitSetDataBuffer.java +++ /dev/null @@ -1,183 +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.ndarray.impl.buffer.misc; - -import java.util.BitSet; -import org.tensorflow.ndarray.impl.buffer.AbstractDataBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; - -class BitSetDataBuffer extends AbstractDataBuffer implements BooleanDataBuffer { - - @Override - public long size() { - return numBits; - } - - @Override - public boolean isReadOnly() { - return readOnly; - } - - @Override - public boolean getBoolean(long index) { - Validator.getArgs(this, index); - return bitSet.get((int)index + offset); - } - - @Override - public BooleanDataBuffer setBoolean(boolean value, long index) { - Validator.setArgs(this, index); - bitSet.set((int)index + offset, value); - return this; - } - - @Override - public BooleanDataBuffer read(boolean[] dst, int offset, int length) { - Validator.readArgs(this, dst.length, offset, length); - for (int i = this.offset, j = offset; i < this.offset + length; ++i, ++j) { - dst[j] = bitSet.get(i); - } - return this; - } - - @Override - public BooleanDataBuffer write(boolean[] src, int offset, int length) { - Validator.readArgs(this, src.length, offset, length); - for (int i = this.offset, j = offset; i < this.offset + length; ++i, ++j) { - bitSet.set(i, src[j]); - } - return this; - } - - @Override - public BooleanDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public BooleanDataBuffer visit(boolean[] array, int arrayOffset, int arrayLength) { - for (int idx = 0; idx < size; ++idx) { - array[idx + arrayOffset] = bitSet.get(idx + offset); - } - return BitSetDataBuffer.this; - } - - @Override - public BooleanDataBuffer visit(BitSet dstBitSet, int dstOffset, long numBits) { - for (int idx = 0; idx < size; ++idx) { - dstBitSet.set(idx + dstOffset, bitSet.get(idx + offset)); - } - return BitSetDataBuffer.this; - } - - @Override - public BooleanDataBuffer fallback() { - if (dst instanceof BooleanDataBuffer) { - BooleanDataBuffer booleanDst = (BooleanDataBuffer)dst; - for (int idx = 0; idx < size; ++idx) { - booleanDst.setBoolean(bitSet.get(idx + offset), idx); - } - } else { - for (int idx = 0; idx < size; ++idx) { - dst.setObject(bitSet.get(idx + offset), idx); - } - } - return BitSetDataBuffer.this; - } - }); - } - - @Override - public BooleanDataBuffer slice(long index, long size) { - Validator.sliceArgs(this, index, size); - return new BitSetDataBuffer(bitSet, size, readOnly, offset + (int)index); - } - - @Override - public R accept(DataStorageVisitor visitor) { - return visitor.visit(bitSet, offset, numBits); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof BooleanDataBuffer)) { - return super.equals(obj); - } - BooleanDataBuffer other = (BooleanDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(boolean[] array, int arrayOffset, int length) { - for (int idx = 0; idx < size(); ++idx) { - if (array[idx + arrayOffset] != bitSet.get(idx + offset)) { - return false; - } - } - return true; - } - - @Override - public Boolean visit(BitSet otherBitSet, int otherOffset, long otherNumBits) { - if (offset == 0 && otherOffset == 0 && numBits == otherNumBits) { - return bitSet.equals(otherBitSet); - } - for (int idx = 0; idx < size(); ++idx) { - if (otherBitSet.get(idx + otherOffset) != bitSet.get(idx + offset)) { - return false; - } - } - return true; - } - - @Override - public Boolean fallback() { - for (int idx = 0; idx < size(); ++idx) { - if (other.getBoolean(idx) != bitSet.get(idx + offset)) { - return false; - } - } - return true; - } - }); - } - - BitSetDataBuffer(BitSet bitSet, long numBits, boolean readOnly) { - this(bitSet, numBits, readOnly, 0); - } - - private BitSetDataBuffer(BitSet bitSet, long numBits, boolean readOnly, int offset) { - this.bitSet = bitSet; - this.numBits = numBits; - this.readOnly = readOnly; - this.offset = offset; - } - - private final BitSet bitSet; - private final long numBits; - private final boolean readOnly; - private final int offset; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/misc/BooleanArrayDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/misc/BooleanArrayDataBuffer.java deleted file mode 100644 index f8d033519ec..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/misc/BooleanArrayDataBuffer.java +++ /dev/null @@ -1,176 +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.ndarray.impl.buffer.misc; - -import java.util.Arrays; -import java.util.BitSet; -import org.tensorflow.ndarray.impl.buffer.AbstractDataBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; - -class BooleanArrayDataBuffer extends AbstractDataBuffer implements - BooleanDataBuffer { - - @Override - public long size() { - return length; - } - - @Override - public boolean isReadOnly() { - return readOnly; - } - - @Override - public boolean getBoolean(long index) { - Validator.getArgs(this, index); - return values[(int)index + offset]; - } - - @Override - public BooleanDataBuffer setBoolean(boolean value, long index) { - Validator.setArgs(this, index); - values[(int)index + offset] = value; - return this; - } - - @Override - public BooleanDataBuffer read(boolean[] dst, int offset, int length) { - System.arraycopy(values, this.offset, dst, offset, length); - return this; - } - - @Override - public BooleanDataBuffer write(boolean[] src, int offset, int length) { - System.arraycopy(src, offset, values, this.offset, length); - return null; - } - - @Override - public BooleanDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public BooleanDataBuffer visit(boolean[] array, int arrayOffset, int arrayLength) { - System.arraycopy(values, offset, array, arrayOffset, (int)size); - return BooleanArrayDataBuffer.this; - } - - @Override - public BooleanDataBuffer visit(BitSet bitSet, int bitSetOffset, long numBits) { - for (int idx = 0; idx < size; ++idx) { - bitSet.set(idx + bitSetOffset, values[idx + offset]); - } - return BooleanArrayDataBuffer.this; - } - - @Override - public BooleanDataBuffer fallback() { - if (dst instanceof BooleanDataBuffer) { - BooleanDataBuffer booleanDst = (BooleanDataBuffer)dst; - for (int idx = 0; idx < size; ++idx) { - booleanDst.setBoolean(values[idx + offset], idx); - } - } else { - for (int idx = 0; idx < size; ++idx) { - dst.setObject(values[idx + offset], idx); - } - } - return BooleanArrayDataBuffer.this; - } - }); - } - - @Override - public BooleanDataBuffer slice(long index, long size) { - Validator.sliceArgs(this, index, size); - return new BooleanArrayDataBuffer(values, readOnly, offset + (int)index, (int)size); - } - - @Override - public R accept(DataStorageVisitor visitor) { - return visitor.visit(values, offset, length); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof BooleanDataBuffer)) { - return super.equals(obj); - } - BooleanDataBuffer other = (BooleanDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(boolean[] array, int arrayOffset, int arrayLength) { - if (offset == 0 && values.length == length && arrayOffset == 0 && array.length == arrayLength) { - return Arrays.equals(array, values); - } - for (int idx = 0; idx < size(); ++idx) { - if (array[idx + arrayOffset] != values[idx + offset]) { - return false; - } - } - return true; - } - - @Override - public Boolean visit(BitSet bitSet, int bitSetOffset, long numBits) { - for (int idx = 0; idx < size(); ++idx) { - if (bitSet.get(idx + bitSetOffset) != values[idx + offset]) { - return false; - } - } - return true; - } - - @Override - public Boolean fallback() { - for (int idx = 0; idx < size(); ++idx) { - if (other.getBoolean(idx) != values[idx + offset]) { - return false; - } - } - return true; - } - }); - } - - BooleanArrayDataBuffer(boolean[] values, boolean readOnly) { - this(values, readOnly, 0, values.length); - } - - private BooleanArrayDataBuffer(boolean[] values, boolean readOnly, int offset, int length) { - this.values = values; - this.readOnly = readOnly; - this.offset = offset; - this.length = length; - } - - private final boolean[] values; - private final boolean readOnly; - private final int offset; - private final int length; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/misc/MiscDataBufferFactory.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/misc/MiscDataBufferFactory.java deleted file mode 100644 index 84cfce6bc66..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/misc/MiscDataBufferFactory.java +++ /dev/null @@ -1,40 +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.ndarray.impl.buffer.misc; - -import java.util.BitSet; -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; - -/** - * Factory of miscellaneous data buffers - */ -public class MiscDataBufferFactory { - - public static BooleanDataBuffer create(BitSet bitSet, long numBits, boolean readOnly) { - return new BitSetDataBuffer(bitSet, numBits, readOnly); - } - - public static BooleanDataBuffer create(boolean[] array, boolean readOnly) { - return new BooleanArrayDataBuffer(array, readOnly); - } - - public static DataBuffer create(T[] array, boolean readOnly) { - return new ArrayDataBuffer<>(array, readOnly); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/AbstractNioDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/AbstractNioDataBuffer.java deleted file mode 100644 index 82bc981ad46..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/AbstractNioDataBuffer.java +++ /dev/null @@ -1,41 +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.ndarray.impl.buffer.nio; - -import java.nio.Buffer; -import org.tensorflow.ndarray.impl.buffer.AbstractDataBuffer; - -/** - * Base class for all JDK-based data buffers. - * - * @param type of elements (or values) stored in this buffer - */ -abstract class AbstractNioDataBuffer extends AbstractDataBuffer { - - @Override - public long size() { - return buf().capacity(); - } - - @Override - public boolean isReadOnly() { - return buf().isReadOnly(); - } - - abstract Buffer buf(); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/ByteNioDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/ByteNioDataBuffer.java deleted file mode 100644 index 5ede97cef78..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/ByteNioDataBuffer.java +++ /dev/null @@ -1,185 +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.ndarray.impl.buffer.nio; - -import java.nio.ByteBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.impl.buffer.adapter.DataBufferAdapterFactory; -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.buffer.layout.DataLayouts; - -/** - * A buffer of bytes using a JDK {@link ByteBuffer} for storage. - */ -final class ByteNioDataBuffer extends AbstractNioDataBuffer - implements ByteDataBuffer { - - @Override - public byte getByte(long index) { - return buf.get((int)index); - } - - @Override - public ByteDataBuffer setByte(byte value, long index) { - buf.put((int)index, value); - return this; - } - - @Override - public ByteDataBuffer read(byte[] dst, int offset, int length) { - buf.duplicate().get(dst, offset, length); - return this; - } - - @Override - public ByteDataBuffer write(byte[] src, int offset, int length) { - buf.duplicate().put(src, offset, length); - return this; - } - - @Override - public ByteDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public ByteDataBuffer visit(ByteBuffer buffer) { - buffer.duplicate().put((ByteBuffer)buf.duplicate().limit((int)size)); - return ByteNioDataBuffer.this; - } - - @Override - public ByteDataBuffer fallback() { - if (dst instanceof ByteDataBuffer) { - ByteDataBuffer byteDst = (ByteDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - byteDst.setByte(getByte(idx), idx); - } - return ByteNioDataBuffer.this; - } - return slowCopyTo(dst, size); - } - }); - } - - @Override - public IntDataBuffer asInts() { - return new IntNioDataBuffer(buf.asIntBuffer()); - } - - @Override - public ShortDataBuffer asShorts() { - return new ShortNioDataBuffer(buf.asShortBuffer()); - } - - @Override - public LongDataBuffer asLongs() { - return new LongNioDataBuffer(buf.asLongBuffer()); - } - - @Override - public FloatDataBuffer asFloats() { - return new FloatNioDataBuffer(buf.asFloatBuffer()); - } - - @Override - public DoubleDataBuffer asDoubles() { - return new DoubleNioDataBuffer(buf.asDoubleBuffer()); - } - - @Override - public BooleanDataBuffer asBooleans() { - return DataBufferAdapterFactory.create(this, DataLayouts.BOOL); - } - - @Override - public ByteDataBuffer offset(long index) { - Validator.offsetArgs(this, index); - return new ByteNioDataBuffer(((ByteBuffer)buf.duplicate().position((int)index)).slice()); - } - - @Override - public ByteDataBuffer narrow(long size) { - Validator.narrowArgs(this, size); - return new ByteNioDataBuffer(((ByteBuffer)buf.duplicate().limit((int)size)).slice()); - } - - @Override - public ByteDataBuffer slice(long index, long size) { - Validator.sliceArgs(this, index, size); - ByteBuffer sliceBuf = buf.duplicate(); - sliceBuf.position((int)index); - sliceBuf.limit((int)index + (int)size); - return new ByteNioDataBuffer(sliceBuf.slice()); - } - - @Override - public R accept(DataStorageVisitor visitor) { - return visitor.visit(buf); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof ByteDataBuffer)) { - return super.equals(obj); - } - ByteDataBuffer other = (ByteDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(ByteBuffer buffer) { - return buf.equals(buffer); - } - - @Override - public Boolean fallback() { - for (int idx = 0; idx < size(); ++idx) { - if (other.getByte(idx) != getByte(idx)) { - return false; - } - } - return true; - } - }); - } - - @Override - ByteBuffer buf() { - return buf; - } - - ByteNioDataBuffer(ByteBuffer buf) { - this.buf = buf; - } - - private ByteBuffer buf; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/DoubleNioDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/DoubleNioDataBuffer.java deleted file mode 100644 index bddc5db1e3f..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/DoubleNioDataBuffer.java +++ /dev/null @@ -1,147 +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.ndarray.impl.buffer.nio; - -import java.nio.DoubleBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; - -/** - * A buffer of bytes using a JDK {@link DoubleBuffer} for storage. - */ -final class DoubleNioDataBuffer extends AbstractNioDataBuffer - implements DoubleDataBuffer { - - @Override - public double getDouble(long index) { - return buf.get((int)index); - } - - @Override - public DoubleDataBuffer setDouble(double value, long index) { - buf.put((int)index, value); - return this; - } - - @Override - public DoubleDataBuffer read(double[] dst, int offset, int length) { - buf.duplicate().get(dst, offset, length); - return this; - } - - @Override - public DoubleDataBuffer write(double[] src, int offset, int length) { - buf.duplicate().put(src, offset, length); - return this; - } - - @Override - public DoubleDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public DoubleDataBuffer visit(DoubleBuffer buffer) { - buffer.duplicate().put((DoubleBuffer)buf.duplicate().limit((int)size)); - return DoubleNioDataBuffer.this; - } - - @Override - public DoubleDataBuffer fallback() { - if (dst instanceof DoubleDataBuffer) { - DoubleDataBuffer doubleDst = (DoubleDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - doubleDst.setDouble(getDouble(idx), idx); - } - return DoubleNioDataBuffer.this; - } - return slowCopyTo(dst, size); - } - }); - } - - @Override - public DoubleDataBuffer offset(long index) { - Validator.offsetArgs(this, index); - return new DoubleNioDataBuffer(((DoubleBuffer)buf.duplicate().position((int)index)).slice()); - } - - @Override - public DoubleDataBuffer narrow(long size) { - Validator.narrowArgs(this, size); - return new DoubleNioDataBuffer(((DoubleBuffer)buf.duplicate().limit((int)size)).slice()); - } - - @Override - public DoubleDataBuffer slice(long index, long size) { - Validator.sliceArgs(this, index, size); - DoubleBuffer sliceBuf = buf.duplicate(); - sliceBuf.position((int)index); - sliceBuf.limit((int)index + (int)size); - return new DoubleNioDataBuffer(sliceBuf.slice()); - } - - @Override - public R accept(DataStorageVisitor visitor) { - return visitor.visit(buf); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof DoubleDataBuffer)) { - return super.equals(obj); - } - DoubleDataBuffer other = (DoubleDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(DoubleBuffer buffer) { - return buf.equals(buffer); - } - - @Override - public Boolean fallback() { - for (int idx = 0; idx < size(); ++idx) { - if (other.getDouble(idx) != getDouble(idx)) { - return false; - } - } - return true; - } - }); - } - - @Override - DoubleBuffer buf() { - return buf; - } - - DoubleNioDataBuffer(DoubleBuffer buf) { - this.buf = buf; - } - - private DoubleBuffer buf; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/FloatNioDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/FloatNioDataBuffer.java deleted file mode 100644 index 06a9a31b56a..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/FloatNioDataBuffer.java +++ /dev/null @@ -1,147 +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.ndarray.impl.buffer.nio; - -import java.nio.FloatBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; - -/** - * A buffer of bytes using a JDK {@link FloatBuffer} for storage. - */ -final class FloatNioDataBuffer extends AbstractNioDataBuffer - implements FloatDataBuffer { - - @Override - public float getFloat(long index) { - return buf.get((int)index); - } - - @Override - public FloatDataBuffer setFloat(float value, long index) { - buf.put((int)index, value); - return this; - } - - @Override - public FloatDataBuffer read(float[] dst, int offset, int length) { - buf.duplicate().get(dst, offset, length); - return this; - } - - @Override - public FloatDataBuffer write(float[] src, int offset, int length) { - buf.duplicate().put(src, offset, length); - return this; - } - - @Override - public FloatDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public FloatDataBuffer visit(FloatBuffer buffer) { - buffer.duplicate().put((FloatBuffer)buf.duplicate().limit((int)size)); - return FloatNioDataBuffer.this; - } - - @Override - public FloatDataBuffer fallback() { - if (dst instanceof FloatDataBuffer) { - FloatDataBuffer floatDst = (FloatDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - floatDst.setFloat(getFloat(idx), idx); - } - return FloatNioDataBuffer.this; - } - return slowCopyTo(dst, size); - } - }); - } - - @Override - public FloatDataBuffer offset(long index) { - Validator.offsetArgs(this, index); - return new FloatNioDataBuffer(((FloatBuffer)buf.duplicate().position((int)index)).slice()); - } - - @Override - public FloatDataBuffer narrow(long size) { - Validator.narrowArgs(this, size); - return new FloatNioDataBuffer(((FloatBuffer)buf.duplicate().limit((int)size)).slice()); - } - - @Override - public FloatDataBuffer slice(long index, long size) { - Validator.sliceArgs(this, index, size); - FloatBuffer sliceBuf = buf.duplicate(); - sliceBuf.position((int)index); - sliceBuf.limit((int)index + (int)size); - return new FloatNioDataBuffer(sliceBuf.slice()); - } - - @Override - public R accept(DataStorageVisitor visitor) { - return visitor.visit(buf); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof FloatDataBuffer)) { - return super.equals(obj); - } - FloatDataBuffer other = (FloatDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(FloatBuffer buffer) { - return buf.equals(buffer); - } - - @Override - public Boolean fallback() { - for (int idx = 0; idx < size(); ++idx) { - if (other.getFloat(idx) != getFloat(idx)) { - return false; - } - } - return true; - } - }); - } - - @Override - FloatBuffer buf() { - return buf; - } - - FloatNioDataBuffer(FloatBuffer buf) { - this.buf = buf; - } - - private FloatBuffer buf; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/IntNioDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/IntNioDataBuffer.java deleted file mode 100644 index cea729e86a7..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/IntNioDataBuffer.java +++ /dev/null @@ -1,147 +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.ndarray.impl.buffer.nio; - -import java.nio.IntBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; -import org.tensorflow.ndarray.buffer.IntDataBuffer; - -/** - * A buffer of bytes using a JDK {@link IntBuffer} for storage. - */ -final class IntNioDataBuffer extends AbstractNioDataBuffer - implements IntDataBuffer { - - @Override - public int getInt(long index) { - return buf.get((int)index); - } - - @Override - public IntDataBuffer setInt(int value, long index) { - buf.put((int)index, value); - return this; - } - - @Override - public IntDataBuffer read(int[] dst, int offset, int length) { - buf.duplicate().get(dst, offset, length); - return this; - } - - @Override - public IntDataBuffer write(int[] src, int offset, int length) { - buf.duplicate().put(src, offset, length); - return this; - } - - @Override - public IntDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public IntDataBuffer visit(IntBuffer buffer) { - buffer.duplicate().put((IntBuffer)buf.duplicate().limit((int)size)); - return IntNioDataBuffer.this; - } - - @Override - public IntDataBuffer fallback() { - if (dst instanceof IntDataBuffer) { - IntDataBuffer intDst = (IntDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - intDst.setInt(getInt(idx), idx); - } - return IntNioDataBuffer.this; - } - return slowCopyTo(dst, size); - } - }); - } - - @Override - public IntDataBuffer offset(long index) { - Validator.offsetArgs(this, index); - return new IntNioDataBuffer(((IntBuffer)buf.duplicate().position((int)index)).slice()); - } - - @Override - public IntDataBuffer narrow(long size) { - Validator.narrowArgs(this, size); - return new IntNioDataBuffer(((IntBuffer)buf.duplicate().limit((int)size)).slice()); - } - - @Override - public IntDataBuffer slice(long index, long size) { - Validator.sliceArgs(this, index, size); - IntBuffer sliceBuf = buf.duplicate(); - sliceBuf.position((int)index); - sliceBuf.limit((int)index + (int)size); - return new IntNioDataBuffer(sliceBuf.slice()); - } - - @Override - public R accept(DataStorageVisitor visitor) { - return visitor.visit(buf); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof IntDataBuffer)) { - return super.equals(obj); - } - IntDataBuffer other = (IntDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(IntBuffer buffer) { - return buf.equals(buffer); - } - - @Override - public Boolean fallback() { - for (int idx = 0; idx < size(); ++idx) { - if (other.getInt(idx) != getInt(idx)) { - return false; - } - } - return true; - } - }); - } - - @Override - IntBuffer buf() { - return buf; - } - - IntNioDataBuffer(IntBuffer buf) { - this.buf = buf; - } - - private IntBuffer buf; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/LongNioDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/LongNioDataBuffer.java deleted file mode 100644 index 7231ee7d408..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/LongNioDataBuffer.java +++ /dev/null @@ -1,147 +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.ndarray.impl.buffer.nio; - -import java.nio.LongBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; -import org.tensorflow.ndarray.buffer.LongDataBuffer; - -/** - * A buffer of bytes using a JDK {@link LongBuffer} for storage. - */ -final class LongNioDataBuffer extends AbstractNioDataBuffer - implements LongDataBuffer { - - @Override - public long getLong(long index) { - return buf.get((int)index); - } - - @Override - public LongDataBuffer setLong(long value, long index) { - buf.put((int)index, value); - return this; - } - - @Override - public LongDataBuffer read(long[] dst, int offset, int length) { - buf.duplicate().get(dst, offset, length); - return this; - } - - @Override - public LongDataBuffer write(long[] src, int offset, int length) { - buf.duplicate().put(src, offset, length); - return this; - } - - @Override - public LongDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public LongDataBuffer visit(LongBuffer buffer) { - buffer.duplicate().put((LongBuffer)buf.duplicate().limit((int)size)); - return LongNioDataBuffer.this; - } - - @Override - public LongDataBuffer fallback() { - if (dst instanceof LongDataBuffer) { - LongDataBuffer longDst = (LongDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - longDst.setLong(getLong(idx), idx); - } - return LongNioDataBuffer.this; - } - return slowCopyTo(dst, size); - } - }); - } - - @Override - public LongDataBuffer offset(long index) { - Validator.offsetArgs(this, index); - return new LongNioDataBuffer(((LongBuffer)buf.duplicate().position((int)index)).slice()); - } - - @Override - public LongDataBuffer narrow(long size) { - Validator.narrowArgs(this, size); - return new LongNioDataBuffer(((LongBuffer)buf.duplicate().limit((int)size)).slice()); - } - - @Override - public LongDataBuffer slice(long index, long size) { - Validator.sliceArgs(this, index, size); - LongBuffer sliceBuf = buf.duplicate(); - sliceBuf.position((int)index); - sliceBuf.limit((int)index + (int)size); - return new LongNioDataBuffer(sliceBuf.slice()); - } - - @Override - public R accept(DataStorageVisitor visitor) { - return visitor.visit(buf); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof LongDataBuffer)) { - return super.equals(obj); - } - LongDataBuffer other = (LongDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(LongBuffer buffer) { - return buf.equals(buffer); - } - - @Override - public Boolean fallback() { - for (int idx = 0; idx < size(); ++idx) { - if (other.getLong(idx) != getLong(idx)) { - return false; - } - } - return true; - } - }); - } - - @Override - LongBuffer buf() { - return buf; - } - - LongNioDataBuffer(LongBuffer buf) { - this.buf = buf; - } - - private LongBuffer buf; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/NioDataBufferFactory.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/NioDataBufferFactory.java deleted file mode 100644 index 4e84fc9bc17..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/NioDataBufferFactory.java +++ /dev/null @@ -1,61 +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.ndarray.impl.buffer.nio; - -import java.nio.ByteBuffer; -import java.nio.DoubleBuffer; -import java.nio.FloatBuffer; -import java.nio.IntBuffer; -import java.nio.LongBuffer; -import java.nio.ShortBuffer; -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; - -/** - * Factory of JDK NIO-based data buffers - */ -public class NioDataBufferFactory { - - public static ByteDataBuffer create(ByteBuffer buffer) { - return new ByteNioDataBuffer(buffer); - } - - public static DoubleDataBuffer create(DoubleBuffer buffer) { - return new DoubleNioDataBuffer(buffer); - } - - public static FloatDataBuffer create(FloatBuffer buffer) { - return new FloatNioDataBuffer(buffer); - } - - public static IntDataBuffer create(IntBuffer buffer) { - return new IntNioDataBuffer(buffer); - } - - public static LongDataBuffer create(LongBuffer buffer) { - return new LongNioDataBuffer(buffer); - } - - public static ShortDataBuffer create(ShortBuffer buffer) { - return new ShortNioDataBuffer(buffer); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/ShortNioDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/ShortNioDataBuffer.java deleted file mode 100644 index 776faa103c2..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/nio/ShortNioDataBuffer.java +++ /dev/null @@ -1,147 +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.ndarray.impl.buffer.nio; - -import java.nio.ShortBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; - -/** - * A buffer of bytes using a JDK {@link ShortBuffer} for storage. - */ -final class ShortNioDataBuffer extends AbstractNioDataBuffer - implements ShortDataBuffer { - - @Override - public short getShort(long index) { - return buf.get((int)index); - } - - @Override - public ShortDataBuffer setShort(short value, long index) { - buf.put((int)index, value); - return this; - } - - @Override - public ShortDataBuffer read(short[] dst, int offset, int length) { - buf.duplicate().get(dst, offset, length); - return this; - } - - @Override - public ShortDataBuffer write(short[] src, int offset, int length) { - buf.duplicate().put(src, offset, length); - return this; - } - - @Override - public ShortDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public ShortDataBuffer visit(ShortBuffer buffer) { - buffer.duplicate().put((ShortBuffer)buf.duplicate().limit((int)size)); - return ShortNioDataBuffer.this; - } - - @Override - public ShortDataBuffer fallback() { - if (dst instanceof ShortDataBuffer) { - ShortDataBuffer shortDst = (ShortDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - shortDst.setShort(getShort(idx), idx); - } - return ShortNioDataBuffer.this; - } - return slowCopyTo(dst, size); - } - }); - } - - @Override - public ShortDataBuffer offset(long index) { - Validator.offsetArgs(this, index); - return new ShortNioDataBuffer(((ShortBuffer)buf.duplicate().position((int)index)).slice()); - } - - @Override - public ShortDataBuffer narrow(long size) { - Validator.narrowArgs(this, size); - return new ShortNioDataBuffer(((ShortBuffer)buf.duplicate().limit((int)size)).slice()); - } - - @Override - public ShortDataBuffer slice(long index, long size) { - Validator.sliceArgs(this, index, size); - ShortBuffer sliceBuf = buf.duplicate(); - sliceBuf.position((int)index); - sliceBuf.limit((int)index + (int)size); - return new ShortNioDataBuffer(sliceBuf.slice()); - } - - @Override - public R accept(DataStorageVisitor visitor) { - return visitor.visit(buf); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof ShortDataBuffer)) { - return super.equals(obj); - } - ShortDataBuffer other = (ShortDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(ShortBuffer buffer) { - return buf.equals(buffer); - } - - @Override - public Boolean fallback() { - for (int idx = 0; idx < size(); ++idx) { - if (other.getShort(idx) != getShort(idx)) { - return false; - } - } - return true; - } - }); - } - - @Override - ShortBuffer buf() { - return buf; - } - - ShortNioDataBuffer(ShortBuffer buf) { - this.buf = buf; - } - - private ShortBuffer buf; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/AbstractRawDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/AbstractRawDataBuffer.java deleted file mode 100644 index c6050385b77..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/AbstractRawDataBuffer.java +++ /dev/null @@ -1,94 +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.ndarray.impl.buffer.raw; - -import org.tensorflow.ndarray.impl.buffer.AbstractDataBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBufferWindow; - -@SuppressWarnings("unchecked") -abstract class AbstractRawDataBuffer> extends AbstractDataBuffer { - - public long size() { - return memory.size(); - } - - @Override - public boolean isReadOnly() { - return readOnly; - } - - public B read(Object dst, int dstLength) { - Validator.readArgs(this, dstLength, 0, dstLength); - memory.copyTo(UnsafeMemoryHandle.fromArray(dst, dstLength), dstLength); - return (B)this; - } - - public B read(Object dst, int dstLength, int offset, int length) { - Validator.readArgs(this, dstLength, offset, length); - memory.copyTo(UnsafeMemoryHandle.fromArray(dst, dstLength).offset(offset), length); - return (B)this; - } - - public B write(Object src, int srcLength) { - Validator.writeArgs(this, srcLength, 0, srcLength); - UnsafeMemoryHandle.fromArray(src, srcLength).copyTo(memory, srcLength); - return (B)this; - } - - public B write(Object src, int srcLength, int offset, int length) { - Validator.writeArgs(this, srcLength, offset, length); - UnsafeMemoryHandle.fromArray(src, srcLength).offset(offset).copyTo(memory, length); - return (B)this; - } - - @Override - public B copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - if (dst instanceof AbstractRawDataBuffer) { - AbstractRawDataBuffer unsafeDst = (AbstractRawDataBuffer)dst; - memory.copyTo(unsafeDst.memory, size); - } else { - super.copyTo(dst, size); - } - return (B)this; - } - - @Override - public B slice(long index, long size) { - Validator.sliceArgs(this, index, size); - return instantiate(memory.slice(index, size)); - } - - @Override - public DataBufferWindow window(long size) { - B windowBuffer = instantiate(memory.slice(0, size)); - return new RawDataBufferWindow<>((AbstractRawDataBuffer)windowBuffer, size()); - } - - protected final UnsafeMemoryHandle memory; - protected final boolean readOnly; - - protected abstract B instantiate(UnsafeMemoryHandle region); - - AbstractRawDataBuffer(UnsafeMemoryHandle memory, boolean readOnly) { - this.memory = memory; - this.readOnly = readOnly; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/BooleanRawDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/BooleanRawDataBuffer.java deleted file mode 100644 index e7e825ea505..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/BooleanRawDataBuffer.java +++ /dev/null @@ -1,146 +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.ndarray.impl.buffer.raw; - -import java.util.Arrays; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; - -final class BooleanRawDataBuffer extends AbstractRawDataBuffer - implements BooleanDataBuffer { - - @Override - public boolean getBoolean(long index) { - Validator.getArgs(this, index); - return memory.getBoolean(index); - } - - @Override - public BooleanDataBuffer setBoolean(boolean value, long index) { - Validator.setArgs(this, index); - memory.setBoolean(value, index); - return this; - } - - @Override - public BooleanDataBuffer read(boolean[] dst) { - return read(dst, dst.length); - } - - @Override - public BooleanDataBuffer read(boolean[] dst, int offset, int length) { - return read(dst, dst.length, offset, length); - } - - @Override - public BooleanDataBuffer write(boolean[] src) { - return write(src, src.length); - } - - @Override - public BooleanDataBuffer write(boolean[] src, int offset, int length) { - return write(src, src.length, offset, length); - } - - @Override - public BooleanDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public BooleanDataBuffer visit(boolean[] array, int offset, int length) { - memory.copyTo(UnsafeMemoryHandle.fromArray(array, offset, length), size); - return BooleanRawDataBuffer.this; - } - - @Override - public BooleanDataBuffer visit(long address, long length, long scale) { - memory.copyTo(UnsafeMemoryHandle.fromAddress(address, length, scale), size); - return BooleanRawDataBuffer.this; - } - - @Override - public BooleanDataBuffer fallback() { - if (dst instanceof BooleanDataBuffer) { - BooleanDataBuffer booleanDst = (BooleanDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - booleanDst.setBoolean(getBoolean(idx), idx); - } - return BooleanRawDataBuffer.this; - } - return slowCopyTo(dst, size); - } - }); - } - - @Override - public R accept(DataStorageVisitor visitor) { - if (memory.isArray()) { - return visitor.visit((boolean[])memory.object, memory.arrayOffset(boolean[].class), (int)memory.size()); - } - return visitor.visit(memory.byteOffset, memory.byteSize, memory.scale); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof BooleanDataBuffer)) { - return super.equals(obj); - } - BooleanDataBuffer other = (BooleanDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(boolean[] array, int offset, int length) { - if (memory.isArray() && memory.arrayOffset(boolean[].class) == 0 && offset == 0) { - boolean[] thisArray = memory.array(); - if (thisArray.length == array.length) { - return Arrays.equals(thisArray, array); - } - } - return fallback(); - } - - @Override - public Boolean fallback() { - for (long idx = 0L; idx < size(); ++idx) { - if (other.getBoolean(idx) != getBoolean(idx)) { - return false; - } - } - return true; - } - }); - } - - @Override - protected BooleanDataBuffer instantiate(UnsafeMemoryHandle memory) { - return new BooleanRawDataBuffer(memory, readOnly); - } - - BooleanRawDataBuffer(UnsafeMemoryHandle memory, boolean readOnly) { - super(memory, readOnly); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/ByteRawDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/ByteRawDataBuffer.java deleted file mode 100644 index b4b490e98ed..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/ByteRawDataBuffer.java +++ /dev/null @@ -1,185 +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.ndarray.impl.buffer.raw; - -import java.nio.ByteBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; - -final class ByteRawDataBuffer extends AbstractRawDataBuffer - implements ByteDataBuffer { - - @Override - public byte getByte(long index) { - Validator.getArgs(this, index); - return memory.getByte(index); - } - - @Override - public ByteDataBuffer setByte(byte value, long index) { - Validator.setArgs(this, index); - memory.setByte(value, index); - return this; - } - - @Override - public ByteDataBuffer read(byte[] dst) { - return read(dst, dst.length); - } - - @Override - public ByteDataBuffer read(byte[] dst, int offset, int length) { - return read(dst, dst.length, offset, length); - } - - @Override - public ByteDataBuffer write(byte[] src) { - return write(src, src.length); - } - - @Override - public ByteDataBuffer write(byte[] src, int offset, int length) { - return write(src, src.length, offset, length); - } - - @Override - public ByteDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public ByteDataBuffer visit(ByteBuffer buffer) { - if (buffer.hasArray()) { - memory.copyTo(UnsafeMemoryHandle.fromArray(buffer.array(), buffer.position(), buffer.limit()), size); - } else if (memory.isArray()) { - buffer.put(memory.toArrayByteBuffer()); - } else { - slowCopyTo(dst, size); - } - return ByteRawDataBuffer.this; - } - - @Override - public ByteDataBuffer visit(long address, long length, long scale) { - memory.copyTo(UnsafeMemoryHandle.fromAddress(address, length, scale), size); - return ByteRawDataBuffer.this; - } - - @Override - public ByteDataBuffer fallback() { - if (dst instanceof ByteDataBuffer) { - ByteDataBuffer byteDst = (ByteDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - byteDst.setByte(getByte(idx), idx); - } - return ByteRawDataBuffer.this; - } - return slowCopyTo(dst, size); - } - }); - } - - @Override - public IntDataBuffer asInts() { - return new IntRawDataBuffer(memory.rescale(Integer.BYTES), readOnly); - } - - @Override - public ShortDataBuffer asShorts() { - return new ShortRawDataBuffer(memory.rescale(Short.BYTES), readOnly); - } - - @Override - public LongDataBuffer asLongs() { - return new LongRawDataBuffer(memory.rescale(Long.BYTES), readOnly); - } - - @Override - public FloatDataBuffer asFloats() { - return new FloatRawDataBuffer(memory.rescale(Float.BYTES), readOnly); - } - - @Override - public DoubleDataBuffer asDoubles() { - return new DoubleRawDataBuffer(memory.rescale(Double.BYTES), readOnly); - } - - @Override - public BooleanDataBuffer asBooleans() { - return new BooleanRawDataBuffer(memory.rescale(Byte.BYTES), readOnly); - } - - @Override - public R accept(DataStorageVisitor visitor) { - if (memory.isArray()) { - return visitor.visit(memory.toArrayByteBuffer()); - } - return visitor.visit(memory.byteOffset, memory.byteSize, memory.scale); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof ByteDataBuffer)) { - return super.equals(obj); - } - ByteDataBuffer other = (ByteDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(ByteBuffer buffer) { - if (memory.isArray()) { - return buffer.equals(memory.toArrayByteBuffer()); - } - return fallback(); - } - - @Override - public Boolean fallback() { - for (long idx = 0L; idx < size(); ++idx) { - if (other.getByte(idx) != getByte(idx)) { - return false; - } - } - return true; - } - }); - } - - @Override - protected ByteDataBuffer instantiate(UnsafeMemoryHandle memory) { - return new ByteRawDataBuffer(memory, readOnly); - } - - ByteRawDataBuffer(UnsafeMemoryHandle memory, boolean readOnly) { - super(memory, readOnly); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/DoubleRawDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/DoubleRawDataBuffer.java deleted file mode 100644 index 680d9565184..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/DoubleRawDataBuffer.java +++ /dev/null @@ -1,149 +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.ndarray.impl.buffer.raw; - -import java.nio.DoubleBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; - -final class DoubleRawDataBuffer extends AbstractRawDataBuffer - implements DoubleDataBuffer { - - @Override - public double getDouble(long index) { - Validator.getArgs(this, index); - return memory.getDouble(index); - } - - @Override - public DoubleDataBuffer setDouble(double value, long index) { - Validator.setArgs(this, index); - memory.setDouble(value, index); - return this; - } - - @Override - public DoubleDataBuffer read(double[] dst) { - return read(dst, dst.length); - } - - @Override - public DoubleDataBuffer read(double[] dst, int offset, int length) { - return read(dst, dst.length, offset, length); - } - - @Override - public DoubleDataBuffer write(double[] src) { - return write(src, src.length); - } - - @Override - public DoubleDataBuffer write(double[] src, int offset, int length) { - return write(src, src.length, offset, length); - } - - @Override - public DoubleDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public DoubleDataBuffer visit(DoubleBuffer buffer) { - if (buffer.hasArray()) { - memory.copyTo(UnsafeMemoryHandle.fromArray(buffer.array(), buffer.position(), buffer.limit()), size); - } else if (memory.isArray()) { - buffer.put(memory.toArrayDoubleBuffer()); - } else { - slowCopyTo(dst, size); - } - return DoubleRawDataBuffer.this; - } - - @Override - public DoubleDataBuffer visit(long address, long length, long scale) { - memory.copyTo(UnsafeMemoryHandle.fromAddress(address, length, scale), size); - return DoubleRawDataBuffer.this; - } - - @Override - public DoubleDataBuffer fallback() { - if (dst instanceof DoubleDataBuffer) { - DoubleDataBuffer doubleDst = (DoubleDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - doubleDst.setDouble(getDouble(idx), idx); - } - return DoubleRawDataBuffer.this; - } - return slowCopyTo(dst, size); - } - }); - } - - @Override - public R accept(DataStorageVisitor visitor) { - if (memory.isArray()) { - return visitor.visit(memory.toArrayDoubleBuffer()); - } - return visitor.visit(memory.byteOffset, memory.byteSize, memory.scale); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof DoubleDataBuffer)) { - return super.equals(obj); - } - DoubleDataBuffer other = (DoubleDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(DoubleBuffer buffer) { - if (memory.isArray()) { - return buffer.equals(memory.toArrayDoubleBuffer()); - } - return fallback(); - } - - @Override - public Boolean fallback() { - for (long idx = 0L; idx < size(); ++idx) { - if (other.getDouble(idx) != getDouble(idx)) { - return false; - } - } - return true; - } - }); - } - - @Override - protected DoubleDataBuffer instantiate(UnsafeMemoryHandle memory) { - return new DoubleRawDataBuffer(memory, readOnly); - } - - DoubleRawDataBuffer(UnsafeMemoryHandle memory, boolean readOnly) { - super(memory, readOnly); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/FloatRawDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/FloatRawDataBuffer.java deleted file mode 100644 index 43bd370a88b..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/FloatRawDataBuffer.java +++ /dev/null @@ -1,150 +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.ndarray.impl.buffer.raw; - -import java.nio.FloatBuffer; - -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; - -final class FloatRawDataBuffer extends AbstractRawDataBuffer - implements FloatDataBuffer { - - @Override - public float getFloat(long index) { - Validator.getArgs(this, index); - return memory.getFloat(index); - } - - @Override - public FloatDataBuffer setFloat(float value, long index) { - Validator.setArgs(this, index); - memory.setFloat(value, index); - return this; - } - - @Override - public FloatDataBuffer read(float[] dst) { - return read(dst, dst.length); - } - - @Override - public FloatDataBuffer read(float[] dst, int offset, int length) { - return read(dst, dst.length, offset, length); - } - - @Override - public FloatDataBuffer write(float[] src) { - return write(src, src.length); - } - - @Override - public FloatDataBuffer write(float[] src, int offset, int length) { - return write(src, src.length, offset, length); - } - - @Override - public FloatDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public FloatDataBuffer visit(FloatBuffer buffer) { - if (buffer.hasArray()) { - memory.copyTo(UnsafeMemoryHandle.fromArray(buffer.array(), buffer.position(), buffer.limit()), size); - } else if (memory.isArray()) { - buffer.put(memory.toArrayFloatBuffer()); - } else { - slowCopyTo(dst, size); - } - return FloatRawDataBuffer.this; - } - - @Override - public FloatDataBuffer visit(long address, long length, long scale) { - memory.copyTo(UnsafeMemoryHandle.fromAddress(address, length, scale), size); - return FloatRawDataBuffer.this; - } - - @Override - public FloatDataBuffer fallback() { - if (dst instanceof FloatDataBuffer) { - FloatDataBuffer floatDst = (FloatDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - floatDst.setFloat(getFloat(idx), idx); - } - return FloatRawDataBuffer.this; - } - return slowCopyTo(dst, size); - } - }); - } - - @Override - public R accept(DataStorageVisitor visitor) { - if (memory.isArray()) { - return visitor.visit(memory.toArrayFloatBuffer()); - } - return visitor.visit(memory.byteOffset, memory.byteSize, memory.scale); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof FloatDataBuffer)) { - return super.equals(obj); - } - FloatDataBuffer other = (FloatDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(FloatBuffer buffer) { - if (memory.isArray()) { - return buffer.equals(memory.toArrayFloatBuffer()); - } - return fallback(); - } - - @Override - public Boolean fallback() { - for (long idx = 0L; idx < size(); ++idx) { - if (other.getFloat(idx) != getFloat(idx)) { - return false; - } - } - return true; - } - }); - } - - @Override - protected FloatDataBuffer instantiate(UnsafeMemoryHandle memory) { - return new FloatRawDataBuffer(memory, readOnly); - } - - FloatRawDataBuffer(UnsafeMemoryHandle memory, boolean readOnly) { - super(memory, readOnly); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/IntRawDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/IntRawDataBuffer.java deleted file mode 100644 index 1c905e2756d..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/IntRawDataBuffer.java +++ /dev/null @@ -1,149 +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.ndarray.impl.buffer.raw; - -import java.nio.IntBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; -import org.tensorflow.ndarray.buffer.IntDataBuffer; - -final class IntRawDataBuffer extends AbstractRawDataBuffer - implements IntDataBuffer { - - @Override - public int getInt(long index) { - Validator.getArgs(this, index); - return memory.getInt(index); - } - - @Override - public IntDataBuffer setInt(int value, long index) { - Validator.setArgs(this, index); - memory.setInt(value, index); - return this; - } - - @Override - public IntDataBuffer read(int[] dst) { - return read(dst, dst.length); - } - - @Override - public IntDataBuffer read(int[] dst, int offset, int length) { - return read(dst, dst.length, offset, length); - } - - @Override - public IntDataBuffer write(int[] src) { - return write(src, src.length); - } - - @Override - public IntDataBuffer write(int[] src, int offset, int length) { - return write(src, src.length, offset, length); - } - - @Override - public IntDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public IntDataBuffer visit(IntBuffer buffer) { - if (buffer.hasArray()) { - memory.copyTo(UnsafeMemoryHandle.fromArray(buffer.array(), buffer.position(), buffer.limit()), size); - } else if (memory.isArray()) { - buffer.put(memory.toArrayIntBuffer()); - } else { - slowCopyTo(dst, size); - } - return IntRawDataBuffer.this; - } - - @Override - public IntDataBuffer visit(long address, long length, long scale) { - memory.copyTo(UnsafeMemoryHandle.fromAddress(address, length, scale), size); - return IntRawDataBuffer.this; - } - - @Override - public IntDataBuffer fallback() { - if (dst instanceof IntDataBuffer) { - IntDataBuffer intDst = (IntDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - intDst.setInt(getInt(idx), idx); - } - return IntRawDataBuffer.this; - } - return slowCopyTo(dst, size); - } - }); - } - - @Override - public R accept(DataStorageVisitor visitor) { - if (memory.isArray()) { - return visitor.visit(memory.toArrayIntBuffer()); - } - return visitor.visit(memory.byteOffset, memory.byteSize, memory.scale); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof IntDataBuffer)) { - return super.equals(obj); - } - IntDataBuffer other = (IntDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(IntBuffer buffer) { - if (memory.isArray()) { - return buffer.equals(memory.toArrayIntBuffer()); - } - return fallback(); - } - - @Override - public Boolean fallback() { - for (long idx = 0L; idx < size(); ++idx) { - if (other.getInt(idx) != getInt(idx)) { - return false; - } - } - return true; - } - }); - } - - @Override - protected IntDataBuffer instantiate(UnsafeMemoryHandle memory) { - return new IntRawDataBuffer(memory, readOnly); - } - - IntRawDataBuffer(UnsafeMemoryHandle memory, boolean readOnly) { - super(memory, readOnly); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/LongRawDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/LongRawDataBuffer.java deleted file mode 100644 index 724868fe81f..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/LongRawDataBuffer.java +++ /dev/null @@ -1,149 +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.ndarray.impl.buffer.raw; - -import java.nio.LongBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; -import org.tensorflow.ndarray.buffer.LongDataBuffer; - -final class LongRawDataBuffer extends AbstractRawDataBuffer - implements LongDataBuffer { - - @Override - public long getLong(long index) { - Validator.getArgs(this, index); - return memory.getLong(index); - } - - @Override - public LongDataBuffer setLong(long value, long index) { - Validator.setArgs(this, index); - memory.setLong(value, index); - return this; - } - - @Override - public LongDataBuffer read(long[] dst) { - return read(dst, dst.length); - } - - @Override - public LongDataBuffer read(long[] dst, int offset, int length) { - return read(dst, dst.length, offset, length); - } - - @Override - public LongDataBuffer write(long[] src) { - return write(src, src.length); - } - - @Override - public LongDataBuffer write(long[] src, int offset, int length) { - return write(src, src.length, offset, length); - } - - @Override - public LongDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public LongDataBuffer visit(LongBuffer buffer) { - if (buffer.hasArray()) { - memory.copyTo(UnsafeMemoryHandle.fromArray(buffer.array(), buffer.position(), buffer.limit()), size); - } else if (memory.isArray()) { - buffer.put(memory.toArrayLongBuffer()); - } else { - slowCopyTo(dst, size); - } - return LongRawDataBuffer.this; - } - - @Override - public LongDataBuffer visit(long address, long length, long scale) { - memory.copyTo(UnsafeMemoryHandle.fromAddress(address, length, scale), size); - return LongRawDataBuffer.this; - } - - @Override - public LongDataBuffer fallback() { - if (dst instanceof LongDataBuffer) { - LongDataBuffer longDst = (LongDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - longDst.setLong(getLong(idx), idx); - } - return LongRawDataBuffer.this; - } - return slowCopyTo(dst, size); - } - }); - } - - @Override - public R accept(DataStorageVisitor visitor) { - if (memory.isArray()) { - return visitor.visit(memory.toArrayLongBuffer()); - } - return visitor.visit(memory.byteOffset, memory.byteSize, memory.scale); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof LongDataBuffer)) { - return super.equals(obj); - } - LongDataBuffer other = (LongDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(LongBuffer buffer) { - if (memory.isArray()) { - return buffer.equals(memory.toArrayLongBuffer()); - } - return fallback(); - } - - @Override - public Boolean fallback() { - for (long idx = 0L; idx < size(); ++idx) { - if (other.getLong(idx) != getLong(idx)) { - return false; - } - } - return true; - } - }); - } - - @Override - protected LongDataBuffer instantiate(UnsafeMemoryHandle memory) { - return new LongRawDataBuffer(memory, readOnly); - } - - LongRawDataBuffer(UnsafeMemoryHandle memory, boolean readOnly) { - super(memory, readOnly); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/RawDataBufferFactory.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/RawDataBufferFactory.java deleted file mode 100644 index 7253b239af2..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/RawDataBufferFactory.java +++ /dev/null @@ -1,148 +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.ndarray.impl.buffer.raw; - -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; - -/** - * Factory of raw data buffers - */ -public class RawDataBufferFactory { - - public static boolean canBeUsed() { - return UnsafeReference.isAvailable(); - } - - public static BooleanDataBuffer create(boolean[] array, boolean readOnly) { - return new BooleanRawDataBuffer(UnsafeMemoryHandle.fromArray(array, array.length), readOnly); - } - - public static ByteDataBuffer create(byte[] array, boolean readOnly) { - if (!canBeUsed()) { - throw new IllegalStateException("Raw data buffers are not available"); - } - return new ByteRawDataBuffer(UnsafeMemoryHandle.fromArray(array, array.length), readOnly); - } - - public static DoubleDataBuffer create(double[] array, boolean readOnly) { - if (!canBeUsed()) { - throw new IllegalStateException("Raw data buffers are not available"); - } - return new DoubleRawDataBuffer(UnsafeMemoryHandle.fromArray(array, array.length), readOnly); - } - - public static FloatDataBuffer create(float[] array, boolean readOnly) { - if (!canBeUsed()) { - throw new IllegalStateException("Raw data buffers are not available"); - } - return new FloatRawDataBuffer(UnsafeMemoryHandle.fromArray(array, array.length), readOnly); - } - - public static IntDataBuffer create(int[] array, boolean readOnly) { - if (!canBeUsed()) { - throw new IllegalStateException("Raw data buffers are not available"); - } - return new IntRawDataBuffer(UnsafeMemoryHandle.fromArray(array, array.length), readOnly); - } - - public static LongDataBuffer create(long[] array, boolean readOnly) { - if (!canBeUsed()) { - throw new IllegalStateException("Raw data buffers are not available"); - } - return new LongRawDataBuffer(UnsafeMemoryHandle.fromArray(array, array.length), readOnly); - } - - public static ShortDataBuffer create(short[] array, boolean readOnly) { - if (!canBeUsed()) { - throw new IllegalStateException("Raw data buffers are not available"); - } - return new ShortRawDataBuffer(UnsafeMemoryHandle.fromArray(array, array.length), readOnly); - } - - protected static BooleanDataBuffer mapNativeBooleans(long address, long size, boolean readOnly) { - if (!canBeUsed()) { - throw new IllegalStateException("Raw data buffers are not available"); - } - Validator.createArgs(size, MAX_64BITS); - return new BooleanRawDataBuffer(UnsafeMemoryHandle.fromAddress(address, size, Byte.BYTES), readOnly); - } - - protected static ByteDataBuffer mapNativeBytes(long address, long size, boolean readOnly) { - if (!canBeUsed()) { - throw new IllegalStateException("Raw data buffers are not available"); - } - Validator.createArgs(size, MAX_64BITS); - return new ByteRawDataBuffer(UnsafeMemoryHandle.fromAddress(address, size, Byte.BYTES), readOnly); - } - - protected static DoubleDataBuffer mapNativeDoubles(long address, long size, boolean readOnly) { - if (!canBeUsed()) { - throw new IllegalStateException("Raw data buffers are not available"); - } - Validator.createArgs(size, MAX_64BITS); - return new DoubleRawDataBuffer(UnsafeMemoryHandle.fromAddress(address, size, Double.BYTES), readOnly); - } - - protected static FloatDataBuffer mapNativeFloats(long address, long size, boolean readOnly) { - if (!canBeUsed()) { - throw new IllegalStateException("Raw data buffers are not available"); - } - Validator.createArgs(size, MAX_64BITS); - return new FloatRawDataBuffer(UnsafeMemoryHandle.fromAddress(address, size, Float.BYTES), readOnly); - } - - protected static IntDataBuffer mapNativeInts(long address, long size, boolean readOnly) { - if (!canBeUsed()) { - throw new IllegalStateException("Raw data buffers are not available"); - } - Validator.createArgs(size, MAX_64BITS); - return new IntRawDataBuffer(UnsafeMemoryHandle.fromAddress(address, size, Integer.BYTES), readOnly); - } - - protected static LongDataBuffer mapNativeLongs(long address, long size, boolean readOnly) { - if (!canBeUsed()) { - throw new IllegalStateException("Raw data buffers are not available"); - } - Validator.createArgs(size, MAX_64BITS); - return new LongRawDataBuffer(UnsafeMemoryHandle.fromAddress(address, size, Long.BYTES), readOnly); - } - - protected static ShortDataBuffer mapNativeShorts(long address, long size, boolean readOnly) { - if (!canBeUsed()) { - throw new IllegalStateException("Raw data buffers are not available"); - } - Validator.createArgs(size, MAX_64BITS); - return new ShortRawDataBuffer(UnsafeMemoryHandle.fromAddress(address, size, Short.BYTES), readOnly); - } - - /* - * The maximum size for a buffer of this type, i.e. the maximum number of bytes it can store. - *

- * As the maximum size may vary depending on the JVM implementation and on the platform, this - * property returns a value that is safe for most of them. - */ - static long MAX_32BITS = Integer.MAX_VALUE - 10; - static long MAX_64BITS = Long.MAX_VALUE - 10; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/RawDataBufferWindow.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/RawDataBufferWindow.java deleted file mode 100644 index dc18a6caa6e..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/RawDataBufferWindow.java +++ /dev/null @@ -1,19 +0,0 @@ -package org.tensorflow.ndarray.impl.buffer.raw; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.impl.buffer.AbstractDataBufferWindow; - -final class RawDataBufferWindow> extends AbstractDataBufferWindow { - - @Override - public void offset(long offset) { - windowMemory.rebase(offset); - } - - > RawDataBufferWindow(R windowBuffer, long bufferLimit) { - super((B)windowBuffer, bufferLimit); - this.windowMemory = windowBuffer.memory; - } - - private final UnsafeMemoryHandle windowMemory; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/ShortRawDataBuffer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/ShortRawDataBuffer.java deleted file mode 100644 index 80f9c289852..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/ShortRawDataBuffer.java +++ /dev/null @@ -1,149 +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.ndarray.impl.buffer.raw; - -import java.nio.ShortBuffer; -import org.tensorflow.ndarray.impl.buffer.Validator; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataStorageVisitor; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; - -final class ShortRawDataBuffer extends AbstractRawDataBuffer - implements ShortDataBuffer { - - @Override - public short getShort(long index) { - Validator.getArgs(this, index); - return memory.getShort(index); - } - - @Override - public ShortDataBuffer setShort(short value, long index) { - Validator.setArgs(this, index); - memory.setShort(value, index); - return this; - } - - @Override - public ShortDataBuffer read(short[] dst) { - return read(dst, dst.length); - } - - @Override - public ShortDataBuffer read(short[] dst, int offset, int length) { - return read(dst, dst.length, offset, length); - } - - @Override - public ShortDataBuffer write(short[] src) { - return write(src, src.length); - } - - @Override - public ShortDataBuffer write(short[] src, int offset, int length) { - return write(src, src.length, offset, length); - } - - @Override - public ShortDataBuffer copyTo(DataBuffer dst, long size) { - Validator.copyToArgs(this, dst, size); - return dst.accept(new DataStorageVisitor() { - - @Override - public ShortDataBuffer visit(ShortBuffer buffer) { - if (buffer.hasArray()) { - memory.copyTo(UnsafeMemoryHandle.fromArray(buffer.array(), buffer.position(), buffer.limit()), size); - } else if (memory.isArray()) { - buffer.put(memory.toArrayShortBuffer()); - } else { - slowCopyTo(dst, size); - } - return ShortRawDataBuffer.this; - } - - @Override - public ShortDataBuffer visit(long address, long length, long scale) { - memory.copyTo(UnsafeMemoryHandle.fromAddress(address, length, scale), size); - return ShortRawDataBuffer.this; - } - - @Override - public ShortDataBuffer fallback() { - if (dst instanceof ShortDataBuffer) { - ShortDataBuffer shortDst = (ShortDataBuffer)dst; - for (long idx = 0L; idx < size; ++idx) { - shortDst.setShort(getShort(idx), idx); - } - return ShortRawDataBuffer.this; - } - return slowCopyTo(dst, size); - } - }); - } - - @Override - public R accept(DataStorageVisitor visitor) { - if (memory.isArray()) { - return visitor.visit(memory.toArrayShortBuffer()); - } - return visitor.visit(memory.byteOffset, memory.byteSize, memory.scale); - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof ShortDataBuffer)) { - return super.equals(obj); - } - ShortDataBuffer other = (ShortDataBuffer)obj; - if (size() != other.size()) { - return false; - } - return other.accept(new DataStorageVisitor() { - - @Override - public Boolean visit(ShortBuffer buffer) { - if (memory.isArray()) { - return buffer.equals(memory.toArrayShortBuffer()); - } - return fallback(); - } - - @Override - public Boolean fallback() { - for (long idx = 0L; idx < size(); ++idx) { - if (other.getShort(idx) != getShort(idx)) { - return false; - } - } - return true; - } - }); - } - - @Override - protected ShortDataBuffer instantiate(UnsafeMemoryHandle memory) { - return new ShortRawDataBuffer(memory, readOnly); - } - - ShortRawDataBuffer(UnsafeMemoryHandle memory, boolean readOnly) { - super(memory, readOnly); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/UnsafeMemoryHandle.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/UnsafeMemoryHandle.java deleted file mode 100644 index bd61e53a128..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/UnsafeMemoryHandle.java +++ /dev/null @@ -1,195 +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.ndarray.impl.buffer.raw; - -import java.nio.ByteBuffer; -import java.nio.DoubleBuffer; -import java.nio.FloatBuffer; -import java.nio.IntBuffer; -import java.nio.LongBuffer; -import java.nio.ShortBuffer; - -final class UnsafeMemoryHandle { - - static UnsafeMemoryHandle fromArray(Object array, int length) { - return fromArray(array, 0, length); - } - - static UnsafeMemoryHandle fromArray(Object array, int arrayOffset, int length) { - long scale = UnsafeReference.UNSAFE.arrayIndexScale(array.getClass()); - int baseOffset = UnsafeReference.UNSAFE.arrayBaseOffset(array.getClass()); - return new UnsafeMemoryHandle(array, baseOffset + (arrayOffset * scale), length * scale, scale); - } - - static UnsafeMemoryHandle fromAddress(long address, long byteSize, long scale) { - return new UnsafeMemoryHandle(address, byteSize, scale); - } - - long size() { - return size; - } - - byte getByte(long index) { - return UnsafeReference.UNSAFE.getByte(object, align(index)); - } - - void setByte(byte value, long index) { - UnsafeReference.UNSAFE.putByte(object, align(index), value); - } - - boolean getBoolean(long index) { - return UnsafeReference.UNSAFE.getBoolean(object, align(index)); - } - - void setBoolean(boolean value, long index) { - UnsafeReference.UNSAFE.putBoolean(object, align(index), value); - } - - short getShort(long index) { - return UnsafeReference.UNSAFE.getShort(object, align(index)); - } - - void setShort(short value, long index) { - UnsafeReference.UNSAFE.putShort(object, align(index), value); - } - - int getInt(long index) { - return UnsafeReference.UNSAFE.getInt(object, align(index)); - } - - void setInt(int value, long index) { - UnsafeReference.UNSAFE.putInt(object, align(index), value); - } - - float getFloat(long index) { - return UnsafeReference.UNSAFE.getFloat(object, align(index)); - } - - void setFloat(float value, long index) { - UnsafeReference.UNSAFE.putFloat(object, align(index), value); - } - - double getDouble(long index) { - return UnsafeReference.UNSAFE.getDouble(object, align(index)); - } - - void setDouble(double value, long index) { - UnsafeReference.UNSAFE.putDouble(object, align(index), value); - } - - long getLong(long index) { - return UnsafeReference.UNSAFE.getLong(object, align(index)); - } - - void setLong(long value, long index) { - UnsafeReference.UNSAFE.putLong(object, align(index), value); - } - - void copyTo(UnsafeMemoryHandle memory, long length) { - UnsafeReference.UNSAFE.copyMemory(object, byteOffset, memory.object, memory.byteOffset, length * scale); - } - - UnsafeMemoryHandle offset(long index) { - long offset = scale(index); - return new UnsafeMemoryHandle(object, this.byteOffset + offset, byteSize - offset, scale); - } - - UnsafeMemoryHandle narrow(long size) { - return new UnsafeMemoryHandle(object, byteOffset, scale(size), scale); - } - - UnsafeMemoryHandle slice(long index, long size) { - return new UnsafeMemoryHandle(object, this.byteOffset + scale(index), scale(size), scale); - } - - UnsafeMemoryHandle rescale(long scale) { - if (object != null) { - throw new IllegalStateException("Raw heap memory cannot be rescaled"); - } - return new UnsafeMemoryHandle(null, byteOffset, byteSize, scale); - } - - void rebase(long index) { - byteOffset = baseOffset + scale(index); - } - - boolean isArray() { - return object != null; - } - - @SuppressWarnings("unchecked") - A array() { - return (A)object; - } - - int arrayOffset(Class arrayClass) { - return (int)((byteOffset - UnsafeReference.UNSAFE.arrayBaseOffset(arrayClass)) / scale); - } - - ByteBuffer toArrayByteBuffer() { - return ByteBuffer.wrap((byte[])object, (int) byteOffset - UnsafeReference.UNSAFE.arrayBaseOffset(byte[].class), (int)size); - } - - ShortBuffer toArrayShortBuffer() { - return ShortBuffer.wrap((short[])object, (int)((byteOffset - UnsafeReference.UNSAFE.arrayBaseOffset(short[].class)) / scale), (int)size); - } - - IntBuffer toArrayIntBuffer() { - return IntBuffer.wrap((int[])object, (int)((byteOffset - UnsafeReference.UNSAFE.arrayBaseOffset(int[].class)) / scale), (int)size); - } - - LongBuffer toArrayLongBuffer() { - return LongBuffer.wrap((long[])object, (int)((byteOffset - UnsafeReference.UNSAFE.arrayBaseOffset(long[].class)) / scale), (int)size); - } - - FloatBuffer toArrayFloatBuffer() { - return FloatBuffer.wrap((float[])object, (int)((byteOffset - UnsafeReference.UNSAFE.arrayBaseOffset(float[].class)) / scale), (int)size); - } - - DoubleBuffer toArrayDoubleBuffer() { - return DoubleBuffer.wrap((double[])object, (int)((byteOffset - UnsafeReference.UNSAFE.arrayBaseOffset(double[].class)) / scale), (int)size); - } - - final Object object; - final long baseOffset; - long byteOffset; - final long byteSize; - final long scale; - final long size; - - private UnsafeMemoryHandle(Object object, long baseOffset, long byteSize, long scale) { - this.object = object; - this.baseOffset = baseOffset; - byteOffset = baseOffset; - this.byteSize = byteSize; - this.scale = scale; - size = byteSize / scale; - } - - private UnsafeMemoryHandle(long address, long byteSize, long scale) { - this(null, address, byteSize, scale); - } - - private long align(long index) { - return byteOffset + index * scale; - } - - private long scale(long value) { - return value * scale; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/UnsafeReference.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/UnsafeReference.java deleted file mode 100644 index 7b95eac7349..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/buffer/raw/UnsafeReference.java +++ /dev/null @@ -1,64 +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.ndarray.impl.buffer.raw; - -import java.lang.reflect.Field; -import sun.misc.Unsafe; - -final class UnsafeReference { - - static boolean isAvailable() { - return UNSAFE != null; - } - - static final Unsafe UNSAFE; - - static { - Unsafe unsafe = null; - try { - Class clazz = Class.forName("sun.misc.Unsafe"); - Field theUnsafe = clazz.getDeclaredField("theUnsafe"); - theUnsafe.setAccessible(true); - Object instance = theUnsafe.get(null); - if (instance.getClass() == clazz) { - // Validate that this Unsafe instance exposes all methods we need - clazz.getDeclaredMethod("getByte", Object.class, long.class); - clazz.getDeclaredMethod("putByte", Object.class, long.class, byte.class); - clazz.getDeclaredMethod("getShort", Object.class, long.class); - clazz.getDeclaredMethod("putShort", Object.class, long.class, short.class); - clazz.getDeclaredMethod("getInt", Object.class, long.class); - clazz.getDeclaredMethod("putInt", Object.class, long.class, int.class); - clazz.getDeclaredMethod("getLong", Object.class, long.class); - clazz.getDeclaredMethod("putLong", Object.class, long.class, long.class); - clazz.getDeclaredMethod("getFloat", Object.class, long.class); - clazz.getDeclaredMethod("putFloat", Object.class, long.class, float.class); - clazz.getDeclaredMethod("getDouble", Object.class, long.class); - clazz.getDeclaredMethod("putDouble", Object.class, long.class, double.class); - clazz.getDeclaredMethod("getBoolean", Object.class, long.class); - clazz.getDeclaredMethod("putBoolean", Object.class, long.class, boolean.class); - clazz.getDeclaredMethod("copyMemory", Object.class, long.class, Object.class, long.class, long.class); - clazz.getDeclaredMethod("arrayBaseOffset", Class.class); - clazz.getDeclaredMethod("arrayIndexScale", Class.class); - unsafe = (Unsafe) instance; - } - } catch (ClassNotFoundException | NoSuchMethodException | NoSuchFieldException | SecurityException | IllegalAccessException | ClassCastException ex) { - // Do nothing, keep unsafe as null - } - UNSAFE = unsafe; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/AbstractDenseNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/AbstractDenseNdArray.java deleted file mode 100644 index 0497095116e..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/AbstractDenseNdArray.java +++ /dev/null @@ -1,163 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.NdArraySequence; -import org.tensorflow.ndarray.impl.AbstractNdArray; -import org.tensorflow.ndarray.impl.dimension.RelativeDimensionalSpace; -import org.tensorflow.ndarray.impl.sequence.FastElementSequence; -import org.tensorflow.ndarray.index.Index; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBufferWindow; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; -import org.tensorflow.ndarray.impl.sequence.SlicingElementSequence; -import org.tensorflow.ndarray.impl.sequence.SingleElementSequence; - -@SuppressWarnings("unchecked") -public abstract class AbstractDenseNdArray> extends AbstractNdArray { - - @Override - public NdArraySequence elements(int dimensionIdx) { - if (dimensionIdx >= shape().numDimensions()) { - throw new IllegalArgumentException("Cannot iterate elements in dimension '" + dimensionIdx + - "' of array with shape " + shape()); - } - if (rank() == 0 && dimensionIdx < 0) { - return new SingleElementSequence<>(this); - } - DimensionalSpace elemDims = dimensions().from(dimensionIdx + 1); - try { - DataBufferWindow> elemWindow = buffer().window(elemDims.physicalSize()); - U element = instantiate(elemWindow.buffer(), elemDims); - return new FastElementSequence(this, dimensionIdx, element, elemWindow); - } catch (UnsupportedOperationException e) { - // If buffer windows are not supported, fallback to slicing (and slower) sequence - return new SlicingElementSequence<>(this, dimensionIdx, elemDims); - } - } - - @Override - public U slice(long position, DimensionalSpace sliceDimensions) { - DataBuffer sliceBuffer = buffer().slice(position, sliceDimensions.physicalSize()); - return instantiate(sliceBuffer, sliceDimensions); - } - - @Override - public U slice(Index... indices) { - if (indices == null) { - throw new IllegalArgumentException("Slicing requires at least one index"); - } - RelativeDimensionalSpace sliceDimensions = dimensions().mapTo(indices); - return slice(sliceDimensions.position(), sliceDimensions); - } - - @Override - public U get(long... coords) { - return slice(positionOf(coords, false), dimensions().from(coords.length)); - } - - @Override - public T getObject(long... coords) { - return buffer().getObject(positionOf(coords, true)); - } - - @Override - public U set(NdArray src, long... coordinates) { - src.copyTo((coordinates == null || coordinates.length == 0) ? this : get(coordinates)); - return (U)this; - } - - @Override - public U setObject(T value, long... coords) { - buffer().setObject(value, positionOf(coords, true)); - return (U)this; - } - - @Override - public U read(DataBuffer dst) { - Validator.readToBufferArgs(this, dst); - DataTransfer.execute(buffer(), dimensions(), dst, DataTransfer::ofValue); - return (U)this; - } - - @Override - public U write(DataBuffer src) { - Validator.writeFromBufferArgs(this, src); - DataTransfer.execute(src, buffer(), dimensions(), DataTransfer::ofValue); - return (U)this; - } - - @Override - public int hashCode() { - if (dimensions().isSegmented()) { - return slowHashCode(); - } - final int prime = 31; - int result = 1; - result = prime * result + buffer().hashCode(); - result = prime * result + shape().hashCode(); - return result; - } - - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (!(obj instanceof AbstractDenseNdArray)) { - return super.equals(obj); - } - AbstractDenseNdArray other = (AbstractDenseNdArray)obj; - if (dimensions().isSegmented() || other.dimensions().isSegmented()) { - return slowEquals(other); - } - if (!shape().equals(other.shape())) { - return false; - } - return buffer().equals(other.buffer()); - } - - protected AbstractDenseNdArray(DimensionalSpace dimensions) { - super(dimensions); - } - - abstract protected DataBuffer buffer(); - - abstract U instantiate(DataBuffer buffer, DimensionalSpace dimensions); - - long positionOf(long[] coords, boolean isValue) { - if (coords == null || coords.length == 0) { - return 0; - } - Validator.coordinates(dimensions, coords, isValue); - return dimensions.positionOf(coords); - } - - @Override - protected void slowCopyTo(NdArray array) { - if (array instanceof AbstractDenseNdArray) { - AbstractDenseNdArray dst = (AbstractDenseNdArray)array; - long offset = 0L; - for (NdArray s : scalars()) { - dst.buffer().setObject(s.getObject(), offset++); - } - } else { - super.slowCopyTo(array); - } - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/BooleanDenseNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/BooleanDenseNdArray.java deleted file mode 100644 index 0764146f962..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/BooleanDenseNdArray.java +++ /dev/null @@ -1,91 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.BooleanNdArray; -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -public class BooleanDenseNdArray extends AbstractDenseNdArray - implements BooleanNdArray { - - public static BooleanNdArray create(BooleanDataBuffer buffer, Shape shape) { - Validator.denseShape(buffer, shape); - return new BooleanDenseNdArray(buffer, shape); - } - - @Override - public boolean getBoolean(long... indices) { - return buffer.getBoolean(positionOf(indices, true)); - } - - @Override - public BooleanNdArray setBoolean(boolean value, long... indices) { - buffer.setBoolean(value, positionOf(indices, true)); - return this; - } - - @Override - public BooleanNdArray copyTo(NdArray dst) { - Validator.copyToNdArrayArgs(this, dst); - if (dst instanceof BooleanDenseNdArray) { - BooleanDenseNdArray booleanDst = (BooleanDenseNdArray)dst; - DataTransfer.execute(buffer, dimensions(), booleanDst.buffer, booleanDst.dimensions(), DataTransfer::ofBoolean); - } else { - slowCopyTo(dst); - } - return this; - } - - @Override - public BooleanNdArray read(BooleanDataBuffer dst) { - Validator.readToBufferArgs(this, dst); - DataTransfer.execute(buffer, dimensions(), dst, DataTransfer::ofBoolean); - return this; - } - - @Override - public BooleanNdArray write(BooleanDataBuffer src) { - Validator.writeFromBufferArgs(this, src); - DataTransfer.execute(src, buffer, dimensions(), DataTransfer::ofBoolean); - return this; - } - - protected BooleanDenseNdArray(BooleanDataBuffer buffer, Shape shape) { - this(buffer, DimensionalSpace.create(shape)); - } - - @Override - BooleanDenseNdArray instantiate(DataBuffer buffer, DimensionalSpace dimensions) { - return new BooleanDenseNdArray((BooleanDataBuffer)buffer, dimensions); - } - - @Override - protected BooleanDataBuffer buffer() { - return buffer; - } - - private final BooleanDataBuffer buffer; - - private BooleanDenseNdArray(BooleanDataBuffer buffer, DimensionalSpace dimensions) { - super(dimensions); - this.buffer = buffer; - } -} \ No newline at end of file diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/ByteDenseNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/ByteDenseNdArray.java deleted file mode 100644 index 172432b5939..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/ByteDenseNdArray.java +++ /dev/null @@ -1,91 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.ByteNdArray; -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -public class ByteDenseNdArray extends AbstractDenseNdArray - implements ByteNdArray { - - public static ByteNdArray create(ByteDataBuffer buffer, Shape shape) { - Validator.denseShape(buffer, shape); - return new ByteDenseNdArray(buffer, shape); - } - - @Override - public byte getByte(long... indices) { - return buffer.getByte(positionOf(indices, true)); - } - - @Override - public ByteNdArray setByte(byte value, long... indices) { - buffer.setByte(value, positionOf(indices, true)); - return this; - } - - @Override - public ByteNdArray copyTo(NdArray dst) { - Validator.copyToNdArrayArgs(this, dst); - if (dst instanceof ByteDenseNdArray) { - ByteDenseNdArray byteDst = (ByteDenseNdArray)dst; - DataTransfer.execute(buffer, dimensions(), byteDst.buffer, byteDst.dimensions(), DataTransfer::ofByte); - } else { - slowCopyTo(dst); - } - return this; - } - - @Override - public ByteNdArray read(ByteDataBuffer dst) { - Validator.readToBufferArgs(this, dst); - DataTransfer.execute(buffer, dimensions(), dst, DataTransfer::ofByte); - return this; - } - - @Override - public ByteNdArray write(ByteDataBuffer src) { - Validator.writeFromBufferArgs(this, src); - DataTransfer.execute(src, buffer, dimensions(), DataTransfer::ofByte); - return this; - } - - protected ByteDenseNdArray(ByteDataBuffer buffer, Shape shape) { - this(buffer, DimensionalSpace.create(shape)); - } - - @Override - ByteDenseNdArray instantiate(DataBuffer buffer, DimensionalSpace dimensions) { - return new ByteDenseNdArray((ByteDataBuffer)buffer, dimensions); - } - - @Override - protected ByteDataBuffer buffer() { - return buffer; - } - - private final ByteDataBuffer buffer; - - private ByteDenseNdArray(ByteDataBuffer buffer, DimensionalSpace dimensions) { - super(dimensions); - this.buffer = buffer; - } -} \ No newline at end of file diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/DataTransfer.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/DataTransfer.java deleted file mode 100644 index d3afa223231..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/DataTransfer.java +++ /dev/null @@ -1,136 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; -import org.tensorflow.ndarray.impl.sequence.PositionIterator; - -final class DataTransfer { - - @FunctionalInterface - interface OfValue> { - void copy(B srcBuffer, long srcIndex, B dstBuffer, long dstIndex); - } - - static > void ofValue(B srcBuf, long srcIdx, B dstBuf, long dstIdx) { - dstBuf.setObject(srcBuf.getObject(srcIdx), dstIdx); - } - - static void ofByte(ByteDataBuffer srcBuf, long srcIdx, ByteDataBuffer dstBuf, long dstIdx) { - dstBuf.setByte(srcBuf.getByte(srcIdx), dstIdx); - } - - static void ofInt(IntDataBuffer srcBuf, long srcIdx, IntDataBuffer dstBuf, long dstIdx) { - dstBuf.setInt(srcBuf.getInt(srcIdx), dstIdx); - } - - static void ofLong(LongDataBuffer srcBuf, long srcIdx, LongDataBuffer dstBuf, long dstIdx) { - dstBuf.setLong(srcBuf.getLong(srcIdx), dstIdx); - } - - static void ofDouble(DoubleDataBuffer srcBuf, long srcIdx, DoubleDataBuffer dstBuf, long dstIdx) { - dstBuf.setDouble(srcBuf.getDouble(srcIdx), dstIdx); - } - - static void ofFloat(FloatDataBuffer srcBuf, long srcIdx, FloatDataBuffer dstBuf, long dstIdx) { - dstBuf.setFloat(srcBuf.getFloat(srcIdx), dstIdx); - } - - static void ofShort(ShortDataBuffer srcBuf, long srcIdx, ShortDataBuffer dstBuf, long dstIdx) { - dstBuf.setShort(srcBuf.getShort(srcIdx), dstIdx); - } - - static void ofBoolean(BooleanDataBuffer srcBuf, long srcIdx, BooleanDataBuffer dstBuf, long dstIdx) { - dstBuf.setBoolean(srcBuf.getBoolean(srcIdx), dstIdx); - } - - static > void execute(B srcBuffer, DimensionalSpace srcDimensions, B dstBuffer, DimensionalSpace dstDimensions, OfValue valueTransfer) { - if (srcDimensions.isSegmented() || dstDimensions.isSegmented()) { - int segmentationIdx = Math.max(srcDimensions.segmentationIdx(), dstDimensions.segmentationIdx()); - copyByElement( - srcBuffer, - PositionIterator.create(srcDimensions, segmentationIdx), - dstBuffer, - PositionIterator.create(dstDimensions, segmentationIdx), - srcDimensions.get(segmentationIdx).elementSize(), - valueTransfer - ); - } else { - srcBuffer.copyTo(dstBuffer, srcDimensions.physicalSize()); - } - } - - static > void execute(B srcBuffer, B dstBuffer, DimensionalSpace dstDimensions, OfValue valueTransfer) { - if (dstDimensions.isSegmented()) { - long elementSize = dstDimensions.get(dstDimensions.segmentationIdx()).elementSize(); - copyByElement( - srcBuffer, - PositionIterator.sequence(elementSize, srcBuffer.size()), - dstBuffer, - PositionIterator.create(dstDimensions, dstDimensions.segmentationIdx()), - elementSize, - valueTransfer - ); - } else { - srcBuffer.copyTo(dstBuffer, dstDimensions.physicalSize()); - } - } - - static > void execute(B srcBuffer, DimensionalSpace srcDimensions, B dstBuffer, OfValue valueTransfer) { - if (srcDimensions.isSegmented()) { - long elementSize = srcDimensions.get(srcDimensions.segmentationIdx()).elementSize(); - copyByElement( - srcBuffer, - PositionIterator.create(srcDimensions, srcDimensions.segmentationIdx()), - dstBuffer, - PositionIterator.sequence(elementSize, dstBuffer.size()), - elementSize, - valueTransfer - ); - } else { - srcBuffer.copyTo(dstBuffer, srcDimensions.physicalSize()); - } - } - - private static > void copyByElement( - B srcBuffer, - PositionIterator srcIterator, - B dstBuffer, - PositionIterator dstIterator, - long elementSize, - OfValue valueTransfer - ) { - if (elementSize == 1) { - while (srcIterator.hasNext()) { - valueTransfer.copy(srcBuffer, srcIterator.nextLong(), dstBuffer, dstIterator.nextLong()); - } - } else { - while (srcIterator.hasNext()) { - srcBuffer.offset(srcIterator.nextLong()).copyTo(dstBuffer.offset(dstIterator.nextLong()), elementSize); - } - } - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/DenseNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/DenseNdArray.java deleted file mode 100644 index 819d95de2fc..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/DenseNdArray.java +++ /dev/null @@ -1,63 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -public class DenseNdArray extends AbstractDenseNdArray> { - - public static NdArray wrap(DataBuffer buffer, Shape shape) { - Validator.denseShape(buffer, shape); - return new DenseNdArray<>(buffer, shape); - } - - @Override - public NdArray copyTo(NdArray dst) { - Validator.copyToNdArrayArgs(this, dst); - if (dst instanceof DenseNdArray) { - DenseNdArray denseDst = (DenseNdArray)dst; - DataTransfer.execute(buffer, dimensions(), denseDst.buffer, denseDst.dimensions(), DataTransfer::ofValue); - } else { - slowCopyTo(dst); - } - return this; - } - - protected DenseNdArray(DataBuffer buffer, Shape shape) { - this(buffer, DimensionalSpace.create(shape)); - } - - @Override - DenseNdArray instantiate(DataBuffer buffer, DimensionalSpace dimensions) { - return new DenseNdArray<>(buffer, dimensions); - } - - @Override - protected DataBuffer buffer() { - return buffer; - } - - private final DataBuffer buffer; - - private DenseNdArray(DataBuffer buffer, DimensionalSpace dimensions) { - super(dimensions); - this.buffer = buffer; - } -} \ No newline at end of file diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/DoubleDenseNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/DoubleDenseNdArray.java deleted file mode 100644 index f54b8d0347a..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/DoubleDenseNdArray.java +++ /dev/null @@ -1,91 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.DoubleNdArray; -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -public class DoubleDenseNdArray extends AbstractDenseNdArray - implements DoubleNdArray { - - public static DoubleNdArray create(DoubleDataBuffer buffer, Shape shape) { - Validator.denseShape(buffer, shape); - return new DoubleDenseNdArray(buffer, shape); - } - - @Override - public double getDouble(long... indices) { - return buffer.getDouble(positionOf(indices, true)); - } - - @Override - public DoubleNdArray setDouble(double value, long... indices) { - buffer.setDouble(value, positionOf(indices, true)); - return this; - } - - @Override - public DoubleNdArray copyTo(NdArray dst) { - Validator.copyToNdArrayArgs(this, dst); - if (dst instanceof DoubleDenseNdArray) { - DoubleDenseNdArray doubleDst = (DoubleDenseNdArray)dst; - DataTransfer.execute(buffer, dimensions(), doubleDst.buffer, doubleDst.dimensions(), DataTransfer::ofDouble); - } else { - slowCopyTo(dst); - } - return this; - } - - @Override - public DoubleNdArray read(DoubleDataBuffer dst) { - Validator.readToBufferArgs(this, dst); - DataTransfer.execute(buffer, dimensions(), dst, DataTransfer::ofDouble); - return this; - } - - @Override - public DoubleNdArray write(DoubleDataBuffer src) { - Validator.writeFromBufferArgs(this, src); - DataTransfer.execute(src, buffer, dimensions(), DataTransfer::ofDouble); - return this; - } - - protected DoubleDenseNdArray(DoubleDataBuffer buffer, Shape shape) { - this(buffer, DimensionalSpace.create(shape)); - } - - @Override - DoubleDenseNdArray instantiate(DataBuffer buffer, DimensionalSpace dimensions) { - return new DoubleDenseNdArray((DoubleDataBuffer)buffer, dimensions); - } - - @Override - protected DoubleDataBuffer buffer() { - return buffer; - } - - private final DoubleDataBuffer buffer; - - private DoubleDenseNdArray(DoubleDataBuffer buffer, DimensionalSpace dimensions) { - super(dimensions); - this.buffer = buffer; - } -} \ No newline at end of file diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/FloatDenseNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/FloatDenseNdArray.java deleted file mode 100644 index 196b5ef8b11..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/FloatDenseNdArray.java +++ /dev/null @@ -1,91 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.FloatNdArray; -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -public class FloatDenseNdArray extends AbstractDenseNdArray - implements FloatNdArray { - - public static FloatNdArray create(FloatDataBuffer buffer, Shape shape) { - Validator.denseShape(buffer, shape); - return new FloatDenseNdArray(buffer, shape); - } - - @Override - public float getFloat(long... indices) { - return buffer.getFloat(positionOf(indices, true)); - } - - @Override - public FloatNdArray setFloat(float value, long... indices) { - buffer.setFloat(value, positionOf(indices, true)); - return this; - } - - @Override - public FloatNdArray copyTo(NdArray dst) { - Validator.copyToNdArrayArgs(this, dst); - if (dst instanceof FloatDenseNdArray) { - FloatDenseNdArray floatDst = (FloatDenseNdArray)dst; - DataTransfer.execute(buffer, dimensions(), floatDst.buffer, floatDst.dimensions(), DataTransfer::ofFloat); - } else { - slowCopyTo(dst); - } - return this; - } - - @Override - public FloatNdArray read(FloatDataBuffer dst) { - Validator.readToBufferArgs(this, dst); - DataTransfer.execute(buffer, dimensions(), dst, DataTransfer::ofFloat); - return this; - } - - @Override - public FloatNdArray write(FloatDataBuffer src) { - Validator.writeFromBufferArgs(this, src); - DataTransfer.execute(src, buffer, dimensions(), DataTransfer::ofFloat); - return this; - } - - protected FloatDenseNdArray(FloatDataBuffer buffer, Shape shape) { - this(buffer, DimensionalSpace.create(shape)); - } - - @Override - FloatDenseNdArray instantiate(DataBuffer buffer, DimensionalSpace dimensions) { - return new FloatDenseNdArray((FloatDataBuffer) buffer, dimensions); - } - - @Override - public FloatDataBuffer buffer() { - return buffer; - } - - private final FloatDataBuffer buffer; - - private FloatDenseNdArray(FloatDataBuffer buffer, DimensionalSpace dimensions) { - super(dimensions); - this.buffer = buffer; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/IntDenseNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/IntDenseNdArray.java deleted file mode 100644 index a7af498dd6f..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/IntDenseNdArray.java +++ /dev/null @@ -1,91 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.IntNdArray; -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -public class IntDenseNdArray extends AbstractDenseNdArray - implements IntNdArray { - - public static IntNdArray create(IntDataBuffer buffer, Shape shape) { - Validator.denseShape(buffer, shape); - return new IntDenseNdArray(buffer, shape); - } - - @Override - public int getInt(long... indices) { - return buffer.getInt(positionOf(indices, true)); - } - - @Override - public IntNdArray setInt(int value, long... indices) { - buffer.setInt(value, positionOf(indices, true)); - return this; - } - - @Override - public IntNdArray copyTo(NdArray dst) { - Validator.copyToNdArrayArgs(this, dst); - if (dst instanceof IntDenseNdArray) { - IntDenseNdArray intDst = (IntDenseNdArray)dst; - DataTransfer.execute(buffer, dimensions(), intDst.buffer, intDst.dimensions(), DataTransfer::ofInt); - } else { - slowCopyTo(dst); - } - return this; - } - - @Override - public IntNdArray read(IntDataBuffer dst) { - Validator.readToBufferArgs(this, dst); - DataTransfer.execute(buffer, dimensions(), dst, DataTransfer::ofInt); - return this; - } - - @Override - public IntNdArray write(IntDataBuffer src) { - Validator.writeFromBufferArgs(this, src); - DataTransfer.execute(src, buffer, dimensions(), DataTransfer::ofInt); - return this; - } - - protected IntDenseNdArray(IntDataBuffer buffer, Shape shape) { - this(buffer, DimensionalSpace.create(shape)); - } - - @Override - IntDenseNdArray instantiate(DataBuffer buffer, DimensionalSpace dimensions) { - return new IntDenseNdArray((IntDataBuffer)buffer, dimensions); - } - - @Override - protected IntDataBuffer buffer() { - return buffer; - } - - private final IntDataBuffer buffer; - - private IntDenseNdArray(IntDataBuffer buffer, DimensionalSpace dimensions) { - super(dimensions); - this.buffer = buffer; - } -} \ No newline at end of file diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/LongDenseNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/LongDenseNdArray.java deleted file mode 100644 index cd56dadfb2b..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/LongDenseNdArray.java +++ /dev/null @@ -1,91 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.LongNdArray; -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -public class LongDenseNdArray extends AbstractDenseNdArray - implements LongNdArray { - - public static LongNdArray create(LongDataBuffer buffer, Shape shape) { - Validator.denseShape(buffer, shape); - return new LongDenseNdArray(buffer, shape); - } - - @Override - public long getLong(long... indices) { - return buffer.getLong(positionOf(indices, true)); - } - - @Override - public LongNdArray setLong(long value, long... indices) { - buffer.setLong(value, positionOf(indices, true)); - return this; - } - - @Override - public LongNdArray copyTo(NdArray dst) { - Validator.copyToNdArrayArgs(this, dst); - if (dst instanceof LongDenseNdArray) { - LongDenseNdArray longDst = (LongDenseNdArray)dst; - DataTransfer.execute(buffer, dimensions(), longDst.buffer, longDst.dimensions(), DataTransfer::ofLong); - } else { - slowCopyTo(dst); - } - return this; - } - - @Override - public LongNdArray read(LongDataBuffer dst) { - Validator.readToBufferArgs(this, dst); - DataTransfer.execute(buffer, dimensions(), dst, DataTransfer::ofLong); - return this; - } - - @Override - public LongNdArray write(LongDataBuffer src) { - Validator.writeFromBufferArgs(this, src); - DataTransfer.execute(src, buffer, dimensions(), DataTransfer::ofLong); - return this; - } - - protected LongDenseNdArray(LongDataBuffer buffer, Shape shape) { - this(buffer, DimensionalSpace.create(shape)); - } - - @Override - LongDenseNdArray instantiate(DataBuffer buffer, DimensionalSpace dimensions) { - return new LongDenseNdArray((LongDataBuffer)buffer, dimensions); - } - - @Override - protected LongDataBuffer buffer() { - return buffer; - } - - private final LongDataBuffer buffer; - - private LongDenseNdArray(LongDataBuffer buffer, DimensionalSpace dimensions) { - super(dimensions); - this.buffer = buffer; - } -} \ No newline at end of file diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/ShortDenseNdArray.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/ShortDenseNdArray.java deleted file mode 100644 index 291c01ac8e1..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/ShortDenseNdArray.java +++ /dev/null @@ -1,91 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.ShortNdArray; -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -public class ShortDenseNdArray extends AbstractDenseNdArray - implements ShortNdArray { - - public static ShortNdArray create(ShortDataBuffer buffer, Shape shape) { - Validator.denseShape(buffer, shape); - return new ShortDenseNdArray(buffer, shape); - } - - @Override - public short getShort(long... indices) { - return buffer.getShort(positionOf(indices, true)); - } - - @Override - public ShortNdArray setShort(short value, long... indices) { - buffer.setShort(value, positionOf(indices, true)); - return this; - } - - @Override - public ShortNdArray copyTo(NdArray dst) { - Validator.copyToNdArrayArgs(this, dst); - if (dst instanceof ShortDenseNdArray) { - ShortDenseNdArray shortDst = (ShortDenseNdArray)dst; - DataTransfer.execute(buffer, dimensions(), shortDst.buffer, shortDst.dimensions(), DataTransfer::ofShort); - } else { - slowCopyTo(dst); - } - return this; - } - - @Override - public ShortNdArray read(ShortDataBuffer dst) { - Validator.readToBufferArgs(this, dst); - DataTransfer.execute(buffer, dimensions(), dst, DataTransfer::ofShort); - return this; - } - - @Override - public ShortNdArray write(ShortDataBuffer src) { - Validator.writeFromBufferArgs(this, src); - DataTransfer.execute(src, buffer, dimensions(), DataTransfer::ofShort); - return this; - } - - protected ShortDenseNdArray(ShortDataBuffer buffer, Shape shape) { - this(buffer, DimensionalSpace.create(shape)); - } - - @Override - ShortDenseNdArray instantiate(DataBuffer buffer, DimensionalSpace dimensions) { - return new ShortDenseNdArray((ShortDataBuffer)buffer, dimensions); - } - - @Override - protected ShortDataBuffer buffer() { - return buffer; - } - - private final ShortDataBuffer buffer; - - private ShortDenseNdArray(ShortDataBuffer buffer, DimensionalSpace dimensions) { - super(dimensions); - this.buffer = buffer; - } -} \ No newline at end of file diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/Validator.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/Validator.java deleted file mode 100644 index b0bcae252fb..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dense/Validator.java +++ /dev/null @@ -1,49 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.IllegalRankException; -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -final class Validator extends org.tensorflow.ndarray.impl.Validator { - - static void coordinates(DimensionalSpace dimensions, long[] coords, - boolean isValue) { - if (coords.length > dimensions.numDimensions()) { - throw new IndexOutOfBoundsException(); - } - if (isValue && coords.length != dimensions.numDimensions()) { - throw new IllegalRankException("Not a scalar value"); - } - } - - static void denseShape(DataBuffer buffer, Shape shape) { - if (shape == null) { - throw new IllegalArgumentException("Shape cannot be null"); - } - if (shape.hasUnknownDimension()) { - throw new IllegalArgumentException("Dense arrays cannot have unknown dimension(s)"); - } - if (buffer.size() < shape.size()) { - throw new IllegalArgumentException("Buffer size is smaller than the shape size"); - }; - } - - private Validator() {} -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/AbstractDimension.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/AbstractDimension.java deleted file mode 100644 index f2a0fb05b6e..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/AbstractDimension.java +++ /dev/null @@ -1,45 +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.ndarray.impl.dimension; - -abstract class AbstractDimension implements Dimension { - - /** - * Dimensions are known to be equal if they have the same number of elements - */ - @Override - public int hashCode() { - final int prime = 17; - long numElements = numElements(); - return 31 * prime + (int)(numElements ^ (numElements >>> 32)); - } - - /** - * Dimensions are known to be equal if they have the same number of elements - */ - @Override - public boolean equals(Object obj) { - if (this == obj) { - return true; - } - if (obj instanceof Dimension) { - Dimension otherDimension = (Dimension) obj; - return numElements() == otherDimension.numElements(); - } - return false; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/Axis.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/Axis.java deleted file mode 100644 index 91973c752a1..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/Axis.java +++ /dev/null @@ -1,61 +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.ndarray.impl.dimension; - -final class Axis extends AbstractDimension { - - @Override - public long numElements() { - return numElements; - } - - @Override - public long positionOf(long coord) { - if (coord >= numElements) { - throw new IndexOutOfBoundsException(); - } - return elementSize * coord; - } - - @Override - public boolean isSegmented() { - return false; // all axis are continuous - } - - @Override - public long elementSize() { - return elementSize; - } - - @Override - public long physicalSize() { - return elementSize * numElements; - } - - @Override - public String toString() { - return String.valueOf(numElements); - } - - Axis(long numElements, long elementSize) { - this.numElements = numElements; - this.elementSize = elementSize; - } - - private final long numElements; - private final long elementSize; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/Dimension.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/Dimension.java deleted file mode 100644 index cbae2d897a8..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/Dimension.java +++ /dev/null @@ -1,36 +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.ndarray.impl.dimension; - -import org.tensorflow.ndarray.index.Index; - -public interface Dimension { - - default Dimension withIndex(Index index) { - return new IndexedDimension(index, this); - } - - long numElements(); - - long elementSize(); - - long physicalSize(); - - long positionOf(long coord); - - boolean isSegmented(); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/DimensionalSpace.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/DimensionalSpace.java deleted file mode 100644 index 7d0f0222bbe..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/DimensionalSpace.java +++ /dev/null @@ -1,224 +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.ndarray.impl.dimension; - -import java.util.Arrays; -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.index.Index; - -public class DimensionalSpace { - - public static DimensionalSpace create(Shape shape) { - Dimension[] dimensions = new Dimension[shape.numDimensions()]; - - // Start from the last dimension, where all elements are continuous - for (int i = dimensions.length - 1, elementSize = 1; i >= 0; --i) { - dimensions[i] = new Axis(shape.size(i), elementSize); - elementSize *= dimensions[i].numElements(); - } - return new DimensionalSpace(dimensions, shape); - } - - public RelativeDimensionalSpace mapTo(Index[] indices) { - if (dimensions == null) { - throw new ArrayIndexOutOfBoundsException(); - } - int dimIdx = 0; - int indexIdx = 0; - int newDimIdx = 0; - int segmentationIdx = -1; - long initialOffset = 0; - - int newAxes = 0; - boolean seenEllipsis = false; - for (Index idx : indices) { - if (idx.isNewAxis()) { - newAxes += 1; - } - if (idx.isEllipsis()) { - if (seenEllipsis) { - throw new IllegalArgumentException("Only one ellipsis allowed"); - } else { - seenEllipsis = true; - } - } - } - int newLength = dimensions.length + newAxes; - - Dimension[] newDimensions = new Dimension[newLength]; - while (indexIdx < indices.length) { - - if (indices[indexIdx].isPoint()) { - // When an index targets a single point in a given dimension, calculate the offset of this - // point and cumulate the offset of any subsequent point as well - long offset = 0; - do { - offset += indices[indexIdx].mapCoordinate(0, dimensions[dimIdx]); - dimIdx++; - } while (++indexIdx < indices.length && indices[indexIdx].isPoint()); - - // If this is the first index, then the offset is the position of the whole dimension - // space within the original one. If not, then we apply the offset to the last vectorial - // dimension - if (newDimIdx == 0) { - initialOffset = offset; - } else { - long reducedSize = dimensions[dimIdx - 1].elementSize(); - newDimensions[newDimIdx - 1] = new ReducedDimension(newDimensions[newDimIdx - 1], offset, reducedSize); - segmentationIdx = newDimIdx - 1; - } - - } else if (indices[indexIdx].isNewAxis()) { - long newSize; - if (dimIdx == 0) { - // includes everything. Should really include future reduction (at()) but that doesn't seem to cause issues - // elsewhere - newSize = dimensions[0].numElements() * dimensions[0].elementSize(); - } else { - newSize = dimensions[dimIdx - 1].elementSize(); - } - - newDimensions[newDimIdx] = new Axis(1, newSize); - segmentationIdx = newDimIdx; // is this correct? - ++newDimIdx; - ++indexIdx; - } else if (indices[indexIdx].isEllipsis()) { - int remainingDimensions = dimensions.length - dimIdx; - int requiredDimensions = 0; - for (int i = indexIdx + 1; i < indices.length; i++) { - if (!indices[i].isNewAxis()) { - requiredDimensions++; - } - } - // while the number of dimensions left < the number of indices that consume axes - while (remainingDimensions > requiredDimensions) { - Dimension dim = dimensions[dimIdx++]; - if (dim.isSegmented()) { - segmentationIdx = newDimIdx; - } - newDimensions[newDimIdx++] = dim; - remainingDimensions--; - } - indexIdx++; - } else { - // Map any other index to the appropriate dimension of this space - Dimension newDimension = indices[indexIdx].apply(dimensions[dimIdx++]); - newDimensions[newDimIdx] = newDimension; - if (newDimension.isSegmented()) { - segmentationIdx = newDimIdx; - } - ++newDimIdx; - ++indexIdx; - } - } - - // When the number of indices provided is smaller than the number of dimensions in this space, - // we copy the remaining dimensions directly to the new space as well. - for (; dimIdx < dimensions.length; ++dimIdx, ++newDimIdx) { - Dimension dim = dimensions[dimIdx]; - newDimensions[newDimIdx] = dim; - if (dim.isSegmented()) { - segmentationIdx = newDimIdx; - } - } - return new RelativeDimensionalSpace(Arrays.copyOf(newDimensions, newDimIdx), segmentationIdx, initialOffset); - } - - public DimensionalSpace from(int dimensionStart) { - if (dimensionStart > dimensions.length) { - throw new IndexOutOfBoundsException(); - } - Dimension[] newDimensions = Arrays.copyOfRange(dimensions, dimensionStart, dimensions.length); - if (segmentationIdx > dimensionStart) { - return new DimensionalSpace(newDimensions, segmentationIdx - dimensionStart); - } - return new DimensionalSpace(newDimensions); - } - - public Shape shape() { - if (shape == null) { - shape = toShape(dimensions); - } - return shape; - } - - public int numDimensions() { - return dimensions.length; - } - - public long numElements(int i) { - return dimensions[i].numElements(); - } - - public long physicalSize() { - return dimensions.length > 0 ? dimensions[0].physicalSize() : 1; // dimensions.length == 0 for scalars - } - - public Dimension get(int i) { - return dimensions[i]; - } - - public boolean isSegmented() { - return segmentationIdx >= 0; - } - - public int segmentationIdx() { - return segmentationIdx; - } - - public long positionOf(long[] coords) { - long position = 0L; - for (int i = 0; i < coords.length; ++i) { - position += dimensions[i].positionOf(coords[i]); - } - return position; - } - - /** Succinct description of the shape meant for debugging. */ - @Override - public String toString() { - return Arrays.toString(dimensions); - } - - DimensionalSpace(Dimension[] dimensions, int segmentationIdx) { - this.dimensions = dimensions; - this.segmentationIdx = segmentationIdx; - } - - private DimensionalSpace(Dimension[] dimensions) { - this(dimensions, -1); - } - - private DimensionalSpace(Dimension[] dimensions, Shape shape) { - this(dimensions); - this.shape = shape; - } - - private final Dimension[] dimensions; - private final int segmentationIdx; - private Shape shape; - - private static Shape toShape(Dimension[] dimensions) { - long[] shapeDimSizes = new long[dimensions.length]; - int i = 0; - for (Dimension dimension : dimensions) { - shapeDimSizes[i++] = dimension.numElements(); - } - return Shape.of(shapeDimSizes); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/IndexedDimension.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/IndexedDimension.java deleted file mode 100644 index 2b609bc3535..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/IndexedDimension.java +++ /dev/null @@ -1,69 +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.ndarray.impl.dimension; - -import org.tensorflow.ndarray.index.Index; - -final class IndexedDimension extends AbstractDimension { - - @Override - public long numElements() { - return numElements; - } - - @Override - public long positionOf(long coord) { - if (coord >= numElements()) { - throw new IndexOutOfBoundsException(); - } - return originalDimension.positionOf(index.mapCoordinate(coord, originalDimension)); - } - - @Override - public boolean isSegmented() { - // TODO (karllessard) for now we consider all indexed dimensions as segmented but might depend - // on the actual index - return true; - } - - @Override - public long elementSize() { - return originalDimension.elementSize(); // indices do not change the size of an inner element - } - - @Override - public long physicalSize() { - // TODO (karllessard) we consider this dimension takes the same amount of memory that the - // original one but might depend on the actual index - return originalDimension.physicalSize(); - } - - @Override - public String toString() { - return String.valueOf(numElements()); - } - - IndexedDimension(Index index, Dimension originalDimension) { - this.index = index; - this.originalDimension = originalDimension; - this.numElements = index.numElements(originalDimension); - } - - private final Index index; - private final Dimension originalDimension; - private final long numElements; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/ReducedDimension.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/ReducedDimension.java deleted file mode 100644 index 4b5cb1adcf8..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/ReducedDimension.java +++ /dev/null @@ -1,62 +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.ndarray.impl.dimension; - -final class ReducedDimension extends AbstractDimension { - - @Override - public long numElements() { - return originalDimension.numElements(); - } - - @Override - public long positionOf(long coord) { - return originalDimension.positionOf(coord) + offset; - } - - @Override - public boolean isSegmented() { - return true; - } - - @Override - public long elementSize() { - return elementSize; - } - - @Override - public long physicalSize() { - // We simplify the computation by assuming that a reduced dimension takes the same amount of - // memory than the original one - return originalDimension.physicalSize(); - } - - @Override - public String toString() { - return String.valueOf(numElements()); - } - - ReducedDimension(Dimension originalDimension, long offset, long elementSize) { - this.originalDimension = originalDimension; - this.offset = offset; - this.elementSize = elementSize; - } - - private final Dimension originalDimension; - private final long offset; - private final long elementSize; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/RelativeDimensionalSpace.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/RelativeDimensionalSpace.java deleted file mode 100644 index 4259bbcf76e..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/RelativeDimensionalSpace.java +++ /dev/null @@ -1,32 +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.ndarray.impl.dimension; - -public class RelativeDimensionalSpace extends DimensionalSpace { - - public long position() { - return position; - } - - RelativeDimensionalSpace(Dimension[] dimensions, int segmentationIdx, long position) { - super(dimensions, segmentationIdx); - this.position = position; - } - - private long position; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/CoordinatesIncrementor.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/CoordinatesIncrementor.java deleted file mode 100644 index 8c9c9f86f4c..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/CoordinatesIncrementor.java +++ /dev/null @@ -1,38 +0,0 @@ -/* - * 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.ndarray.impl.sequence; - -final class CoordinatesIncrementor { - - boolean increment() { - for (int i = coords.length - 1; i >= 0; --i) { - if ((coords[i] = (coords[i] + 1) % shape[i]) > 0) { - return true; - } - } - return false; - } - - CoordinatesIncrementor(long[] shape, int dimensionIdx) { - this.shape = shape; - this.coords = new long[dimensionIdx + 1]; - } - - final long[] shape; - final long[] coords; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/FastElementSequence.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/FastElementSequence.java deleted file mode 100644 index 92cebeb2338..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/FastElementSequence.java +++ /dev/null @@ -1,81 +0,0 @@ -/* - * 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.ndarray.impl.sequence; - -import java.util.Iterator; -import java.util.function.BiConsumer; - -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.NdArraySequence; -import org.tensorflow.ndarray.buffer.DataBufferWindow; -import org.tensorflow.ndarray.impl.AbstractNdArray; - -/** - * A sequence recycling the same {@code NdArray} instance when iterating its elements - * - * @param Type of the elements - * @param Type of the {@code NdArray} with this sequence - */ -public final class FastElementSequence> implements NdArraySequence { - - public FastElementSequence(AbstractNdArray ndArray, int dimensionIdx, U element, DataBufferWindow elementWindow) { - this.ndArray = ndArray; - this.dimensionIdx = dimensionIdx; - this.element = element; - this.elementWindow = elementWindow; - } - - @Override - public Iterator iterator() { - return new SequenceIterator(); - } - - @Override - public void forEachIndexed(BiConsumer consumer) { - PositionIterator.createIndexed(ndArray.dimensions(), dimensionIdx).forEachIndexed((long[] coords, long position) -> { - elementWindow.slideTo(position); - consumer.accept(coords, element); - }); - } - - @Override - public NdArraySequence asSlices() { - return new SlicingElementSequence(ndArray, dimensionIdx); - } - - private class SequenceIterator implements Iterator { - - @Override - public boolean hasNext() { - return positionIterator.hasNext(); - } - - @Override - public U next() { - elementWindow.slideTo(positionIterator.nextLong()); - return element; - } - - private final PositionIterator positionIterator = PositionIterator.create(ndArray.dimensions(), dimensionIdx); - } - - private final AbstractNdArray ndArray; - private final int dimensionIdx; - private final U element; - private final DataBufferWindow elementWindow; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/IndexedPositionIterator.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/IndexedPositionIterator.java deleted file mode 100644 index 30ece1599b6..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/IndexedPositionIterator.java +++ /dev/null @@ -1,28 +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.ndarray.impl.sequence; - -public interface IndexedPositionIterator extends PositionIterator { - - @FunctionalInterface - interface CoordsLongConsumer { - void consume(long[] coords, long position); - } - - void forEachIndexed(CoordsLongConsumer consumer); -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/IndexedSequentialPositionIterator.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/IndexedSequentialPositionIterator.java deleted file mode 100644 index 80b3de681bd..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/IndexedSequentialPositionIterator.java +++ /dev/null @@ -1,51 +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.ndarray.impl.sequence; - -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -class IndexedSequentialPositionIterator extends SequentialPositionIterator implements IndexedPositionIterator { - - @Override - public void forEachIndexed(CoordsLongConsumer consumer) { - while (hasNext()) { - consumer.consume(coords, nextLong()); - incrementCoords(); - } - } - - private void incrementCoords() { - for (int i = coords.length - 1; i >= 0; --i) { - if (coords[i] < shape[i] - 1) { - coords[i] += 1L; - return; - } - coords[i] = 0L; - } - } - - IndexedSequentialPositionIterator(DimensionalSpace dimensions, int dimensionIdx) { - super(dimensions, dimensionIdx); - this.shape = dimensions.shape().asArray(); - this.coords = new long[dimensionIdx + 1]; - //this.coordsIncrementor = new CoordinatesIncrementor(dimensions.shape().asArray(), dimensionIdx); - } - - private final long[] shape; - private final long[] coords; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/NdPositionIterator.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/NdPositionIterator.java deleted file mode 100644 index 789474c58ae..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/NdPositionIterator.java +++ /dev/null @@ -1,70 +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.ndarray.impl.sequence; - -import java.util.NoSuchElementException; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -class NdPositionIterator implements IndexedPositionIterator { - - @Override - public boolean hasNext() { - return coords != null; - } - - @Override - public long nextLong() { - if (!hasNext()) { - throw new NoSuchElementException(); - } - long position = dimensions.positionOf(coords); - increment(); - return position; - } - - @Override - public void forEachIndexed(CoordsLongConsumer consumer) { - while (hasNext()) { - consumer.consume(coords, dimensions.positionOf(coords)); - increment(); - } - } - - private void increment() { - if (!increment(coords, dimensions)) { - coords = null; - } - } - - static boolean increment(long[] coords, DimensionalSpace dimensions) { - for (int i = coords.length - 1; i >= 0; --i) { - if ((coords[i] = (coords[i] + 1) % dimensions.get(i).numElements()) > 0) { - return true; - } - } - return false; - } - - NdPositionIterator(DimensionalSpace dimensions, int dimensionIdx) { - this.dimensions = dimensions; - this.coords = new long[dimensionIdx + 1]; - } - - private final DimensionalSpace dimensions; - private long[] coords; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/PositionIterator.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/PositionIterator.java deleted file mode 100644 index 83ed940563c..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/PositionIterator.java +++ /dev/null @@ -1,42 +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.ndarray.impl.sequence; - -import java.util.PrimitiveIterator; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -public interface PositionIterator extends PrimitiveIterator.OfLong { - - static PositionIterator create(DimensionalSpace dimensions, int dimensionIdx) { - if (dimensions.isSegmented()) { - return new NdPositionIterator(dimensions, dimensionIdx); - } - return new SequentialPositionIterator(dimensions, dimensionIdx); - } - - static IndexedPositionIterator createIndexed(DimensionalSpace dimensions, int dimensionIdx) { - if (dimensions.isSegmented()) { - return new NdPositionIterator(dimensions, dimensionIdx); - } - return new IndexedSequentialPositionIterator(dimensions, dimensionIdx); - } - - static PositionIterator sequence(long stride, long end) { - return new SequentialPositionIterator(stride, end); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/SequentialPositionIterator.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/SequentialPositionIterator.java deleted file mode 100644 index 65c6fc966cc..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/SequentialPositionIterator.java +++ /dev/null @@ -1,55 +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.ndarray.impl.sequence; - -import java.util.NoSuchElementException; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -class SequentialPositionIterator implements PositionIterator { - - @Override - public boolean hasNext() { - return index < end; - } - - @Override - public long nextLong() { - if (!hasNext()) { - throw new NoSuchElementException(); - } - return stride * index++; - } - - SequentialPositionIterator(DimensionalSpace dimensions, int dimensionIdx) { - long size = 1; - for (int i = 0; i <= dimensionIdx; ++i) { - size *= dimensions.get(i).numElements(); - } - this.stride = dimensions.get(dimensionIdx).elementSize(); - this.end = size; - } - - SequentialPositionIterator(long stride, long end) { - this.stride = stride; - this.end = end; - } - - private final long stride; - private final long end; - private long index; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/SingleElementSequence.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/SingleElementSequence.java deleted file mode 100644 index 59525bf486b..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/SingleElementSequence.java +++ /dev/null @@ -1,71 +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.ndarray.impl.sequence; - -import java.util.Iterator; -import java.util.function.BiConsumer; -import org.tensorflow.ndarray.IllegalRankException; -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.NdArraySequence; -import org.tensorflow.ndarray.impl.AbstractNdArray; - -/** - * A sequence of one single element - * - * @param Type of the element - * @param Type of the {@code NdArray} with this sequence - */ -public final class SingleElementSequence> implements NdArraySequence { - - public SingleElementSequence(AbstractNdArray ndArray) { - this.ndArray = ndArray; - } - - @Override - public Iterator iterator() { - return new Iterator() { - - @Override - public boolean hasNext() { - return element != null; - } - - @Override - public U next() { - U ret = element; - element = null; - return ret; - } - - @SuppressWarnings("unchecked") - private U element = (U)ndArray; - }; - } - - @Override - public NdArraySequence asSlices() { - return this; // no need to slice, as there are only one element - } - - @Override - public void forEachIndexed(BiConsumer consumer) { - throw new IllegalRankException("Single element has no coordinates to iterate on, use forEach()"); - } - - private final AbstractNdArray ndArray; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/SlicingElementSequence.java b/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/SlicingElementSequence.java deleted file mode 100644 index 6fe8398ea70..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/impl/sequence/SlicingElementSequence.java +++ /dev/null @@ -1,77 +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.ndarray.impl.sequence; - -import java.util.Iterator; -import java.util.function.BiConsumer; -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.NdArraySequence; -import org.tensorflow.ndarray.impl.AbstractNdArray; -import org.tensorflow.ndarray.impl.dimension.DimensionalSpace; - -/** - * A sequence creating a new {@code NdArray} instance (slice) for each element of an iteration - * - * @param Type of the element - * @param Type of the {@code NdArray} with this sequence - */ -public final class SlicingElementSequence> implements NdArraySequence { - - public SlicingElementSequence(AbstractNdArray ndArray, int dimensionIdx) { - this(ndArray, dimensionIdx, ndArray.dimensions().from(dimensionIdx + 1)); - } - - public SlicingElementSequence(AbstractNdArray ndArray, int dimensionIdx, DimensionalSpace elementDimensions) { - this.ndArray = ndArray; - this.dimensionIdx = dimensionIdx; - this.elementDimensions = elementDimensions; - } - - @Override - public Iterator iterator() { - PositionIterator positionIterator = PositionIterator.create(ndArray.dimensions(), dimensionIdx); - return new Iterator() { - - @Override - public boolean hasNext() { - return positionIterator.hasNext(); - } - - @Override - public U next() { - return ndArray.slice(positionIterator.next(), elementDimensions); - } - }; - } - - @Override - public void forEachIndexed(BiConsumer consumer) { - PositionIterator.createIndexed(ndArray.dimensions(), dimensionIdx).forEachIndexed((long[] coords, long position) -> - consumer.accept(coords, ndArray.slice(position, elementDimensions)) - ); - } - - @Override - public NdArraySequence asSlices() { - return this; - } - - private final AbstractNdArray ndArray; - private final int dimensionIdx; - private final DimensionalSpace elementDimensions; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/index/All.java b/ndarray/src/main/java/org/tensorflow/ndarray/index/All.java deleted file mode 100644 index 9d3139f3248..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/index/All.java +++ /dev/null @@ -1,57 +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.ndarray.index; - -import org.tensorflow.ndarray.impl.dimension.Dimension; - -final class All implements Index { - - static final All INSTANCE = new All(); - - @Override - public long numElements(Dimension dim) { - return dim.numElements(); - } - - @Override - public long mapCoordinate(long coordinate, Dimension dim) { - return coordinate; - } - - @Override - public Dimension apply(Dimension dim) { - return dim; - } - - private All() { - } - - @Override - public boolean beginMask() { - return true; - } - - @Override - public boolean endMask() { - return true; - } - - @Override - public String toString() { - return All.class.getSimpleName() + "()"; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/index/At.java b/ndarray/src/main/java/org/tensorflow/ndarray/index/At.java deleted file mode 100644 index 31ce021ddc8..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/index/At.java +++ /dev/null @@ -1,74 +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.ndarray.index; - -import java.util.StringJoiner; -import org.tensorflow.ndarray.impl.dimension.Dimension; - -final class At implements Index { - - @Override - public long numElements(Dimension dim) { - return 1; - } - - @Override - public long mapCoordinate(long coordinate, Dimension dim) { - long coord = this.coord >= 0 ? this.coord : dim.numElements() + this.coord; - return dim.positionOf(coord); - } - - @Override - public Dimension apply(Dimension dim) { - if (!keepDim) { - throw new UnsupportedOperationException("Should be handled in DimensionalSpace."); - } - - return dim.withIndex(this); - } - - @Override - public boolean isPoint() { - return !keepDim; - } - - At(long coord, boolean keepDim) { - this.coord = coord; - this.keepDim = keepDim; - } - - private final long coord; - private final boolean keepDim; - - @Override - public long begin() { - return coord; - } - - @Override - public long end() { - return coord + 1; - } - - @Override - public String toString() { - return new StringJoiner(", ", At.class.getSimpleName() + "(", ")") - .add("coord=" + coord) - .add("keepDim=" + keepDim) - .toString(); - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/index/Ellipsis.java b/ndarray/src/main/java/org/tensorflow/ndarray/index/Ellipsis.java deleted file mode 100644 index d4085735df2..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/index/Ellipsis.java +++ /dev/null @@ -1,48 +0,0 @@ -/* - 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.ndarray.index; - -import org.tensorflow.ndarray.impl.dimension.Dimension; - -final class Ellipsis implements Index { - - static final Ellipsis INSTANCE = new Ellipsis(); - - private Ellipsis() { - - } - - @Override - public long numElements(Dimension dim) { - throw new UnsupportedOperationException("Should be handled in DimensionalSpace."); - } - - @Override - public long mapCoordinate(long coordinate, Dimension dim) { - throw new UnsupportedOperationException("Should be handled in DimensionalSpace."); - } - - @Override - public boolean isEllipsis() { - return true; - } - - @Override - public String toString() { - return Ellipsis.class.getSimpleName() + "()"; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/index/Hyperslab.java b/ndarray/src/main/java/org/tensorflow/ndarray/index/Hyperslab.java deleted file mode 100644 index 55c4e510748..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/index/Hyperslab.java +++ /dev/null @@ -1,90 +0,0 @@ -/* - * Copyright 2020 Matteo Di Giovinazzo. - * - * 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.ndarray.index; - -import java.util.StringJoiner; -import org.tensorflow.ndarray.impl.dimension.Dimension; - -/** - * A hyperslab is a rectangular pattern defined by four arrays. - * - * The {@code start} defines the origin of the hyperslab in the original coordinates. - * The {@code stride} is the number of elements to increment between selected elements. - * A stride of '1' is every element, a stride of '2' is every second element, etc. - * The default stride is 1. - * The {@code count} is the number of elements in the hyperslab selection. - * When the stride is 1, the selection is a hyper rectangle with a corner at {@code start} - * and size {@code count[0]} by {@code count[1]} by ... - * When stride is greater than one, the hyperslab bounded by start and the corners - * defined by {@code stride[n] * count[n]}. - * The {@code block} is a count on the number of repetitions of the hyperslab. - * The default block size is '1', which is one hyperslab. A block of 2 would be - * two hyperslabs in that dimension, with the second starting at {@code start[n]+ (count[n] * stride[n]) + 1}. - * - * @see https://portal.hdfgroup.org/display/HDF5/Reading+From+or+Writing+To+a+Subset+of+a+Dataset - * @see https://portal.hdfgroup.org/display/HDF5/H5S_SELECT_HYPERSLAB - * @see https://support.hdfgroup.org/HDF5/doc1.6/UG/12_Dataspaces.html - * @author Matteo Di Giovinazzo - */ -final class Hyperslab implements Index { - - @Override - public long numElements(Dimension dimension) { - return count * block; - } - - @Override - public long mapCoordinate(long coordinate, Dimension dimension) { - return start + stride * (coordinate / block) + (coordinate % block); - } - - @Override - public Dimension apply(Dimension dim) { - return dim.withIndex(this); - } - - @Override - public boolean isPoint() { - return false; - } - - Hyperslab(long start, long stride, long count, long block) { - this.start = start; - this.stride = stride; - this.count = count; - this.block = block; - } - - private final long start; - private final long stride; - private final long count; - private final long block; - - @Override - public String toString() { - return new StringJoiner(", ", Hyperslab.class.getSimpleName() + "Hyperslab(", ")") - .add("start=" + start) - .add("stride=" + stride) - .add("count=" + count) - .add("block=" + block) - .toString(); - } - - @Override - public boolean isStridedSlicingCompliant() { - return false; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/index/Index.java b/ndarray/src/main/java/org/tensorflow/ndarray/index/Index.java deleted file mode 100644 index 617ca4d474b..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/index/Index.java +++ /dev/null @@ -1,131 +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.ndarray.index; - -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.impl.dimension.Dimension; - -/** - * An index used for slicing a view out of an N-dimensional array. - * - *

A slice, i.e. a reduced view, of an N-dimensional array is obtain by calling - * {@link NdArray#slice(Index...)}, given a list of indices that select which elements on a given dimension should be - * included/excluded from that view. - */ -public interface Index { - - /** - * Returns the number of elements that can be retrieved using this index on the given dimension. - * - *

An index that maps one-by-one all elements of the dimensions will return a value - * equal to {@code dim.numElements()}, while an index that only maps a subset of these will return a smaller value. - * - * @param dim the indexed dimension - * @return number of elements accessible - */ - long numElements(Dimension dim); - - /** - * Transforms an element coordinate to a new coordinate by applying this index to the given dimension. - * - *

For example, if the coordinate is 0 and this index flips the {@code n} elements on this - * dimension, then the returned value will be {@code n-1}. - * - * @param coordinate coordinate to transform - * @param dim dimension the indexed dimension - * @return transformed coordinate - */ - long mapCoordinate(long coordinate, Dimension dim); - - /** - * Applies this index to the given dimension. - * - *

When accessing the elements from the returned dimension, this index will automatically - * apply and may transform the original position. - * - * @param dim dimension to apply this index to - * @return an indexed dimension - */ - default Dimension apply(Dimension dim) { - return dim.withIndex(this); - } - - /** - * Returns true if this index is a single point, reducing the number of dimensions by one - */ - default boolean isPoint() { - return false; - } - - /** - * Returns true if this index is a new axis, adding a dimension of size 1 - */ - default boolean isNewAxis() { - return false; - } - - /** - * Returns true if this index is an ellipsis, expanding to take as many dimensions as possible (and applying all() to - * them) - */ - default boolean isEllipsis() { - return false; - } - - /** - * Get whether the Index supports strided slice style indexing (using start, end, stride, and flags, i.e. TensorFlow's). - */ - default boolean isStridedSlicingCompliant() { - return true; - } - - /** - * Get the start of the index, for strided slice style indexing. - */ - default long begin() { - return 0; - } - - /** - * Get the end of the index, strided slice style indexing. - */ - default long end() { - return 0; - } - - /** - * Get the stride of the index, for strided slice style indexing. - */ - default long stride() { - return 1; - } - - /** - * Get whether the Index should start at the beginning of the dimension, for strided slice style indexing. - */ - default boolean beginMask() { - return false; - } - - /** - * Get whether the Index should end at the beginning of the dimension, for strided slice style indexing. - */ - default boolean endMask() { - return false; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/index/Indices.java b/ndarray/src/main/java/org/tensorflow/ndarray/index/Indices.java deleted file mode 100644 index 346ab705595..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/index/Indices.java +++ /dev/null @@ -1,363 +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.ndarray.index; - -import org.tensorflow.ndarray.IllegalRankException; -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.NdArrays; -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffers; - -/** - * Helper class for instantiating {@link Index} objects. - */ -public final class Indices { - - /** - * A coordinate that selects a specific element on a given dimension. - * - *

When this index is applied to a given dimension, the dimension is resolved as a - * single element and therefore is excluded from the computation of the rank. - * - *

For example, given a 3D matrix on the axis [x, y, z], if - * {@code matrix.slice(all(), at(0), at(0)}, then the rank of the returned slice is 1 and its number of elements is - * {@code x.numElements()} - * - * @param coord coordinate of the element on the indexed axis - * @return index - */ - public static Index at(long coord) { - return new At(coord, false); - } - - /** - * A coordinate that selects a specific element on a given dimension. - * - *

This is equivalent to call {@link #at(long)} but where the value of the coordinate is - * provided by an N-dimensional array. - * - * @param coord scalar indicating the coordinate of the element on the indexed axis - * @return index - * @throws IllegalRankException if {@code coord} is not a scalar (rank 0) - */ - public static Index at(NdArray coord) { - if (coord.rank() > 0) { - throw new IllegalRankException("Only scalars are accepted as a value index"); - } - return new At(coord.getObject().longValue(), false); - } - - /** - * A coordinate that selects a specific element on a given dimension. - * - *

When this index is applied to a given dimension, the dimension is resolved as a - * single element and therefore, if {@code keepDim} is false, is excluded from the computation of the rank. If {@code} - * keepDim is true, the dimension is collapsed down to one element. - * - *

For example, given a 3D matrix on the axis [x, y, z], if - * {@code matrix.slice(all(), at(0), at(0)}, then the rank of the returned slice is 1 and its number of elements is - * {@code x.numElements()} - * - * @param coord coordinate of the element on the indexed axis - * @param keepDim whether to remove the dimension. - * @return index - */ - public static Index at(long coord, boolean keepDim) { - return new At(coord, keepDim); - } - - /** - * A coordinate that selects a specific element on a given dimension. - * - *

This is equivalent to call {@link #at(long, boolean)} but where the value of the coordinate is - * provided by an N-dimensional array. - *

- * If {@code} keepDim is true, the dimension is collapsed down to one element instead of being removed. - * - * @param coord scalar indicating the coordinate of the element on the indexed axis - * @param keepDim whether to remove the dimension. - * @return index - * @throws IllegalRankException if {@code coord} is not a scalar (rank 0) - */ - public static Index at(NdArray coord, boolean keepDim) { - if (coord.rank() > 0) { - throw new IllegalRankException("Only scalars are accepted as a value index"); - } - return new At(coord.getObject().longValue(), keepDim); - } - - /** - * An index that returns all elements of a dimension in the original order. - * - *

Applying this index to a given dimension will return the original dimension - * directly. - * - *

For example, given a vector with {@code n} elements, {@code all()} returns - * x0, x1, ..., xn-1 - * - * @return index - */ - public static Index all() { - return All.INSTANCE; - } - - /** - * An index that returns only specific elements on a given dimension. - * - *

For example, given a vector with {@code n} elements on the {@code x} axis, and {@code n > 10}, - * {@code seq(8, 0, 3)} returns x8, x0, x3 - * - * @param coords coordinates of the elements in the sequence - * @return index - */ - public static Index seq(long... coords) { - if (coords == null) { - throw new IllegalArgumentException(); - } - return new Sequence(NdArrays.wrap(Shape.of(coords.length), DataBuffers.of(coords, true, false))); - } - - /** - * An index that returns only specific elements on a given dimension. - * - *

This is equivalent to {@link #seq(long...)} but where the coordinates of the elements in - * the sequence are provided by an N-dimensional array. - * - * @param coords vector of coordinates of the elements in the sequence - * @return index - * @throws IllegalRankException if {@code coords} is not a vector (rank 1) - */ - public static Index seq(NdArray coords) { - if (coords.rank() != 1) { - throw new IllegalRankException("Only vectors are accepted as an element index"); - } - return new Sequence(coords); - } - - /** - * An index that returns only elements found at an even position in the original dimension. - * - *

For example, given a vector with {@code n} elements on the {@code x} axis, and n is even, - * {@code even()} returns x0, x2, ..., xn-2 - * - * @return index - */ - public static Index even() { - return step(2); - } - - /** - * An index that returns only elements found at an odd position in the original dimension. - * - *

For example, given a vector with {@code n} elements on the {@code x} axis, and n is even, - * {@code odd()} returns x1, x3, ..., xn-1 - * - * @return index - */ - public static Index odd() { - return sliceFrom(1, 2); - } - - /** - * An index that skips a fixed amount of coordinates between each values returned. - * - *

For example, given a vector with {@code n} elements on the {@code x} axis, - * {@code step(k)} returns x0, xk, xk*2, ... - * - * @param stride the number of elements between each steps - * @return index - */ - public static Index step(long stride) { - return new Step(stride); - } - - /** - * An index that returns only elements on a given dimension starting at a specific coordinate. - * - *

For example, given a vector with {@code n} elements on the {@code x} axis, and {@code n > k}, - * {@code from(k)} returns xk, xk+1, ..., xn-1 - * - * @param start coordinate of the first element of the sequence - * @return index - */ - public static Index sliceFrom(long start) { - return sliceFrom(start, 1); - } - - /** - * An index that returns only elements on a given dimension starting at a specific coordinate, using the given - * stride. - * - *

For example, given a vector with {@code n} elements on the {@code x} axis, and {@code n > k}, - * {@code from(k)} returns xk, xk+1, ..., xn-1 - * - * @param start coordinate of the first element of the sequence - * @param stride the stride to use - * @return index - * @see #slice(long, long, long) - */ - public static Index sliceFrom(long start, long stride) { - return new SliceFrom(start, stride); - } - - /** - * An index that returns only elements on a given dimension up to a specific coordinate. - * - *

For example, given a vector with {@code n} elements on the {@code x} axis, and {@code n > k}, - * {@code to(k)} returns x0, x1, ..., xk - * - * @param end coordinate of the last element of the sequence (exclusive) - * @return index - */ - public static Index sliceTo(long end) { - return sliceTo(end, 1); - } - - /** - * An index that returns only elements on a given dimension up to a specific coordinate, using the given stride. - * - *

For example, given a vector with {@code n} elements on the {@code x} axis, and {@code n > k}, - * {@code to(k)} returns x0, x1, ..., xk - * - * @param end coordinate of the last element of the sequence (exclusive) - * @param stride the stride to use - * @return index - * @see #slice(long, long, long) - */ - public static Index sliceTo(long end, long stride) { - return new SliceTo(end, stride); - } - - /** - * An index that returns only elements on a given dimension between two coordinates. - * - *

For example, given a vector with {@code n} elements on the {@code x} axis, and {@code n > k > j}, - * {@code range(j, k)} returns xj, xj+1, ..., xk - * - * @param start coordinate of the first element of the sequence - * @param end coordinate of the last element of the sequence (exclusive) - * @return index - */ - public static Index range(long start, long end) { - return slice(start, end); - } - - /** - * An index that returns only elements on a given dimension between two coordinates. - * - *

For example, given a vector with {@code n} elements on the {@code x} axis, and {@code n > k > j}, - * {@code range(j, k)} returns xj, xj+1, ..., xk - * - * @return index - */ - public static Index flip() { - return slice(null, null, -1); - } - - /** - * An index that returns elements according to an hyperslab defined by {@code start}, {@code stride}, {@code count}, - * {@code block}. See {@link Hyperslab}. - * - * @param start Starting location for the hyperslab. - * @param stride The number of elements to separate each element or block to be selected. - * @param count The number of elements or blocks to select along the dimension. - * @param block The size of the block selected from the dimension. - * @return index - */ - public static Index hyperslab(long start, long stride, long count, long block) { - return new Hyperslab(start, stride, count, block); - } - - /** - * An index that inserts a new dimension of size 1 into the resulting array. - * - * @return index - */ - public static Index newAxis() { - return NewAxis.INSTANCE; - } - - /** - * An index that expands to fill all available source dimensions. Works the same as Python's {@code ...}. - * - * @return index - */ - public static Index ellipsis() { - return Ellipsis.INSTANCE; - } - - /** - * An index that returns elements between {@code start} and {@code end}. If {@code start} or {@code end} is {@code - * null}, starts or ends at the beginning or the end, respectively. - *

- * Analogous to Python's {@code :} slice syntax. - * - * @return index - */ - public static Index slice(long start, long end) { - return slice(start, end, 1); - } - - /** - * An index that returns every {@code stride}-th element between {@code start} and {@code end}. If {@code start} or - * {@code end} is {@code null}, starts or ends at the beginning or the end, respectively. - *

- * Analogous to Python's {@code :} slice syntax. - * - * @return index - */ - public static Index slice(long start, long end, long stride) { - return new Slice(start, end, stride); - } - - /** - * An index that returns elements between {@code start} and {@code end}. If {@code start} or {@code end} is {@code - * null}, starts or ends at the beginning or the end, respectively. - *

- * Analogous to Python's {@code :} slice syntax. - * - * @return index - */ - public static Index slice(Long start, Long end) { - return slice(start, end, 1); - } - - /** - * An index that returns every {@code stride}-th element between {@code start} and {@code end}. If {@code start} or - * {@code end} is {@code null}, starts or ends at the beginning or the end, respectively. - *

- * Analogous to Python's {@code :} slice syntax. - * - * @return index - */ - public static Index slice(Long start, Long end, long stride) { - if (start == null && end == null) { - if (stride == 1) { - return Indices.all(); - } else { - return Indices.step(stride); - } - } else if (start == null) { - return Indices.sliceTo(end, stride); - } else if (end == null) { - return Indices.sliceFrom(start, stride); - } - - return slice(start.longValue(), end.longValue(), stride); - } - -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/index/NewAxis.java b/ndarray/src/main/java/org/tensorflow/ndarray/index/NewAxis.java deleted file mode 100644 index a68b1ed9ad1..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/index/NewAxis.java +++ /dev/null @@ -1,53 +0,0 @@ -/* - 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.ndarray.index; - -import org.tensorflow.ndarray.impl.dimension.Dimension; - -final class NewAxis implements Index { - - static final NewAxis INSTANCE = new NewAxis(); - - private NewAxis() { - - } - - @Override - public long numElements(Dimension dim) { - return 1; - } - - @Override - public long mapCoordinate(long coordinate, Dimension dim) { - return coordinate; - } - - @Override - public Dimension apply(Dimension dim) { - throw new IllegalStateException(); - } - - @Override - public boolean isNewAxis() { - return true; - } - - @Override - public String toString() { - return NewAxis.class.getSimpleName() + "()"; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/index/Sequence.java b/ndarray/src/main/java/org/tensorflow/ndarray/index/Sequence.java deleted file mode 100644 index 5b93e434e54..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/index/Sequence.java +++ /dev/null @@ -1,52 +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.ndarray.index; - -import java.util.StringJoiner; -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.impl.dimension.Dimension; - -final class Sequence implements Index { - - @Override - public long numElements(Dimension dim) { - return coords.size(); - } - - @Override - public long mapCoordinate(long coordinate, Dimension dim) { - return coords.getObject(coordinate).longValue(); - } - - Sequence(NdArray coords) { - this.coords = coords; - } - - private final NdArray coords; - - @Override - public String toString() { - return new StringJoiner(", ", Sequence.class.getSimpleName() + "(", ")") - .add("coords=" + coords) - .toString(); - } - - @Override - public boolean isStridedSlicingCompliant() { - return false; - } -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/index/Slice.java b/ndarray/src/main/java/org/tensorflow/ndarray/index/Slice.java deleted file mode 100644 index 1be4368261c..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/index/Slice.java +++ /dev/null @@ -1,89 +0,0 @@ -/* - 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.ndarray.index; - -import java.util.StringJoiner; -import org.tensorflow.ndarray.impl.dimension.Dimension; - -final class Slice implements Index { - - Slice(long start, long end, long stride) { - this.start = start; - this.end = end; - this.stride = stride; - - if (stride == 0) { - throw new IllegalArgumentException("Can not have a stride of 0"); - } - } - - @Override - public long numElements(Dimension dim) { - long length = end(dim) - start(dim); - - return (length / stride) + (length % stride != 0 ? 1 : 0); - } - - @Override - public long mapCoordinate(long coordinate, Dimension dim) { - return start(dim) + stride * coordinate; - } - - @Override - public long begin() { - return start; - } - - @Override - public long end() { - return end; - } - - @Override - public long stride() { - return stride; - } - - @Override - public String toString() { - return new StringJoiner(", ", Slice.class.getSimpleName() + "(", ")") - .add("start=" + start) - .add("end=" + end) - .add("stride=" + stride) - .toString(); - } - - private long start(Dimension dim) { - if (start < 0) { - return dim.numElements() + start; - } - - return start; - } - - private long end(Dimension dim) { - if (end < 0) { - return dim.numElements() + end; - } else { - return end; - } - } - - private final long start; - private final long end; - private final long stride; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/index/SliceFrom.java b/ndarray/src/main/java/org/tensorflow/ndarray/index/SliceFrom.java deleted file mode 100644 index c968a325cf7..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/index/SliceFrom.java +++ /dev/null @@ -1,86 +0,0 @@ -/* - 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.ndarray.index; - -import java.util.StringJoiner; -import org.tensorflow.ndarray.impl.dimension.Dimension; - -final class SliceFrom implements Index { - - SliceFrom(long start, long stride) { - this.start = start; - this.stride = stride; - - if (stride == 0) { - throw new IllegalArgumentException("Can not have a stride of 0"); - } - } - - @Override - public long numElements(Dimension dim) { - long length = end(dim) - start(dim); - - return (length / stride) + (length % stride != 0 ? 1 : 0); - } - - @Override - public long mapCoordinate(long coordinate, Dimension dim) { - return start(dim) + stride * coordinate; - } - - @Override - public long begin() { - return start; - } - - @Override - public boolean endMask() { - return true; - } - - @Override - public long stride() { - return stride; - } - - @Override - public String toString() { - return new StringJoiner(", ", SliceFrom.class.getSimpleName() + "(", ")") - .add("start=" + start) - .add("stride=" + stride) - .toString(); - } - - private long start(Dimension dim) { - if (start < 0) { - return dim.numElements() + start; - } - - return start; - } - - private long end(Dimension dim) { - if (stride > 0) { - return dim.numElements(); - } else { - return -1; // it's exclusive - } - } - - private final long start; - private final long stride; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/index/SliceTo.java b/ndarray/src/main/java/org/tensorflow/ndarray/index/SliceTo.java deleted file mode 100644 index 761d1d52a3a..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/index/SliceTo.java +++ /dev/null @@ -1,86 +0,0 @@ -/* - 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.ndarray.index; - -import java.util.StringJoiner; -import org.tensorflow.ndarray.impl.dimension.Dimension; - -final class SliceTo implements Index { - - SliceTo(long end, long stride) { - this.end = end; - this.stride = stride; - - if (stride == 0) { - throw new IllegalArgumentException("Can not have a stride of 0"); - } - } - - @Override - public long numElements(Dimension dim) { - long length = end(dim) - start(dim); - - return (length / stride) + (length % stride != 0 ? 1 : 0); - } - - @Override - public long mapCoordinate(long coordinate, Dimension dim) { - return start(dim) + stride * coordinate; - } - - @Override - public long end() { - return end; - } - - @Override - public boolean beginMask() { - return true; - } - - @Override - public long stride() { - return stride; - } - - @Override - public String toString() { - return new StringJoiner(", ", SliceTo.class.getSimpleName() + "(", ")") - .add("end=" + end) - .add("stride=" + stride) - .toString(); - } - - private long start(Dimension dim) { - if (stride > 0) { - return 0; - } - - return dim.numElements() - 1; // it's inclusive - } - - private long end(Dimension dim) { - if (end < 0) { - return dim.numElements() + end; - } else { - return end; - } - } - - private final long end; - private final long stride; -} diff --git a/ndarray/src/main/java/org/tensorflow/ndarray/index/Step.java b/ndarray/src/main/java/org/tensorflow/ndarray/index/Step.java deleted file mode 100644 index c9a21c507b6..00000000000 --- a/ndarray/src/main/java/org/tensorflow/ndarray/index/Step.java +++ /dev/null @@ -1,83 +0,0 @@ -/* - 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.ndarray.index; - -import java.util.StringJoiner; -import org.tensorflow.ndarray.impl.dimension.Dimension; - -final class Step implements Index { - - Step(long stride) { - this.stride = stride; - - if (stride == 0) { - throw new IllegalArgumentException("Can not have a stride of 0"); - } - } - - @Override - public long numElements(Dimension dim) { - long length = end(dim) - start(dim); - - return (length / stride) + (length % stride != 0 ? 1 : 0); - } - - @Override - public long mapCoordinate(long coordinate, Dimension dim) { - return start(dim) + stride * coordinate; - } - - @Override - public boolean beginMask() { - return true; - } - - @Override - public boolean endMask() { - return true; - } - - @Override - public long stride() { - return stride; - } - - @Override - public String toString() { - return new StringJoiner(", ", Step.class.getSimpleName() + "(", ")") - .add("stride=" + stride) - .toString(); - } - - private long start(Dimension dim) { - if (stride > 0) { - return 0; - } - - return dim.numElements() - 1; // it's inclusive - } - - private long end(Dimension dim) { - if (stride > 0) { - return dim.numElements(); - } else { - return -1; // it's exclusive - } - } - - private final long stride; -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/BooleanNdArrayTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/BooleanNdArrayTestBase.java deleted file mode 100644 index 6426ff5a1c2..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/BooleanNdArrayTestBase.java +++ /dev/null @@ -1,57 +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.ndarray; - -import static org.junit.jupiter.api.Assertions.assertTrue; -import static org.junit.jupiter.api.Assertions.assertFalse; -import static org.tensorflow.ndarray.NdArrays.vectorOf; - -import org.junit.jupiter.api.Test; - -public abstract class BooleanNdArrayTestBase extends NdArrayTestBase { - - @Override - protected abstract BooleanNdArray allocate(Shape shape); - - @Override - protected Boolean valueOf(Long val) { - return val > 0; - } - - @Test - public void iteratePrimitiveElements() { - BooleanNdArray matrix3d = allocate(Shape.of(5, 4, 5)); - - matrix3d.scalars().forEachIndexed((coords, scalar) -> - scalar.setBoolean(coords[2] > 0) - ); - - assertFalse(matrix3d.getBoolean(0, 0, 0)); - assertTrue(matrix3d.getBoolean(0, 0, 1)); - assertTrue(matrix3d.getBoolean(0, 0, 4)); - assertTrue(matrix3d.getBoolean(0, 1, 2)); - - matrix3d.elements(1).forEach(vector -> - vector.set(vectorOf(true, false, true, false, true)) - ); - - assertTrue(matrix3d.getBoolean(0, 0, 0)); - assertFalse(matrix3d.getBoolean(0, 0, 1)); - assertTrue(matrix3d.getBoolean(0, 0, 4)); - assertTrue(matrix3d.getBoolean(0, 1, 2)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/ByteNdArrayTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/ByteNdArrayTestBase.java deleted file mode 100644 index 407efffda94..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/ByteNdArrayTestBase.java +++ /dev/null @@ -1,55 +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.ndarray; - -import static org.junit.jupiter.api.Assertions.assertEquals; - -import org.junit.jupiter.api.Test; - -public abstract class ByteNdArrayTestBase extends NdArrayTestBase { - - @Override - protected abstract ByteNdArray allocate(Shape shape); - - @Override - protected Byte valueOf(Long val) { - return val.byteValue(); - } - - @Test - public void iteratePrimitiveElements() { - ByteNdArray matrix3d = allocate(Shape.of(5, 4, 5)); - - matrix3d.scalars().forEachIndexed((coords, scalar) -> - scalar.setByte((byte)coords[2]) - ); - - assertEquals(0, matrix3d.getByte(0, 0, 0)); - assertEquals(1, matrix3d.getByte(0, 0, 1)); - assertEquals(4, matrix3d.getByte(0, 0, 4)); - assertEquals(2, matrix3d.getByte(0, 1, 2)); - - matrix3d.elements(1).forEach(vector -> - vector.set(NdArrays.vectorOf((byte)5, (byte)6, (byte)7, (byte)8, (byte)9)) - ); - - assertEquals(5, matrix3d.getByte(0, 0, 0)); - assertEquals(6, matrix3d.getByte(0, 0, 1)); - assertEquals(9, matrix3d.getByte(0, 0, 4)); - assertEquals(7, matrix3d.getByte(0, 1, 2)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/DoubleNdArrayTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/DoubleNdArrayTestBase.java deleted file mode 100644 index d4f98e2caa0..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/DoubleNdArrayTestBase.java +++ /dev/null @@ -1,55 +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.ndarray; - -import static org.junit.jupiter.api.Assertions.assertEquals; - -import org.junit.jupiter.api.Test; - -public abstract class DoubleNdArrayTestBase extends NdArrayTestBase { - - @Override - protected abstract DoubleNdArray allocate(Shape shape); - - @Override - protected Double valueOf(Long val) { - return val.doubleValue(); - } - - @Test - public void iteratePrimitiveElements() { - DoubleNdArray matrix3d = allocate(Shape.of(5, 4, 5)); - - matrix3d.scalars().forEachIndexed((coords, scalar) -> - scalar.setDouble((double)coords[2]) - ); - - assertEquals(0.0, matrix3d.getDouble(0, 0, 0), 0.0); - assertEquals(1.0, matrix3d.getDouble(0, 0, 1), 0.0); - assertEquals(4.0, matrix3d.getDouble(0, 0, 4), 0.0); - assertEquals(2.0, matrix3d.getDouble(0, 1, 2), 0.0); - - matrix3d.elements(1).forEach(vector -> - vector.set(NdArrays.vectorOf(5.0, 6.0, 7.0, 8.0, 9.0)) - ); - - assertEquals(5, matrix3d.getDouble(0, 0, 0), 0.0); - assertEquals(6, matrix3d.getDouble(0, 0, 1), 0.0); - assertEquals(9, matrix3d.getDouble(0, 0, 4), 0.0); - assertEquals(7, matrix3d.getDouble(0, 1, 2), 0.0); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/FloatNdArrayTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/FloatNdArrayTestBase.java deleted file mode 100644 index 55f05ae3de1..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/FloatNdArrayTestBase.java +++ /dev/null @@ -1,55 +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.ndarray; - -import static org.junit.jupiter.api.Assertions.assertEquals; - -import org.junit.jupiter.api.Test; - -public abstract class FloatNdArrayTestBase extends NdArrayTestBase { - - @Override - protected abstract FloatNdArray allocate(Shape shape); - - @Override - protected Float valueOf(Long val) { - return val.floatValue(); - } - - @Test - public void iteratePrimitiveElements() { - FloatNdArray matrix3d = allocate(Shape.of(5, 4, 5)); - - matrix3d.scalars().forEachIndexed((coords, scalar) -> - scalar.setFloat((float)coords[2]) - ); - - assertEquals(0.0f, matrix3d.getFloat(0, 0, 0), 0.0f); - assertEquals(1.0f, matrix3d.getFloat(0, 0, 1), 0.0f); - assertEquals(4.0f, matrix3d.getFloat(0, 0, 4), 0.0f); - assertEquals(2.0f, matrix3d.getFloat(0, 1, 2), 0.0f); - - matrix3d.elements(1).forEach(vector -> - vector.set(NdArrays.vectorOf(5.0f, 6.0f, 7.0f, 8.0f, 9.0f)) - ); - - assertEquals(5, matrix3d.getFloat(0, 0, 0), 0.0f); - assertEquals(6, matrix3d.getFloat(0, 0, 1), 0.0f); - assertEquals(9, matrix3d.getFloat(0, 0, 4), 0.0f); - assertEquals(7, matrix3d.getFloat(0, 1, 2), 0.0f); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/IndexTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/IndexTest.java deleted file mode 100644 index 6f92dab9b99..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/IndexTest.java +++ /dev/null @@ -1,205 +0,0 @@ -/* - 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.ndarray; - -import static org.junit.jupiter.api.Assertions.assertEquals; -import static org.junit.jupiter.api.Assertions.assertTrue; - -import org.junit.jupiter.api.Test; -import org.tensorflow.ndarray.index.Indices; - -public class IndexTest { - @Test - public void testNullConversions(){ - assertTrue(Indices.slice(null, 0L).beginMask(), - "Passed null for slice start but didn't set begin mask"); - - assertTrue(Indices.slice(null, 0L).beginMask(), - "Passed null for slice start but didn't set begin mask"); - - assertTrue(Indices.slice(null, null).beginMask(), - "Passed null for slice start but didn't set begin mask"); - - assertTrue(Indices.slice(0L, null).endMask(), - "Passed null for slice end but didn't set end mask"); - - assertTrue(Indices.slice(0L, null).endMask(), - "Passed null for slice end but didn't set end mask"); - - assertTrue(Indices.slice(null, null).endMask(), - "Passed null for slice end but didn't set end mask"); - } - - @Test - public void testNewaxis(){ - IntNdArray matrix3d = NdArrays.ofInts(Shape.of(5, 4, 5)); - - matrix3d.scalars().forEachIndexed((coords, scalar) -> - scalar.setInt((int)coords[2]) - ); - - IntNdArray slice1 = matrix3d.slice(Indices.all(), Indices.all(), Indices.all(), Indices.newAxis()); - - assertEquals(Shape.of(5, 4, 5, 1), slice1.shape()); - assertEquals(0, slice1.getInt(0, 0, 0, 0)); - assertEquals(1, slice1.getInt(0, 0, 1, 0)); - assertEquals(4, slice1.getInt(0, 0, 4, 0)); - assertEquals(2, slice1.getInt(0, 1, 2, 0)); - - IntNdArray slice2 = matrix3d.slice(Indices.all(), Indices.all(), Indices.newAxis(), Indices.all()); - - assertEquals(Shape.of(5, 4, 1, 5), slice2.shape()); - assertEquals(0, slice2.getInt(0, 0, 0, 0)); - assertEquals(1, slice2.getInt(0, 0, 0, 1)); - assertEquals(4, slice2.getInt(0, 0, 0, 4)); - assertEquals(2, slice2.getInt(0, 1, 0, 2)); - - IntNdArray slice3 = matrix3d.slice(Indices.all(), Indices.newAxis(), Indices.all(), Indices.all()); - - assertEquals(Shape.of(5, 1, 4, 5), slice3.shape()); - assertEquals(0, slice3.getInt(0, 0, 0, 0)); - assertEquals(1, slice3.getInt(0, 0, 0, 1)); - assertEquals(4, slice3.getInt(0, 0, 0, 4)); - assertEquals(2, slice3.getInt(0, 0, 1, 2)); - - IntNdArray slice4 = matrix3d.slice(Indices.newAxis(), Indices.all(), Indices.all(), Indices.all()); - - assertEquals(Shape.of(1, 5, 4, 5), slice4.shape()); - assertEquals(0, slice4.getInt(0, 0, 0, 0)); - assertEquals(1, slice4.getInt(0, 0, 0, 1)); - assertEquals(4, slice4.getInt(0, 0, 0, 4)); - assertEquals(2, slice4.getInt(0, 0, 1, 2)); - - } - - @Test - public void testEllipsis(){ - IntNdArray matrix3d = NdArrays.ofInts(Shape.of(5, 4, 5)); - - matrix3d.scalars().forEachIndexed((coords, scalar) -> - scalar.setInt((int)coords[2]) - ); - - assertEquals( - matrix3d.slice(Indices.all(), Indices.all(), Indices.at(0)), - matrix3d.slice(Indices.ellipsis(), Indices.at(0)) - ); - - assertEquals( - matrix3d.slice(Indices.at(0), Indices.all(), Indices.all()), - matrix3d.slice(Indices.at(0), Indices.ellipsis()) - ); - - assertEquals( - matrix3d.slice(Indices.at(0), Indices.all(), Indices.at(0)), - matrix3d.slice(Indices.at(0), Indices.ellipsis(), Indices.at(0)) - ); - - // newaxis interacts specially with ellipsis (since it doesn't consume a dimension), test this - - assertEquals( - matrix3d.slice(Indices.all(), Indices.all(), Indices.newAxis(), Indices.at(0)), - matrix3d.slice(Indices.ellipsis(), Indices.newAxis(), Indices.at(0)) - ); - - assertEquals( - matrix3d.slice(Indices.newAxis(), Indices.all(), Indices.all(), Indices.at(0)), - matrix3d.slice(Indices.newAxis(), Indices.ellipsis(), Indices.at(0)) - ); - - assertEquals( - matrix3d.slice(Indices.all(), Indices.all(), Indices.at(0), Indices.newAxis()), - matrix3d.slice(Indices.ellipsis(), Indices.at(0), Indices.newAxis()) - ); - } - - @Test - public void testSlice(){ - IntNdArray matrix3d = NdArrays.ofInts(Shape.of(5, 4, 5)); - - matrix3d.scalars().forEachIndexed((coords, scalar) -> - scalar.setInt((int)coords[2]) - ); - - IntNdArray slice1 = matrix3d.slice(Indices.all(), Indices.sliceTo(3), Indices.all()); - - assertEquals(Shape.of(5, 3, 5), slice1.shape()); - assertEquals(0, slice1.getInt(0, 0, 0)); - assertEquals(1, slice1.getInt(0, 0, 1)); - assertEquals(2, slice1.getInt(0, 1, 2)); - - IntNdArray slice2 = matrix3d.slice(Indices.all(), Indices.all(), Indices.slice(1, 4)); - - assertEquals(Shape.of(5, 4, 3), slice2.shape()); - assertEquals(1, slice2.getInt(0, 0, 0)); - assertEquals(3, slice2.getInt(0, 0, 2)); - assertEquals(2, slice2.getInt(0, 1, 1)); - - assertEquals(slice2, matrix3d.slice(Indices.all(), Indices.all(), Indices.slice(1, -1))); - - assertEquals(slice2, matrix3d.slice(Indices.all(), Indices.all(), Indices.slice(-4, -1))); - - assertEquals(Shape.of(5, 4, 0), matrix3d.slice(Indices.all(), Indices.all(), Indices.slice(1, 4, -2)).shape()); - - IntNdArray slice3 = matrix3d.slice(Indices.all(), Indices.all(), Indices.slice(4, 1, -2)); - - assertEquals(Shape.of(5, 4, 2), slice3.shape()); - assertEquals(4, slice3.getInt(0, 0, 0)); - assertEquals(2, slice3.getInt(0, 1, 1)); - - assertEquals(slice3, matrix3d.slice(Indices.all(), Indices.all(), Indices.slice(-1, 1, -2))); - - assertEquals(slice3, matrix3d.slice(Indices.all(), Indices.all(), Indices.slice(-1, -4, -2))); - - IntNdArray slice4 = matrix3d.slice(Indices.all(), Indices.all(), Indices.slice(null, null, -1)); - - assertEquals(Shape.of(5, 4, 5), slice4.shape()); - assertEquals(4, slice4.getInt(0, 0, 0)); - assertEquals(3, slice4.getInt(0, 0, 1)); - assertEquals(2, slice4.getInt(0, 1, 2)); - } - - @Test - public void testAt(){ - IntNdArray matrix3d = NdArrays.ofInts(Shape.of(5, 4, 5)); - - matrix3d.scalars().forEachIndexed((coords, scalar) -> - scalar.setInt((int)coords[2]) - ); - - IntNdArray slice1 = matrix3d.slice(Indices.all(), Indices.all(), Indices.at(0)); - - assertEquals(Shape.of(5, 4), slice1.shape()); - assertEquals(0, slice1.getInt(0, 0)); - - IntNdArray slice2 = matrix3d.slice(Indices.all(), Indices.all(), Indices.at(3)); - - assertEquals(Shape.of(5, 4), slice2.shape()); - assertEquals(3, slice2.getInt(0, 0)); - - IntNdArray slice3 = matrix3d.slice(Indices.all(), Indices.all(), Indices.at(-3)); - - assertEquals(Shape.of(5, 4), slice3.shape()); - assertEquals(2, slice3.getInt(0, 0)); - - IntNdArray slice4 = matrix3d.slice(Indices.all(), Indices.all(), Indices.at(-3, true)); - - assertEquals(Shape.of(5, 4, 1), slice4.shape()); - assertEquals(2, slice4.getInt(0, 0, 0)); - } - -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/IntNdArrayTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/IntNdArrayTestBase.java deleted file mode 100644 index 1a3c7cb1a12..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/IntNdArrayTestBase.java +++ /dev/null @@ -1,55 +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.ndarray; - -import static org.junit.jupiter.api.Assertions.assertEquals; - -import org.junit.jupiter.api.Test; - -public abstract class IntNdArrayTestBase extends NdArrayTestBase { - - @Override - protected abstract IntNdArray allocate(Shape shape); - - @Override - protected Integer valueOf(Long val) { - return val.intValue(); - } - - @Test - public void iteratePrimitiveElements() { - IntNdArray matrix3d = allocate(Shape.of(5, 4, 5)); - - matrix3d.scalars().forEachIndexed((coords, scalar) -> - scalar.setInt((int)coords[2]) - ); - - assertEquals(0, matrix3d.getInt(0, 0, 0)); - assertEquals(1, matrix3d.getInt(0, 0, 1)); - assertEquals(4, matrix3d.getInt(0, 0, 4)); - assertEquals(2, matrix3d.getInt(0, 1, 2)); - - matrix3d.elements(1).forEach(vector -> - vector.set(NdArrays.vectorOf(5, 6, 7, 8, 9)) - ); - - assertEquals(5, matrix3d.getInt(0, 0, 0)); - assertEquals(6, matrix3d.getInt(0, 0, 1)); - assertEquals(9, matrix3d.getInt(0, 0, 4)); - assertEquals(7, matrix3d.getInt(0, 1, 2)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/LongNdArrayTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/LongNdArrayTestBase.java deleted file mode 100644 index b91c19d6557..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/LongNdArrayTestBase.java +++ /dev/null @@ -1,55 +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.ndarray; - -import static org.junit.jupiter.api.Assertions.assertEquals; - -import org.junit.jupiter.api.Test; - -public abstract class LongNdArrayTestBase extends NdArrayTestBase { - - @Override - protected abstract LongNdArray allocate(Shape shape); - - @Override - protected Long valueOf(Long val) { - return val; - } - - @Test - public void iteratePrimitiveElements() { - LongNdArray matrix3d = allocate(Shape.of(5, 4, 5)); - - matrix3d.scalars().forEachIndexed((coords, scalar) -> - scalar.setLong(coords[2]) - ); - - assertEquals(0, matrix3d.getLong(0, 0, 0)); - assertEquals(1, matrix3d.getLong(0, 0, 1)); - assertEquals(4, matrix3d.getLong(0, 0, 4)); - assertEquals(2, matrix3d.getLong(0, 1, 2)); - - matrix3d.elements(1).forEach(vector -> - vector.set(NdArrays.vectorOf(5L, 6L, 7L, 8L, 9L)) - ); - - assertEquals(5, matrix3d.getLong(0, 0, 0)); - assertEquals(6, matrix3d.getLong(0, 0, 1)); - assertEquals(9, matrix3d.getLong(0, 0, 4)); - assertEquals(7, matrix3d.getLong(0, 1, 2)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/NdArrayTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/NdArrayTestBase.java deleted file mode 100644 index 26ac533daa8..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/NdArrayTestBase.java +++ /dev/null @@ -1,338 +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.ndarray; - -import static org.junit.jupiter.api.Assertions.assertEquals; -import static org.junit.jupiter.api.Assertions.assertNotEquals; -import static org.junit.jupiter.api.Assertions.fail; -import static org.tensorflow.ndarray.NdArrays.vectorOfObjects; -import static org.tensorflow.ndarray.index.Indices.all; -import static org.tensorflow.ndarray.index.Indices.at; -import static org.tensorflow.ndarray.index.Indices.even; -import static org.tensorflow.ndarray.index.Indices.flip; -import static org.tensorflow.ndarray.index.Indices.sliceFrom; -import static org.tensorflow.ndarray.index.Indices.odd; -import static org.tensorflow.ndarray.index.Indices.range; -import static org.tensorflow.ndarray.index.Indices.seq; -import static org.tensorflow.ndarray.index.Indices.sliceTo; - -import java.nio.BufferOverflowException; -import java.nio.BufferUnderflowException; -import org.junit.jupiter.api.Test; -import org.tensorflow.ndarray.buffer.DataBuffer; - -public abstract class NdArrayTestBase { - - protected abstract NdArray allocate(Shape shape); - - protected abstract DataBuffer allocateBuffer(long size); - - protected abstract T valueOf(Long val); - - protected T zeroOrNull() { - return valueOf(0L); - } - - @Test - public void shapeAndSizes() { - Shape scalarShape = Shape.scalar(); - NdArray scalar = allocate(scalarShape); - assertEquals(scalarShape, scalar.shape()); - assertEquals(0, scalar.rank()); - assertEquals(scalarShape, Shape.of()); - - Shape vectorShape = Shape.of(10); - NdArray vector = allocate(vectorShape); - assertEquals(vectorShape, vector.shape()); - assertEquals(1, vector.rank()); - } - - @Test - public void setAndGetValues() { - NdArray matrix = allocate(Shape.of(5, 4)); - assertEquals(zeroOrNull(), matrix.getObject(3, 3)); - - matrix.setObject(valueOf(10L), 3, 3); - assertEquals(valueOf(10L), matrix.getObject(3, 3)); - try { - matrix.setObject(valueOf(10L), 3, 4); - fail(); - } catch (IndexOutOfBoundsException e) { - // as expected - } - try { - matrix.setObject(valueOf(10L), -1, 3); - fail(); - } catch (IndexOutOfBoundsException e) { - // as expected - } - try { - matrix.getObject(3); - fail(); - } catch (IllegalRankException e) { - // as expected - } - try { - matrix.setObject(valueOf(10L), 3); - fail(); - } catch (IllegalRankException e) { - // as expected - } - - NdArray matrix2 = allocate(Shape.of(3, 2)) - .set(vectorOfObjects(valueOf(1L), valueOf(2L)), 0) - .set(vectorOfObjects(valueOf(3L), valueOf(4L)), 1) - .setObject(valueOf(5L), 2, 0) - .setObject(valueOf(6L), 2, 1); - - assertEquals(valueOf(1L), matrix2.getObject(0, 0)); - assertEquals(valueOf(2L), matrix2.getObject(0, 1)); - assertEquals(valueOf(3L), matrix2.getObject(1, 0)); - assertEquals(valueOf(4L), matrix2.getObject(1, 1)); - assertEquals(valueOf(5L), matrix2.getObject(2, 0)); - assertEquals(valueOf(6L), matrix2.getObject(2, 1)); - } - - @Test - public void iterateElements() { - NdArray matrix3d = allocate(Shape.of(5, 4, 5)); - - matrix3d.scalars().forEachIndexed((coords, scalar) -> { - scalar.setObject(valueOf(coords[2])); - }); - - assertEquals(valueOf(0L), matrix3d.getObject(0, 0, 0)); - assertEquals(valueOf(1L), matrix3d.getObject(0, 0, 1)); - assertEquals(valueOf(4L), matrix3d.getObject(0, 0, 4)); - assertEquals(valueOf(2L), matrix3d.getObject(0, 1, 2)); - - matrix3d.elements(1).forEach(vector -> { - vector.set(vectorOfObjects(valueOf(5L), valueOf(6L), valueOf(7L), valueOf(8L), valueOf(9L))); - }); - - assertEquals(valueOf(5L), matrix3d.getObject(0, 0, 0)); - assertEquals(valueOf(6L), matrix3d.getObject(0, 0, 1)); - assertEquals(valueOf(9L), matrix3d.getObject(0, 0, 4)); - assertEquals(valueOf(7L), matrix3d.getObject(0, 1, 2)); - - long value = 0L; - for (NdArray matrix : matrix3d.elements(0)) { - assertEquals(2L, matrix.shape().numDimensions()); - assertEquals(4L, matrix.shape().size(0)); - assertEquals(5L, matrix.shape().size(1)); - - for (NdArray vector : matrix.elements(0)) { - assertEquals(1L, vector.shape().numDimensions()) ; - assertEquals(5L, vector.shape().size(0)); - - for (NdArray scalar : vector.scalars()) { - assertEquals(0L, scalar.shape().numDimensions()) ; - scalar.setObject(valueOf(value++)); - try { - scalar.elements(0); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - } - } - } - assertEquals(valueOf(0L), matrix3d.getObject(0, 0, 0)); - assertEquals(valueOf(5L), matrix3d.getObject(0, 1, 0)); - assertEquals(valueOf(9L), matrix3d.getObject(0, 1, 4)); - assertEquals(valueOf(20L), matrix3d.getObject(1, 0, 0)); - assertEquals(valueOf(25L), matrix3d.getObject(1, 1, 0)); - assertEquals(valueOf(99L), matrix3d.getObject(4, 3, 4)); - } - - @Test - public void slices() { - NdArray matrix3d = allocate(Shape.of(5, 4, 5)); - - T val100 = valueOf(100L); - matrix3d.setObject(val100, 1, 0, 0); - T val101 = valueOf(101L); - matrix3d.setObject(val101, 1, 0, 1); - - // Vector (1,0,*) - NdArray vector10X = matrix3d.get(1, 0); - assertEquals(Shape.of(5), vector10X.shape()); - assertEquals(val100, vector10X.getObject(0)); - assertEquals(val101, vector10X.getObject(1)); - - T val102 = valueOf(102L); - vector10X.setObject(val102, 2); - assertEquals(val102, vector10X.getObject(2)); - assertEquals(val102, matrix3d.getObject(1, 0, 2)); - - // Vector (*,0,0) - NdArray vectorX00 = matrix3d.slice(all(), at(0), at(0)); - assertEquals(Shape.of(5), vectorX00.shape()); - assertEquals(val100, vectorX00.getObject(1)); - T val200 = valueOf(200L); - vectorX00.setObject(val200, 2); - assertEquals(val200, vectorX00.getObject(2)); - assertEquals(val200, matrix3d.getObject(2, 0, 0)); - - // Vector (1,0,[2,0]) - NdArray vector10_20 = matrix3d.slice(at(1), at(0), seq(2, 0)); - assertEquals(vector10_20.shape(), Shape.of(2)); - assertEquals(val102, vector10_20.getObject(0)); - assertEquals(val100, vector10_20.getObject(1)); - - // Vector (1,0,[even]) - NdArray vector10_even = matrix3d.slice(at(1), at(0), even()); - assertEquals(vector10_even.shape(), Shape.of(3)); - assertEquals(val100, vector10_even.getObject(0)); - assertEquals(val102, vector10_even.getObject(1)); - - // Vector ([odd]) from vector (1,0,[even]) - NdArray vector10_even_odd = vector10_even.slice(odd()); - assertEquals(vector10_even_odd.shape(), Shape.of(1)); - assertEquals(val102, vector10_even_odd.getObject(0)); - - // Vector (1,0,[flip]) - NdArray vector10_flip = matrix3d.slice(at(1), at(0), flip()); - assertEquals(vector10_flip.shape(), Shape.of(5)); - assertEquals(val100, vector10_flip.getObject(4)); - assertEquals(val101, vector10_flip.getObject(3)); - - // Vector (1,0,[from 1]) from vector (1,0,*) - NdArray vector10_1toX = vector10X.slice(sliceFrom(1)); - assertEquals(vector10_1toX.shape(), Shape.of(4)); - assertEquals(val101, vector10_1toX.getObject(0)); - assertEquals(val102, vector10_1toX.getObject(1)); - - // Vector (1,0,[to 1]) from vector (1,0,*) - NdArray vector10_Xto1 = vector10X.slice(sliceTo(2)); - assertEquals(vector10_Xto1.shape(), Shape.of(2)); - assertEquals(val100, vector10_Xto1.getObject(0)); - assertEquals(val101, vector10_Xto1.getObject(1)); - - // Vector (1,0,[1 to 3]) - NdArray vector10_1to3 = matrix3d.slice(at(1), at(0), range(1, 3)); - assertEquals(vector10_1to3.shape(), Shape.of(2)); - assertEquals(val101, vector10_1to3.getObject(0)); - assertEquals(val102, vector10_1to3.getObject(1)); - - // Scalar (1,0,0) from vector (1,0,*) - NdArray scalar100 = vector10X.get(0); - assertEquals(Shape.of(), scalar100.shape()); - assertEquals(val100, scalar100.getObject()); - - // Slice scalar (1,0,z) - LongNdArray z = NdArrays.scalarOf(2L); - NdArray scalar102 = matrix3d.slice(at(1), at(0), at(z)); - assertEquals(scalar102.shape(), Shape.of()); - assertEquals(val102, scalar102.getObject()); - - // Slicing the 3D matrix so we only keep the first element of the second dimension - NdArray matrix_X0Z = matrix3d.slice(all(), at(0)); - assertEquals(2, matrix_X0Z.rank()); - assertEquals(Shape.of(5, 5), matrix_X0Z.shape()); - assertEquals(val100, matrix_X0Z.getObject(1, 0)); - assertEquals(val101, matrix_X0Z.getObject(1, 1)); - assertEquals(val200, matrix_X0Z.getObject(2, 0)); - } - - @Test - public void writeAndReadWithBuffers() { - DataBuffer buffer = allocateBuffer(15L); - for (long val = 0L; val < buffer.size(); ++val) { - buffer.setObject(valueOf(val), val); - } - NdArray matrix = allocate(Shape.of(3, 5)); - matrix.write(buffer); - assertEquals(valueOf(0L), matrix.getObject(0, 0)); - assertEquals(valueOf(4L), matrix.getObject(0, 4)); - assertEquals(valueOf(5L), matrix.getObject(1, 0)); - assertEquals(valueOf(10L), matrix.getObject(2, 0)); - assertEquals(valueOf(14L), matrix.getObject(2, 4)); - - matrix.setObject(valueOf(100L), 1, 0); - matrix.read(buffer); - assertEquals(valueOf(0L), buffer.getObject(0)); - assertEquals(valueOf(4L), buffer.getObject(4)); - assertEquals(valueOf(100L), buffer.getObject(5)); - assertEquals(valueOf(10L), buffer.getObject(10)); - assertEquals(valueOf(14L), buffer.getObject(14)); - - try { - matrix.write(buffer.narrow(10)); - fail(); - } catch (BufferUnderflowException e) { - // as expected - } - try { - matrix.read(buffer.narrow(10)); - fail(); - } catch (BufferOverflowException e) { - // as expected - } - } - - @Test - public void ndArrayCopies() { - NdArray matrixA = allocate(Shape.of(3, 5)); - - long value = 0L; - for (NdArray s : matrixA.scalars()) { - s.setObject(valueOf(value++)); - } - NdArray matrixB = allocate(Shape.of(3, 5)).setObject(valueOf(100L), 1, 0); - matrixA.copyTo(matrixB); - assertEquals(valueOf(0L), matrixB.getObject(0, 0)); - assertEquals(valueOf(4L), matrixB.getObject(0, 4)); - assertEquals(valueOf(5L), matrixB.getObject(1, 0)); - assertEquals(valueOf(10L), matrixB.getObject(2, 0)); - assertEquals(valueOf(14L), matrixB.getObject(2, 4)); - - NdArray matrixC = allocate(Shape.of(3, 4)); - try { - matrixA.copyTo(matrixC); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - } - - @Test - public void equalsAndHashCode() { - NdArray array1 = allocate(Shape.of(2, 2)); - NdArray array2 = allocate(Shape.of(2, 2)); - NdArray array3 = allocate(Shape.of(2, 2)); - NdArray array4 = allocate(Shape.of(1, 2, 2)); - - @SuppressWarnings("unchecked") - T[][][] values = (T[][][])(new Object[][][] { - { { valueOf(0L), valueOf(1L) }, { valueOf(2L), valueOf(0L) } } - }); - - StdArrays.copyTo(values[0], array1); - StdArrays.copyTo(values[0], array2); - StdArrays.copyTo(values[0], array3); - array3.setObject(valueOf(0L), 0, 1); - StdArrays.copyTo(values, array4); - - assertEquals(array1, array2); - assertEquals(array1.hashCode(), array2.hashCode()); - assertNotEquals(array1, array3); - assertNotEquals(array1.hashCode(), array3.hashCode()); - assertNotEquals(array1, array4); - assertNotEquals(array1.hashCode(), array4.hashCode()); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/ShapeTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/ShapeTest.java deleted file mode 100644 index d2e3e432a2c..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/ShapeTest.java +++ /dev/null @@ -1,170 +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.ndarray; - -import org.junit.jupiter.api.Test; - -import static org.junit.jupiter.api.Assertions.*; - -public class ShapeTest { - - @Test - public void allKnownDimensions() { - Shape shape = Shape.of(5, 4, 5); - assertEquals(3, shape.numDimensions()); - assertEquals(5, shape.size(0)); - assertEquals(4, shape.size(1)); - assertEquals(5, shape.size(2)); - assertEquals(100, shape.size()); - assertArrayEquals(new long[] {5, 4, 5}, shape.asArray()); - try { - shape.size(3); - fail(); - } catch (IndexOutOfBoundsException e) { - // as expected - } - assertEquals(5, shape.size(-1)); - assertEquals(4, shape.size(-2)); - assertEquals(5, shape.size(-3)); - try { - shape.size(-4); - fail(); - } catch (IndexOutOfBoundsException e) { - // as expected - } - assertFalse(shape.isUnknown()); - assertFalse(shape.hasUnknownDimension()); - assertFalse(shape.isScalar()); - } - - @Test - public void hashCodeEquals() { - Shape shape1 = Shape.of(5, 4, 5); - Shape shape2 = Shape.of(5, 4, 5); - Shape shape3 = Shape.of(5, 4, 5, 6); - Shape shape4 = Shape.of(5, 4, 1); - - assertEquals(shape1, shape2); - assertEquals(shape1.hashCode(), shape2.hashCode()); - assertNotEquals(shape1, shape3); - assertNotEquals(shape1.hashCode(), shape3.hashCode()); - assertNotEquals(shape1, shape4); - assertNotEquals(shape1.hashCode(), shape4.hashCode()); - - Shape scalar1 = Shape.of(); - Shape scalar2 = Shape.of(); - assertEquals(scalar1, scalar2); - assertNotEquals(scalar1, shape1); - - Shape unknown1 = Shape.of(-1, 4, 5); - Shape unknown2 = Shape.of(-1, 4, 5); - assertNotEquals(unknown1, unknown2); - assertNotEquals(unknown1, shape1); - assertEquals(unknown1, unknown1); - - Shape sizeUnknown1 = Shape.unknown(); - Shape sizeUnknown2 = Shape.unknown(); - assertNotEquals(sizeUnknown1, sizeUnknown2); - assertEquals(sizeUnknown1, sizeUnknown1); - } - - @Test - public void testShapeModification() { - Shape one = Shape.of(2, 4, 6, 8); - assertEquals(one.head(), Shape.of(2)); - assertEquals(one.tail(), Shape.of(4, 6, 8)); - - Shape two = Shape.of(5); - assertEquals(two.head(), two); - assertEquals(two.tail(), Shape.of()); - - try { - Shape.of().head(); - fail(); - } catch (IndexOutOfBoundsException e) { - // as expected - } - - assertEquals(Shape.of().tail(), Shape.of()); - - Shape three = Shape.of(2, 4, 6); - assertEquals(three.prepend(5), Shape.of(5, 2, 4, 6)); - - assertEquals(Shape.of(5, 2, 4, 6), two.append(three)); - assertEquals(Shape.of(2, 4, 6, 5), two.prepend(three)); - assertEquals(Shape.of(1, 2, 3, 4), Shape.of(1, 2).append(Shape.of(3, 4))); - assertEquals(Shape.of(1, 2, 3, 4), Shape.of(1, 2, 3).append(4)); - assertEquals(Shape.of(1, 2, 3, 4), Shape.of(1, 2, 3, 4).append(Shape.scalar())); - assertEquals(Shape.of(3, 4, 1, 2), Shape.of(1, 2).prepend(Shape.of(3, 4))); - assertEquals(Shape.of(4, 6), three.takeLast(2)); - assertEquals(Shape.scalar(), three.takeLast(0)); - assertEquals(Shape.of(2, 4), three.take(2)); - assertEquals(Shape.scalar(), three.take(0)); - - try { - Shape.unknown().append(Shape.of(1, 2)); - fail(); - } catch (NullPointerException e) { - // as expected - } - - try { - Shape.unknown().prepend(Shape.of(1, 2)); - fail(); - } catch (NullPointerException e) { - // as expected - } - - // changing the values of the array returned by asArray should not mutate the shape - long[] internalShape = one.asArray(); - assertNotNull(internalShape); - internalShape[0] = 42L; - assertEquals(2L, one.size(0)); - } - - @Test - public void testShapeCompatible() { - Shape a = Shape.unknown(); - Shape b = Shape.of(2, 2); - assertTrue(a.isCompatibleWith(b)); - assertTrue(b.isCompatibleWith(a)); - - a = Shape.of(2, 2); - assertTrue(a.isCompatibleWith(b)); - assertTrue(b.isCompatibleWith(a)); - - a = Shape.of(2, -1); - assertTrue(a.isCompatibleWith(b)); - assertTrue(b.isCompatibleWith(a)); - - a = Shape.of(-1, 2); - assertTrue(a.isCompatibleWith(b)); - assertTrue(b.isCompatibleWith(a)); - - a = Shape.of(-1, -1); - assertTrue(a.isCompatibleWith(b)); - assertTrue(b.isCompatibleWith(a)); - - a = Shape.of(1, 2); - assertFalse(a.isCompatibleWith(b)); - assertFalse(b.isCompatibleWith(a)); - - a = Shape.of(1, 2, 3); - assertFalse(a.isCompatibleWith(b)); - assertFalse(b.isCompatibleWith(a)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/ShortNdArrayTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/ShortNdArrayTestBase.java deleted file mode 100644 index f9043fec4f5..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/ShortNdArrayTestBase.java +++ /dev/null @@ -1,55 +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.ndarray; - -import static org.junit.jupiter.api.Assertions.assertEquals; - -import org.junit.jupiter.api.Test; - -public abstract class ShortNdArrayTestBase extends NdArrayTestBase { - - @Override - protected abstract ShortNdArray allocate(Shape shape); - - @Override - protected Short valueOf(Long val) { - return val.shortValue(); - } - - @Test - public void iteratePrimitiveElements() { - ShortNdArray matrix3d = allocate(Shape.of(5, 4, 5)); - - matrix3d.scalars().forEachIndexed((coords, scalar) -> - scalar.setShort((short)coords[2]) - ); - - assertEquals(0, matrix3d.getShort(0, 0, 0)); - assertEquals(1, matrix3d.getShort(0, 0, 1)); - assertEquals(4, matrix3d.getShort(0, 0, 4)); - assertEquals(2, matrix3d.getShort(0, 1, 2)); - - matrix3d.elements(1).forEach(vector -> - vector.set(NdArrays.vectorOf((short)5, (short)6, (short)7, (short)8, (short)9)) - ); - - assertEquals(5, matrix3d.getShort(0, 0, 0)); - assertEquals(6, matrix3d.getShort(0, 0, 1)); - assertEquals(9, matrix3d.getShort(0, 0, 4)); - assertEquals(7, matrix3d.getShort(0, 1, 2)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/StdArraysTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/StdArraysTest.java deleted file mode 100644 index b7b41564c33..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/StdArraysTest.java +++ /dev/null @@ -1,211 +0,0 @@ -package org.tensorflow.ndarray; - -import static org.junit.jupiter.api.Assertions.assertArrayEquals; -import static org.junit.jupiter.api.Assertions.assertEquals; -import static org.junit.jupiter.api.Assertions.assertNull; -import static org.junit.jupiter.api.Assertions.fail; - -import org.junit.jupiter.api.Test; - -public class StdArraysTest { - - @Test - public void vectors() { - IntNdArray vector = NdArrays.ofInts(Shape.of(2)); - - StdArrays.copyTo(new int[] {1, 2}, vector); - assertEquals(1, vector.getInt(0)); - assertEquals(2, vector.getInt(1)); - - try { - StdArrays.copyTo(new int[] {1, 2, 3}, vector); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - try { - StdArrays.copyTo(new int[] {1, 2}, NdArrays.ofInts(Shape.of(4))); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - try { - StdArrays.copyTo(new int[] {1, 2}, NdArrays.ofInts(Shape.of(2, 2))); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - - int[] array = StdArrays.array1dCopyOf(vector); - assertEquals(1, array[0]); - assertEquals(2, array[1]); - - array = new int[3]; - StdArrays.copyFrom(vector, array); - assertEquals(1, array[0]); - assertEquals(2, array[1]); - assertEquals(0, array[2]); - - try { - StdArrays.copyFrom(vector, new int[1]); - fail(); - } catch (ArrayIndexOutOfBoundsException e) { - // as expected - } - try { - StdArrays.copyFrom(vector, new int[1][2]); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - try { - StdArrays.copyFrom(vector, new int[2][2][2]); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - } - - @Test - public void matrices() { - IntNdArray matrix = NdArrays.ofInts(Shape.of(2, 2)); - - StdArrays.copyTo(new int[][] { - {1, 2}, - {3, 4} - }, matrix); - assertEquals(1, matrix.getInt(0, 0)); - assertEquals(2, matrix.getInt(0, 1)); - assertEquals(3, matrix.getInt(1, 0)); - assertEquals(4, matrix.getInt(1, 1)); - try { - StdArrays.copyTo(new int[][] {{1, 2, 3}, {4, 5, 6}}, matrix); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - try { - StdArrays.copyTo(new int[][] {{1, 2}, {3, 4}}, NdArrays.ofInts(Shape.of(3, 3))); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - try { - StdArrays.copyTo(new int[][] {{1, 2}, {3, 4}}, NdArrays.ofInts(Shape.of(2, 2, 1))); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - - int[][] array = StdArrays.array2dCopyOf(matrix); - assertEquals(1, array[0][0]); - assertEquals(2, array[0][1]); - assertEquals(3, array[1][0]); - assertEquals(4, array[1][1]); - - array = new int[3][3]; - StdArrays.copyFrom(matrix, array); - assertArrayEquals(new int[] { 1, 2, 0 }, array[0]); - assertArrayEquals(new int[] { 3, 4, 0 }, array[1]); - assertArrayEquals(new int[] { 0, 0, 0 }, array[2]); - - try { - StdArrays.copyFrom(matrix, new int[1][2]); - fail(); - } catch (ArrayIndexOutOfBoundsException e) { - // as expected - } - try { - StdArrays.copyFrom(matrix, new int[2][1]); - fail(); - } catch (ArrayIndexOutOfBoundsException e) { - // as expected - } - try { - StdArrays.copyFrom(matrix, new int[2]); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - try { - StdArrays.copyFrom(matrix, new int[1][2][2]); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - try { - StdArrays.copyFrom(matrix, new int[2][2][2]); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - } - - @Test - public void objectMatrix() { - NdArray matrix = StdArrays.ndCopyOf(new String[][] {{"ab", "bc"}, {"cd", "de"}}); - assertEquals(NdArrays.vectorOfObjects("ab", "bc"), matrix.get(0)); - assertEquals(NdArrays.vectorOfObjects("cd", "de"), matrix.get(1)); - - String[][] array = StdArrays.array2dCopyOf(matrix, String.class); - assertEquals("ab", array[0][0]); - assertEquals("bc", array[0][1]); - assertEquals("cd", array[1][0]); - assertEquals("de", array[1][1]); - - array = new String[2][3]; - StdArrays.copyFrom(matrix, array); - assertEquals("ab", array[0][0]); - assertEquals("bc", array[0][1]); - assertNull(array[0][2]); - assertEquals("cd", array[1][0]); - assertEquals("de", array[1][1]); - assertNull(array[1][2]); - } - - @Test - public void cannotInitDenseMatrixWithRaggedArray() { - IntNdArray matrix = NdArrays.ofInts(Shape.of(2, 2)); - try { - StdArrays.copyTo(new int[][]{ - {1, 2}, - {3} - }, matrix); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - } - - @Test - public void computeShapeDense3DMatrix() { - Shape shape = StdArrays.shapeOf(new int[][][] { - { - {1, 2, 3}, {4, 5, 6} - }, - { - {1, 2, 3}, {4, 5, 6} - } - }); - assertArrayEquals(new long[] {2, 2, 3}, shape.asArray()); - } - - @Test - public void shapeOfRagged3DMatrix() { - Shape shape = StdArrays.shapeOf(new int[][][] { - { - {1, 2, 3}, {4, 5, 6}, {7, 8, 9} - }, - { - {1, 2, 3}, {4, 5, 6} - } - }); - assertArrayEquals(new long[] {2, Shape.UNKNOWN_SIZE, 3}, shape.asArray()); - } - - @Test - public void shapeOfEmptyArray() { - Shape shape = StdArrays.shapeOf(new int[2][2][3]); - assertArrayEquals(new long[] {2, 2, 3}, shape.asArray()); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/benchmark/NdArrayBenchmark.java b/ndarray/src/test/java/org/tensorflow/ndarray/benchmark/NdArrayBenchmark.java deleted file mode 100644 index fb7022bc830..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/benchmark/NdArrayBenchmark.java +++ /dev/null @@ -1,163 +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.ndarray.benchmark; - -import static org.tensorflow.ndarray.index.Indices.all; -import static org.tensorflow.ndarray.index.Indices.at; - -import java.awt.image.BufferedImage; -import java.awt.image.Raster; -import java.io.IOException; -import javax.imageio.ImageIO; -import org.openjdk.jmh.annotations.Benchmark; -import org.openjdk.jmh.annotations.BenchmarkMode; -import org.openjdk.jmh.annotations.Fork; -import org.openjdk.jmh.annotations.Measurement; -import org.openjdk.jmh.annotations.Mode; -import org.openjdk.jmh.annotations.Scope; -import org.openjdk.jmh.annotations.Setup; -import org.openjdk.jmh.annotations.State; -import org.openjdk.jmh.annotations.Warmup; -import org.openjdk.jmh.runner.RunnerException; -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.FloatNdArray; -import org.tensorflow.ndarray.NdArrays; -import org.tensorflow.ndarray.StdArrays; - -@Fork(value = 1, jvmArgs = {"-Xms4G", "-Xmx4G"}) -@BenchmarkMode(Mode.AverageTime) -@Warmup(iterations = 3) -@Measurement(iterations = 5) -@State(Scope.Benchmark) -public class NdArrayBenchmark { - - public static void main(String[] args) throws IOException, RunnerException { - org.openjdk.jmh.Main.main(args); - } - - @Setup - public void setUp() throws IOException { - BufferedImage image = ImageIO.read(getClass().getClassLoader().getResourceAsStream(TEST_IMAGE)); - - int numPixels = image.getWidth() * image.getHeight(); - pixels = NdArrays.ofFloats(Shape.of(numPixels, 3)); - channels = NdArrays.ofFloats(Shape.of(3, numPixels)); - - Raster imageData = image.getData(); - float[] pixel = new float[3]; - for (int y = 0, pixelIdx = 0; y < image.getHeight(); ++y) { - for (int x = 0; x < image.getWidth(); ++x, ++pixelIdx) { - imageData.getPixel(x, y, pixel); - StdArrays.copyTo(pixel, pixels.get(pixelIdx)); - StdArrays.copyTo(pixel, channels.slice(all(), at(pixelIdx))); - } - } - batches = NdArrays.ofFloats(Shape.of(BATCH_SIZE, 3, numPixels)); - firstBatch = batches.get(0); - } - - @Benchmark - @Measurement(batchSize = 2049 * 1537) - public void getElementAtIndex() { - pixels.get(0); - } - - @Benchmark - @Measurement(batchSize = 2049 * 1537) - public void slicing() { - batches.slice(at(0), all(), at(0)); - } - - @Benchmark - public void readingAllPixelsChannelsBySequence() { - pixels.scalars().forEach(pixel -> pixel.getFloat()); - } - - @Benchmark - public void readingAllPixelsChannelsBySequenceSlices() { - pixels.scalars().asSlices().forEach(pixel -> pixel.getFloat()); - } - - @Benchmark - @Measurement(batchSize = 100) - public void readingAllPixelsChannelsByIndex() { - long[] shape = pixels.shape().asArray(); - for (int i = 0; i < shape[0]; ++i) { - for (int j = 0; j < shape[1]; ++j) { - pixels.getFloat(i, j); - } - } - } - - @Benchmark - @Measurement(batchSize = BATCH_SIZE) - public void writeFirstBatchChannels() { - firstBatch.set(channels); - } - - @Benchmark - public void writeAllBatchChannels() { - batches.elements(0).forEach(batch -> - batch.set(channels) - ); - } - - @Benchmark - @Measurement(batchSize = 2049 * 1537) - public void writeOnePixelBySlicing() { - batches.slice(at(0), all(), at(0)).set(pixels.get(0)); - } - - @Benchmark - public void writeAllPixelsBySlicing() { - batches.elements(0).forEach(batch -> - pixels.elements(0).forEachIndexed((coords, pixel) -> - batch.slice(all(), at(coords[0])).set(pixel) - ) - ); - } - - @Benchmark - @Measurement(batchSize = 2049 * 1537) - public void writeOnePixelsByIndex() { - batches - .setFloat(pixels.getFloat(0, 0), 0, 0, 0) - .setFloat(pixels.getFloat(0, 1), 0, 1, 0) - .setFloat(pixels.getFloat(0, 2), 0, 2, 0); - } - - @Benchmark - public void writeAllPixelsByIndex() { - batches.elements(0).forEach(batch -> - pixels.elements(0).forEachIndexed((coords, pixel) -> { - long pixelIndex = coords[0]; - batch - .setFloat(pixel.getFloat(0), 0, pixelIndex) - .setFloat(pixel.getFloat(1), 1, pixelIndex) - .setFloat(pixel.getFloat(2), 2, pixelIndex); - }) - ); - } - - private static final String TEST_IMAGE = "castle.jpg"; - private static final int BATCH_SIZE = 60; - - private FloatNdArray pixels; - private FloatNdArray channels; - private FloatNdArray batches; - private FloatNdArray firstBatch; -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/BooleanDataBufferTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/buffer/BooleanDataBufferTestBase.java deleted file mode 100644 index 3f6df8aa1ce..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/BooleanDataBufferTestBase.java +++ /dev/null @@ -1,142 +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.ndarray.buffer; - -import static org.junit.jupiter.api.Assertions.assertTrue; -import static org.junit.jupiter.api.Assertions.assertArrayEquals; -import static org.junit.jupiter.api.Assertions.assertEquals; -import static org.junit.jupiter.api.Assertions.assertFalse; -import static org.junit.jupiter.api.Assertions.assertNotEquals; - -import java.util.Arrays; -import java.util.BitSet; -import org.junit.jupiter.api.Test; -import org.tensorflow.ndarray.impl.buffer.misc.MiscDataBufferFactory; - -public abstract class BooleanDataBufferTestBase extends DataBufferTestBase { - - @Override - protected abstract BooleanDataBuffer allocate(long size); - - @Override - protected Boolean valueOf(Long val) { - return val != 0; - } - - @Test - public void writeAndReadFromArray() { - BooleanDataBuffer buffer = allocate(10L); - boolean[] values = new boolean[]{true, false, false, true, false}; - - buffer.write(values); - assertTrue(buffer.getObject(0)); - assertFalse(buffer.getObject(1)); - - buffer.offset(5).write(values); - assertTrue(buffer.getObject(5)); - - boolean[] read = new boolean[5]; - buffer.read(read); - assertArrayEquals(values, read); - - buffer.write(values, 2, 3); - assertFalse(buffer.getObject(0)); - assertTrue(buffer.getObject(1)); - assertFalse(buffer.getObject(2)); - - Arrays.fill(read, false); - buffer.read(read, 1, 2); - assertFalse(read[0]); - assertFalse(read[1]); - assertTrue(read[2]); - assertFalse(read[3]); - } - - @Test - public void equalWithBitSetBuffer() { - BitSet bitSet1 = BitSet.valueOf(new byte[] { 0x01, 0x01 }); - BooleanDataBuffer bitSet1Buffer = MiscDataBufferFactory.create(bitSet1, 12, true); - - BitSet bitSet2 = BitSet.valueOf(new byte[] { 0x11, 0x01 }); - BooleanDataBuffer bitSet2Buffer = MiscDataBufferFactory.create(bitSet2, 12, true); - - BooleanDataBuffer buffer = allocate(12) - .setBoolean(true, 0) - .setBoolean(true, 8); - - assertTrue(bitSet1Buffer.equals(buffer)); - assertTrue(buffer.equals(bitSet1Buffer)); - assertEquals(bitSet1Buffer.hashCode(), buffer.hashCode()); - - assertFalse(bitSet2Buffer.equals(buffer)); - assertFalse(buffer.equals(bitSet2Buffer)); - assertNotEquals(bitSet2Buffer.hashCode(), buffer.hashCode()); - } - - @Test - public void equalWithBooleanArrayBuffer() { - boolean[] array1 = new boolean[] { false, false, false, true, true, false }; - BooleanDataBuffer array1Buffer = MiscDataBufferFactory.create(array1, true); - - boolean[] array2 = new boolean[] { false, false, false, true, true, true }; - BooleanDataBuffer array2Buffer = MiscDataBufferFactory.create(array2, true); - - BooleanDataBuffer buffer = allocate(6) - .setBoolean(true, 3) - .setBoolean(true, 4); - - assertTrue(array1Buffer.equals(buffer)); - assertTrue(buffer.equals(array1Buffer)); - assertEquals(array1Buffer.hashCode(), buffer.hashCode()); - - assertFalse(array2Buffer.equals(buffer)); - assertFalse(buffer.equals(array2Buffer)); - assertNotEquals(array2Buffer.hashCode(), buffer.hashCode()); - } - - @Test - public void equalWithBooleanObjectBuffer() { - Boolean[] array1 = new Boolean[] { false, false, false, true, true, false }; - DataBuffer array1Buffer = MiscDataBufferFactory.create(array1, true); - - boolean[] array2 = new boolean[] { false, false, false, true, true, true }; - DataBuffer array2Buffer = MiscDataBufferFactory.create(array2, true); - - BooleanDataBuffer buffer = allocate(6) - .setBoolean(true, 3) - .setBoolean(true, 4); - - assertTrue(array1Buffer.equals(buffer)); - assertTrue(buffer.equals(array1Buffer)); - assertEquals(array1Buffer.hashCode(), buffer.hashCode()); - - assertFalse(array2Buffer.equals(buffer)); - assertFalse(buffer.equals(array2Buffer)); - assertNotEquals(array2Buffer.hashCode(), buffer.hashCode()); - } - - @Test - public void notEqualWithOtherTypes() { - BooleanDataBuffer buffer = allocate(2) - .setBoolean(false, 0) - .setBoolean(true, 1); - ByteDataBuffer byteBuffer = DataBuffers.of((byte)0, (byte)1); - - assertFalse(buffer.equals(byteBuffer)); - assertFalse(byteBuffer.equals(buffer)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/ByteDataBufferTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/buffer/ByteDataBufferTestBase.java deleted file mode 100644 index 777368466f5..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/ByteDataBufferTestBase.java +++ /dev/null @@ -1,145 +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.ndarray.buffer; - -import static org.junit.jupiter.api.Assertions.assertArrayEquals; -import static org.junit.jupiter.api.Assertions.assertEquals; -import static org.junit.jupiter.api.Assertions.assertFalse; -import static org.junit.jupiter.api.Assertions.assertNotEquals; -import static org.junit.jupiter.api.Assertions.assertTrue; - -import java.nio.ByteBuffer; -import java.util.Arrays; -import org.junit.jupiter.api.Test; -import org.tensorflow.ndarray.impl.buffer.misc.MiscDataBufferFactory; -import org.tensorflow.ndarray.impl.buffer.nio.NioDataBufferFactory; -import org.tensorflow.ndarray.impl.buffer.raw.RawDataBufferFactory; - -public abstract class ByteDataBufferTestBase extends DataBufferTestBase { - - @Override - protected abstract ByteDataBuffer allocate(long size); - - @Override - protected Byte valueOf(Long val) { - return val.byteValue(); - } - - @Test - public void writeAndReadFromArray() { - ByteDataBuffer buffer = allocate(10L); - byte[] oneToFive = new byte[]{ 1, 2, 3, 4, 5 }; - - buffer.write(oneToFive); - assertEquals(2, buffer.getByte(1)); - - buffer.offset(5).write(oneToFive); - assertEquals(2, buffer.getByte(1)); - assertEquals(2, buffer.getByte(6)); - - byte[] read = new byte[5]; - buffer.read(read); - assertArrayEquals(oneToFive, read); - - buffer.write(oneToFive, 2, 2); - assertEquals(3, buffer.getByte(0)); - assertEquals(4, buffer.getByte(1)); - assertEquals(3, buffer.getByte(2)); - - Arrays.fill(read, valueOf(0L)); - buffer.read(read, 1, 2); - assertEquals(0, read[0]); - assertEquals(3, read[1]); - assertEquals(4, read[2]); - assertEquals(0, read[3]); - } - - @Test - public void equalWithByteNioBuffer() { - ByteDataBuffer nioBuffer1 = NioDataBufferFactory.create(ByteBuffer.wrap(new byte[] { 0x01, 0x10 })); - ByteDataBuffer nioBuffer2 = NioDataBufferFactory.create(ByteBuffer.wrap(new byte[] { 0x01, 0x11 })); - - ByteDataBuffer buffer = allocate(2) - .setByte((byte)0x01, 0) - .setByte((byte)0x10, 1); - - assertTrue(nioBuffer1.equals(buffer)); - assertTrue(buffer.equals(nioBuffer1)); - assertEquals(nioBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(nioBuffer2.equals(buffer)); - assertFalse(buffer.equals(nioBuffer2)); - assertNotEquals(nioBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void equalWithByteRawBuffer() { - ByteDataBuffer rawBuffer1 = RawDataBufferFactory.create(new byte[] { 0x01, 0x10 }, true); - ByteDataBuffer rawBuffer2 = RawDataBufferFactory.create(new byte[] { 0x01, 0x11 }, true); - - ByteDataBuffer buffer = allocate(2) - .setByte((byte)0x01, 0) - .setByte((byte)0x10, 1); - - assertTrue(rawBuffer1.equals(buffer)); - assertTrue(buffer.equals(rawBuffer1)); - assertEquals(rawBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(rawBuffer2.equals(buffer)); - assertFalse(buffer.equals(rawBuffer2)); - assertNotEquals(rawBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void equalWithByteObjectBuffer() { - DataBuffer objBuffer1 = MiscDataBufferFactory.create(new Byte[] { 0x01, 0x10 }, true); - DataBuffer objBuffer2 = MiscDataBufferFactory.create(new Byte[] { 0x01, 0x11 }, true); - - ByteDataBuffer buffer = allocate(2) - .setByte((byte)0x01, 0) - .setByte((byte)0x10, 1); - - assertTrue(objBuffer1.equals(buffer)); - assertTrue(buffer.equals(objBuffer1)); - assertEquals(objBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(objBuffer2.equals(buffer)); - assertFalse(buffer.equals(objBuffer2)); - assertNotEquals(objBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void notEqualWithOtherTypes() { - ByteDataBuffer buffer = allocate(2) - .setByte((byte)1, 0) - .setByte((byte)16, 1); - LongDataBuffer longBuffer = DataBuffers.of(1L, 16L); - - assertFalse(buffer.equals(longBuffer)); - assertFalse(longBuffer.equals(buffer)); - - try { - IntDataBuffer intBuffer = buffer.asInts(); - - assertFalse(buffer.equals(intBuffer)); - assertFalse(intBuffer.equals(buffer)); - - } catch (IllegalStateException e) { - // some byte buffers cannot be converted to ints, ignore the test in that case - } - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/DataBufferTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/buffer/DataBufferTestBase.java deleted file mode 100644 index 9a023915735..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/DataBufferTestBase.java +++ /dev/null @@ -1,293 +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.ndarray.buffer; - -import static org.junit.jupiter.api.Assertions.assertEquals; -import static org.junit.jupiter.api.Assertions.assertFalse; -import static org.junit.jupiter.api.Assertions.assertNotEquals; -import static org.junit.jupiter.api.Assertions.assertSame; -import static org.junit.jupiter.api.Assertions.assertTrue; -import static org.junit.jupiter.api.Assertions.fail; - -import java.nio.BufferOverflowException; -import java.nio.BufferUnderflowException; -import org.junit.jupiter.api.Test; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBufferWindow; -import org.tensorflow.ndarray.buffer.DataBuffers; - -public abstract class DataBufferTestBase { - - protected final boolean enableLargeBufferTests = System.getProperty("testLargeBuffers") != null; - - protected long maxSize() { - return DataBuffers.MAX_32BITS; - } - - protected abstract DataBuffer allocate(long size); - - protected abstract T valueOf(Long val); - - @Test - public void bufferSize() { - DataBuffer buffer = allocate(10L); - assertEquals(10L, buffer.size()); - - buffer = allocate(0L); - assertEquals(0L, buffer.size()); - - if (enableLargeBufferTests) { - buffer = allocate(maxSize()); - assertEquals(maxSize(), buffer.size()); - } - } - - @Test - public void offsetNarrowAndSlice() { - DataBuffer buffer = allocate(10L).setObject(valueOf(1L), 5); // 0, 0, 0, 0, 0, 1, 0, 0, 0, 0 - assertEquals(10L, buffer.size()); - assertEquals(valueOf(1L), buffer.getObject(5)); - - DataBuffer subBuffer = buffer.slice(2, 6); // 0, 0, 0, 1, 0, 0 - assertEquals(6L, subBuffer.size()); - assertEquals(valueOf(1L), subBuffer.getObject(3)); - - subBuffer = subBuffer.offset(2L); // 0, 1, 0, 0 - assertEquals(4L, subBuffer.size()); - assertEquals(valueOf(1L), subBuffer.getObject(1)); - - subBuffer = subBuffer.narrow(2L); // 0, 1 - assertEquals(2L, subBuffer.size()); - assertEquals(valueOf(1L), subBuffer.getObject(1)); - try { - subBuffer.getObject(2); - fail(); - } catch (IndexOutOfBoundsException e) { - //as expected - } - try { - buffer.slice(2, 12); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - try { - buffer.slice(-1, 3); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - try { - buffer.slice(2, -1); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - try { - buffer.offset(-1L); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - try { - buffer.offset(11L); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - try { - buffer.narrow(-1L); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - try { - buffer.narrow(11L); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - } - - @Test - public void putAndGet() { - DataBuffer buffer = allocate(10L); - - buffer.setObject(valueOf(5L), 5L); - assertEquals(valueOf(5L), buffer.getObject(5L)); - try { - buffer.setObject(valueOf(10L), 10L); - fail(); - } catch (IndexOutOfBoundsException e) { - // as expected - } - try { - buffer.getObject(10L); - fail(); - } catch (IndexOutOfBoundsException e) { - // as expected - } - try { - buffer.setObject(valueOf(-1L), -1L); - fail(); - } catch (IndexOutOfBoundsException e) { - // as expected - } - try { - buffer.getObject(-1L); - fail(); - } catch (IndexOutOfBoundsException e) { - // as expected - } - } - - @Test - public void copyToBuffer() { - DataBuffer srcBuffer = allocate(25L); - srcBuffer.setObject(valueOf(5L), 5L); - srcBuffer.setObject(valueOf(10L), 10L); - srcBuffer.setObject(valueOf(15L), 15L); - srcBuffer.setObject(valueOf(20L), 20L); - try { - srcBuffer.copyTo(srcBuffer, srcBuffer.size()); - fail(); - } catch (IllegalArgumentException e) { - // as expected - } - DataBuffer dstBuffer = allocate(30L); - srcBuffer.copyTo(dstBuffer, srcBuffer.size()); - assertEquals(valueOf(5L), dstBuffer.getObject(5L)); - try { - srcBuffer.copyTo(dstBuffer, dstBuffer.size()); - fail(); - } catch (BufferUnderflowException e) { - // as expected - } - try { - dstBuffer.copyTo(srcBuffer, dstBuffer.size()); - fail(); - } catch (BufferOverflowException e) { - // as expected - } - } - - @Test - public void createFromVarargs() { - DataBuffer buffer = DataBuffers.ofObjects(valueOf(1L), valueOf(2L), valueOf(3L)); - assertEquals(3, buffer.size()); - assertEquals(valueOf(1L), buffer.getObject(0)); - assertEquals(valueOf(2L), buffer.getObject(1)); - assertEquals(valueOf(3L), buffer.getObject(2)); - } - - @Test - public void equalWithObjectBuffer() { - DataBuffer buffer1 = allocate(2) - .setObject(valueOf(0L), 0) - .setObject(valueOf(1L), 1); - DataBuffer buffer2 = allocate(2) - .setObject(valueOf(0L), 0) - .setObject(valueOf(1L), 1); - DataBuffer buffer3 = allocate(2) - .setObject(valueOf(1L), 0) - .setObject(valueOf(0L), 1); - DataBuffer buffer4 = allocate(1) - .setObject(valueOf(0L), 0); - DataBuffer buffer5 = allocate(3) - .setObject(valueOf(0L), 0) - .setObject(valueOf(1L), 1) - .setObject(valueOf(2L), 2); - - assertTrue(buffer1.equals(buffer2)); - assertTrue(buffer2.equals(buffer1)); - assertEquals(buffer1.hashCode(), buffer1.hashCode()); - assertEquals(buffer1.hashCode(), buffer2.hashCode()); - - assertFalse(buffer3.equals(buffer1)); - assertFalse(buffer1.equals(buffer3)); - assertNotEquals(buffer3.hashCode(), buffer1.hashCode()); - - assertFalse(buffer4.equals(buffer1)); - assertFalse(buffer1.equals(buffer4)); - assertNotEquals(buffer4.hashCode(), buffer1.hashCode()); - - assertFalse(buffer5.equals(buffer1)); - assertFalse(buffer1.equals(buffer5)); - assertNotEquals(buffer5.hashCode(), buffer1.hashCode()); - } - - @Test - public void bufferWindow() { - DataBuffer buffer = allocate(20); - DataBufferWindow> bufferWindow; - try { - bufferWindow = buffer.window(4); - } catch (UnsupportedOperationException e) { - return; // skip test if this buffer does not support windows - } - assertEquals(0, bufferWindow.offset()); - assertEquals(4, bufferWindow.size()); - assertEquals(4, bufferWindow.buffer().size()); - - for (long i = 0; i < buffer.size(); ++i) { - buffer.setObject(valueOf(i), i); - } - assertEquals(valueOf(2L), bufferWindow.buffer().getObject(2)); - DataBuffer windowBuffer = bufferWindow.buffer(); - - bufferWindow.slide(10); - assertEquals(10, bufferWindow.offset()); - assertEquals(4, bufferWindow.size()); - assertEquals(valueOf(12L), bufferWindow.buffer().getObject(2)); - assertSame(windowBuffer, bufferWindow.buffer()); - - bufferWindow.slide(-2); - assertEquals(8, bufferWindow.offset()); - assertEquals(4, bufferWindow.size()); - assertEquals(valueOf(10L), bufferWindow.buffer().getObject(2)); - - bufferWindow.slideTo(16); - assertEquals(16, bufferWindow.offset()); - assertEquals(4, bufferWindow.size()); - assertEquals(valueOf(18L), bufferWindow.buffer().getObject(2)); - - try { - bufferWindow.slide(1); - fail(); - } catch (IndexOutOfBoundsException e) { - // as expected - } - try { - bufferWindow.slide(-17); - fail(); - } catch (IndexOutOfBoundsException e) { - // as expected - } - try { - bufferWindow.slideTo(-1); - fail(); - } catch (IndexOutOfBoundsException e) { - // as expected - } - try { - bufferWindow.slideTo(17); - fail(); - } catch (IndexOutOfBoundsException e) { - // as expected - } - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/DoubleDataBufferTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/buffer/DoubleDataBufferTestBase.java deleted file mode 100644 index 4dee064968c..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/DoubleDataBufferTestBase.java +++ /dev/null @@ -1,135 +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.ndarray.buffer; - -import static org.junit.jupiter.api.Assertions.assertArrayEquals; -import static org.junit.jupiter.api.Assertions.assertEquals; -import static org.junit.jupiter.api.Assertions.assertFalse; -import static org.junit.jupiter.api.Assertions.assertNotEquals; -import static org.junit.jupiter.api.Assertions.assertTrue; - -import java.nio.DoubleBuffer; -import java.util.Arrays; -import org.junit.jupiter.api.Test; -import org.tensorflow.ndarray.impl.buffer.misc.MiscDataBufferFactory; -import org.tensorflow.ndarray.impl.buffer.nio.NioDataBufferFactory; -import org.tensorflow.ndarray.impl.buffer.raw.RawDataBufferFactory; - -public abstract class DoubleDataBufferTestBase extends DataBufferTestBase { - - @Override - protected abstract DoubleDataBuffer allocate(long size); - - @Override - protected Double valueOf(Long val) { - return val.doubleValue(); - } - - @Test - public void writeAndReadFromArray() { - DoubleDataBuffer buffer = allocate(10L); - double[] oneToFive = new double[]{ 1.0, 2.0, 3.0, 4.0, 5.0 }; - - buffer.write(oneToFive); - assertEquals(2.0, buffer.getDouble(1), 0.0); - - buffer.offset(5).write(oneToFive); - assertEquals(2.0, buffer.getDouble(1), 0.0); - assertEquals(2.0, buffer.getDouble(6), 0.0); - - double[] read = new double[5]; - buffer.read(read); - assertArrayEquals(oneToFive, read, 0.0); - - buffer.write(oneToFive, 2, 2); - assertEquals(3.0, buffer.getDouble(0), 0.0); - assertEquals(4.0, buffer.getDouble(1), 0.0); - assertEquals(3.0, buffer.getDouble(2), 0.0); - - Arrays.fill(read, valueOf(0L)); - buffer.read(read, 1, 2); - assertEquals(0.0, read[0], 0.0); - assertEquals(3.0, read[1], 0.0); - assertEquals(4.0, read[2], 0.0); - assertEquals(0.0, read[3], 0.0); - } - - @Test - public void equalWithDoubleNioBuffer() { - DoubleDataBuffer nioBuffer1 = NioDataBufferFactory.create(DoubleBuffer.wrap(new double[] { 1.0, 16.0 })); - DoubleDataBuffer nioBuffer2 = NioDataBufferFactory.create(DoubleBuffer.wrap(new double[] { 1.0, 25.0 })); - - DoubleDataBuffer buffer = allocate(2) - .setDouble(1.0, 0) - .setDouble(16.0, 1); - - assertTrue(nioBuffer1.equals(buffer)); - assertTrue(buffer.equals(nioBuffer1)); - assertEquals(nioBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(nioBuffer2.equals(buffer)); - assertFalse(buffer.equals(nioBuffer2)); - assertNotEquals(nioBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void equalWithDoubleRawBuffer() { - DoubleDataBuffer rawBuffer1 = RawDataBufferFactory.create(new double[] { 1.0, 16.0 }, true); - DoubleDataBuffer rawBuffer2 = RawDataBufferFactory.create(new double[] { 1.0, 25.0 }, true); - - DoubleDataBuffer buffer = allocate(2) - .setDouble(1.0, 0) - .setDouble(16.0, 1); - - assertTrue(rawBuffer1.equals(buffer)); - assertTrue(buffer.equals(rawBuffer1)); - assertEquals(rawBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(rawBuffer2.equals(buffer)); - assertFalse(buffer.equals(rawBuffer2)); - assertNotEquals(rawBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void equalWithDoubleObjectBuffer() { - DataBuffer objBuffer1 = MiscDataBufferFactory.create(new Double[] { 1.0, 16.0 }, true); - DataBuffer objBuffer2 = MiscDataBufferFactory.create(new Double[] { 1.0, 25.0 }, true); - - DoubleDataBuffer buffer = allocate(2) - .setDouble(1.0, 0) - .setDouble(16.0, 1); - - assertTrue(objBuffer1.equals(buffer)); - assertTrue(buffer.equals(objBuffer1)); - assertEquals(objBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(objBuffer2.equals(buffer)); - assertFalse(buffer.equals(objBuffer2)); - assertNotEquals(objBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void notEqualWithOtherTypes() { - DoubleDataBuffer buffer = allocate(2) - .setDouble(1.0, 0) - .setDouble(16.0, 1); - FloatDataBuffer floatBuffer = DataBuffers.of(1.0f, 16.0f); - - assertFalse(buffer.equals(floatBuffer)); - assertFalse(floatBuffer.equals(buffer)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/FloatDataBufferTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/buffer/FloatDataBufferTestBase.java deleted file mode 100644 index 49c4f15b808..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/FloatDataBufferTestBase.java +++ /dev/null @@ -1,135 +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.ndarray.buffer; - -import static org.junit.jupiter.api.Assertions.assertArrayEquals; -import static org.junit.jupiter.api.Assertions.assertEquals; -import static org.junit.jupiter.api.Assertions.assertFalse; -import static org.junit.jupiter.api.Assertions.assertNotEquals; -import static org.junit.jupiter.api.Assertions.assertTrue; - -import java.nio.FloatBuffer; -import java.util.Arrays; -import org.junit.jupiter.api.Test; -import org.tensorflow.ndarray.impl.buffer.misc.MiscDataBufferFactory; -import org.tensorflow.ndarray.impl.buffer.nio.NioDataBufferFactory; -import org.tensorflow.ndarray.impl.buffer.raw.RawDataBufferFactory; - -public abstract class FloatDataBufferTestBase extends DataBufferTestBase { - - @Override - protected abstract FloatDataBuffer allocate(long size); - - @Override - protected Float valueOf(Long val) { - return val.floatValue(); - } - - @Test - public void writeAndReadFromArray() { - FloatDataBuffer buffer = allocate(10L); - float[] oneToFive = new float[]{ 1.0f, 2.0f, 3.0f, 4.0f, 5.0f }; - - buffer.write(oneToFive); - assertEquals(2.0f, buffer.getFloat(1), 0.0f); - - buffer.offset(5).write(oneToFive); - assertEquals(2.0f, buffer.getFloat(1), 0.0f); - assertEquals(2.0f, buffer.getFloat(6), 0.0f); - - float[] read = new float[5]; - buffer.read(read); - assertArrayEquals(oneToFive, read, 0.0f); - - buffer.write(oneToFive, 2, 2); - assertEquals(3.0f, buffer.getFloat(0), 0.0f); - assertEquals(4.0f, buffer.getFloat(1), 0.0f); - assertEquals(3.0f, buffer.getFloat(2), 0.0f); - - Arrays.fill(read, valueOf(0L)); - buffer.read(read, 1, 2); - assertEquals(0.0f, read[0], 0.0f); - assertEquals(3.0f, read[1], 0.0f); - assertEquals(4.0f, read[2], 0.0f); - assertEquals(0.0f, read[3], 0.0f); - } - - @Test - public void equalWithFloatNioBuffer() { - FloatDataBuffer nioBuffer1 = NioDataBufferFactory.create(FloatBuffer.wrap(new float[] { 1.0f, 16.0f })); - FloatDataBuffer nioBuffer2 = NioDataBufferFactory.create(FloatBuffer.wrap(new float[] { 1.0f, 25.0f })); - - FloatDataBuffer buffer = allocate(2) - .setFloat(1.0f, 0) - .setFloat(16.0f, 1); - - assertTrue(nioBuffer1.equals(buffer)); - assertTrue(buffer.equals(nioBuffer1)); - assertEquals(nioBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(nioBuffer2.equals(buffer)); - assertFalse(buffer.equals(nioBuffer2)); - assertNotEquals(nioBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void equalWithFloatRawBuffer() { - FloatDataBuffer rawBuffer1 = RawDataBufferFactory.create(new float[] { 1.0f, 16.0f }, true); - FloatDataBuffer rawBuffer2 = RawDataBufferFactory.create(new float[] { 1.0f, 25.0f }, true); - - FloatDataBuffer buffer = allocate(2) - .setFloat(1.0f, 0) - .setFloat(16.0f, 1); - - assertTrue(rawBuffer1.equals(buffer)); - assertTrue(buffer.equals(rawBuffer1)); - assertEquals(rawBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(rawBuffer2.equals(buffer)); - assertFalse(buffer.equals(rawBuffer2)); - assertNotEquals(rawBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void equalWithFloatObjectBuffer() { - DataBuffer objBuffer1 = MiscDataBufferFactory.create(new Float[] { 1.0f, 16.0f }, true); - DataBuffer objBuffer2 = MiscDataBufferFactory.create(new Float[] { 1.0f, 25.0f }, true); - - FloatDataBuffer buffer = allocate(2) - .setFloat(1.0f, 0) - .setFloat(16.0f, 1); - - assertTrue(objBuffer1.equals(buffer)); - assertTrue(buffer.equals(objBuffer1)); - assertEquals(objBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(objBuffer2.equals(buffer)); - assertFalse(buffer.equals(objBuffer2)); - assertNotEquals(objBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void notEqualWithOtherTypes() { - FloatDataBuffer buffer = allocate(2) - .setFloat(1.0f, 0) - .setFloat(16.0f, 1); - DoubleDataBuffer doubleBuffer = DataBuffers.of(1.0, 16.0); - - assertFalse(buffer.equals(doubleBuffer)); - assertFalse(doubleBuffer.equals(buffer)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/IntDataBufferTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/buffer/IntDataBufferTestBase.java deleted file mode 100644 index f3642e88ef8..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/IntDataBufferTestBase.java +++ /dev/null @@ -1,135 +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.ndarray.buffer; - -import static org.junit.jupiter.api.Assertions.assertArrayEquals; -import static org.junit.jupiter.api.Assertions.assertEquals; -import static org.junit.jupiter.api.Assertions.assertFalse; -import static org.junit.jupiter.api.Assertions.assertNotEquals; -import static org.junit.jupiter.api.Assertions.assertTrue; - -import java.nio.IntBuffer; -import java.util.Arrays; -import org.junit.jupiter.api.Test; -import org.tensorflow.ndarray.impl.buffer.misc.MiscDataBufferFactory; -import org.tensorflow.ndarray.impl.buffer.nio.NioDataBufferFactory; -import org.tensorflow.ndarray.impl.buffer.raw.RawDataBufferFactory; - -public abstract class IntDataBufferTestBase extends DataBufferTestBase { - - @Override - protected abstract IntDataBuffer allocate(long size); - - @Override - protected Integer valueOf(Long val) { - return val.intValue(); - } - - @Test - public void writeAndReadFromArray() { - IntDataBuffer buffer = allocate(10L); - int[] oneToFive = new int[]{ 1, 2, 3, 4, 5 }; - - buffer.write(oneToFive); - assertEquals(2, buffer.getInt(1)); - - buffer.offset(5).write(oneToFive); - assertEquals(2, buffer.getInt(1)); - assertEquals(2, buffer.getInt(6)); - - int[] read = new int[5]; - buffer.read(read); - assertArrayEquals(oneToFive, read); - - buffer.write(oneToFive, 2, 2); - assertEquals(3, buffer.getInt(0)); - assertEquals(4, buffer.getInt(1)); - assertEquals(3, buffer.getInt(2)); - - Arrays.fill(read, valueOf(0L)); - buffer.read(read, 1, 2); - assertEquals(0, read[0]); - assertEquals(3, read[1]); - assertEquals(4, read[2]); - assertEquals(0, read[3]); - } - - @Test - public void equalWithIntNioBuffer() { - IntDataBuffer nioBuffer1 = NioDataBufferFactory.create(IntBuffer.wrap(new int[] { 1, 16 })); - IntDataBuffer nioBuffer2 = NioDataBufferFactory.create(IntBuffer.wrap(new int[] { 1, 25 })); - - IntDataBuffer buffer = allocate(2) - .setInt(1, 0) - .setInt(16, 1); - - assertTrue(nioBuffer1.equals(buffer)); - assertTrue(buffer.equals(nioBuffer1)); - assertEquals(nioBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(nioBuffer2.equals(buffer)); - assertFalse(buffer.equals(nioBuffer2)); - assertNotEquals(nioBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void equalWithIntRawBuffer() { - IntDataBuffer rawBuffer1 = RawDataBufferFactory.create(new int[] { 1, 16 }, true); - IntDataBuffer rawBuffer2 = RawDataBufferFactory.create(new int[] { 1, 25 }, true); - - IntDataBuffer buffer = allocate(2) - .setInt(1, 0) - .setInt(16, 1); - - assertTrue(rawBuffer1.equals(buffer)); - assertTrue(buffer.equals(rawBuffer1)); - assertEquals(rawBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(rawBuffer2.equals(buffer)); - assertFalse(buffer.equals(rawBuffer2)); - assertNotEquals(rawBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void equalWithIntObjectBuffer() { - DataBuffer objBuffer1 = MiscDataBufferFactory.create(new Integer[] { 1, 16 }, true); - DataBuffer objBuffer2 = MiscDataBufferFactory.create(new Integer[] { 1, 25 }, true); - - IntDataBuffer buffer = allocate(2) - .setInt(1, 0) - .setInt(16, 1); - - assertTrue(objBuffer1.equals(buffer)); - assertTrue(buffer.equals(objBuffer1)); - assertEquals(objBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(objBuffer2.equals(buffer)); - assertFalse(buffer.equals(objBuffer2)); - assertNotEquals(objBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void notEqualWithOtherTypes() { - IntDataBuffer buffer = allocate(2) - .setInt(1, 0) - .setInt(16, 1); - LongDataBuffer longBuffer = DataBuffers.of(1L, 16L); - - assertFalse(buffer.equals(longBuffer)); - assertFalse(longBuffer.equals(buffer)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/LongDataBufferTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/buffer/LongDataBufferTestBase.java deleted file mode 100644 index e0d8b1b4539..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/LongDataBufferTestBase.java +++ /dev/null @@ -1,135 +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.ndarray.buffer; - -import static org.junit.jupiter.api.Assertions.assertArrayEquals; -import static org.junit.jupiter.api.Assertions.assertEquals; -import static org.junit.jupiter.api.Assertions.assertFalse; -import static org.junit.jupiter.api.Assertions.assertNotEquals; -import static org.junit.jupiter.api.Assertions.assertTrue; - -import java.nio.LongBuffer; -import java.util.Arrays; -import org.junit.jupiter.api.Test; -import org.tensorflow.ndarray.impl.buffer.misc.MiscDataBufferFactory; -import org.tensorflow.ndarray.impl.buffer.nio.NioDataBufferFactory; -import org.tensorflow.ndarray.impl.buffer.raw.RawDataBufferFactory; - -public abstract class LongDataBufferTestBase extends DataBufferTestBase { - - @Override - protected abstract LongDataBuffer allocate(long size); - - @Override - protected Long valueOf(Long val) { - return val; - } - - @Test - public void writeAndReadFromArray() { - LongDataBuffer buffer = allocate(10L); - long[] oneToFive = new long[]{ 1L, 2L, 3L, 4L, 5L }; - - buffer.write(oneToFive); - assertEquals(2, buffer.getLong(1)); - - buffer.offset(5).write(oneToFive); - assertEquals(2L, buffer.getLong(1)); - assertEquals(2L, buffer.getLong(6)); - - long[] read = new long[5]; - buffer.read(read); - assertArrayEquals(oneToFive, read); - - buffer.write(oneToFive, 2, 2); - assertEquals(3L, buffer.getLong(0)); - assertEquals(4L, buffer.getLong(1)); - assertEquals(3L, buffer.getLong(2)); - - Arrays.fill(read, valueOf(0L)); - buffer.read(read, 1, 2); - assertEquals(0L, read[0]); - assertEquals(3L, read[1]); - assertEquals(4L, read[2]); - assertEquals(0L, read[3]); - } - - @Test - public void equalWithLongNioBuffer() { - LongDataBuffer nioBuffer1 = NioDataBufferFactory.create(LongBuffer.wrap(new long[] { 1, 16 })); - LongDataBuffer nioBuffer2 = NioDataBufferFactory.create(LongBuffer.wrap(new long[] { 1, 25 })); - - LongDataBuffer buffer = allocate(2) - .setLong(1, 0) - .setLong(16, 1); - - assertTrue(nioBuffer1.equals(buffer)); - assertTrue(buffer.equals(nioBuffer1)); - assertEquals(nioBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(nioBuffer2.equals(buffer)); - assertFalse(buffer.equals(nioBuffer2)); - assertNotEquals(nioBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void equalWithLongRawBuffer() { - LongDataBuffer rawBuffer1 = RawDataBufferFactory.create(new long[] { 1, 16 }, true); - LongDataBuffer rawBuffer2 = RawDataBufferFactory.create(new long[] { 1, 25 }, true); - - LongDataBuffer buffer = allocate(2) - .setLong(1, 0) - .setLong(16, 1); - - assertTrue(rawBuffer1.equals(buffer)); - assertTrue(buffer.equals(rawBuffer1)); - assertEquals(rawBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(rawBuffer2.equals(buffer)); - assertFalse(buffer.equals(rawBuffer2)); - assertNotEquals(rawBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void equalWithLongObjectBuffer() { - DataBuffer objBuffer1 = MiscDataBufferFactory.create(new Long[] { 1L, 16L }, true); - DataBuffer objBuffer2 = MiscDataBufferFactory.create(new Long[] { 1L, 25L }, true); - - LongDataBuffer buffer = allocate(2) - .setLong(1, 0) - .setLong(16, 1); - - assertTrue(objBuffer1.equals(buffer)); - assertTrue(buffer.equals(objBuffer1)); - assertEquals(objBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(objBuffer2.equals(buffer)); - assertFalse(buffer.equals(objBuffer2)); - assertNotEquals(objBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void notEqualWithOtherTypes() { - LongDataBuffer buffer = allocate(2) - .setLong(1L, 0) - .setLong(16L, 1); - IntDataBuffer intBuffer = DataBuffers.of(1, 16); - - assertFalse(buffer.equals(intBuffer)); - assertFalse(intBuffer.equals(buffer)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/ShortDataBufferTestBase.java b/ndarray/src/test/java/org/tensorflow/ndarray/buffer/ShortDataBufferTestBase.java deleted file mode 100644 index f3269e85a8f..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/buffer/ShortDataBufferTestBase.java +++ /dev/null @@ -1,135 +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.ndarray.buffer; - -import static org.junit.jupiter.api.Assertions.assertArrayEquals; -import static org.junit.jupiter.api.Assertions.assertEquals; -import static org.junit.jupiter.api.Assertions.assertFalse; -import static org.junit.jupiter.api.Assertions.assertNotEquals; -import static org.junit.jupiter.api.Assertions.assertTrue; - -import java.nio.ShortBuffer; -import java.util.Arrays; -import org.junit.jupiter.api.Test; -import org.tensorflow.ndarray.impl.buffer.misc.MiscDataBufferFactory; -import org.tensorflow.ndarray.impl.buffer.nio.NioDataBufferFactory; -import org.tensorflow.ndarray.impl.buffer.raw.RawDataBufferFactory; - -public abstract class ShortDataBufferTestBase extends DataBufferTestBase { - - @Override - protected abstract ShortDataBuffer allocate(long size); - - @Override - protected Short valueOf(Long val) { - return val.shortValue(); - } - - @Test - public void writeAndReadFromArray() { - ShortDataBuffer buffer = allocate(10L); - short[] oneToFive = new short[]{ 1, 2, 3, 4, 5 }; - - buffer.write(oneToFive); - assertEquals(2, buffer.getShort(1)); - - buffer.offset(5).write(oneToFive); - assertEquals(2, buffer.getShort(1), 0); - assertEquals(2, buffer.getShort(6), 0); - - short[] read = new short[5]; - buffer.read(read); - assertArrayEquals(oneToFive, read); - - buffer.write(oneToFive, 2, 2); - assertEquals(3, buffer.getShort(0)); - assertEquals(4, buffer.getShort(1)); - assertEquals(3, buffer.getShort(2)); - - Arrays.fill(read, valueOf(0L)); - buffer.read(read, 1, 2); - assertEquals(0, read[0]); - assertEquals(3, read[1]); - assertEquals(4, read[2]); - assertEquals(0, read[3]); - } - - @Test - public void equalWithShortNioBuffer() { - ShortDataBuffer nioBuffer1 = NioDataBufferFactory.create(ShortBuffer.wrap(new short[] { 1, 16 })); - ShortDataBuffer nioBuffer2 = NioDataBufferFactory.create(ShortBuffer.wrap(new short[] { 1, 25 })); - - ShortDataBuffer buffer = allocate(2) - .setShort((short)1, 0) - .setShort((short)16, 1); - - assertTrue(nioBuffer1.equals(buffer)); - assertTrue(buffer.equals(nioBuffer1)); - assertEquals(nioBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(nioBuffer2.equals(buffer)); - assertFalse(buffer.equals(nioBuffer2)); - assertNotEquals(nioBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void equalWithShortRawBuffer() { - ShortDataBuffer rawBuffer1 = RawDataBufferFactory.create(new short[] { 1, 16 }, true); - ShortDataBuffer rawBuffer2 = RawDataBufferFactory.create(new short[] { 1, 25 }, true); - - ShortDataBuffer buffer = allocate(2) - .setShort((short)1, 0) - .setShort((short)16, 1); - - assertTrue(rawBuffer1.equals(buffer)); - assertTrue(buffer.equals(rawBuffer1)); - assertEquals(rawBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(rawBuffer2.equals(buffer)); - assertFalse(buffer.equals(rawBuffer2)); - assertNotEquals(rawBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void equalWithShortObjectBuffer() { - DataBuffer objBuffer1 = MiscDataBufferFactory.create(new Short[] { 1, 16 }, true); - DataBuffer objBuffer2 = MiscDataBufferFactory.create(new Short[] { 1, 25 }, true); - - ShortDataBuffer buffer = allocate(2) - .setShort((short)1, 0) - .setShort((short)16, 1); - - assertTrue(objBuffer1.equals(buffer)); - assertTrue(buffer.equals(objBuffer1)); - assertEquals(objBuffer1.hashCode(), buffer.hashCode()); - - assertFalse(objBuffer2.equals(buffer)); - assertFalse(buffer.equals(objBuffer2)); - assertNotEquals(objBuffer2.hashCode(), buffer.hashCode()); - } - - @Test - public void notEqualWithOtherTypes() { - ShortDataBuffer buffer = allocate(2) - .setShort((short)1, 0) - .setShort((short)16, 1); - LongDataBuffer longBuffer = DataBuffers.of(1L, 16L); - - assertFalse(buffer.equals(longBuffer)); - assertFalse(longBuffer.equals(buffer)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/BigIntegerDataBufferAdapterTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/BigIntegerDataBufferAdapterTest.java deleted file mode 100644 index 4bb86fe3f33..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/BigIntegerDataBufferAdapterTest.java +++ /dev/null @@ -1,67 +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.ndarray.impl.buffer.adapter; - -import java.math.BigInteger; -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBufferTestBase; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.buffer.layout.DataLayout; - -public class BigIntegerDataBufferAdapterTest extends DataBufferTestBase { - - @Override - protected DataBuffer allocate(long size) { - return LAYOUT.applyTo(DataBuffers.ofBytes(size * LAYOUT.scale())); - } - - @Override - protected long maxSize() { - return super.maxSize() / 3; - } - - @Override - protected BigInteger valueOf(Long val) { - return BigInteger.valueOf(val); - } - - private static DataLayout LAYOUT = new DataLayout() { - - @Override - public void writeObject(ByteDataBuffer buffer, BigInteger value, long index) { - byte[] bytes = value.toByteArray(); - buffer.setByte(bytes.length > 2 ? bytes[2] : 0, index); - buffer.setByte(bytes.length > 1 ? bytes[1] : 0, index + 1); - buffer.setByte(bytes[0], index + 2); - } - - @Override - public BigInteger readObject(ByteDataBuffer buffer, long index) { - byte byte2 = buffer.getByte(index); - byte byte1 = buffer.getByte(index + 1); - byte byte0 = buffer.getByte(index + 2); - return new BigInteger(new byte[] { byte2, byte1, byte0 }); - } - - @Override - public int scale() { - return 3; - } - }; -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/BooleanDataBufferAdapterTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/BooleanDataBufferAdapterTest.java deleted file mode 100644 index a15e8f388a8..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/BooleanDataBufferAdapterTest.java +++ /dev/null @@ -1,45 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.BooleanDataBufferTestBase; -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.buffer.layout.BooleanDataLayout; - -public class BooleanDataBufferAdapterTest extends BooleanDataBufferTestBase { - - @Override - protected BooleanDataBuffer allocate(long size) { - return LAYOUT.applyTo(DataBuffers.ofBytes(size * LAYOUT.scale())); - } - - private static BooleanDataLayout LAYOUT = new BooleanDataLayout() { - - @Override - public void writeBoolean(ByteDataBuffer buffer, boolean value, long index) { - buffer.setByte((byte)(value ? 1 : 0), index); - } - - @Override - public boolean readBoolean(ByteDataBuffer buffer, long index) { - return buffer.getByte(index) > 0; - } - }; -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/ByteDataBufferAdapterTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/ByteDataBufferAdapterTest.java deleted file mode 100644 index 8a6287601f5..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/ByteDataBufferAdapterTest.java +++ /dev/null @@ -1,27 +0,0 @@ -package org.tensorflow.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.ByteDataBufferTestBase; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.buffer.layout.ByteDataLayout; - -public class ByteDataBufferAdapterTest extends ByteDataBufferTestBase { - - public ByteDataBuffer allocate(long size) { - return LAYOUT.applyTo(DataBuffers.ofShorts(size * LAYOUT.scale())); - } - - private static ByteDataLayout LAYOUT = new ByteDataLayout() { - - @Override - public void writeByte(ShortDataBuffer buffer, byte value, long index) { - buffer.setShort(value, index); - } - - @Override - public byte readByte(ShortDataBuffer buffer, long index) { - return (byte)buffer.getShort(index); - } - }; -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/DoubleDataBufferAdapterTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/DoubleDataBufferAdapterTest.java deleted file mode 100644 index 8dfee1182b1..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/DoubleDataBufferAdapterTest.java +++ /dev/null @@ -1,61 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.buffer.DoubleDataBufferTestBase; -import org.tensorflow.ndarray.buffer.layout.DoubleDataLayout; - -public class DoubleDataBufferAdapterTest extends DoubleDataBufferTestBase { - - @Override - protected DoubleDataBuffer allocate(long size) { - return LAYOUT.applyTo(DataBuffers.ofBytes(size * LAYOUT.scale())); - } - - @Override - protected long maxSize() { - return super.maxSize() / 3; - } - - private static DoubleDataLayout LAYOUT = new DoubleDataLayout() { - - @Override - public void writeDouble(ByteDataBuffer buffer, double value, long index) { - long bits = Double.doubleToLongBits(value); - buffer.setByte((byte)((bits >> 56) & 0xFF), index); - buffer.setByte((byte)((bits >> 48) & 0xFF), index + 1); - buffer.setByte((byte)((bits >> 40) & 0xFF), index + 2); - } - - @Override - public double readDouble(ByteDataBuffer buffer, long index) { - long byte7 = buffer.getByte(index); - long byte6 = buffer.getByte(index + 1); - long byte5 = buffer.getByte(index + 2); - return Double.longBitsToDouble(((byte7 & 0xFF) << 56) | ((byte6 & 0xFF) << 48) | ((byte5 & 0xFF) << 40)); - } - - @Override - public int scale() { - return 3; - } - }; -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/FloatDataBufferAdapterTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/FloatDataBufferAdapterTest.java deleted file mode 100644 index 82b8ee947dd..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/FloatDataBufferAdapterTest.java +++ /dev/null @@ -1,52 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBufferTestBase; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.buffer.layout.FloatDataLayout; - -public class FloatDataBufferAdapterTest extends FloatDataBufferTestBase { - - @Override - public FloatDataBuffer allocate(long size) { - return LAYOUT.applyTo(DataBuffers.ofShorts(size * LAYOUT.scale())); - } - - @Override - protected long maxSize() { - return super.maxSize() / 2; - } - - private static FloatDataLayout LAYOUT = new FloatDataLayout() { - - @Override - public void writeFloat(ShortDataBuffer buffer, float value, long index) { - int bits = Float.floatToIntBits(value); - buffer.setShort((short)(bits >> 16), index); - } - - @Override - public float readFloat(ShortDataBuffer buffer, long index) { - int i = buffer.getShort(index); - return Float.intBitsToFloat(i << 16); - } - }; -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/IntDataBufferAdapterTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/IntDataBufferAdapterTest.java deleted file mode 100644 index 9c00f92b00d..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/IntDataBufferAdapterTest.java +++ /dev/null @@ -1,51 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBufferTestBase; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.buffer.layout.IntDataLayout; - -public class IntDataBufferAdapterTest extends IntDataBufferTestBase { - - @Override - protected IntDataBuffer allocate(long size) { - return LAYOUT.applyTo(DataBuffers.ofShorts(size * LAYOUT.scale())); - } - - @Override - protected long maxSize() { - return super.maxSize() / 2; - } - - private static IntDataLayout LAYOUT = new IntDataLayout() { - - @Override - public void writeInt(ShortDataBuffer buffer, int value, long index) { - buffer.setShort((short)(((value & 0x80000000) >> 16) | (value & 0x7FFF)), index); - } - - @Override - public int readInt(ShortDataBuffer buffer, long index) { - int i = buffer.getShort(index); - return ((i & 0x8000) << 16) | ((i & 0x7FFF)); - } - }; -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/LongDataBufferAdapterTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/LongDataBufferAdapterTest.java deleted file mode 100644 index 40bc4c55b3e..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/LongDataBufferAdapterTest.java +++ /dev/null @@ -1,60 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBufferTestBase; -import org.tensorflow.ndarray.buffer.layout.LongDataLayout; - -public class LongDataBufferAdapterTest extends LongDataBufferTestBase { - - @Override - protected LongDataBuffer allocate(long size) { - return LAYOUT.applyTo(DataBuffers.ofBytes(size * LAYOUT.scale())); - } - - @Override - protected long maxSize() { - return super.maxSize() / 3; - } - - private static LongDataLayout LAYOUT = new LongDataLayout() { - - @Override - public void writeLong(ByteDataBuffer buffer, long value, long index) { - buffer.setByte((byte)(((value >> 56) & 0x80) | ((value >> 16) & 0x7F)), index); - buffer.setByte((byte)((value >> 8) & 0xFF), index + 1); - buffer.setByte((byte)(value & 0xFF), index + 2); - } - - @Override - public long readLong(ByteDataBuffer buffer, long index) { - long msb = buffer.getByte(index); - long midb = buffer.getByte(index + 1); - long lsb = buffer.getByte(index + 2); - return ((msb & 0x80) << 56) | ((msb & 0x7F) << 16) | ((midb & 0xFF) << 8) | (lsb & 0xFF); - } - - @Override - public int scale() { - return 3; - } - }; -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/ShortDataBufferAdapterTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/ShortDataBufferAdapterTest.java deleted file mode 100644 index 3c11d3a46ad..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/adapter/ShortDataBufferAdapterTest.java +++ /dev/null @@ -1,45 +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.ndarray.impl.buffer.adapter; - -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBufferTestBase; -import org.tensorflow.ndarray.buffer.layout.ShortDataLayout; - -public class ShortDataBufferAdapterTest extends ShortDataBufferTestBase { - - public ShortDataBuffer allocate(long size) { - return LAYOUT.applyTo(DataBuffers.ofBytes(size * LAYOUT.scale())); - } - - private static ShortDataLayout LAYOUT = new ShortDataLayout() { - - @Override - public void writeShort(ByteDataBuffer buffer, short value, long index) { - buffer.setByte((byte)(((value & 0x8000) >> 8) | (value & 0x7F)), index); - } - - @Override - public short readShort(ByteDataBuffer buffer, long index) { - int b = buffer.getByte(index); - return (short)(((b & 0x80) << 8) | (b & 0x7F)); - } - }; -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/layout/Bfloat16LayoutTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/layout/Bfloat16LayoutTest.java deleted file mode 100644 index 48ddeb1c56e..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/layout/Bfloat16LayoutTest.java +++ /dev/null @@ -1,84 +0,0 @@ -/* - * 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.ndarray.impl.buffer.layout; - -import static org.junit.jupiter.api.Assertions.assertEquals; - -import org.junit.jupiter.api.Test; - -public class Bfloat16LayoutTest { - - @Test - public void testFloat32to16() { - - // Zero and subnormals - assertEquals((short)0x0000, Bfloat16Layout.float32to16(0.0f)); - assertEquals((short)0x8000, Bfloat16Layout.float32to16(-0.0f)); - assertEquals((short)0x0001, Bfloat16Layout.float32to16(1e-40f)); - assertEquals((short)0xC000, Bfloat16Layout.float32to16(-2.0f)); - assertEquals((short)0x0000, Bfloat16Layout.float32to16(4.59e-41f)); - - // Infinite and NaN - assertEquals((short)0x7F80, Bfloat16Layout.float32to16(Float.POSITIVE_INFINITY)); - assertEquals((short)0xFF80, Bfloat16Layout.float32to16(Float.NEGATIVE_INFINITY)); - assertEquals((short)0x7FC0, Bfloat16Layout.float32to16(Float.NaN)); - assertEquals((short)0x7FC0, Bfloat16Layout.float32to16(Float.intBitsToFloat(0xFFFFFFFF))); - - // Normalized - assertEquals((short)0x3F80, Bfloat16Layout.float32to16(1.0f)); - assertEquals((short)0xBF80, Bfloat16Layout.float32to16(-1.0f)); - assertEquals((short)0x42C8, Bfloat16Layout.float32to16(100.0f)); - assertEquals((short)0xC2CA, Bfloat16Layout.float32to16(-101.0f)); - assertEquals((short)0x3F8F, Bfloat16Layout.float32to16(1.1171875f)); - assertEquals((short)0x4800, Bfloat16Layout.float32to16(131072f)); - assertEquals((short)0x7F7F, Bfloat16Layout.float32to16(3.3895314e38f)); - assertEquals((short)0xFF7F, Bfloat16Layout.float32to16(-3.3895314e38f)); - - // Rounding up - assertEquals((short)0x3FCF, Bfloat16Layout.float32to16(1.6191406f)); // 1.6171875 - assertEquals((short)0x4780, Bfloat16Layout.float32to16(65600.0f)); // 65536.0 - } - - @Test - public void testFloat16to32() { - - // Zero and subnormals - assertEquals(0.0f, Bfloat16Layout.float16to32((short)0x0000), 0); - assertEquals(-0.0f, Bfloat16Layout.float16to32((short)0x8000), 0); - assertEquals(9.18355E-41f, Bfloat16Layout.float16to32((short)0x0001), 1e-8f); - assertEquals(-9.403955E-38, Bfloat16Layout.float16to32((short)0x8200), 1e-8f); - - // Infinite and NaN - assertEquals(Float.POSITIVE_INFINITY, Bfloat16Layout.float16to32((short)0x7F80), 0); - assertEquals(Float.NEGATIVE_INFINITY, Bfloat16Layout.float16to32((short)0xFF80), 0); - assertEquals(Float.NaN, Bfloat16Layout.float16to32((short)0x7FC0), 0); - assertEquals(Float.intBitsToFloat(0xFFFFFFFF), Bfloat16Layout.float16to32((short)0x7FC0), 0); - - // Normalized - assertEquals(1.0f, Bfloat16Layout.float16to32((short)0x3F80), 0); - assertEquals(-1.0f, Bfloat16Layout.float16to32((short)0xBF80), 0); - assertEquals(100.0f, Bfloat16Layout.float16to32((short)0x42C8), 0); - assertEquals(-101.0f, Bfloat16Layout.float16to32((short)0xC2CA), 0); - assertEquals(1.1171875f, Bfloat16Layout.float16to32((short)0x3F8F), 0); - assertEquals(131072f, Bfloat16Layout.float16to32((short)0x4800), 0); - assertEquals(3.3895314e38f, Bfloat16Layout.float16to32((short)0x7F7F), 0); - assertEquals(-3.3895314e38f, Bfloat16Layout.float16to32((short)0xFF7F), 0); - assertEquals(1.6171875f, Bfloat16Layout.float16to32((short)0x3FCF), 0); - assertEquals(65536.0, Bfloat16Layout.float16to32((short)0x4780), 0); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/layout/BoolLayoutTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/layout/BoolLayoutTest.java deleted file mode 100644 index 6ba903cadec..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/layout/BoolLayoutTest.java +++ /dev/null @@ -1,42 +0,0 @@ -/* - * 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.ndarray.impl.buffer.layout; - -import static org.junit.jupiter.api.Assertions.assertEquals; -import static org.junit.jupiter.api.Assertions.assertFalse; -import static org.junit.jupiter.api.Assertions.assertTrue; - -import org.junit.jupiter.api.Test; - -public class BoolLayoutTest { - - @Test - public void booleanToByteTest() { - assertEquals((byte)1, BoolLayout.booleanToByte(true)); - assertEquals((byte)0, BoolLayout.booleanToByte(false)); - } - - @Test - public void byteToBooleanTest() { - assertTrue(BoolLayout.byteToBoolean((byte)1)); - assertTrue(BoolLayout.byteToBoolean((byte)127)); - assertTrue(BoolLayout.byteToBoolean((byte)-128)); - assertTrue(BoolLayout.byteToBoolean((byte)255)); - assertFalse(BoolLayout.byteToBoolean((byte)0)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/layout/Float16LayoutTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/layout/Float16LayoutTest.java deleted file mode 100644 index 7bc430ac4ba..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/layout/Float16LayoutTest.java +++ /dev/null @@ -1,90 +0,0 @@ -/* - * 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.ndarray.impl.buffer.layout; - -import static org.junit.jupiter.api.Assertions.assertEquals; - -import org.junit.jupiter.api.Test; - -public class Float16LayoutTest { - - @Test - public void testFloat32to16() { - - // Zero and subnormals - assertEquals((short)0x0000, Float16Layout.float32to16(0.0f)); - assertEquals((short)0x8000, Float16Layout.float32to16(-0.0f)); - assertEquals((short)0x0001, Float16Layout.float32to16(6e-8f)); - assertEquals((short)0x8200, Float16Layout.float32to16(-3.052e-5f)); - assertEquals((short)0x0000, Float16Layout.float32to16(6e-9f)); - - // Infinite and NaN - assertEquals((short)0x7C00, Float16Layout.float32to16(Float.POSITIVE_INFINITY)); - assertEquals((short)0xFC00, Float16Layout.float32to16(Float.NEGATIVE_INFINITY)); - assertEquals((short)0x7C00, Float16Layout.float32to16(65520.0f)); - assertEquals((short)0x7C00, Float16Layout.float32to16(165536.0f)); - assertEquals((short)0xFC00, Float16Layout.float32to16(-65520.0f)); - assertEquals((short)0x7E00, Float16Layout.float32to16(Float.NaN)); - assertEquals((short)0x7E00, Float16Layout.float32to16(Float.intBitsToFloat(0xFFFFFFFF))); - - // Normalized - assertEquals((short)0x7BFF, Float16Layout.float32to16(65519.0f)); - assertEquals((short)0x3C00, Float16Layout.float32to16(1.0f)); - assertEquals((short)0xBC00, Float16Layout.float32to16(-1.0f)); - assertEquals((short)0x5640, Float16Layout.float32to16(100.0f)); - assertEquals((short)0xD650, Float16Layout.float32to16(-101.0f)); - assertEquals((short)0x3C7E, Float16Layout.float32to16(1.123f)); - - // Rounding up - assertEquals((short)0x3C7E, Float16Layout.float32to16(1.1235f)); // 1.123 - assertEquals((short)0x3C7F, Float16Layout.float32to16(1.1236f)); // 1.124 - assertEquals((short)0x4000, Float16Layout.float32to16(2.0009f)); // 2.0 - assertEquals((short)0x4001, Float16Layout.float32to16(2.001f)); // 2.002 - assertEquals((short)0x5C00, Float16Layout.float32to16(256.125f)); // 256.0 - assertEquals((short)0x5C01, Float16Layout.float32to16(256.126f)); // 256.3 - assertEquals((short)0x5C01, Float16Layout.float32to16(256.30f)); // 256.3 - assertEquals((short)0x5C01, Float16Layout.float32to16(256.374f)); // 256.3 - assertEquals((short)0x5C02, Float16Layout.float32to16(256.375f)); // 256.5 - assertEquals((short)0x5C02, Float16Layout.float32to16(256.51f)); // 256.5 - } - - @Test - public void testFloat16to32() { - - // Zero and subnormals - assertEquals(0.0f, Float16Layout.float16to32((short)0x0000), 0); - assertEquals(-0.0f, Float16Layout.float16to32((short)0x8000), 0); - assertEquals(6e-8f, Float16Layout.float16to32((short)0x0001), 1e-8f); - assertEquals(-3.052e-5f, Float16Layout.float16to32((short)0x8200), 1e-8f); - - // Infinite and NaN - assertEquals(Float.POSITIVE_INFINITY, Float16Layout.float16to32((short)0x7C00), 0); - assertEquals(Float.NEGATIVE_INFINITY, Float16Layout.float16to32((short)0xFC00), 0); - assertEquals(Float.NaN, Float16Layout.float16to32((short)0x7E00), 0); - assertEquals(Float.intBitsToFloat(0xFFFFFFFF), Float16Layout.float16to32((short)0x7E00), 0); - - // Normalized - assertEquals(1.0f, Float16Layout.float16to32((short)0x3C00), 1e-1f); - assertEquals(-1.0f, Float16Layout.float16to32((short)0xBC00), 1e-1f); - assertEquals(100.0f, Float16Layout.float16to32((short)0x5640), 1e-1f); - assertEquals(-101.0f, Float16Layout.float16to32((short)0xD650), 1e-1f); - assertEquals(1.123f, Float16Layout.float16to32((short)0x3C7E), 1e-3f); - assertEquals(1.123f, Float16Layout.float16to32((short)0x3C7E), 1e-3f); - assertEquals(-62.34f, Float16Layout.float16to32((short)0xD3CB), 1e-2f); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/misc/ArrayDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/misc/ArrayDataBufferTest.java deleted file mode 100644 index 1c43a3e3638..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/misc/ArrayDataBufferTest.java +++ /dev/null @@ -1,265 +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.ndarray.impl.buffer.misc; - -import static org.junit.jupiter.api.Assertions.assertEquals; -import static org.junit.jupiter.api.Assertions.assertFalse; -import static org.junit.jupiter.api.Assertions.assertNotEquals; -import static org.junit.jupiter.api.Assertions.assertTrue; - -import java.math.BigDecimal; -import org.junit.jupiter.api.Test; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBufferTestBase; - -public class ArrayDataBufferTest extends DataBufferTestBase { - - @Override - protected DataBuffer allocate(long size) { - return new ArrayDataBuffer<>(new BigDecimal[(int)size], false); - } - - @Override - protected BigDecimal valueOf(Long val) { - return BigDecimal.valueOf(val); - } - - @Test - public void byteArrayBufferEquals() { - DataBuffer buffer1 = new ArrayDataBuffer<>(new byte[][] { { 0x01 }, { 0x03 } }, true); - DataBuffer buffer2 = new ArrayDataBuffer<>(new byte[][] { { 0x01 }, { 0x03 } }, true); - DataBuffer buffer3 = new ArrayDataBuffer<>(new byte[][] { { 0x02 }, { 0x03 } }, true); - DataBuffer buffer4 = new ArrayDataBuffer<>(new byte[][][] { { { 0x01 } }, { { 0x03 } } }, true); - DataBuffer buffer5 = new ArrayDataBuffer<>(new byte[][][] { { { 0x01 } }, { { 0x03 } } }, true); - - assertTrue(buffer1.equals(buffer2)); - assertTrue(buffer2.equals(buffer1)); - assertEquals(buffer1.hashCode(), buffer2.hashCode()); - - assertFalse(buffer1.equals(buffer3)); - assertFalse(buffer3.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer3.hashCode()); - - assertFalse(buffer1.equals(buffer4)); - assertFalse(buffer4.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer4.hashCode()); - - assertTrue(buffer4.equals(buffer5)); - assertTrue(buffer4.equals(buffer5)); - assertEquals(buffer4.hashCode(), buffer5.hashCode()); - } - - @Test - public void intArrayBufferEquals() { - DataBuffer buffer1 = new ArrayDataBuffer<>(new int[][] { { 10 }, { 30 } }, true); - DataBuffer buffer2 = new ArrayDataBuffer<>(new int[][] { { 10 }, { 30 } }, true); - DataBuffer buffer3 = new ArrayDataBuffer<>(new int[][] { { 20 }, { 30 } }, true); - DataBuffer buffer4 = new ArrayDataBuffer<>(new int[][][] { { { 10 } }, { { 30 } } }, true); - DataBuffer buffer5 = new ArrayDataBuffer<>(new int[][][] { { { 10 } }, { { 30 } } }, true); - - assertTrue(buffer1.equals(buffer2)); - assertTrue(buffer2.equals(buffer1)); - assertEquals(buffer1.hashCode(), buffer2.hashCode()); - - assertFalse(buffer1.equals(buffer3)); - assertFalse(buffer3.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer3.hashCode()); - - assertFalse(buffer1.equals(buffer4)); - assertFalse(buffer4.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer4.hashCode()); - - assertTrue(buffer4.equals(buffer5)); - assertTrue(buffer4.equals(buffer5)); - assertEquals(buffer4.hashCode(), buffer5.hashCode()); - } - - @Test - public void shortArrayBufferEquals() { - DataBuffer buffer1 = new ArrayDataBuffer<>(new short[][] { { 10 }, { 30 } }, true); - DataBuffer buffer2 = new ArrayDataBuffer<>(new short[][] { { 10 }, { 30 } }, true); - DataBuffer buffer3 = new ArrayDataBuffer<>(new short[][] { { 20 }, { 30 } }, true); - DataBuffer buffer4 = new ArrayDataBuffer<>(new short[][][] { { { 10 } }, { { 30 } } }, true); - DataBuffer buffer5 = new ArrayDataBuffer<>(new short[][][] { { { 10 } }, { { 30 } } }, true); - - assertTrue(buffer1.equals(buffer2)); - assertTrue(buffer2.equals(buffer1)); - assertEquals(buffer1.hashCode(), buffer2.hashCode()); - - assertFalse(buffer1.equals(buffer3)); - assertFalse(buffer3.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer3.hashCode()); - - assertFalse(buffer1.equals(buffer4)); - assertFalse(buffer4.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer4.hashCode()); - - assertTrue(buffer4.equals(buffer5)); - assertTrue(buffer4.equals(buffer5)); - assertEquals(buffer4.hashCode(), buffer5.hashCode()); - } - - @Test - public void longArrayBufferEquals() { - DataBuffer buffer1 = new ArrayDataBuffer<>(new long[][] { { 10 }, { 30 } }, true); - DataBuffer buffer2 = new ArrayDataBuffer<>(new long[][] { { 10 }, { 30 } }, true); - DataBuffer buffer3 = new ArrayDataBuffer<>(new long[][] { { 20 }, { 30 } }, true); - DataBuffer buffer4 = new ArrayDataBuffer<>(new long[][][] { { { 10 } }, { { 30 } } }, true); - DataBuffer buffer5 = new ArrayDataBuffer<>(new long[][][] { { { 10 } }, { { 30 } } }, true); - - assertTrue(buffer1.equals(buffer2)); - assertTrue(buffer2.equals(buffer1)); - assertEquals(buffer1.hashCode(), buffer2.hashCode()); - - assertFalse(buffer1.equals(buffer3)); - assertFalse(buffer3.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer3.hashCode()); - - assertFalse(buffer1.equals(buffer4)); - assertFalse(buffer4.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer4.hashCode()); - - assertTrue(buffer4.equals(buffer5)); - assertTrue(buffer4.equals(buffer5)); - assertEquals(buffer4.hashCode(), buffer5.hashCode()); - } - - @Test - public void floatArrayBufferEquals() { - DataBuffer buffer1 = new ArrayDataBuffer<>(new float[][] { { 10 }, { 30 } }, true); - DataBuffer buffer2 = new ArrayDataBuffer<>(new float[][] { { 10 }, { 30 } }, true); - DataBuffer buffer3 = new ArrayDataBuffer<>(new float[][] { { 20 }, { 30 } }, true); - DataBuffer buffer4 = new ArrayDataBuffer<>(new float[][][] { { { 10 } }, { { 30 } } }, true); - DataBuffer buffer5 = new ArrayDataBuffer<>(new float[][][] { { { 10 } }, { { 30 } } }, true); - - assertTrue(buffer1.equals(buffer2)); - assertTrue(buffer2.equals(buffer1)); - assertEquals(buffer1.hashCode(), buffer2.hashCode()); - - assertFalse(buffer1.equals(buffer3)); - assertFalse(buffer3.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer3.hashCode()); - - assertFalse(buffer1.equals(buffer4)); - assertFalse(buffer4.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer4.hashCode()); - - assertTrue(buffer4.equals(buffer5)); - assertTrue(buffer4.equals(buffer5)); - assertEquals(buffer4.hashCode(), buffer5.hashCode()); - } - - @Test - public void doubleArrayBufferEquals() { - DataBuffer buffer1 = new ArrayDataBuffer<>(new double[][] { { 10 }, { 30 } }, true); - DataBuffer buffer2 = new ArrayDataBuffer<>(new double[][] { { 10 }, { 30 } }, true); - DataBuffer buffer3 = new ArrayDataBuffer<>(new double[][] { { 20 }, { 30 } }, true); - DataBuffer buffer4 = new ArrayDataBuffer<>(new double[][][] { { { 10 } }, { { 30 } } }, true); - DataBuffer buffer5 = new ArrayDataBuffer<>(new double[][][] { { { 10 } }, { { 30 } } }, true); - - assertTrue(buffer1.equals(buffer2)); - assertTrue(buffer2.equals(buffer1)); - assertEquals(buffer1.hashCode(), buffer2.hashCode()); - - assertFalse(buffer1.equals(buffer3)); - assertFalse(buffer3.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer3.hashCode()); - - assertFalse(buffer1.equals(buffer4)); - assertFalse(buffer4.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer4.hashCode()); - - assertTrue(buffer4.equals(buffer5)); - assertTrue(buffer4.equals(buffer5)); - assertEquals(buffer4.hashCode(), buffer5.hashCode()); - } - - @Test - public void booleanArrayBufferEquals() { - DataBuffer buffer1 = new ArrayDataBuffer<>(new boolean[][] { { true }, { false } }, true); - DataBuffer buffer2 = new ArrayDataBuffer<>(new boolean[][] { { true }, { false} }, true); - DataBuffer buffer3 = new ArrayDataBuffer<>(new boolean[][] { { false }, { false } }, true); - DataBuffer buffer4 = new ArrayDataBuffer<>(new boolean[][][] { { { true } }, { { false } } }, true); - DataBuffer buffer5 = new ArrayDataBuffer<>(new boolean[][][] { { { true } }, { { false } } }, true); - - assertTrue(buffer1.equals(buffer2)); - assertTrue(buffer2.equals(buffer1)); - assertEquals(buffer1.hashCode(), buffer2.hashCode()); - - assertFalse(buffer1.equals(buffer3)); - assertFalse(buffer3.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer3.hashCode()); - - assertFalse(buffer1.equals(buffer4)); - assertFalse(buffer4.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer4.hashCode()); - - assertTrue(buffer4.equals(buffer5)); - assertTrue(buffer4.equals(buffer5)); - assertEquals(buffer4.hashCode(), buffer5.hashCode()); - } - - @Test - public void objectArrayBufferEquals() { - DataBuffer buffer1 = new ArrayDataBuffer<>(new String[][] { { "10" }, { "30" } }, true); - DataBuffer buffer2 = new ArrayDataBuffer<>(new String[][] { { "10" }, { "30" } }, true); - DataBuffer buffer3 = new ArrayDataBuffer<>(new String[][] { { "20" }, { "30" } }, true); - DataBuffer buffer4 = new ArrayDataBuffer<>(new String[][][] { { { "10" } }, { { "30" } } }, true); - DataBuffer buffer5 = new ArrayDataBuffer<>(new String[][][] { { { "10" } }, { { "30" } } }, true); - - assertTrue(buffer1.equals(buffer2)); - assertTrue(buffer2.equals(buffer1)); - assertEquals(buffer1.hashCode(), buffer2.hashCode()); - - assertFalse(buffer1.equals(buffer3)); - assertFalse(buffer3.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer3.hashCode()); - - assertFalse(buffer1.equals(buffer4)); - assertFalse(buffer4.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer4.hashCode()); - - assertTrue(buffer4.equals(buffer5)); - assertTrue(buffer4.equals(buffer5)); - assertEquals(buffer4.hashCode(), buffer5.hashCode()); - } - - @Test - public void nullableObjectArrayBufferEquals() { - DataBuffer buffer1 = new ArrayDataBuffer<>(new String[][] { null, { "30" } }, true); - DataBuffer buffer2 = new ArrayDataBuffer<>(new String[][] { null, { "30" } }, true); - DataBuffer buffer3 = new ArrayDataBuffer<>(new String[][] { { "20" }, { "30" } }, true); - DataBuffer buffer4 = new ArrayDataBuffer<>(new String[][][] { { { "10" } }, null }, true); - DataBuffer buffer5 = new ArrayDataBuffer<>(new String[][][] { { { "10" } }, null }, true); - - assertTrue(buffer1.equals(buffer2)); - assertTrue(buffer2.equals(buffer1)); - assertEquals(buffer1.hashCode(), buffer2.hashCode()); - - assertFalse(buffer1.equals(buffer3)); - assertFalse(buffer3.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer3.hashCode()); - - assertFalse(buffer1.equals(buffer4)); - assertFalse(buffer4.equals(buffer1)); - assertNotEquals(buffer1.hashCode(), buffer4.hashCode()); - - assertTrue(buffer4.equals(buffer5)); - assertTrue(buffer4.equals(buffer5)); - assertEquals(buffer4.hashCode(), buffer5.hashCode()); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/misc/BitSetDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/misc/BitSetDataBufferTest.java deleted file mode 100644 index ec5c513869a..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/misc/BitSetDataBufferTest.java +++ /dev/null @@ -1,34 +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.ndarray.impl.buffer.misc; - -import java.util.BitSet; -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.BooleanDataBufferTestBase; - -public class BitSetDataBufferTest extends BooleanDataBufferTestBase { - - @Override - protected BooleanDataBuffer allocate(long size) { - return new BitSetDataBuffer(new BitSet((int)size), size, false); - } - - @Override - protected Boolean valueOf(Long val) { - return val != 0; - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/misc/StringArrayDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/misc/StringArrayDataBufferTest.java deleted file mode 100644 index 3e9c3c0cdbf..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/misc/StringArrayDataBufferTest.java +++ /dev/null @@ -1,33 +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.ndarray.impl.buffer.misc; - -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBufferTestBase; - -public class StringArrayDataBufferTest extends DataBufferTestBase { - - @Override - protected DataBuffer allocate(long size) { - return new ArrayDataBuffer<>(new String[(int)size], false); - } - - @Override - protected String valueOf(Long val) { - return val.toString(); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/ByteNioDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/ByteNioDataBufferTest.java deleted file mode 100644 index 28ff5a6c104..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/ByteNioDataBufferTest.java +++ /dev/null @@ -1,29 +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.ndarray.impl.buffer.nio; - -import java.nio.ByteBuffer; -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.ByteDataBufferTestBase; - -public class ByteNioDataBufferTest extends ByteDataBufferTestBase { - - @Override - protected ByteDataBuffer allocate(long size) { - return new ByteNioDataBuffer(ByteBuffer.allocate((int)size)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/DoubleNioDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/DoubleNioDataBufferTest.java deleted file mode 100644 index 7a4d39dce94..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/DoubleNioDataBufferTest.java +++ /dev/null @@ -1,29 +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.ndarray.impl.buffer.nio; - -import java.nio.DoubleBuffer; -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.buffer.DoubleDataBufferTestBase; - -public class DoubleNioDataBufferTest extends DoubleDataBufferTestBase { - - @Override - protected DoubleDataBuffer allocate(long size) { - return new DoubleNioDataBuffer(DoubleBuffer.allocate((int)size)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/FloatNioDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/FloatNioDataBufferTest.java deleted file mode 100644 index 08089e76ad8..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/FloatNioDataBufferTest.java +++ /dev/null @@ -1,29 +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.ndarray.impl.buffer.nio; - -import java.nio.FloatBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBufferTestBase; - -public class FloatNioDataBufferTest extends FloatDataBufferTestBase { - - @Override - protected FloatDataBuffer allocate(long size) { - return new FloatNioDataBuffer(FloatBuffer.allocate((int)size)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/IntNioDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/IntNioDataBufferTest.java deleted file mode 100644 index 00a993e42ed..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/IntNioDataBufferTest.java +++ /dev/null @@ -1,29 +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.ndarray.impl.buffer.nio; - -import java.nio.IntBuffer; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBufferTestBase; - -public class IntNioDataBufferTest extends IntDataBufferTestBase { - - @Override - protected IntDataBuffer allocate(long size) { - return new IntNioDataBuffer(IntBuffer.allocate((int)size)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/LongNioDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/LongNioDataBufferTest.java deleted file mode 100644 index 5922d2b922c..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/LongNioDataBufferTest.java +++ /dev/null @@ -1,29 +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.ndarray.impl.buffer.nio; - -import java.nio.LongBuffer; -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBufferTestBase; - -public class LongNioDataBufferTest extends LongDataBufferTestBase { - - @Override - protected LongDataBuffer allocate(long size) { - return new LongNioDataBuffer(LongBuffer.allocate((int)size)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/ShortNioDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/ShortNioDataBufferTest.java deleted file mode 100644 index c76191fbcf1..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/nio/ShortNioDataBufferTest.java +++ /dev/null @@ -1,29 +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.ndarray.impl.buffer.nio; - -import java.nio.ShortBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBufferTestBase; - -public class ShortNioDataBufferTest extends ShortDataBufferTestBase { - - @Override - protected ShortDataBuffer allocate(long size) { - return new ShortNioDataBuffer(ShortBuffer.allocate((int)size)); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/BooleanRawDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/BooleanRawDataBufferTest.java deleted file mode 100644 index 1f09d76055d..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/BooleanRawDataBufferTest.java +++ /dev/null @@ -1,28 +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.ndarray.impl.buffer.raw; - -import org.tensorflow.ndarray.buffer.BooleanDataBuffer; -import org.tensorflow.ndarray.buffer.BooleanDataBufferTestBase; - -public class BooleanRawDataBufferTest extends BooleanDataBufferTestBase { - - @Override - protected BooleanDataBuffer allocate(long size) { - return new BooleanRawDataBuffer(UnsafeMemoryHandle.fromArray(new boolean[(int)size], (int)size), false); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/ByteRawDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/ByteRawDataBufferTest.java deleted file mode 100644 index 4a415aff49f..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/ByteRawDataBufferTest.java +++ /dev/null @@ -1,28 +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.ndarray.impl.buffer.raw; - -import org.tensorflow.ndarray.buffer.ByteDataBuffer; -import org.tensorflow.ndarray.buffer.ByteDataBufferTestBase; - -public class ByteRawDataBufferTest extends ByteDataBufferTestBase { - - @Override - protected ByteDataBuffer allocate(long size) { - return new ByteRawDataBuffer(UnsafeMemoryHandle.fromArray(new byte[(int)size], (int)size), false); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/DoubleRawDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/DoubleRawDataBufferTest.java deleted file mode 100644 index df845092dd1..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/DoubleRawDataBufferTest.java +++ /dev/null @@ -1,28 +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.ndarray.impl.buffer.raw; - -import org.tensorflow.ndarray.buffer.DoubleDataBuffer; -import org.tensorflow.ndarray.buffer.DoubleDataBufferTestBase; - -public class DoubleRawDataBufferTest extends DoubleDataBufferTestBase { - - @Override - protected DoubleDataBuffer allocate(long size) { - return new DoubleRawDataBuffer(UnsafeMemoryHandle.fromArray(new double[(int)size], (int)size), false); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/FloatRawDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/FloatRawDataBufferTest.java deleted file mode 100644 index bc453d79f37..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/FloatRawDataBufferTest.java +++ /dev/null @@ -1,28 +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.ndarray.impl.buffer.raw; - -import org.tensorflow.ndarray.buffer.FloatDataBuffer; -import org.tensorflow.ndarray.buffer.FloatDataBufferTestBase; - -public class FloatRawDataBufferTest extends FloatDataBufferTestBase { - - @Override - protected FloatDataBuffer allocate(long size) { - return new FloatRawDataBuffer(UnsafeMemoryHandle.fromArray(new float[(int)size], (int)size), false); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/IntRawDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/IntRawDataBufferTest.java deleted file mode 100644 index 1142f19131d..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/IntRawDataBufferTest.java +++ /dev/null @@ -1,28 +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.ndarray.impl.buffer.raw; - -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.buffer.IntDataBufferTestBase; - -public class IntRawDataBufferTest extends IntDataBufferTestBase { - - @Override - protected IntDataBuffer allocate(long size) { - return new IntRawDataBuffer(UnsafeMemoryHandle.fromArray(new int[(int)size], (int)size), false); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/LongRawDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/LongRawDataBufferTest.java deleted file mode 100644 index af86d64a414..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/LongRawDataBufferTest.java +++ /dev/null @@ -1,28 +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.ndarray.impl.buffer.raw; - -import org.tensorflow.ndarray.buffer.LongDataBuffer; -import org.tensorflow.ndarray.buffer.LongDataBufferTestBase; - -public class LongRawDataBufferTest extends LongDataBufferTestBase { - - @Override - protected LongDataBuffer allocate(long size) { - return new LongRawDataBuffer(UnsafeMemoryHandle.fromArray(new long[(int)size], (int)size), false); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/ShortRawDataBufferTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/ShortRawDataBufferTest.java deleted file mode 100644 index 1ce1f25391b..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/buffer/raw/ShortRawDataBufferTest.java +++ /dev/null @@ -1,28 +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.ndarray.impl.buffer.raw; - -import org.tensorflow.ndarray.buffer.ShortDataBuffer; -import org.tensorflow.ndarray.buffer.ShortDataBufferTestBase; - -public class ShortRawDataBufferTest extends ShortDataBufferTestBase { - - @Override - protected ShortDataBuffer allocate(long size) { - return new ShortRawDataBuffer(UnsafeMemoryHandle.fromArray(new short[(int)size], (int)size), false); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/BooleanDenseNdArrayTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/BooleanDenseNdArrayTest.java deleted file mode 100644 index 36540104eb7..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/BooleanDenseNdArrayTest.java +++ /dev/null @@ -1,35 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.BooleanNdArray; -import org.tensorflow.ndarray.BooleanNdArrayTestBase; -import org.tensorflow.ndarray.NdArrays; - -public class BooleanDenseNdArrayTest extends BooleanNdArrayTestBase { - - @Override protected BooleanNdArray allocate(Shape shape) { - return NdArrays.ofBooleans(shape); - } - - @Override protected DataBuffer allocateBuffer(long size) { - return DataBuffers.ofBooleans(size); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/ByteDenseNdArrayTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/ByteDenseNdArrayTest.java deleted file mode 100644 index 2e5d1939bc3..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/ByteDenseNdArrayTest.java +++ /dev/null @@ -1,35 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.ByteNdArray; -import org.tensorflow.ndarray.ByteNdArrayTestBase; -import org.tensorflow.ndarray.NdArrays; - -public class ByteDenseNdArrayTest extends ByteNdArrayTestBase { - - @Override protected ByteNdArray allocate(Shape shape) { - return NdArrays.ofBytes(shape); - } - - @Override protected DataBuffer allocateBuffer(long size) { - return DataBuffers.ofBytes(size); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/DenseNdArrayTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/DenseNdArrayTest.java deleted file mode 100644 index 375f7643875..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/DenseNdArrayTest.java +++ /dev/null @@ -1,51 +0,0 @@ -package org.tensorflow.ndarray.impl.dense; - -import static org.junit.jupiter.api.Assertions.assertFalse; -import static org.junit.jupiter.api.Assertions.assertTrue; - -import org.junit.jupiter.api.Test; -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.IntNdArray; -import org.tensorflow.ndarray.NdArrays; -import org.tensorflow.ndarray.StdArrays; -import org.tensorflow.ndarray.index.Indices; - -public class DenseNdArrayTest { - - @Test - public void arrayEquals() { - IntNdArray array = NdArrays.ofInts(Shape.of(2, 2)) - .set(NdArrays.vectorOf(1, 2), 0) - .set(NdArrays.vectorOf(3, 4), 1); - - assertTrue(array.equals(StdArrays.ndCopyOf(new int[][] {{1, 2}, {3, 4}}))); - assertTrue(array.equals(StdArrays.ndCopyOf(new Integer[][] {{1, 2}, {3, 4}}))); - assertFalse(array.equals(NdArrays.vectorOf(1, 2, 3, 4))); - assertFalse(array.equals(StdArrays.ndCopyOf(new int[][] {{3, 4}, {1, 2}}))); - assertFalse(array.equals(StdArrays.ndCopyOf(new long[][] {{1L, 2L}, {3L, 4L}}))); - } - - @Test - public void equalsAndHashCodeOnSlices() { - IntNdArray vector1 = NdArrays.vectorOf(3, 4); - IntNdArray vector2 = NdArrays.vectorOf(1, 2, 3, 4); - IntNdArray matrix1 = StdArrays.ndCopyOf(new int[][] {{1, 2}, {3, 4}}); - IntNdArray matrix2 = StdArrays.ndCopyOf(new int[][] {{1, 0, 2, 0}, {3, 0, 4, 0}}); - IntNdArray matrix3d1 = StdArrays.ndCopyOf(new int[][][] { - {{1, 2}, {3, 4}}, - {{5, 6}, {7, 8}} - }); - IntNdArray matrix3d2 = StdArrays.ndCopyOf(new int[][][] { - {{1, 2}, {4, 5}}, - {{3, 4}, {6, 7}} - }); - - assertTrue(vector1.equals(vector2.slice(Indices.sliceFrom(2)))); - assertTrue(vector1.equals(matrix1.get(1))); - assertTrue(vector1.equals(matrix2.get(1).slice(Indices.even()))); - assertTrue(matrix1.equals(matrix2.slice(Indices.all(), Indices.even()))); - assertTrue(matrix3d1.get(0).equals(matrix1)); - assertFalse(matrix3d1.get(0).equals(vector2)); - assertTrue(matrix1.equals(matrix3d2.slice(Indices.all(), Indices.at(0)))); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/DoubleDenseNdArrayTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/DoubleDenseNdArrayTest.java deleted file mode 100644 index 9810a744c50..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/DoubleDenseNdArrayTest.java +++ /dev/null @@ -1,35 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.DoubleNdArray; -import org.tensorflow.ndarray.DoubleNdArrayTestBase; -import org.tensorflow.ndarray.NdArrays; - -public class DoubleDenseNdArrayTest extends DoubleNdArrayTestBase { - - @Override protected DoubleNdArray allocate(Shape shape) { - return NdArrays.ofDoubles(shape); - } - - @Override protected DataBuffer allocateBuffer(long size) { - return DataBuffers.ofDoubles(size); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/FloatDenseNdArrayTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/FloatDenseNdArrayTest.java deleted file mode 100644 index efee2bf2cb8..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/FloatDenseNdArrayTest.java +++ /dev/null @@ -1,35 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.FloatNdArray; -import org.tensorflow.ndarray.FloatNdArrayTestBase; -import org.tensorflow.ndarray.NdArrays; - -public class FloatDenseNdArrayTest extends FloatNdArrayTestBase { - - @Override protected FloatNdArray allocate(Shape shape) { - return NdArrays.ofFloats(shape); - } - - @Override protected DataBuffer allocateBuffer(long size) { - return DataBuffers.ofFloats(size); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/IntDenseNdArrayTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/IntDenseNdArrayTest.java deleted file mode 100644 index 712f6f44333..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/IntDenseNdArrayTest.java +++ /dev/null @@ -1,35 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.IntNdArray; -import org.tensorflow.ndarray.IntNdArrayTestBase; -import org.tensorflow.ndarray.NdArrays; - -public class IntDenseNdArrayTest extends IntNdArrayTestBase { - - @Override protected IntNdArray allocate(Shape shape) { - return NdArrays.ofInts(shape); - } - - @Override protected DataBuffer allocateBuffer(long size) { - return DataBuffers.ofInts(size); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/LongDenseNdArrayTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/LongDenseNdArrayTest.java deleted file mode 100644 index 346e3845080..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/LongDenseNdArrayTest.java +++ /dev/null @@ -1,35 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.LongNdArray; -import org.tensorflow.ndarray.LongNdArrayTestBase; -import org.tensorflow.ndarray.NdArrays; - -public class LongDenseNdArrayTest extends LongNdArrayTestBase { - - @Override protected LongNdArray allocate(Shape shape) { - return NdArrays.ofLongs(shape); - } - - @Override protected DataBuffer allocateBuffer(long size) { - return DataBuffers.ofLongs(size); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/ShortDenseNdArrayTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/ShortDenseNdArrayTest.java deleted file mode 100644 index 6f845c7c65d..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/ShortDenseNdArrayTest.java +++ /dev/null @@ -1,35 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.NdArrays; -import org.tensorflow.ndarray.ShortNdArray; -import org.tensorflow.ndarray.ShortNdArrayTestBase; - -public class ShortDenseNdArrayTest extends ShortNdArrayTestBase { - - @Override protected ShortNdArray allocate(Shape shape) { - return NdArrays.ofShorts(shape); - } - - @Override protected DataBuffer allocateBuffer(long size) { - return DataBuffers.ofShorts(size); - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/StringDenseNdArrayTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/StringDenseNdArrayTest.java deleted file mode 100644 index 5afc1420ab2..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/dense/StringDenseNdArrayTest.java +++ /dev/null @@ -1,43 +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.ndarray.impl.dense; - -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBuffer; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.NdArray; -import org.tensorflow.ndarray.NdArrayTestBase; -import org.tensorflow.ndarray.NdArrays; - -public class StringDenseNdArrayTest extends NdArrayTestBase { - - @Override protected NdArray allocate(Shape shape) { - return NdArrays.ofObjects(String.class, shape); - } - - @Override protected DataBuffer allocateBuffer(long size) { - return DataBuffers.ofObjects(String.class, size); - } - - @Override protected String valueOf(Long val) { - return val.toString(); - } - - protected String zeroOrNull() { - return null; - } -} diff --git a/ndarray/src/test/java/org/tensorflow/ndarray/impl/sequence/ElementSequenceTest.java b/ndarray/src/test/java/org/tensorflow/ndarray/impl/sequence/ElementSequenceTest.java deleted file mode 100644 index bad78404e9b..00000000000 --- a/ndarray/src/test/java/org/tensorflow/ndarray/impl/sequence/ElementSequenceTest.java +++ /dev/null @@ -1,145 +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.ndarray.impl.sequence; - -import static org.junit.jupiter.api.Assertions.assertArrayEquals; -import static org.junit.jupiter.api.Assertions.assertEquals; -import static org.junit.jupiter.api.Assertions.fail; - -import java.util.ArrayList; -import java.util.Arrays; -import java.util.List; -import org.junit.jupiter.api.Test; -import org.tensorflow.ndarray.Shape; -import org.tensorflow.ndarray.buffer.DataBufferWindow; -import org.tensorflow.ndarray.buffer.DataBuffers; -import org.tensorflow.ndarray.buffer.IntDataBuffer; -import org.tensorflow.ndarray.IntNdArray; -import org.tensorflow.ndarray.NdArraySequence; -import org.tensorflow.ndarray.NdArrays; -import org.tensorflow.ndarray.impl.AbstractNdArray; - -public class ElementSequenceTest { - - @Test - public void iterateVectorsWithIndex() { - IntNdArray array = NdArrays.ofInts(Shape.of(2, 3, 2)); - - NdArraySequence sequence = new SlicingElementSequence( - (AbstractNdArray)array, 1); - List coords = new ArrayList<>((int)array.shape().size()); - sequence.forEachIndexed((c, e) -> coords.add(Arrays.copyOf(c, c.length))); - - assertEquals(6, coords.size()); - assertArrayEquals(new long[] {0, 0}, coords.get(0)); - assertArrayEquals(new long[] {0, 1}, coords.get(1)); - assertArrayEquals(new long[] {0, 2}, coords.get(2)); - assertArrayEquals(new long[] {1, 0}, coords.get(3)); - assertArrayEquals(new long[] {1, 1}, coords.get(4)); - assertArrayEquals(new long[] {1, 2}, coords.get(5)); - } - - @Test - public void iterateScalarsWithIndex() { - IntNdArray array = NdArrays.ofInts(Shape.of(2, 3, 2)); - - NdArraySequence cursor = new SlicingElementSequence( - (AbstractNdArray)array, 2); - List coords = new ArrayList<>((int)array.shape().size()); - cursor.forEachIndexed((c, e) -> coords.add(Arrays.copyOf(c, c.length))); - - assertEquals(12, coords.size()); - assertArrayEquals(new long[] {0, 0, 0}, coords.get(0)); - assertArrayEquals(new long[] {0, 0, 1}, coords.get(1)); - assertArrayEquals(new long[] {0, 1, 0}, coords.get(2)); - assertArrayEquals(new long[] {0, 1, 1}, coords.get(3)); - assertArrayEquals(new long[] {0, 2, 0}, coords.get(4)); - assertArrayEquals(new long[] {0, 2, 1}, coords.get(5)); - assertArrayEquals(new long[] {1, 0, 0}, coords.get(6)); - assertArrayEquals(new long[] {1, 0, 1}, coords.get(7)); - assertArrayEquals(new long[] {1, 1, 0}, coords.get(8)); - assertArrayEquals(new long[] {1, 1, 1}, coords.get(9)); - assertArrayEquals(new long[] {1, 2, 0}, coords.get(10)); - assertArrayEquals(new long[] {1, 2, 1}, coords.get(11)); - } - - @Test - public void slicingElementSequenceReturnsUniqueInstances() { - IntNdArray array = NdArrays.ofInts(Shape.of(2, 3, 2)); - NdArraySequence sequence = new SlicingElementSequence( - (AbstractNdArray) array, 1); - List elements = new ArrayList<>(); - sequence.forEach(e -> { - elements.forEach(tmp -> { - if (tmp == e) { - fail(); - } - }); - elements.add(e); - }); - } - - @Test - public void fastElementSequenceReturnsSameInstance() { - IntNdArray array = NdArrays.ofInts(Shape.of(2, 3, 2)); - IntNdArray element = array.get(0); - NdArraySequence sequence = new FastElementSequence( - (AbstractNdArray) array, 1, element, mockDataBufferWindow(2)); - sequence.forEach(e -> { - if (e != element) { - fail(); - } - }); - } - - private DataBufferWindow mockDataBufferWindow(long size) { - return new DataBufferWindow() { - - @Override - public long offset() { - return offset; - } - - @Override - public long size() { - return size; - } - - @Override - public DataBufferWindow slideTo(long index) { - offset = index; - return this; - } - - @Override - public DataBufferWindow slide(long step) { - offset += step; - return this; - } - - @Override - public IntDataBuffer buffer() { - return buffer; - } - - private long offset; - private final long size = 2; - private final IntDataBuffer buffer = DataBuffers.ofInts(2); - }; - } -} diff --git a/ndarray/src/test/resources/COPYRIGHT.txt b/ndarray/src/test/resources/COPYRIGHT.txt deleted file mode 100644 index 5e7bd50bb48..00000000000 --- a/ndarray/src/test/resources/COPYRIGHT.txt +++ /dev/null @@ -1 +0,0 @@ -All images in this folder and its subfolders are free of any copyright. \ No newline at end of file diff --git a/ndarray/src/test/resources/castle.jpg b/ndarray/src/test/resources/castle.jpg 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