Reland "[WebNN] Fallback the node when its output doesn't have shape info" (microsoft#22685)

The previous PR was reverted because it causes the whole model to
fallback when there is output shape info missing. This PR fixes the
issue by removing redundant fallbacks.

Author: shiyi9801

onnxruntime/core/providers/webnn/builders/helper.cc

@@ -69,30 +69,28 @@ bool IsNodeSupported(const Node& node, const GraphViewer& graph_viewer, const We
   }
 }
 
-bool IsInputSupported(const NodeArg& input, const std::string& parent_name, const logging::Logger& logger) {
-  const auto& input_name = input.Name();
-  const auto* shape_proto = input.Shape();
+bool IsTensorShapeSupported(const NodeArg& node_arg, const std::string& parent_name, const logging::Logger& logger) {
+  const auto& node_arg_name = node_arg.Name();
+  const auto* shape_proto = node_arg.Shape();
   // Optional tensors can be indicated by an empty name, just ignore it.
-  if (input_name.empty()) {
+  if (node_arg_name.empty()) {
     return true;
   }
-  // We do not support input with no shape.
+  // We do not support input/output with no shape.
   if (!shape_proto) {
-    LOGS(logger, VERBOSE) << "Input [" << input_name << "] of [" << parent_name
-                          << "] has not shape";
+    LOGS(logger, VERBOSE) << "Node arg [" << node_arg_name << "] of [" << parent_name << "] has not shape";
     return false;
   }
 
   for (const auto& dim : shape_proto->dim()) {
     // WebNN doesn't support dynamic shape - use sessionOptions.freeDimensionOverrides to fix the shape.
     if (!dim.has_dim_value()) {
       LOGS(logger, VERBOSE) << "Dynamic shape is not supported, "
-                            << "use sessionOptions.FreeDimensionOverrides to set a fixed shape for input: "
-                            << input_name;
+                            << "use sessionOptions.FreeDimensionOverrides to set a fixed shape: " << node_arg_name;
       return false;
     }
     if (dim.dim_value() == 0) {
-      LOGS(logger, VERBOSE) << "The shape of [" << input_name << "] has 0 dimension which is not supported by WebNN";
+      LOGS(logger, VERBOSE) << "The shape of [" << node_arg_name << "] has 0 dimension which is not supported by WebNN";
       return false;
     }
   }
@@ -106,13 +104,6 @@ std::vector<std::vector<NodeIndex>> GetSupportedNodes(const GraphViewer& graph_v
                                                       const emscripten::val& wnn_limits,
                                                       const logging::Logger& logger) {
   std::vector<std::vector<size_t>> supported_node_groups;
-
-  for (const auto* input : graph_viewer.GetInputs()) {
-    if (!IsInputSupported(*input, "graph", logger)) {
-      return supported_node_groups;
-    }
-  }
-
   std::vector<size_t> supported_node_group;
   const auto& node_indices = graph_viewer.GetNodesInTopologicalOrder();
 

onnxruntime/core/providers/webnn/builders/helper.h

@@ -180,7 +180,7 @@ inline bool IsEmptyTensor(const InitializedTensorSet& initializers, const std::s
   return std::any_of(dims.begin(), dims.end(), [](auto d) { return d == 0; });
 }
 
-bool IsInputSupported(const NodeArg& node_arg, const std::string& parent_name, const logging::Logger& logger);
+bool IsTensorShapeSupported(const NodeArg& node_arg, const std::string& parent_name, const logging::Logger& logger);
 
 // Get a list of groups of supported nodes, each group represents a subgraph supported by WebNN EP.
 std::vector<std::vector<NodeIndex>> GetSupportedNodes(const GraphViewer& graph_viewer,

onnxruntime/core/providers/webnn/builders/impl/base_op_builder.cc

@@ -32,7 +32,7 @@ bool BaseOpBuilder::IsOpSupported(const InitializedTensorSet& initializers, cons
   if (!HasSupportedInputs(node, wnn_limits, logger))
     return false;
 
-  if (!HasSupportedOutputsImpl(node, wnn_limits, logger))
+  if (!HasSupportedOutputs(node, wnn_limits, logger))
     return false;
 
   if (!HasSupportedOpSet(node, logger))
@@ -45,7 +45,7 @@ bool BaseOpBuilder::HasSupportedInputs(const Node& node, const emscripten::val&
                                        const logging::Logger& logger) const {
   const auto node_name = MakeString("Node [", node.Name(), "] type [", node.OpType(), "]");
   for (const auto* input : node.InputDefs()) {
-    if (!IsInputSupported(*input, node_name, logger)) {
+    if (!IsTensorShapeSupported(*input, node_name, logger)) {
       return false;
     }
   }
@@ -66,6 +66,18 @@ bool BaseOpBuilder::HasSupportedInputsImpl(const Node& node,
   return IsDataTypeSupportedByOp(op_type, input_type, wnn_limits, "input", "Input", logger);
 }
 
+bool BaseOpBuilder::HasSupportedOutputs(const Node& node, const emscripten::val& wnn_limits,
+                                        const logging::Logger& logger) const {
+  const auto node_name = MakeString("Node [", node.Name(), "] type [", node.OpType(), "]");
+  for (const auto* output : node.OutputDefs()) {
+    if (!IsTensorShapeSupported(*output, node_name, logger)) {
+      return false;
+    }
+  }
+
+  return HasSupportedOutputsImpl(node, wnn_limits, logger);
+}
+
 bool BaseOpBuilder::HasSupportedOutputsImpl(const Node& node,
                                             const emscripten::val& wnn_limits,
                                             const logging::Logger& logger) const {

onnxruntime/core/providers/webnn/builders/impl/base_op_builder.h

@@ -54,6 +54,7 @@ class BaseOpBuilder : public IOpBuilder {
  private:
   bool HasSupportedOpSet(const Node& node, const logging::Logger& logger) const;
   bool HasSupportedInputs(const Node& node, const emscripten::val& wnn_limits, const logging::Logger& logger) const;
+  bool HasSupportedOutputs(const Node& node, const emscripten::val& wnn_limits, const logging::Logger& logger) const;
 };
 
 }  // namespace webnn

onnxruntime/core/providers/webnn/builders/model_builder.cc

@@ -227,7 +227,7 @@ Status ModelBuilder::RegisterModelInputOutput(const NodeArg& node_arg, bool is_i
     if (!shape.empty()) {
       dims.reserve(shape.size());
       for (const auto& dim : shape) {
-        // dim_param free dimensions should have already been excluded by IsInputSupported().
+        // dim_param free dimensions should have already been excluded by IsTensorShapeSupported().
         assert(dim.has_dim_value());
         dims.push_back(SafeInt<int32_t>(dim.dim_value()));
       }