[WebNN EP] Support Trilu op (microsoft#20730)

Adds support for Trilu via WebNN Triangular op

js/web/docs/webnn-operators.md

@@ -88,5 +88,6 @@ operators and the supported opset domain/versions in **WebNN EP** by ONNX Runtim
 | Tan | ai.onnx(7+) | tan | ✗ | ✓ | |
 | Tanh | ai.onnx(7-12, 13+) | tanh | ✓ | ✓ | |
 | Transpose | ai.onnx(7-12, 13-20, 21+) | transpose | ✓ | ✓ | |
+| Trilu | ai.onnx(14+) | triangular | ✗ | ✓ | Input 'k' (option 'diagonal' for WebNN) if present should be a constant |
 | Unsqueeze | ai.onnx(7-10, 11-12, 13-20, 21+) | reshape | ✓ | ✓ | |
 | Where | ai.onnx(7-8, 9-15, 16+) | where | ✗ | ✓ | |

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

@@ -236,6 +236,7 @@ static const InlinedHashMap<std::string, WebnnOpInfo> op_map = {
     {"Tan", {"tan", false}},
     {"Tanh", {"tanh", true}},
     {"Transpose", {"transpose", true}},
+    {"Trilu", {"triangular", false}},
     {"Unsqueeze", {"reshape", true}},
     {"Where", {"where", false}},
 };

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

@@ -0,0 +1,103 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Copyright (c) Intel Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#include "core/providers/common.h"
+#include "core/providers/shared/utils/utils.h"
+#include "core/providers/webnn/builders/helper.h"
+#include "core/providers/webnn/builders/model_builder.h"
+#include "core/providers/webnn/builders/op_builder_factory.h"
+
+#include "base_op_builder.h"
+
+namespace onnxruntime {
+namespace webnn {
+
+class TriangularOpBuilder : public BaseOpBuilder {
+  // Add operator related.
+ public:
+  void AddInitializersToSkip(ModelBuilder& model_builder, const Node& node) const override;
+
+ private:
+  Status AddToModelBuilderImpl(ModelBuilder& model_builder, const Node& node,
+                               const logging::Logger& logger) const override ORT_MUST_USE_RESULT;
+
+  // Operator support related.
+ private:
+  bool IsOpSupportedImpl(const InitializedTensorSet& initializers, const Node& node,
+                         const WebnnDeviceType /* device_type */, const logging::Logger& logger) const override;
+};
+
+// Add operator related.
+
+void TriangularOpBuilder::AddInitializersToSkip(ModelBuilder& model_builder, const Node& node) const {
+  // Skip diagonal initializer if present.
+  if (node.InputDefs().size() > 1) {
+    model_builder.AddInitializerToSkip(node.InputDefs()[1]->Name());
+  }
+}
+
+Status TriangularOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
+                                                  const Node& node,
+                                                  const logging::Logger& logger) const {
+  const auto& input_defs = node.InputDefs();
+  const auto& initializers = model_builder.GetInitializerTensors();
+  emscripten::val input = model_builder.GetOperand(input_defs[0]->Name());
+  emscripten::val output = emscripten::val::object();
+  NodeAttrHelper helper(node);
+  emscripten::val options = emscripten::val::object();
+
+  const bool upper = helper.Get("upper", 1);
+  options.set("upper", upper);
+
+  if (!GetTensorName(input_defs, 1).empty()) {
+    // Optional input diagonal is provided, use diagonal initializer data.
+    const auto diagonal_tensor = *initializers.at(input_defs[1]->Name());
+
+    std::vector<uint8_t> unpacked_tensor;
+    ORT_RETURN_IF_ERROR(onnxruntime::utils::UnpackInitializerData(diagonal_tensor, unpacked_tensor));
+    const auto diagonal = *reinterpret_cast<int64_t*>(unpacked_tensor.data());
+    options.set("diagonal", narrow<int32_t>(diagonal));
+  }
+
+  output = model_builder.GetBuilder().call<emscripten::val>("triangular", input, options);
+
+  model_builder.AddOperand(node.OutputDefs()[0]->Name(), std::move(output));
+  return Status::OK();
+}
+
+// Operator support related.
+bool TriangularOpBuilder::IsOpSupportedImpl(const InitializedTensorSet& initializers,
+                                            const Node& node,
+                                            const WebnnDeviceType /* device_type */,
+                                            const logging::Logger& logger) const {
+  const auto& input_defs = node.InputDefs();
+  std::vector<int64_t> input_shape;
+  if (!GetShape(*input_defs[0], input_shape, logger))
+    return false;
+  const auto input_size = input_shape.size();
+  if (input_size < 2) {
+    LOGS(logger, VERBOSE) << "Triangular only support input size >= 2d shape, input is "
+                          << input_size << "d shape";
+    return false;
+  }
+
+  const std::string diagonal_name = GetTensorName(input_defs, 1);
+  emscripten::val diagonal = emscripten::val::object();
+  // Inputs contain optional 'diagonal' input.
+  if (!diagonal_name.empty()) {
+    if (!Contains(initializers, diagonal_name)) {
+      LOGS(logger, VERBOSE) << "The diagonal must be a constant initializer.";
+      return false;
+    }
+  }
+  return true;
+}
+
+void CreateTriangularOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations) {
+  op_registrations.builders.push_back(std::make_unique<TriangularOpBuilder>());
+  op_registrations.op_builder_map.emplace(op_type, op_registrations.builders.back().get());
+}
+
+}  // namespace webnn
+}  // namespace onnxruntime

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

@@ -182,6 +182,9 @@ static OpBuilderRegistrations CreateOpBuilderRegistrations() {
     CreateTransposeOpBuilder("Transpose", op_registrations);
   }
 
+  {  // Trilu
+    CreateTriangularOpBuilder("Trilu", op_registrations);
+  }
   return op_registrations;
 }
 

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

@@ -47,6 +47,7 @@ void CreateSplitOpBuilder(const std::string& op_type, OpBuilderRegistrations& op
 void CreateSqueezeUnsqueezeOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations);
 void CreateTernaryOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations);
 void CreateTransposeOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations);
+void CreateTriangularOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations);
 void CreateUnaryOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations);
 
 }  // namespace webnn