diff --git a/js/web/docs/webnn-operators.md b/js/web/docs/webnn-operators.md index 19e1fcb8fd..966c93a85a 100644 --- a/js/web/docs/webnn-operators.md +++ b/js/web/docs/webnn-operators.md @@ -50,7 +50,7 @@ operators and the supported opset domain/versions in **WebNN EP** by ONNX Runtim | LessOrEqual | ai.onnx(12-15, 16+) | lesserOrEqual | ✗ | ✓ | | | Log | ai.onnx(7-12, 13+) | log | ✗ | ✓ | | | LpPool | ai.onnx(7-10, 11-17, 18+) | l2Pool2d | ✗ | ✓ | Only supports 4-D input, 2-D 'kernel_shape', 'p' value is 2 | -| MatMul | ai.onnx(7-8, 9-12, 13+) | matmul | ✓ | ✓ | WebNN CPU doesn't support broadcasting for MatMul | +| MatMul | ai.onnx(7-8, 9-12, 13+) | matmul | ✓ | ✓ | | | Max | ai.onnx(7, 8-11, 12, 13+) | max | ✓ | ✓ | | | MaxPool | ai.onnx(7, 8-9, 10, 11, 12+) | maxPool2d | ✓ | ✓ | Only supports 4-D input, 2-D 'kernel_shape', 'storage_order' != 1, one output | | Min | ai.onnx(7, 8-11, 12, 13+) | min | ✓ | ✓ | | @@ -73,7 +73,7 @@ operators and the supported opset domain/versions in **WebNN EP** by ONNX Runtim | ReduceSumSquare | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceSumSquare | ✗ | ✓ | Input 'axes' if present should be a constant | | Relu | ai.onnx(7-12, 13, 14+) | relu | ✓ | ✓ | | | Reshape | ai.onnx(7-12, 13, 14-18, 19-20, 21+) | reshape | ✓ | ✓ | Input 'shape' should be a constant, 0 dimension value in 'shape' is not supported | -| Resize | ai.onnx(11-12, 13-17, 18, 19+) | resample2d | ✓ | ✓ | Only supports 4-D input, exclude_outside != 0, input 'scales' and 'sizes' if present must be a constant, WebNN CPU backend only supports 'linear' mode, WebNN GPU backend only supports 'linear' and 'nearest' modes | +| Resize | ai.onnx(11-12, 13-17, 18, 19+) | resample2d | ✓ | ✓ | Only supports 4-D input, exclude_outside != 0, input 'scales' and 'sizes' if present must be a constant, 'linear' and 'nearest' modes | | Shape | ai.onnx(7-12, 13-14, 15-18, 19-20, 21+) | slice | ✓ | ✓ | | | Sigmoid | ai.onnx(7-12, 13+) | sigmoid | ✓ | ✓ | | | Softplus | ai.onnx(7+) | softplus | ✗ | ✓ | | @@ -81,7 +81,7 @@ operators and the supported opset domain/versions in **WebNN EP** by ONNX Runtim | Sin | ai.onnx(7+) | sin | ✗ | ✓ | | | Slice | ai.onnx(7-9, 10, 11-12, 13+) | slice | ✓ | ✓ | Input 'starts', 'ends', 'axes', and 'steps' if present must be a constant, only supports 'steps' value 1 | | Softmax | ai.onnx(7-10, 11-12, 13+) | softmax | ✓ | ✓ | Only supports input rank >= 2 | -| Split | ai.onnx(7-10, 11-12, 13-17, 18+) | split | ✓ | ✓ | Input 'split' if present should be a constant, WebNN CPU backend only supports up to 4 outputs | +| Split | ai.onnx(7-10, 11-12, 13-17, 18+) | split | ✓ | ✓ | Input 'split' if present should be a constant | | Sqrt | ai.onnx(7-12, 13+) | sqrt | ✓ | ✓ | | | Squeeze | ai.onnx(7-10, 11-12, 13-20, 21+) | reshape | ✓ | ✓ | Input 'axes' if present should be a constant | | Sub | ai.onnx(7-12, 13, 14+) | sub | ✓ | ✓ | | diff --git a/onnxruntime/core/providers/webnn/builders/impl/concat_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/concat_op_builder.cc index d3fa00e5fe..e4f98b09e0 100644 --- a/onnxruntime/core/providers/webnn/builders/impl/concat_op_builder.cc +++ b/onnxruntime/core/providers/webnn/builders/impl/concat_op_builder.cc @@ -36,40 +36,14 @@ Status ConcatOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder, NodeAttrHelper helper(node); uint32_t axis = static_cast(HandleNegativeAxis(helper.Get("axis", 1), rank)); - const size_t num_inputs = input_defs.size(); std::vector inputs; for (const auto* input : input_defs) { LOGS(logger, VERBOSE) << "input name " << input->Name(); inputs.push_back(model_builder.GetOperand(input->Name())); } - emscripten::val output = emscripten::val::undefined(); - if (num_inputs <= 4 || model_builder.GetPreferredLayout() == DataLayout::NCHW) { - output = model_builder.GetBuilder().call("concat", emscripten::val::array(inputs), axis); - } else { - // WebNN XNNPack backend only supports the concat with inputs number <= 4, - // decomposing the Concat with inputs number > 4 into multiple WebNN concat ops. - size_t remaining_inputs = num_inputs; - size_t max_inputs = 4; - while (remaining_inputs > 0) { - std::vector chunk_inputs; - - // Push the last concated output to the next chunk_inputs. - if (output != emscripten::val::undefined()) { - chunk_inputs.push_back(output); - max_inputs = 3; - } - - size_t chunk_size = std::min(remaining_inputs, max_inputs); - - for (size_t i = 0; i < chunk_size; i++) { - chunk_inputs.push_back(inputs[num_inputs - remaining_inputs + i]); - } - - output = model_builder.GetBuilder().call("concat", emscripten::val::array(chunk_inputs), axis); - remaining_inputs -= chunk_size; - } - } + emscripten::val output = + model_builder.GetBuilder().call("concat", emscripten::val::array(inputs), axis); model_builder.AddOperand(node.OutputDefs()[0]->Name(), std::move(output)); return Status::OK(); diff --git a/onnxruntime/core/providers/webnn/builders/impl/gemm_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/gemm_op_builder.cc index 248463f473..53f885019a 100644 --- a/onnxruntime/core/providers/webnn/builders/impl/gemm_op_builder.cc +++ b/onnxruntime/core/providers/webnn/builders/impl/gemm_op_builder.cc @@ -23,7 +23,7 @@ class GemmOpBuilder : public BaseOpBuilder { // Operator support related. private: - bool IsOpSupportedImpl(const InitializedTensorSet& initializers, const Node& node, + bool IsOpSupportedImpl(const InitializedTensorSet& /* initializers */, const Node& node, const WebnnDeviceType /* device_type */, const logging::Logger& logger) const override; bool HasSupportedInputsImpl(const Node& node, const WebnnDeviceType /* device_type */, const logging::Logger& logger) const override; @@ -64,13 +64,9 @@ Status GemmOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder, const N b = model_builder.GetBuilder().call("reshape", b, emscripten::val::array(GetVecUint32FromVecInt64(b_shape))); } - // The inputs of MatMul must be at least 3D for WebNN CPU backend. Use GEMM for 2D case. - // TODO: Remove this workaround when it is fixed in Chromium. - if (model_builder.GetWebnnDeviceType() == WebnnDeviceType::CPU && a_shape.size() == 2) { - output = model_builder.GetBuilder().call("gemm", a, b); - } else { - output = model_builder.GetBuilder().call("matmul", a, b); - } + + output = model_builder.GetBuilder().call("matmul", a, b); + // If the inputs are both 1D， reduce the output to a scalar. if (extended_a_shape && extended_b_shape) { output = model_builder.GetBuilder().call("reshape", output, emscripten::val::array()); @@ -132,11 +128,10 @@ Status GemmOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder, const N // Operator support related. -bool GemmOpBuilder::IsOpSupportedImpl(const InitializedTensorSet& initializers, +bool GemmOpBuilder::IsOpSupportedImpl(const InitializedTensorSet& /* initializers */, const Node& node, - const WebnnDeviceType device_type, + const WebnnDeviceType /* device_type */, const logging::Logger& logger) const { - (void)initializers; const auto& op_type = node.OpType(); const auto& input_defs(node.InputDefs()); const size_t a_idx = 0, b_idx = 1, c_idx = 2; // A*B+C @@ -194,30 +189,6 @@ bool GemmOpBuilder::IsOpSupportedImpl(const InitializedTensorSet& initializers, } } - if (op_type == "MatMul") { - // If the first argument is 1-D, it is promoted to a matrix by prepending a 1 to its dimensions. - // If the second argument is 1-D, it is promoted to a matrix by appending a 1 to its dimensions. - if (a_shape.size() == 1) a_shape.insert(a_shape.begin(), 1); - if (b_shape.size() == 1) b_shape.push_back(1); - - // WebNN CPU backend has two more constraints. - // https://source.chromium.org/chromium/chromium/src/+/main:third_party/blink/renderer/modules/ml/webnn/ml_graph_xnnpack.cc;l=1177 - // TODO: Remove this workaround when Chromium enables broadcast for MatMul on WebNN CPU backend. - if (device_type == WebnnDeviceType::CPU) { - if (a_shape.size() != b_shape.size()) { - LOGS(logger, VERBOSE) << "The rank of two inputs for WebNN CPU backend MatMul must be the same."; - return false; - } - - for (size_t i = 0; i < a_shape.size() - 2; i++) { - if (a_shape[i] != b_shape[i]) { - LOGS(logger, VERBOSE) << "WebNN CPU backend can't support broadcasting for MatMul."; - return false; - } - } - } - } - return true; } diff --git a/onnxruntime/core/providers/webnn/builders/impl/resize_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/resize_op_builder.cc index ea54b70a66..c4ca980fec 100644 --- a/onnxruntime/core/providers/webnn/builders/impl/resize_op_builder.cc +++ b/onnxruntime/core/providers/webnn/builders/impl/resize_op_builder.cc @@ -30,7 +30,7 @@ class ResizeOpBuilder : public BaseOpBuilder { // Operator support related. private: bool IsOpSupportedImpl(const InitializedTensorSet& initializers, const Node& node, - const WebnnDeviceType device_type, const logging::Logger& logger) const override; + const WebnnDeviceType /* device_type */, const logging::Logger& logger) const override; // Resize opset 10- is very different than Resize opset 11+, with many key attributes missing. // We only support Resize opset 11+ here. @@ -164,7 +164,7 @@ Status ResizeOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder, bool ResizeOpBuilder::IsOpSupportedImpl(const InitializedTensorSet& initializers, const Node& node, - const WebnnDeviceType device_type, + const WebnnDeviceType /* device_type */, const logging::Logger& logger) const { const auto& input_defs = node.InputDefs(); @@ -184,18 +184,10 @@ bool ResizeOpBuilder::IsOpSupportedImpl(const InitializedTensorSet& initializers const auto mode = helper.Get("mode", "nearest"); bool is_linear_resize = mode == "linear"; bool is_nearest_resize = mode == "nearest"; - // WebNN CPU backend only supports "linear" mode. - // WebNN GPU backend only supports "linear" and "nearest" modes. - if (device_type == WebnnDeviceType::CPU) { - if (!is_linear_resize) { - LOGS(logger, VERBOSE) << "Resize unsupported input mode, " << mode << " for CPU backend."; - return false; - } - } else { - if (!is_linear_resize && !is_nearest_resize) { - LOGS(logger, VERBOSE) << "Resize unsupported input mode, " << mode << " for GPU backend."; - return false; - } + // WebNN only supports "linear" and "nearest" modes. + if (!is_linear_resize && !is_nearest_resize) { + LOGS(logger, VERBOSE) << "Resize does not support input mode: " << mode; + return false; } const auto exclude_outside = helper.Get("exclude_outside", 0); diff --git a/onnxruntime/core/providers/webnn/builders/impl/split_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/split_op_builder.cc index c50b678bf2..ea3b8ef384 100644 --- a/onnxruntime/core/providers/webnn/builders/impl/split_op_builder.cc +++ b/onnxruntime/core/providers/webnn/builders/impl/split_op_builder.cc @@ -27,7 +27,7 @@ class SplitOpBuilder : public BaseOpBuilder { // Operator support related. private: bool IsOpSupportedImpl(const InitializedTensorSet& initializers, const Node& node, - const WebnnDeviceType device_type, const logging::Logger& logger) const override; + const WebnnDeviceType /* device_type */, const logging::Logger& logger) const override; }; // Add operator related. @@ -94,7 +94,7 @@ Status SplitOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder, bool SplitOpBuilder::IsOpSupportedImpl(const InitializedTensorSet& initializers, const Node& node, - const WebnnDeviceType device_type, + const WebnnDeviceType /* device_type */, const logging::Logger& logger) const { const auto& input_defs = node.InputDefs(); std::vector input_shape; @@ -126,10 +126,6 @@ bool SplitOpBuilder::IsOpSupportedImpl(const InitializedTensorSet& initializers, LOGS(logger, VERBOSE) << "Cannot get split."; return false; } - if (split.size() > 4 && device_type == WebnnDeviceType::CPU) { - LOGS(logger, VERBOSE) << "WebNN CPU backend only supports up to 4 outputs."; - return false; - } } else { if (helper.HasAttr("num_outputs")) { // Split has 'num_outputs' attribute when opset is 18. @@ -138,10 +134,6 @@ bool SplitOpBuilder::IsOpSupportedImpl(const InitializedTensorSet& initializers, LOGS(logger, VERBOSE) << "The 'num_outputs' must be a positive integer."; return false; } - if (num_outputs > 4 && device_type == WebnnDeviceType::CPU) { - LOGS(logger, VERBOSE) << "WebNN CPU backend only supports up to 4 outputs."; - return false; - } } else { const auto opset = node.SinceVersion(); if (opset >= 18) { diff --git a/onnxruntime/core/providers/webnn/builders/model_builder.h b/onnxruntime/core/providers/webnn/builders/model_builder.h index 8c1848eb83..80077b3abe 100644 --- a/onnxruntime/core/providers/webnn/builders/model_builder.h +++ b/onnxruntime/core/providers/webnn/builders/model_builder.h @@ -53,7 +53,7 @@ class ModelBuilder { void AddInitializerToSkip(const std::string& tensor_name); // There are some input which will not be used, add it to a list which will not - // be added to CoreML model, since CoreML does not like input unused. + // be added to WebNN model, since WebNN does not like input unused. void AddInputToSkip(const std::string& input_name); std::string GetUniqueName(const std::string& base_name);