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[WebNN EP] Support Sign and CumSum operators (#22616)

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This PR supports Sign and CumSum operators for WebNN EP. @Honry @fdwr
PTAL, thanks.
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Bin Miao 2024-11-04 12:08:16 +08:00 committed by GitHub
parent ac6fe48375
commit 777fe7922c
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7 changed files with 101 additions and 8 deletions
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2
js/web/docs/webnn-operators.md
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@ -25,6 +25,7 @@ operators and the supported opset domain/versions in **WebNN EP** by ONNX Runtim
| Conv | ai.onnx(7-10, 11+) | conv2d | ✓ | ✓ | Only supports 3-D or 4-D input and 'W' (weight) |
| ConvTranspose | ai.onnx(7-10, 11+) | convTranspose2d | ✓ | ✓ | Only supports 3-D or 4-D input and 'W' (weight). WebNN CPU backend only supports default dilations and group |
| Cos | ai.onnx(7+) | cos | ✓ | ✓ | |
| CumSum | ai.onnx(11-13, 14+) | cumulativeSum | ✓ | ✓ | |
| Div | ai.onnx(7-12, 13, 14+) | div | ✓ | ✓ | |
| DequantizeLinear | ai.onnx(10-12, 13-18, 19-20, 21-22, 23+) | dequantizeLinear | ✗ | ✓ | |
| Dropout | ai.onnx(7-9, 10-11, 12, 13-21, 22+) | identity | ✓ | ✓ | Only supports test mode |
@ -87,6 +88,7 @@ operators and the supported opset domain/versions in **WebNN EP** by ONNX Runtim
| ScatterND | ai.onnx(11-12, 13-15, 16-17, 18+) | scatterND | ✗ | ✓ | Only supports 'reduction' == 'none' |
| Shape | ai.onnx(7-12, 13-14, 15-18, 19-20, 21+) | slice | ✓ | ✓ | |
| Sigmoid | ai.onnx(7-12, 13+) | sigmoid | ✓ | ✓ | |
| Sign | ai.onnx(9-12, 13+) | sign | ✓ | ✓ | |
| Softplus | ai.onnx(7+) | softplus | ✓ | ✓ | |
| Softsign | ai.onnx(7+) | softsign | ✓ | ✓ | |
| Sin | ai.onnx(7+) | sin | ✓ | ✓ | |

16
js/web/test/suite-test-list.jsonc
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@ -1699,13 +1699,13 @@
"test_cos",
// "test_cosh_example",
// "test_cosh",
// "test_cumsum_1d_exclusive",
// "test_cumsum_1d_reverse_exclusive",
// "test_cumsum_1d_reverse",
// "test_cumsum_1d",
// "test_cumsum_2d_axis_0",
// "test_cumsum_2d_axis_1",
// "test_cumsum_2d_negative_axis",
"test_cumsum_1d_exclusive",
"test_cumsum_1d_reverse_exclusive",
"test_cumsum_1d_reverse",
"test_cumsum_1d",
"test_cumsum_2d_axis_0",
"test_cumsum_2d_axis_1",
"test_cumsum_2d_negative_axis",
// "test_depthtospace_crd_mode_example",
// "test_depthtospace_crd_mode",
// "test_depthtospace_dcr_mode",
@ -2352,7 +2352,7 @@
// "test_shrink_soft",
"test_sigmoid_example",
"test_sigmoid",
// "test_sign",
"test_sign",
// "test_simple_rnn_batchwise",
// "test_simple_rnn_defaults",
// "test_simple_rnn_with_initial_bias",

2
onnxruntime/core/providers/webnn/builders/helper.h
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@ -204,6 +204,7 @@ static const InlinedHashMap<std::string, std::string> op_map = {
{"ConvInteger", "conv2dInteger"},
{"ConvTranspose", "convTranspose2d"},
{"Cos", "cos"},
{"CumSum", "cumulativeSum"},
{"Div", "div"},
{"DequantizeLinear", "dequantizeLinear"},
{"Dropout", "identity"},
@ -268,6 +269,7 @@ static const InlinedHashMap<std::string, std::string> op_map = {
{"ScatterND", "scatterND"},
{"Shape", "slice"},
{"Sigmoid", "sigmoid"},
{"Sign", "sign"},
{"Softplus", "softplus"},
{"Softsign", "softsign"},
{"Sin", "sin"},

80
onnxruntime/core/providers/webnn/builders/impl/cumsum_op_builder.cc Normal file
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@ -0,0 +1,80 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Copyright (c) Intel Corporation. All rights reserved.
// Licensed under the MIT License.
#include "core/common/safeint.h"
#include "core/framework/tensorprotoutils.h"
#include "core/optimizer/initializer.h"
#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 CumSumOpBuilder : public BaseOpBuilder {
// Add operator related.
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.
Status CumSumOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
const Node& node,
const logging::Logger& logger) const {
const auto& input_defs = node.InputDefs();
emscripten::val input = model_builder.GetOperand(input_defs[0]->Name());
std::vector<int64_t> input_shape;
ORT_RETURN_IF_NOT(GetShape(*input_defs[0], input_shape, logger), "Cannot get input shape");
const auto input_rank = input_shape.size();
NodeAttrHelper helper(node);
int64_t axis = helper.Get("axis", 0);
axis = HandleNegativeAxis(axis, input_rank);
const auto exclusive = helper.Get("exclusive", 0);
const auto reverse = helper.Get("reverse", 0);
emscripten::val options = emscripten::val::object();
options.set("exclusive", exclusive == 1);
options.set("reversed", reverse == 1);
options.set("label", node.Name());
emscripten::val output = emscripten::val::object();
output = model_builder.GetBuilder().call<emscripten::val>("cumulativeSum", input, gsl::narrow<uint32_t>(axis), options);
model_builder.AddOperand(node.OutputDefs()[0]->Name(), std::move(output));
return Status::OK();
}
// Operator support related.
bool CumSumOpBuilder::IsOpSupportedImpl(const InitializedTensorSet& /* initializers */,
const Node& node,
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;
return true;
}
void CreateCumSumOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations) {
op_registrations.builders.push_back(std::make_unique<CumSumOpBuilder>());
op_registrations.op_builder_map.emplace(op_type, op_registrations.builders.back().get());
}
} // namespace webnn
} // namespace onnxruntime

3
onnxruntime/core/providers/webnn/builders/impl/unary_op_builder.cc
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@ -51,6 +51,8 @@ Status UnaryOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder, const
output = model_builder.GetBuilder().call<emscripten::val>("neg", input, options);
} else if (op_type == "Reciprocal") {
output = model_builder.GetBuilder().call<emscripten::val>("reciprocal", input, options);
} else if (op_type == "Sign") {
output = model_builder.GetBuilder().call<emscripten::val>("sign", input, options);
} else if (op_type == "Sin") {
output = model_builder.GetBuilder().call<emscripten::val>("sin", input, options);
} else if (op_type == "Sqrt") {
@ -82,6 +84,7 @@ void CreateUnaryOpBuilder(const std::string& op_type, OpBuilderRegistrations& op
"Log",
"Neg",
"Reciprocal",
"Sign",
"Sin",
"Sqrt",
"Tan",

5
onnxruntime/core/providers/webnn/builders/op_builder_factory.cc
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@ -26,6 +26,7 @@ static OpBuilderRegistrations CreateOpBuilderRegistrations() {
CreateUnaryOpBuilder("Log", op_registrations);
CreateUnaryOpBuilder("Neg", op_registrations);
CreateUnaryOpBuilder("Reciprocal", op_registrations);
CreateUnaryOpBuilder("Sign", op_registrations);
CreateUnaryOpBuilder("Sin", op_registrations);
CreateUnaryOpBuilder("Sqrt", op_registrations);
CreateUnaryOpBuilder("Tan", op_registrations);
@ -80,6 +81,10 @@ static OpBuilderRegistrations CreateOpBuilderRegistrations() {
CreateConcatOpBuilder("Concat", op_registrations);
}
{ // CumSum
CreateConcatOpBuilder("CumSum", op_registrations);
}
{ // Dropout
CreateDropoutOpBuilder("Dropout", op_registrations);
}

1
onnxruntime/core/providers/webnn/builders/op_builder_factory.h
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@ -26,6 +26,7 @@ void CreateCastOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_
void CreateClipOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations);
void CreateConvOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations);
void CreateConcatOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations);
void CreateCumSumOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations);
void CreateDropoutOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations);
void CreateDynamicQuantizeLinearOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations);
void CreateExpandOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations);