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[WebNN] Add limit to QDQ ops (#23076)

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WebNN requires the `scale_shape` to be a subsample of the `input_shape`.
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Wanming Lin 2024-12-18 04:52:08 +08:00 committed by GitHub
parent 54edb43e77
commit a5b60ec03f
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2 changed files with 36 additions and 2 deletions
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4
js/web/docs/webnn-operators.md
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@ -27,7 +27,7 @@ operators and the supported opset domain/versions in **WebNN EP** by ONNX Runtim
| Cos | ai.onnx(7+) | cos | ✓ | ✓ | |
| CumSum | ai.onnx(11-13, 14+) | cumulativeSum | ✓ | ✓ | 'axis' input should be a constant |
| Div | ai.onnx(7-12, 13, 14+) | div | ✓ | ✓ | |
| DequantizeLinear | ai.onnx(10-12, 13-18, 19-20, 21-22, 23+) | dequantizeLinear | ✗ | ✓ | |
| DequantizeLinear | ai.onnx(10-12, 13-18, 19-20, 21-22, 23+) | dequantizeLinear | ✓ | ✓ | The shape of x_scale should be a subsample of the shape of input |
| Dropout | ai.onnx(7-9, 10-11, 12, 13-21, 22+) | identity | ✓ | ✓ | Only supports test mode |
| Einsum | ai.onnx(12+) | reshape, transpose, matmul, reduceSum, mul, triangular | ✓ | ✓ | |
| Elu | ai.onnx(7+) | elu | ✓ | ✓ | WebNN CPU backend only supports 'alpha' value is 1.0 |
@ -71,7 +71,7 @@ operators and the supported opset domain/versions in **WebNN EP** by ONNX Runtim
| Pad | ai.onnx(7-10, 11-12, 13-17, 18, 19-20, 21+) | pad | ✓ | ✓ | modes == 'wrap' is not supported |
| Pow | ai.onnx(7-11, 12, 13-14, 15+) | pow | ✓ | ✓ | |
| PRelu | ai.onnx(7-8, 9-15, 16+) | prelu | ✓ | ✓ | WebNN CPU backend restricts the last dimension of input and slope to be same (Chromium issue: https://issues.chromium.org/issues/335517470) |
| QuantizeLinear | ai.onnx(10-12, 13-18, 19-20, 21-22, 23+) | quantizeLinear | ✗ | ✓ | |
| QuantizeLinear | ai.onnx(10-12, 13-18, 19-20, 21-22, 23+) | quantizeLinear | ✓ | ✓ | The shape of x_scale should be a subsample of the shape of input |
| Reciprocal | ai.onnx(7-12, 13+) | reciprocal | ✓ | ✓ | |
| ReduceL1 | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceL1 | ✓ | ✓ | Input 'axes' if present should be a constant |
| ReduceL2 | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceL2 | ✓ | ✓ | Input 'axes' if present should be a constant |

34
onnxruntime/core/providers/webnn/builders/impl/qdq_op_builder.cc
View file

@ -22,6 +22,8 @@ class QDQOpBuilder : public BaseOpBuilder {
const logging::Logger& logger) const override ORT_MUST_USE_RESULT;
// Operator support related.
bool IsOpSupportedImpl(const InitializedTensorSet& /* initializers */, const Node& node,
const WebnnDeviceType /* device_type */, const logging::Logger& logger) const override;
bool HasSupportedInputsImpl(const InitializedTensorSet& /* initializers */, const Node& node,
const emscripten::val& wnn_limits, const logging::Logger& logger) const override;
};
@ -118,6 +120,38 @@ Status QDQOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
return Status::OK();
}
// Operator support related.
bool QDQOpBuilder::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;
std::vector<int64_t> scale_shape;
if (!GetShape(*input_defs[0], input_shape, logger) || !GetShape(*input_defs[1], scale_shape, logger)) {
return false;
}
// WebNN requires the scale_shape to be a subsample of the input_shape.
if (scale_shape.size() > input_shape.size()) {
LOGS(logger, VERBOSE) << "The rank of scale is larger than the rank of input";
return false;
}
for (size_t i = 0; i < scale_shape.size(); ++i) {
auto scale_dim = scale_shape[scale_shape.size() - i - 1];
auto input_dim = input_shape[input_shape.size() - i - 1];
if (input_dim % scale_dim != 0) {
LOGS(logger, VERBOSE) << "The shape of scale is not a subsample of the shape of input";
return false;
}
}
return true;
}
bool QDQOpBuilder::HasSupportedInputsImpl(const InitializedTensorSet& /* initializers */, const Node& node,
const emscripten::val& wnn_limits, const logging::Logger& logger) const {
const auto& input_defs = node.InputDefs();