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[WebNN] Fix bug in SkipSimplifiedLayerNormalization (#23236)

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The input should be added by skip and bias (if it exits) firstly.
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Wanming Lin 2025-01-08 06:24:26 +08:00 committed by GitHub
parent 655b3efee4
commit 519fae019b
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GPG key ID: B5690EEEBB952194
1 changed files with 19 additions and 17 deletions
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36
onnxruntime/core/providers/webnn/builders/impl/normalization_op_builder.cc
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@ -76,8 +76,6 @@ Status NormalizationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder
options.set("epsilon", epsilon);
emscripten::val output = emscripten::val::undefined();
// SkipSimplifiedLayerNormalization's output: input_skip_bias_sum.
emscripten::val input_skip_bias_sum = emscripten::val::undefined();
if (op_type == "BatchNormalization") {
ORT_RETURN_IF_NOT(input_defs.size() == 5, "BatchNormalization requires five inputs.");
emscripten::val mean = model_builder.GetOperand(input_defs[3]->Name());
@ -107,7 +105,7 @@ Status NormalizationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder
| | | | | |
Y:2 axis B:epsilon A:X A:scale B:bias
If it is SkipSimplifiedLayerNormalization and its output input_skip_bias_sum exists,
If it is SkipSimplifiedLayerNormalization, X should be input_skip_bias_sum:
input_skip_bias_sum = X + skip + bias (if it exists)
*/
@ -115,6 +113,23 @@ Status NormalizationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder
ORT_RETURN_IF_NOT(GetType(*input_defs[0], input_type, logger), "Cannot get input type");
emscripten::val common_options = emscripten::val::object();
// If it is SkipSimplifiedLayerNormalization, add the skip and bias (if it exists) to the input.
if (op_type == "SkipSimplifiedLayerNormalization") {
emscripten::val skip = model_builder.GetOperand(input_defs[1]->Name());
common_options.set("label", node.Name() + "_add_skip");
input = model_builder.GetBuilder().call<emscripten::val>("add", input, skip, common_options);
if (!bias.isUndefined()) {
common_options.set("label", node.Name() + "_add_skip_bias");
input = model_builder.GetBuilder().call<emscripten::val>("add", input, bias, common_options);
}
// Add SkipSimplifiedLayerNormalization's output input_skip_bias_sum if it exists.
// Now input equals to input_skip_bias_sum.
if (TensorExists(output_defs, 3)) {
model_builder.AddOperand(output_defs[3]->Name(), input);
}
}
// Pow
emscripten::val pow_constant = model_builder.CreateOrGetConstant<float>(input_type, 2);
common_options.set("label", node.Name() + "_pow");
@ -146,24 +161,11 @@ Status NormalizationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder
common_options.set("label", node.Name() + "_mul");
output = model_builder.GetBuilder().call<emscripten::val>("mul", scale, div, common_options);
// Add (if bias exits)
// Add (if bias exists)
if (!bias.isUndefined()) {
common_options.set("label", node.Name() + "_add_bias");
output = model_builder.GetBuilder().call<emscripten::val>("add", output, bias, common_options);
}
// SkipSimplifiedLayerNormalization's output input_skip_bias_sum is the sum of input, skip, and bias.
if (op_type == "SkipSimplifiedLayerNormalization" && TensorExists(output_defs, 3)) {
emscripten::val skip = model_builder.GetOperand(input_defs[1]->Name());
common_options.set("label", node.Name() + "_add_skip");
input_skip_bias_sum = model_builder.GetBuilder().call<emscripten::val>("add", input, skip, common_options);
if (!bias.isUndefined()) {
common_options.set("label", node.Name() + "_add_skip_bias");
input_skip_bias_sum = model_builder.GetBuilder().call<emscripten::val>(
"add", input_skip_bias_sum, bias, common_options);
}
model_builder.AddOperand(output_defs[3]->Name(), std::move(input_skip_bias_sum));
}
}
} else if (op_type == "InstanceNormalization") {
// WebNN spec only supports 4D input for instanceNormalization.