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[QNN EP] Check the axis attribute for LayerNorm for HTP (#16872)

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Check the axis attribute for LayerNorm for HTP

### Description
Add code to check the axis value for LayerNorm for HTP explicitly to
make sure only the last dimension is allowed.
This commit is contained in:
Hector Li 2023-07-27 09:59:46 -07:00 committed by GitHub
parent 2748f51603
commit ec935a5533
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3 changed files with 14 additions and 3 deletions
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1
onnxruntime/core/providers/qnn/builder/opbuilder/base_op_builder.h
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@ -135,7 +135,6 @@ class BaseOpBuilder : public IOpBuilder {
{"Elu", QNN_OP_ELU},
{"Relu", QNN_OP_RELU},
{"Gelu", QNN_OP_GELU},
{"Sigmoid", QNN_OP_SIGMOID},
{"HardSwish", QNN_OP_HARD_SWISH},

12
onnxruntime/core/providers/qnn/builder/opbuilder/layer_norm_op_builder.cc
View file

@ -54,6 +54,18 @@ Status LayerNormOpBuilder::IsOpSupported(QnnModelWrapper& qnn_model_wrapper,
ORT_RETURN_IF(!is_quantized_model && output_data_type != float_elem_type, "QNN LayerNorm data type ", output_data_type->c_str(), " is not supported in CPU backend.");
ORT_RETURN_IF(outputs.size() > 1, "QNN LayerNorm only support 1 output.");
// QNN Op validation can also do the same work, but the message is not so clear.
// Explicit check and provide clear message here
if (is_quantized_model) {
std::vector<uint32_t> input_shape;
ORT_RETURN_IF_NOT(qnn_model_wrapper.GetOnnxShape(inputs[0].node_arg, input_shape), "Cannot get shape of input 0");
const size_t input_rank = input_shape.size();
int32_t default_axis = -1;
Qnn_Scalar_t axis_qnn_scalar = QNN_SCALAR_INIT;
ORT_RETURN_IF_ERROR(ProcessAxisAttribute(qnn_model_wrapper, node_unit, axis_qnn_scalar, default_axis));
ORT_RETURN_IF(static_cast<size_t>(default_axis) != input_rank - 1, "QNN LayerNorm for HTP only support axis with last input dimension");
}
return AddToModelBuilder(qnn_model_wrapper, node_unit, logger, is_quantized_model, true);
}

4
onnxruntime/test/providers/qnn/layer_norm_test.cc
View file

@ -122,8 +122,8 @@ static void RunLayerNormQDQTest(const std::vector<int64_t>& input_shape,
// Check that QNN compiles DQ -> LayerNormalization -> Q as a single unit.
// Use an input of rank 3.
// Failed QNN op validation: QnnDsp <E> Param[0] has incorrect Value 3
TEST_F(QnnHTPBackendTests, DISABLED_TestQDQLayerNorm1DAxis0) {
RunLayerNormQDQTest({1, 2, 3}, {1, 2, 3}, ExpectedEPNodeAssignment::All);
TEST_F(QnnHTPBackendTests, TestQDQLayerNorm1DAxis0) {
RunLayerNormQDQTest({1, 2, 3}, {1, 2, 3}, ExpectedEPNodeAssignment::None);
}
// Failed QNN FinalizeGraphs: QnnDsp <E> Failed to finalize graph (id: 1) with err 1002