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aparmp-quicSanket Kale
aparmp-quic
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Sanket Kale
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[QNN EP] Enable Conv Op with "auto_pad" param set as VALID (microsoft#25444)
Enable Conv Op and ConvTranspose Op with "auto_pad" param set as VALID ### Description QNN_EP reject the Conv Op and ConvTranspose on HTP if "auto_pad" is "VALID". This configuration is supported on HTP. ### Motivation and Context To enable Conv and ConvTranspose op with auto_pad as "VALID" running on NPU and prevent them from falling back to CPU.
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‎onnxruntime/core/providers/qnn/builder/opbuilder/conv_op_builder.cc‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -94,7 +94,7 @@ Status ConvOpBuilder::IsOpSupported(QnnModelWrapper& qnn_model_wrapper,
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NodeAttrHelper node_helper(node_unit);
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auto auto_pad = node_helper.Get("auto_pad", std::string("NOTSET"));
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ORT_RETURN_IF(auto_pad != "NOTSET" && auto_pad != "SAME_LOWER" && auto_pad != "SAME_UPPER",
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ORT_RETURN_IF(auto_pad != "NOTSET" && auto_pad != "SAME_LOWER" && auto_pad != "SAME_UPPER" && auto_pad != "VALID",
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"QNN Conv operators do not support 'auto_pad' value: ", auto_pad.c_str());
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OnnxConvType conv_type = {};
@@ -667,7 +667,7 @@ Status ConvOpBuilder::ProcessAttributesAndOutputs(QnnModelWrapper& qnn_model_wra
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pads.assign(kernel_shape.size() * 2, 0);
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pads = node_helper.Get("pads", pads);
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auto auto_pad = node_helper.Get("auto_pad", std::string("NOTSET"));
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ORT_RETURN_IF(auto_pad != "NOTSET" && auto_pad != "SAME_LOWER" && auto_pad != "SAME_UPPER",
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ORT_RETURN_IF(auto_pad != "NOTSET" && auto_pad != "SAME_LOWER" && auto_pad != "SAME_UPPER" && auto_pad != "VALID",
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"QNN Conv operators do not support 'auto_pad' value: ", auto_pad.c_str());
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if (auto_pad != "NOTSET") {

‎onnxruntime/test/providers/qnn/conv_test.cc‎

Lines changed: 92 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -2111,6 +2111,98 @@ TEST_F(QnnHTPBackendTests, ConvTranspose1DU8U8S32_AutoPadLower) {
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13);
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}
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// Tests Conv's auto_pad value "VALID" on HTP backend (compares to CPU EP).
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TEST_F(QnnHTPBackendTests, ConvU8U8S32_AutoPadValid) {
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RunHTPConvOpTest<uint8_t, uint8_t>("Conv",
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TestInputDef<float>({1, 1, 5, 5}, false, 0.f, 10.f), // Dynamic input
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TestInputDef<float>({1, 1, 4, 4}, true, -1.f, 1.f), // Static weights
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TestInputDef<float>({1}, true, {1.0f}), // Initializer bias
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{1, 1}, // strides
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{}, // pads
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{1, 1}, // dilations
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1, // default group
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"VALID", // auto_pad
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ExpectedEPNodeAssignment::All,
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false, // use_contrib_qdq
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13);
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RunHTPConvOpTest<uint8_t, uint8_t>("Conv",
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TestInputDef<float>({1, 1, 5, 5, 5}, false, 0.f, 10.f), // Dynamic input
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TestInputDef<float>({1, 1, 4, 4, 4}, true, -1.f, 1.f), // Static weights
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TestInputDef<float>({1}, true, {1.0f}), // Initializer bias
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{1, 1, 1}, // strides
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{}, // pads
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{1, 1, 1}, // dilations
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1, // default group
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"VALID", // auto_pad
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ExpectedEPNodeAssignment::All,
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false, // use_contrib_qdq
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13);
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}
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// Tests ConvTranspose's auto_pad value "VALID" on HTP backend (compares to CPU EP).
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TEST_F(QnnHTPBackendTests, ConvTransposeU8U8S32_AutoPadValid) {
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RunHTPConvOpTest<uint8_t, uint8_t>("ConvTranspose",
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TestInputDef<float>({1, 1, 5, 5}, false, 0.f, 10.f), // Dynamic input
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TestInputDef<float>({1, 1, 4, 4}, true, -1.f, 1.f), // Static weights
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TestInputDef<float>({1}, true, {1.0f}), // Initializer bias
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{1, 1}, // strides
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{}, // pads
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{1, 1}, // dilations
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1, // default group
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"VALID", // auto_pad
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ExpectedEPNodeAssignment::All,
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false, // use_contrib_qdq
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13);
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RunHTPConvOpTest<uint8_t, uint8_t>("ConvTranspose",
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TestInputDef<float>({1, 1, 5, 5, 5}, false, 0.f, 10.f), // Dynamic input
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TestInputDef<float>({1, 1, 4, 4, 4}, true, -1.f, 1.f), // Static weights
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TestInputDef<float>({1}, true, {1.0f}), // Initializer bias
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{1, 1, 1}, // strides
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{}, // pads
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{1, 1, 1}, // dilations
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1, // default group
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"VALID", // auto_pad
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ExpectedEPNodeAssignment::All,
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false, // use_contrib_qdq
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13);
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}
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// Tests Conv1d auto_pad value "VALID" on HTP backend (compares to CPU EP).
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TEST_F(QnnHTPBackendTests, Conv1DU8U8S32_AutoPadValid) {
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std::vector<float> input_data = {0.f, 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f};
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RunHTPConvOpTest<uint8_t, uint8_t>("Conv",
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TestInputDef<float>({1, 2, 4}, false, input_data), // Dynamic input
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TestInputDef<float>({1, 2, 2}, true, {1.f, 2.f, 3.f, 4.f}), // Static weight
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TestInputDef<float>({1}, true, {1.0f}), // Initializer bias
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{1}, // strides
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{0}, // pads
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{1}, // dilations
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1, // default group
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"VALID", // auto_pad
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ExpectedEPNodeAssignment::All,
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false, // use_contrib_qdq
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13);
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}
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// Tests ConvTranspose 1d auto_pad value "VALID" on HTP backend (compares to CPU EP).
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TEST_F(QnnHTPBackendTests, ConvTranspose1DU8U8S32_AutoPadValid) {
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std::vector<float> input_data = {0.f, 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f};
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RunHTPConvOpTest<uint8_t, uint8_t>("ConvTranspose",
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TestInputDef<float>({1, 2, 4}, false, input_data), // Dynamic input
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TestInputDef<float>({2, 1, 2}, true, {1.f, 2.f, 3.f, 4.f}), // Static weight
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TestInputDef<float>({1}, true, {1.0f}), // Initializer bias
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{1}, // strides
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{0}, // pads
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{1}, // dilations
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1, // default group
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"VALID", // auto_pad
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ExpectedEPNodeAssignment::All,
2202+
false, // use_contrib_qdq
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13);
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}
2205+
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// Fails with QNN SDK 2.35.0:
21152207
// value pair (-4.54545403, -4.54687548) at index #3 don't match, which is -0.00142145 from -4.54545
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TEST_F(QnnHTPBackendTests, DISABLED_ConvU8U8S32_large_input1_padding_bias_initializer) {

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