[DML EP] Add DML implementation for BiasGelu (#13795)
### Description Add DML implementation for BiasGelu
This commit is contained in:
Patrice Vignola
GitHub
Родитель
e0dcbc3832
Коммит
e9b92fdf33
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@ -1118,6 +1118,7 @@ Do not modify directly.*
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|**Operator Domain:** *com.microsoft*||||
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|Attention|*in* input:**T**<br> *in* weights:**T**<br> *in* bias:**T**<br> *in* mask_index:**M**<br> *in* past:**T**<br> *in* extra_add:**T**<br> *in* key:**T**<br> *in* value:**T**<br> *out* output:**T**<br> *out* present:**T**|1+|**M** = tensor(int32)<br/> **T** = tensor(float), tensor(float16)|
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|BiasGelu|*in* A:**T**<br> *in* B:**T**<br> *out* C:**T**|1+|**T** = tensor(float), tensor(float16)|
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|ConvTransposeWithDynamicPads|*in* X:**T**<br> *in* W:**T**<br> *in* Pads:**tensor(int64)**<br> *in* B:**T**<br> *out* Y:**T**|1+|**T** = tensor(float), tensor(float16)|
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|DequantizeLinear|*in* x:**T1**<br> *in* x_scale:**T2**<br> *in* x_zero_point:**T1**<br> *out* y:**T2**|1+|**T1** = tensor(float)<br/> **T2** = tensor(uint8)|
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|FusedMatMul|*in* A:**T**<br> *in* B:**T**<br> *out* Y:**T**|1+|**T** = tensor(float), tensor(float16)|
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@ -0,0 +1,45 @@
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// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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#include "precomp.h"
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namespace Dml
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{
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class DmlOperatorBiasGelu : public DmlOperator
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{
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public:
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DmlOperatorBiasGelu(const MLOperatorKernelCreationContext& kernelCreationContext)
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: DmlOperator(kernelCreationContext)
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{
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ML_CHECK_VALID_ARGUMENT(kernelCreationContext.GetInputCount() == 2);
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ML_CHECK_VALID_ARGUMENT(kernelCreationContext.GetOutputCount() == 1);
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// Broadcast bias to have the same dimensions as the input
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std::vector<uint32_t> inputTensorShape = kernelCreationContext.GetTensorShapeDescription().GetInputTensorShape(0);
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DmlOperator::Initialize(kernelCreationContext, std::nullopt, std::nullopt, inputTensorShape);
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std::vector<DML_TENSOR_DESC> inputDescs = GetDmlInputDescs();
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std::vector<DML_TENSOR_DESC> outputDescs = GetDmlOutputDescs();
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ML_CHECK_VALID_ARGUMENT(inputDescs.size() == 2);
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ML_CHECK_VALID_ARGUMENT(outputDescs.size() == 1);
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TensorDesc biasInputTensorDesc(m_inputTensorDescs[0].GetDmlDataType(), m_inputTensorDescs[0].GetSizes());
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DML_TENSOR_DESC biasInputDmlTensorDesc = biasInputTensorDesc.GetDmlDesc();
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DML_ACTIVATION_GELU_OPERATOR_DESC geluDesc = {};
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DML_OPERATOR_DESC geluOpDesc = { DML_OPERATOR_ACTIVATION_GELU, &geluDesc };
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DML_ELEMENT_WISE_ADD1_OPERATOR_DESC addDesc = {};
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addDesc.ATensor = &inputDescs[0];
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addDesc.BTensor = &inputDescs[1];
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addDesc.FusedActivation = &geluOpDesc;
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addDesc.OutputTensor = &outputDescs[0];
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DML_OPERATOR_DESC addOpDesc = { DML_OPERATOR_ELEMENT_WISE_ADD1, &addDesc };
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SetDmlOperatorDesc(addOpDesc, kernelCreationContext);
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}
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};
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DML_OP_DEFINE_CREATION_FUNCTION(BiasGelu, DmlOperatorBiasGelu);
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} // namespace Dml
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@ -233,6 +233,7 @@ DML_OP_EXTERN_CREATION_FUNCTION(Erf);
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DML_OP_EXTERN_CREATION_FUNCTION(Where);
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DML_OP_EXTERN_CREATION_FUNCTION(Shrink);
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DML_OP_EXTERN_CREATION_FUNCTION(Gelu);
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DML_OP_EXTERN_CREATION_FUNCTION(BiasGelu);
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DML_OP_EXTERN_CREATION_FUNCTION(OneHot);
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DML_OP_EXTERN_CREATION_FUNCTION(EyeLike);
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DML_OP_EXTERN_CREATION_FUNCTION(MaxUnpool);
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@ -714,6 +715,7 @@ constexpr static OperatorRegistrationInformation operatorRegistrationInformation
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// Contrib operators
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{REG_INFO_MS( 1, Gelu, typeNameListDefault, supportedTypeListFloat16to32, DmlGraphSupport::Supported)},
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{REG_INFO_MS( 1, BiasGelu, typeNameListDefault, supportedTypeListFloat16to32, DmlGraphSupport::Supported)},
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{REG_INFO_MS( 1, FusedMatMul, typeNameListDefault, supportedTypeListFloat16to32, DmlGraphSupport::Supported)},
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{REG_INFO_MS( 1, QLinearSigmoid, typeNameListDefault, supportedTypeListQLinearSigmoid, DmlGraphSupport::Supported, requiredConstantCpuInputs(), std::nullopt, QueryQLinearSigmoid)},
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{REG_INFO_MS( 1, Attention, typeNameListAttention, supportedTypeListAttention, DmlGraphSupport::Supported, requiredConstantCpuInputs(), std::nullopt, QueryAttention)},
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@ -1557,6 +1557,7 @@ using ShapeInferenceHelper_ParametricSoftplus = GetOutputShapeAsInputShapeHelper
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using ShapeInferenceHelper_Dropout = GetOutputShapeAsInputShapeHelper;
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using ShapeInferenceHelper_Shrink = GetOutputShapeAsInputShapeHelper;
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using ShapeInferenceHelper_Gelu = GetOutputShapeAsInputShapeHelper;
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using ShapeInferenceHelper_BiasGelu = GetOutputShapeAsInputShapeHelper;
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using ShapeInferenceHelper_Identity7 = GetOutputShapeAsInputShapeHelper;
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using ShapeInferenceHelper_Identity13 = GetOutputShapeAsInputShapeHelper;
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@ -390,6 +390,7 @@ namespace OperatorHelper
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static const int sc_sinceVer_ConvTransposeWithDynamicPads = 1;
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static const int sc_sinceVer_QLinearAdd = 1;
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static const int sc_sinceVer_Gelu = 1;
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static const int sc_sinceVer_BiasGelu = 1;
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static const int sc_sinceVer_FusedMatMul = 1;
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static const int sc_sinceVer_QLinearSigmoid = 1;
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static const int sc_sinceVer_Attention = 1;
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@ -113,7 +113,7 @@ TEST(BiasGeluTest, Two_One_Dim) {
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RunBiasGeluTest(input_a_data, input_b_data, {2, 4}, {4});
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}
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#if defined(USE_CUDA) || defined(USE_ROCM)
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#if defined(USE_CUDA) || defined(USE_ROCM) || defined(USE_DML)
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TEST(BiasGeluTest, Two_One_Dim_fp16) {
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#ifdef USE_CUDA
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int min_cuda_architecture = 530;
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@ -187,6 +187,8 @@ TEST(BiasGeluTest, Two_One_Dim_bfloat16) {
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execution_providers.push_back(DefaultRocmExecutionProvider());
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#elif USE_DNNL
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execution_providers.push_back(DefaultDnnlExecutionProvider());
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#elif USE_DML
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execution_providers.push_back(DefaultDmlExecutionProvider());
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#endif
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tester.Run(OpTester::ExpectResult::kExpectSuccess, "", {}, nullptr, &execution_providers);
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}
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