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153 changes: 153 additions & 0 deletions
153
...ore/providers/dml/DmlExecutionProvider/src/Operators/DmlOperatorQLinearAveragePooling.cpp
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| // Copyright (c) Microsoft Corporation. All rights reserved. | ||
| // Licensed under the MIT License. | ||
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| #include "precomp.h" | ||
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| namespace Dml | ||
| { | ||
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| class DmlOperatorQLinearAveragePooling : public DmlOperator, public PoolingHelperBase | ||
| { | ||
| // For QLinear Avg Pool ORT and DML have same indexing order | ||
| enum OrtInputTensors : uint32_t | ||
| { | ||
| ortInput, | ||
| ortInputScale, | ||
| ortInputZeroPoint, | ||
| ortOutputScale, | ||
| ortOutputZeroPoint, | ||
| ortInputCount | ||
| }; | ||
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| public: | ||
| using Self = DmlOperatorQLinearAveragePooling; | ||
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| DmlOperatorQLinearAveragePooling( | ||
| const MLOperatorKernelCreationContext& kernelInfo) | ||
| : DmlOperator(kernelInfo), | ||
| //QLinearAveragePoolingHelper(kernelInfo, kernelInfo.GetTensorShapeDescription(), false) | ||
| PoolingHelperBase(kernelInfo, kernelInfo.GetTensorShapeDescription(), false) | ||
| { | ||
| DmlOperator::Initialize(kernelInfo); | ||
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| std::vector<DimensionType> inputShape = kernelInfo.GetTensorShapeDescription().GetInputTensorShape(OrtInputTensors::ortInput); | ||
| std::vector<DimensionType> outputShape = kernelInfo.GetTensorShapeDescription().GetOutputTensorShape(0); | ||
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| assert(m_kernel.spatialDimensionCount <= ARRAYSIZE(m_kernel.windowSize)); | ||
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| // DML requires that DimensionCount be equal to Input.DimCount - 2 for Pooling | ||
| uint32_t expectedSpatialDimCount = m_inputTensorDescs[0].GetDimensionCount() - 2; | ||
| if (m_kernel.spatialDimensionCount < expectedSpatialDimCount) | ||
| { | ||
| size_t shift = expectedSpatialDimCount - m_kernel.spatialDimensionCount; | ||
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| for (int i = gsl::narrow_cast<int>(m_kernel.spatialDimensionCount) - 1; i >= 0; i--) | ||
| { | ||
| m_kernel.windowSize[i + shift] = m_kernel.windowSize[i]; | ||
| m_kernel.windowSize[i] = 1; | ||
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| m_kernel.strides[i + shift] = m_kernel.strides[i]; | ||
| m_kernel.strides[i] = 1; | ||
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| m_kernel.startPadding[i + shift] = m_kernel.startPadding[i]; | ||
| m_kernel.startPadding[i] = 0; | ||
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| m_kernel.endPadding[i + shift] = m_kernel.endPadding[i]; | ||
| m_kernel.endPadding[i] = 0; | ||
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| m_kernel.dilations[i + shift] = m_kernel.dilations[i]; | ||
| m_kernel.dilations[i] = 1; | ||
| } | ||
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| m_kernel.spatialDimensionCount = expectedSpatialDimCount; | ||
| } | ||
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| // Initialize the input descriptions with broadcasting | ||
| m_inputTensorDescs[OrtInputTensors::ortInput] = CreateTensorDescFromInput(kernelInfo, OrtInputTensors::ortInput, TensorAxis::DoNotCoerce, TensorAxis::W, TensorAxis::RightAligned, inputShape); | ||
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| uint32_t dmlDimSize = m_inputTensorDescs[OrtInputTensors::ortInput].GetDimensionCount(); | ||
| // Resize the Input Scale to be the same dimension as the input tensor. | ||
| // The 1D tensor needs to be moved to the H channel. | ||
| m_inputTensorDescs[OrtInputTensors::ortInputScale] = CreateTensorDescFromInput( | ||
| kernelInfo, | ||
| OrtInputTensors::ortInputScale, | ||
| TensorAxis::DoNotCoerce, | ||
| TensorAxis::H, | ||
| TensorAxis::LeftAligned, | ||
| std::nullopt, | ||
| dmlDimSize | ||
| ); | ||
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| // Resize the Input ZeroPoint to be the same dimension as the input tensor. | ||
| // The 1D tensor needs to be moved to the H channel. | ||
| if (kernelInfo.IsInputValid(OrtInputTensors::ortInputZeroPoint)) | ||
| { | ||
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| m_inputTensorDescs[OrtInputTensors::ortInputZeroPoint] = CreateTensorDescFromInput( | ||
| kernelInfo, | ||
| OrtInputTensors::ortInputZeroPoint, | ||
| TensorAxis::DoNotCoerce, | ||
| TensorAxis::H, | ||
| TensorAxis::LeftAligned, | ||
| std::nullopt, | ||
| dmlDimSize | ||
| ); | ||
| } | ||
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| // Resize the Output Scale to be the same dimension as the input tensor. | ||
| // The 1D tensor needs to be moved to the H channel. | ||
| m_inputTensorDescs[OrtInputTensors::ortOutputScale] = CreateTensorDescFromInput( | ||
| kernelInfo, | ||
| OrtInputTensors::ortInputScale, | ||
| TensorAxis::DoNotCoerce, | ||
| TensorAxis::H, | ||
| TensorAxis::LeftAligned, | ||
| std::nullopt, | ||
| dmlDimSize | ||
| ); | ||
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| // Resize the Input ZeroPoint to be the same dimension as the input tensor. | ||
| // The 1D tensor needs to be moved to the H channel. | ||
| if (kernelInfo.IsInputValid(OrtInputTensors::ortOutputZeroPoint)) | ||
| { | ||
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| m_inputTensorDescs[OrtInputTensors::ortOutputZeroPoint] = CreateTensorDescFromInput( | ||
| kernelInfo, | ||
| OrtInputTensors::ortOutputZeroPoint, | ||
| TensorAxis::DoNotCoerce, | ||
| TensorAxis::H, | ||
| TensorAxis::LeftAligned, | ||
| std::nullopt, | ||
| dmlDimSize | ||
| ); | ||
| } | ||
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| // Initialize the output description while overriding the shape | ||
| m_outputTensorDescs[0] = CreateTensorDescFromOutput(kernelInfo, 0, TensorAxis::DoNotCoerce, TensorAxis::W, TensorAxis::RightAligned, outputShape); | ||
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| std::vector<DML_TENSOR_DESC> inputDescs = GetDmlInputDescs(); | ||
| std::vector<DML_TENSOR_DESC> outputDescs = GetDmlOutputDescs(); | ||
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| DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_DESC qLinearAvgPooldesc = {}; | ||
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| qLinearAvgPooldesc.InputTensor = &inputDescs[OrtInputTensors::ortInput]; | ||
| qLinearAvgPooldesc.InputScaleTensor = &inputDescs[OrtInputTensors::ortInputScale]; | ||
| qLinearAvgPooldesc.InputZeroPointTensor = &inputDescs[OrtInputTensors::ortInputZeroPoint]; | ||
| qLinearAvgPooldesc.OutputScaleTensor = &inputDescs[OrtInputTensors::ortOutputScale];; | ||
| qLinearAvgPooldesc.OutputZeroPointTensor = &inputDescs[OrtInputTensors::ortOutputZeroPoint];; | ||
| qLinearAvgPooldesc.OutputTensor = &outputDescs[0]; | ||
| qLinearAvgPooldesc.DimensionCount = m_kernel.spatialDimensionCount; | ||
| qLinearAvgPooldesc.WindowSize = m_kernel.windowSize; | ||
| qLinearAvgPooldesc.Strides = m_kernel.strides; | ||
| qLinearAvgPooldesc.StartPadding = m_kernel.startPadding; | ||
| qLinearAvgPooldesc.EndPadding = m_kernel.endPadding; | ||
| qLinearAvgPooldesc.IncludePadding = kernelInfo.GetOptionalAttribute<bool>(AttrName::CountIncludePad, false); | ||
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| DML_OPERATOR_DESC opDesc = { (DML_OPERATOR_TYPE) DML_OPERATOR_QUANTIZED_LINEAR_AVERAGE_POOLING, &qLinearAvgPooldesc }; | ||
| SetDmlOperatorDesc(opDesc, kernelInfo); | ||
| } | ||
| }; | ||
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| DML_OP_DEFINE_CREATION_FUNCTION(QLinearAveragePool, DmlOperatorQLinearAveragePooling); | ||
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| } // namespace Dml |
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