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Enable QLinearAveragePooling DML EP (#17384)
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DML EP Implementation for
[QLinearAveragePool](https://github.com/microsoft/onnxruntime/blob/main/docs/ContribOperators.md#com.microsoft.QLinearAveragePool)
```
Note: Google Test filter = *QLinear*Pool*
[==========] Running 72 tests from 2 test suites.
[----------] Global test environment set-up.
[----------] 36 tests from QLinearGlobalAveragePool
[ RUN      ] QLinearGlobalAveragePool.Nhwc_1x1x32x32
[       OK ] QLinearGlobalAveragePool.Nhwc_1x1x32x32 (410 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_1x32x32x1
[       OK ] QLinearGlobalAveragePool.Nchw_1x32x32x1 (641 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_1x256x8x8
[       OK ] QLinearGlobalAveragePool.Nhwc_1x256x8x8 (156 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_1x8x8x256
[       OK ] QLinearGlobalAveragePool.Nchw_1x8x8x256 (134 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_1x255x7x7
[       OK ] QLinearGlobalAveragePool.Nhwc_1x255x7x7 (160 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_1x7x7x255
[       OK ] QLinearGlobalAveragePool.Nchw_1x7x7x255 (145 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_1x255x8x8
[       OK ] QLinearGlobalAveragePool.Nhwc_1x255x8x8 (148 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_1x8x8x255
[       OK ] QLinearGlobalAveragePool.Nchw_1x8x8x255 (129 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_1x256x7x7
[       OK ] QLinearGlobalAveragePool.Nhwc_1x256x7x7 (134 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_1x7x7x256
[       OK ] QLinearGlobalAveragePool.Nchw_1x7x7x256 (131 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_3x256x8x8
[       OK ] QLinearGlobalAveragePool.Nhwc_3x256x8x8 (159 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_3x8x8x256
[       OK ] QLinearGlobalAveragePool.Nchw_3x8x8x256 (168 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_3x255x7x7
[       OK ] QLinearGlobalAveragePool.Nhwc_3x255x7x7 (139 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_3x7x7x255
[       OK ] QLinearGlobalAveragePool.Nchw_3x7x7x255 (170 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_3x255x8x8
[       OK ] QLinearGlobalAveragePool.Nhwc_3x255x8x8 (155 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_3x8x8x255
[       OK ] QLinearGlobalAveragePool.Nchw_3x8x8x255 (156 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_3x256x7x7
[       OK ] QLinearGlobalAveragePool.Nhwc_3x256x7x7 (133 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_3x7x7x256
[       OK ] QLinearGlobalAveragePool.Nchw_3x7x7x256 (149 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_1x1x32x32_S8
[       OK ] QLinearGlobalAveragePool.Nhwc_1x1x32x32_S8 (131 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_1x32x32x1_S8
[       OK ] QLinearGlobalAveragePool.Nchw_1x32x32x1_S8 (127 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_1x256x8x8_S8
[       OK ] QLinearGlobalAveragePool.Nhwc_1x256x8x8_S8 (153 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_1x8x8x256_S8
[       OK ] QLinearGlobalAveragePool.Nchw_1x8x8x256_S8 (129 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_1x255x7x7_S8
[       OK ] QLinearGlobalAveragePool.Nhwc_1x255x7x7_S8 (133 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_1x7x7x255_S8
[       OK ] QLinearGlobalAveragePool.Nchw_1x7x7x255_S8 (135 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_1x255x8x8_S8
[       OK ] QLinearGlobalAveragePool.Nhwc_1x255x8x8_S8 (129 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_1x8x8x255_S8
[       OK ] QLinearGlobalAveragePool.Nchw_1x8x8x255_S8 (152 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_1x256x7x7_S8
[       OK ] QLinearGlobalAveragePool.Nhwc_1x256x7x7_S8 (140 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_1x7x7x256_S8
[       OK ] QLinearGlobalAveragePool.Nchw_1x7x7x256_S8 (133 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_3x256x8x8_S8
[       OK ] QLinearGlobalAveragePool.Nhwc_3x256x8x8_S8 (135 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_3x8x8x256_S8
[       OK ] QLinearGlobalAveragePool.Nchw_3x8x8x256_S8 (147 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_3x255x7x7_S8
[       OK ] QLinearGlobalAveragePool.Nhwc_3x255x7x7_S8 (156 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_3x7x7x255_S8
[       OK ] QLinearGlobalAveragePool.Nchw_3x7x7x255_S8 (155 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_3x255x8x8_S8
[       OK ] QLinearGlobalAveragePool.Nhwc_3x255x8x8_S8 (138 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_3x8x8x255_S8
[       OK ] QLinearGlobalAveragePool.Nchw_3x8x8x255_S8 (155 ms)
[ RUN      ] QLinearGlobalAveragePool.Nhwc_3x256x7x7_S8
[       OK ] QLinearGlobalAveragePool.Nhwc_3x256x7x7_S8 (144 ms)
[ RUN      ] QLinearGlobalAveragePool.Nchw_3x7x7x256_S8
[       OK ] QLinearGlobalAveragePool.Nchw_3x7x7x256_S8 (139 ms)
[----------] 36 tests from QLinearGlobalAveragePool (5968 ms total)

[----------] 36 tests from QLinearPoolTest
[ RUN      ] QLinearPoolTest.AveragePool1D_ExcludePadPixel
[       OK ] QLinearPoolTest.AveragePool1D_ExcludePadPixel (480 ms)
[ RUN      ] QLinearPoolTest.AveragePool1D_IncludePadPixel
[       OK ] QLinearPoolTest.AveragePool1D_IncludePadPixel (481 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_ExcludePadPixel
[       OK ] QLinearPoolTest.AveragePool2D_ExcludePadPixel (512 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_IncludePadPixel
[       OK ] QLinearPoolTest.AveragePool2D_IncludePadPixel (455 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_MultiChannel
[       OK ] QLinearPoolTest.AveragePool2D_MultiChannel (463 ms)
[ RUN      ] QLinearPoolTest.AveragePool3D_ExcludePadPixel
[       OK ] QLinearPoolTest.AveragePool3D_ExcludePadPixel (448 ms)
[ RUN      ] QLinearPoolTest.AveragePool3D_IncludePadPixel
[       OK ] QLinearPoolTest.AveragePool3D_IncludePadPixel (458 ms)
[ RUN      ] QLinearPoolTest.AveragePool1D_ExcludePadPixel_nhwc
[       OK ] QLinearPoolTest.AveragePool1D_ExcludePadPixel_nhwc (171 ms)
[ RUN      ] QLinearPoolTest.AveragePool1D_IncludePadPixel_nhwc
[       OK ] QLinearPoolTest.AveragePool1D_IncludePadPixel_nhwc (169 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_ExcludePadPixel_nhwc
[       OK ] QLinearPoolTest.AveragePool2D_ExcludePadPixel_nhwc (152 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_IncludePadPixel_nhwc
[       OK ] QLinearPoolTest.AveragePool2D_IncludePadPixel_nhwc (660 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_MultiChannel_nhwc
[       OK ] QLinearPoolTest.AveragePool2D_MultiChannel_nhwc (150 ms)
[ RUN      ] QLinearPoolTest.AveragePool3D_ExcludePadPixel_nhwc
[       OK ] QLinearPoolTest.AveragePool3D_ExcludePadPixel_nhwc (145 ms)
[ RUN      ] QLinearPoolTest.AveragePool3D_IncludePadPixel_nhwc
[       OK ] QLinearPoolTest.AveragePool3D_IncludePadPixel_nhwc (146 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_BigImage
[       OK ] QLinearPoolTest.AveragePool2D_BigImage (505 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_BigImage_nhwc
[       OK ] QLinearPoolTest.AveragePool2D_BigImage_nhwc (161 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_Global
[       OK ] QLinearPoolTest.AveragePool2D_Global (481 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_Global_nhwc
[       OK ] QLinearPoolTest.AveragePool2D_Global_nhwc (152 ms)
[ RUN      ] QLinearPoolTest.AveragePool1D_ExcludePadPixel_S8
[       OK ] QLinearPoolTest.AveragePool1D_ExcludePadPixel_S8 (461 ms)
[ RUN      ] QLinearPoolTest.AveragePool1D_IncludePadPixel_S8
[       OK ] QLinearPoolTest.AveragePool1D_IncludePadPixel_S8 (448 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_ExcludePadPixel_S8
[       OK ] QLinearPoolTest.AveragePool2D_ExcludePadPixel_S8 (471 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_IncludePadPixel_S8
[       OK ] QLinearPoolTest.AveragePool2D_IncludePadPixel_S8 (473 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_MultiChannel_S8
[       OK ] QLinearPoolTest.AveragePool2D_MultiChannel_S8 (1507 ms)
[ RUN      ] QLinearPoolTest.AveragePool3D_ExcludePadPixel_S8
[       OK ] QLinearPoolTest.AveragePool3D_ExcludePadPixel_S8 (477 ms)
[ RUN      ] QLinearPoolTest.AveragePool3D_IncludePadPixel_S8
[       OK ] QLinearPoolTest.AveragePool3D_IncludePadPixel_S8 (493 ms)
[ RUN      ] QLinearPoolTest.AveragePool1D_ExcludePadPixel_nhwc_S8
[       OK ] QLinearPoolTest.AveragePool1D_ExcludePadPixel_nhwc_S8 (158 ms)
[ RUN      ] QLinearPoolTest.AveragePool1D_IncludePadPixel_nhwc_S8
[       OK ] QLinearPoolTest.AveragePool1D_IncludePadPixel_nhwc_S8 (146 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_ExcludePadPixel_nhwc_S8
[       OK ] QLinearPoolTest.AveragePool2D_ExcludePadPixel_nhwc_S8 (146 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_IncludePadPixel_nhwc_S8
[       OK ] QLinearPoolTest.AveragePool2D_IncludePadPixel_nhwc_S8 (158 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_MultiChannel_nhwc_S8
[       OK ] QLinearPoolTest.AveragePool2D_MultiChannel_nhwc_S8 (157 ms)
[ RUN      ] QLinearPoolTest.AveragePool3D_ExcludePadPixel_nhwc_S8
[       OK ] QLinearPoolTest.AveragePool3D_ExcludePadPixel_nhwc_S8 (145 ms)
[ RUN      ] QLinearPoolTest.AveragePool3D_IncludePadPixel_nhwc_S8
[       OK ] QLinearPoolTest.AveragePool3D_IncludePadPixel_nhwc_S8 (147 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_BigImage_S8
[       OK ] QLinearPoolTest.AveragePool2D_BigImage_S8 (537 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_BigImage_nhwc_S8
[       OK ] QLinearPoolTest.AveragePool2D_BigImage_nhwc_S8 (173 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_Global_S8
[       OK ] QLinearPoolTest.AveragePool2D_Global_S8 (457 ms)
[ RUN      ] QLinearPoolTest.AveragePool2D_Global_nhwc_S8
[       OK ] QLinearPoolTest.AveragePool2D_Global_nhwc_S8 (150 ms)
[----------] 36 tests from QLinearPoolTest (12914 ms total)

[----------] Global test environment tear-down
[==========] 72 tests from 2 test suites ran. (18885 ms total)
[  PASSED  ] 72 tests.
memleakdbg:
----- No memory leaks detected -----
```
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@raoanag
raoanag committed Oct 13, 2023
1 parent adb2dd3 commit 43ea845
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Showing 14 changed files with 679 additions and 48 deletions.
37 changes: 35 additions & 2 deletions onnxruntime/core/providers/dml/DmlExecutionProvider/src/External/DirectMLHelpers/ApiTraits.h
View file
Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,26 @@ struct DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_DESC
_Maybenull_ const DML_TENSOR_DESC* BiasTensor;
const DML_TENSOR_DESC* OutputTensor;
};
const int DML_OPERATOR_MATRIX_MULTIPLY_INTEGER_TO_FLOAT = 0x80000011;
const int DML_OPERATOR_MATRIX_MULTIPLY_INTEGER_TO_FLOAT = 0x80000011;

struct DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_DESC
{
const DML_TENSOR_DESC* InputTensor;
const DML_TENSOR_DESC* InputScaleTensor;
_Maybenull_ const DML_TENSOR_DESC* InputZeroPointTensor;
const DML_TENSOR_DESC* OutputScaleTensor;
_Maybenull_ const DML_TENSOR_DESC* OutputZeroPointTensor;
const DML_TENSOR_DESC* OutputTensor;
UINT DimensionCount;
_Field_size_(DimensionCount) const UINT* Strides;
_Field_size_(DimensionCount) const UINT* WindowSize;
_Field_size_(DimensionCount) const UINT* StartPadding;
_Field_size_(DimensionCount) const UINT* EndPadding;
_Field_size_(DimensionCount) const UINT* Dilations;
BOOL IncludePadding;
};
const int DML_OPERATOR_QUANTIZED_LINEAR_AVERAGE_POOLING = 0x8000000B;


namespace ApiTraits
{
Expand All @@ -38,7 +57,7 @@ struct EnumTraits<DML_TENSOR_TYPE>
template <>
struct EnumTraits<DML_OPERATOR_TYPE>
{
static constexpr auto ValueCount = 161;
static constexpr auto ValueCount = 162;
static constexpr size_t ActivationFunctionCount = 24;
};

Expand Down Expand Up @@ -497,6 +516,12 @@ struct OperatorDescTraits<DML_ROI_POOLING_OPERATOR_DESC>
static constexpr DML_OPERATOR_TYPE Type = DML_OPERATOR_ROI_POOLING;
};

template <>
struct OperatorDescTraits<DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_DESC>
{
static constexpr DML_OPERATOR_TYPE Type = (DML_OPERATOR_TYPE) DML_OPERATOR_QUANTIZED_LINEAR_AVERAGE_POOLING;
};

template <>
struct OperatorDescTraits<DML_SLICE_OPERATOR_DESC>
{
Expand Down Expand Up @@ -1492,6 +1517,12 @@ struct OperatorTypeTraits<(DML_OPERATOR_TYPE)DML_OPERATOR_ROI_POOLING>
using DescType = DML_ROI_POOLING_OPERATOR_DESC;
};

template <>
struct OperatorTypeTraits<(DML_OPERATOR_TYPE)DML_OPERATOR_QUANTIZED_LINEAR_AVERAGE_POOLING>
{
using DescType = DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_DESC;
};

template <>
struct OperatorTypeTraits<(DML_OPERATOR_TYPE)DML_OPERATOR_SLICE>
{
Expand Down Expand Up @@ -2524,6 +2555,8 @@ auto OperatorTypeVisitor(DML_OPERATOR_TYPE type, Visitor&& visitor, Ts&&... args
#pragma warning(disable: 4063)
case DML_OPERATOR_MATRIX_MULTIPLY_INTEGER_TO_FLOAT:
return std::invoke(std::forward<Visitor>(visitor), DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_DESC{}, std::forward<Ts>(args)...);
case DML_OPERATOR_QUANTIZED_LINEAR_AVERAGE_POOLING:
return std::invoke(std::forward<Visitor>(visitor), DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_DESC{}, std::forward<Ts>(args)...);
#pragma warning(pop)

default:
Expand Down
25 changes: 25 additions & 0 deletions ...ime/core/providers/dml/DmlExecutionProvider/src/External/DirectMLHelpers/DirectMLSchema.h
View file
Original file line number Diff line number Diff line change
Expand Up @@ -829,6 +829,31 @@ constexpr DML_OPERATOR_SCHEMA DML_ROI_POOLING_OPERATOR_SCHEMA {
DML_ROI_POOLING_OPERATOR_SCHEMA_FIELDS,
};


constexpr DML_SCHEMA_FIELD DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA_FIELDS[13] {
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "InputTensor", false },
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "InputScaleTensor", false },
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "InputZeroPointTensor", true },
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "OutputScaleTensor", false },
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "OutputZeroPointTensor", true },
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_OUTPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "OutputTensor", false },
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_ATTRIBUTE, DML_SCHEMA_FIELD_TYPE_UINT, "DimensionCount", false },
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_ATTRIBUTE, DML_SCHEMA_FIELD_TYPE_UINT_ARRAY, "Strides", false },
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_ATTRIBUTE, DML_SCHEMA_FIELD_TYPE_UINT_ARRAY, "WindowSize", false },
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_ATTRIBUTE, DML_SCHEMA_FIELD_TYPE_UINT_ARRAY, "StartPadding", false },
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_ATTRIBUTE, DML_SCHEMA_FIELD_TYPE_UINT_ARRAY, "EndPadding", false },
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_ATTRIBUTE, DML_SCHEMA_FIELD_TYPE_UINT_ARRAY, "Dilations", false },
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_ATTRIBUTE, DML_SCHEMA_FIELD_TYPE_UINT, "IncludePadding", false },
};

constexpr DML_OPERATOR_SCHEMA DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA {
"DML_OPERATOR_QUANTIZED_LINEAR_AVERAGE_POOLING",
static_cast<DML_OPERATOR_TYPE>(DML_OPERATOR_QUANTIZED_LINEAR_AVERAGE_POOLING),
DML_SCHEMA_OPERATOR_SUPPORT_FLAG_NONE,
13,
DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA_FIELDS,
};

constexpr DML_SCHEMA_FIELD DML_SLICE_OPERATOR_SCHEMA_FIELDS[6] {
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "InputTensor", false },
DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_OUTPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "OutputTensor", false },
Expand Down
22 changes: 22 additions & 0 deletions .../providers/dml/DmlExecutionProvider/src/External/DirectMLHelpers/GeneratedSchemaHelpers.h
View file
Original file line number Diff line number Diff line change
Expand Up @@ -473,6 +473,24 @@ inline std::vector<OperatorField> GetFields(const DML_ROI_POOLING_OPERATOR_DESC&
OperatorField(&DML_ROI_POOLING_OPERATOR_SCHEMA.Fields[4], ToOperatorFieldType(static_cast<DML_SIZE_2D>(desc.PooledSize))),
};
}
inline std::vector<OperatorField> GetFields(const DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_DESC& desc)
{
return {
OperatorField(&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA.Fields[0], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.InputTensor))),
OperatorField(&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA.Fields[1], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.InputScaleTensor))),
OperatorField(&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA.Fields[2], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.InputZeroPointTensor))),
OperatorField(&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA.Fields[3], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.OutputScaleTensor))),
OperatorField(&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA.Fields[4], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.OutputZeroPointTensor))),
OperatorField(&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA.Fields[5], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.OutputTensor))),
OperatorField(&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA.Fields[6], ToOperatorFieldType(static_cast<UINT>(desc.DimensionCount))),
OperatorField(&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA.Fields[7], ToOperatorFieldType(static_cast<const UINT*>(desc.Strides), desc.DimensionCount)),
OperatorField(&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA.Fields[8], ToOperatorFieldType(static_cast<const UINT*>(desc.WindowSize), desc.DimensionCount)),
OperatorField(&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA.Fields[9], ToOperatorFieldType(static_cast<const UINT*>(desc.StartPadding), desc.DimensionCount)),
OperatorField(&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA.Fields[10], ToOperatorFieldType(static_cast<const UINT*>(desc.EndPadding), desc.DimensionCount)),
OperatorField(&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA.Fields[11], ToOperatorFieldType(static_cast<const UINT*>(desc.Dilations), desc.DimensionCount)),
OperatorField(&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA.Fields[12], ToOperatorFieldType(static_cast<UINT>(desc.IncludePadding))),
};
}
inline std::vector<OperatorField> GetFields(const DML_SLICE_OPERATOR_DESC& desc)
{
return {
Expand Down Expand Up @@ -2492,6 +2510,10 @@ inline AbstractOperatorDesc ConvertOperatorDesc(const DML_OPERATOR_DESC& opDesc)
return AbstractOperatorDesc(
&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA,
GetFields(*static_cast<const DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_DESC*>(opDesc.Desc)));
case DML_OPERATOR_QUANTIZED_LINEAR_AVERAGE_POOLING:
return AbstractOperatorDesc(
&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA,
GetFields(*static_cast<const DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_DESC*>(opDesc.Desc)));
#pragma warning(pop)

default:
Expand Down
46 changes: 27 additions & 19 deletions onnxruntime/core/providers/dml/DmlExecutionProvider/src/Operators/DmlOperatorAttention.cpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -6,9 +6,11 @@
/*
Abbreviations: B is batch_size, S is sequence_length, W is hidden_size
N is number of attention heads, H is head size, and W=N*H
M is mask_index tensor
M is mask_index tensor, P is optional past tensor
M A B C // M, A, B, and C are Inputs
// M, A, B, C and P are Inputs
M A B C
| \ | /
| Gemm
| / | \
Expand All @@ -17,13 +19,30 @@ Abbreviations: B is batch_size, S is sequence_length, W is hidden_size
| Slice Slice Slice
| | | |
| | | |
| Identity Identity Identity // The identities are used to transpose NCHW -> NHCW while
| | | | // keeping the GEMM strides as NCHW to better target metacommands
| Identity Identity Identity // The identities are used to transpose NCHW -> NHCW while
| | | | // keeping the GEMM strides as NCHW to better target metacommands
| | | |
----------------- MHA -----
|
|
Output // Final output
| | | | P
| | | | / \
| | | | / \
| | | | Slice Slice
| | | | | |
| | | | | |
| | | | | |
--------------------------MHA -----------
/ | \
/ | \
/ | \
/ | \
/ | \
/ | \
Output1 presentKey presentValue
\ /
\ /
\ /
Concat
|
Output2 (present)
This kernel creates a DML_GRAPH, as mentioned above.
For reference, refer to this Doc:
Expand Down Expand Up @@ -540,24 +559,13 @@ class DmlOperatorAttention : public DmlOperator
void CALLBACK QueryAttention(IMLOperatorSupportQueryContextPrivate* context, /*out*/ bool* isSupported)
{
*isSupported = false;
// `past` input tensor is not supported yet
if (context->IsInputValid(4))
{
return;
}

// `past_sequence_length` input tensor is not supported yet
if (context->IsInputValid(6))
{
return;
}

// `present` output tensor is not supported yet
if (context->IsOutputValid(1))
{
return;
}

// `unidirectional == 1` is not supported yet
MLOperatorAttributes attributes(context);
if (attributes.GetOptionalAttribute<int32_t>(AttrName::Unidirectional, 0) != 0)
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