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[rocm-libraries] ROCm/rocm-libraries#4591 (commit d34e981)

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[CK] Add BF16^3 support to grouped conv bwd weight: bilinear
 and scale (#4591)
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## Motivation

Until now, XDL grouped conv bwd weight for bilinear and scale only
supported bf16f32bf16.
Therefore, bf16bf16bf16 support should be added.

## Technical Details

Instances were added to the relevant files in
`library/include/ck/library/tensor_operation_instance/gpu/grouped_conv_bwd_weight/`
folder. In addition, `add()` functions were included in new files in
`library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight_bilinear/xdl/`
and
`library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight_scale/xdl/`
folders. The new .cpp files were also included in the `CMakeFiles.txt`
files of both folders.

## Test Plan

Execute `grouped_convnd_bwd_weight` tests to check execution on
different architectures.
The tests for bilinear and scale already include the tuple
`std::tuple<ck::half_t, ck::half_t, ck::half_t, ck::Number<3>>`, so in
principle, there is nothing to modify in the tests themselves.

## Test Result

`gfx1201`: Tests passed.
`gfx1100`: Tests passed.
`gfx90a`: Tests passed.

## Submission Checklist

- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
This commit is contained in:
JP-Fernando
2026-03-11 12:06:35 +00:00
committed by assistant-librarian[bot]
parent 2312eef6c3
commit 6f0ecf361e
10 changed files with 195 additions and 30 deletions
Download Patch File Download Diff File Expand all files Collapse all files

18
library/include/ck/library/tensor_operation_instance/gpu/grouped_conv_bwd_weight/device_grouped_conv_bwd_weight_xdl_bilinear_instance.hpp
View File

@@ -149,7 +149,7 @@ template <ck::index_t NDimSpatial,
typename BLayout,
typename ELayout,
ConvolutionBackwardWeightSpecialization ConvSpec>
using device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_bilinear_instances = std::tuple<
using device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_f32_bf16_bilinear_instances = std::tuple<
// clang-format off
//#########################################| Num| InLayout| WeiLayout| OutLayout| DsData| InData| WeiData| OutData| AccData| DsData| In| Wei| Out| ConvBackward| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransfer| CBlockTransfer|
//#########################################| Dim| | | | Layout| Type| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Weight| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| ClusterLengths| ScalarPerVector|
@@ -177,6 +177,22 @@ using device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_bilinear_instances = std
// clang-format on
>;
template <ck::index_t NDimSpatial,
typename ALayout,
typename BLayout,
typename ELayout,
ConvolutionBackwardWeightSpecialization ConvSpec>
using device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_bilinear_instances = std::tuple<
// clang-format off
//#########################################| Num| InLayout| WeiLayout| OutLayout| DsData| InData| WeiData| OutData| AccData| DsData| In| Wei| Out| ConvBackward| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransfer| CBlockTransfer|
//#########################################| Dim| | | | Layout| Type| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Weight| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| ClusterLengths| ScalarPerVector|
//#########################################| Spatial| | | | | | | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| MBlock_MPerBlock| NWaveNPerXdl|
//#########################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | NBlock_NPerBlock| |
// generic instance
DeviceGroupedConvBwdWeightMultipleD_Xdl_CShuffle< NDimSpatial, ALayout, BLayout, ELayout, Tuple<BLayout>, BF16, BF16, BF16, F32, Tuple<BF16>, PassThrough, Bilinear, PassThrough, ConvSpec, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<1, 4, 8, 2>, S<0, 3, 1, 2>, S<0, 2, 1, 3>, 2, 1, 4, true, S<1, 4, 8, 2>, S<0, 3, 1, 2>, S<0, 2, 1, 3>, 2, 1, 4, true, 1, 1, S<1, 16, 1, 4>, 1>
// clang-format on
>;
template <ck::index_t NDimSpatial,
typename ALayout,
typename BLayout,

18
library/include/ck/library/tensor_operation_instance/gpu/grouped_conv_bwd_weight/device_grouped_conv_bwd_weight_xdl_scale_instance.hpp
View File

@@ -148,7 +148,7 @@ template <ck::index_t NDimSpatial,
typename BLayout,
typename ELayout,
ConvolutionBackwardWeightSpecialization ConvSpec>
using device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_scale_instances = std::tuple<
using device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_f32_bf16_scale_instances = std::tuple<
// clang-format off
//#########################################| Num| InLayout| WeiLayout| OutLayout| DsData| InData| WeiData| OutData| AccData| DsData| In| Wei| Out| ConvBackward| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransfer| CBlockTransfer|
//#########################################| Dim| | | | Layout| Type| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Weight| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| ClusterLengths| ScalarPerVector|
@@ -176,6 +176,22 @@ using device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_scale_instances = std::t
// clang-format on
>;
template <ck::index_t NDimSpatial,
typename ALayout,
typename BLayout,
typename ELayout,
ConvolutionBackwardWeightSpecialization ConvSpec>
using device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_scale_instances = std::tuple<
// clang-format off
//#########################################| Num| InLayout| WeiLayout| OutLayout| DsData| InData| WeiData| OutData| AccData| DsData| In| Wei| Out| ConvBackward| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransfer| CBlockTransfer|
//#########################################| Dim| | | | Layout| Type| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Weight| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| ClusterLengths| ScalarPerVector|
//#########################################| Spatial| | | | | | | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| MBlock_MPerBlock| NWaveNPerXdl|
//#########################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | NBlock_NPerBlock| |
// generic instance
DeviceGroupedConvBwdWeightMultipleD_Xdl_CShuffle< NDimSpatial, ALayout, BLayout, ELayout, Empty_Tuple, BF16, BF16, BF16, F32, Empty_Tuple, PassThrough, Scale, PassThrough, ConvSpec, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<1, 4, 8, 2>, S<0, 3, 1, 2>, S<0, 2, 1, 3>, 2, 1, 4, true, S<1, 4, 8, 2>, S<0, 3, 1, 2>, S<0, 2, 1, 3>, 2, 1, 4, true, 1, 1, S<1, 16, 1, 4>, 1>
// clang-format on
>;
template <ck::index_t NDimSpatial,
typename ALayout,
typename BLayout,

24
library/include/ck/library/tensor_operation_instance/gpu/grouped_convolution_backward_weight_bilinear.hpp
View File

@@ -11,6 +11,7 @@
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
#include "ck/utility/data_type.hpp"
namespace ck {
namespace tensor_operation {
@@ -65,6 +66,19 @@ void add_device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_bf16
PassThrough,
Bilinear,
PassThrough>>>& instances);
void add_device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_bf16_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeightMultipleD<3,
NDHWGC,
GKZYXC,
NDHWGK,
Tuple<GKZYXC>,
BF16,
BF16,
BF16,
Tuple<BF16>,
PassThrough,
Bilinear,
PassThrough>>>& instances);
#endif
#ifdef CK_ENABLE_FP16
void add_device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_f16_instances(
@@ -255,6 +269,16 @@ struct DeviceOperationInstanceFactory<
add_device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instances(
op_ptrs);
}
if constexpr(is_same_v<InDataType, ck::bhalf_t> &&
is_same_v<WeiDataType, ck::bhalf_t> &&
is_same_v<OutDataType, ck::bhalf_t> &&
is_same_v<ComputeTypeA, ck::bhalf_t> &&
is_same_v<ComputeTypeB, ck::bhalf_t>)
{
add_device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_bf16_instances(
op_ptrs);
}
#endif
#if defined CK_ENABLE_FP16 && defined CK_ENABLE_FP8 && defined CK_ENABLE_BF8
if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&

23
library/include/ck/library/tensor_operation_instance/gpu/grouped_convolution_backward_weight_scale.hpp
View File

@@ -66,6 +66,19 @@ void add_device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_bf16_f3
PassThrough,
Scale,
PassThrough>>>& instances);
void add_device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_bf16_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeightMultipleD<3,
NDHWGC,
GKZYXC,
NDHWGK,
Tuple<>,
BF16,
BF16,
BF16,
Tuple<>,
PassThrough,
Scale,
PassThrough>>>& instances);
#endif
#ifdef CK_ENABLE_FP16
void add_device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_f16_instances(
@@ -255,6 +268,16 @@ struct DeviceOperationInstanceFactory<
add_device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instances(
op_ptrs);
}
if constexpr(is_same_v<InDataType, ck::bhalf_t> &&
is_same_v<WeiDataType, ck::bhalf_t> &&
is_same_v<OutDataType, ck::bhalf_t> &&
is_same_v<ComputeTypeA, ck::bhalf_t> &&
is_same_v<ComputeTypeB, ck::bhalf_t>)
{
add_device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_bf16_instances(
op_ptrs);
}
#endif
#if defined CK_ENABLE_FP16 && defined CK_ENABLE_FP8 && defined CK_ENABLE_BF8
if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&

4
library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight_bilinear/CMakeLists.txt
View File

@@ -6,7 +6,9 @@ set(GROUPED_CONV3D_BWD_WEIGHT_BILINEAR
xdl/device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_f16_instance.cpp
xdl/device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_f32_instance.cpp
xdl/device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_f32_tf32_instance.cpp
xdl/device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_bf16_instance.cpp)
xdl/device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_bf16_instance.cpp
xdl/device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instance.cpp
)
if((DTYPES MATCHES "fp8" AND DTYPES MATCHES "bf8" AND DTYPES MATCHES "fp16") OR NOT DEFINED DTYPES)
list(APPEND GROUPED_CONV3D_BWD_WEIGHT_BILINEAR

50
library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight_bilinear/xdl/device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instance.cpp Normal file
View File

@@ -0,0 +1,50 @@
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
#include "ck/library/tensor_operation_instance/gpu/grouped_conv_bwd_weight/device_grouped_conv_bwd_weight_xdl_bilinear_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// Compilation parameters for in[n, hi, wi, g, c] * wei[g, k, y, x, c] = out[n, ho, wo, g, k]
void add_device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeightMultipleD<3,
NDHWGC,
GKZYXC,
NDHWGK,
Tuple<GKZYXC>,
BF16,
F32,
BF16,
Tuple<F32>,
PassThrough,
Bilinear,
PassThrough>>>& instances)
{
// 1. Default
add_device_operation_instances(
instances,
device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_f32_bf16_bilinear_instances<
3,
NDHWGC,
GKZYXC,
NDHWGK,
ConvBwdWeightDefault>{});
// 2. Filter1x1Stride1Pad0
add_device_operation_instances(
instances,
device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_f32_bf16_bilinear_instances<
3,
NDHWGC,
GKZYXC,
NDHWGK,
ConvBwdWeightFilter1x1Stride1Pad0>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck

18
library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight_bilinear/xdl/device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_bf16_instance.cpp
View File

@@ -9,22 +9,21 @@ namespace tensor_operation {
namespace device {
namespace instance {
// Compilation parameters for in[n, hi, wi, g, c] * wei[g, k, y, x, c] = out[n, ho, wo, g, k]
void add_device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instances(
void add_device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_bf16_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeightMultipleD<3,
NDHWGC,
GKZYXC,
NDHWGK,
Tuple<GKZYXC>,
BF16,
F32,
BF16,
Tuple<F32>,
BF16,
Tuple<BF16>,
PassThrough,
Bilinear,
PassThrough>>>& instances)
{
// 1. Default
// Default bwd weight bilinear
add_device_operation_instances(
instances,
device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_bilinear_instances<
@@ -33,15 +32,6 @@ void add_device_grouped_conv3d_bwd_weight_xdl_bilinear_ndhwgc_gkzyxc_ndhwgk_bf16
GKZYXC,
NDHWGK,
ConvBwdWeightDefault>{});
// 2. Filter1x1Stride1Pad0
add_device_operation_instances(
instances,
device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_bilinear_instances<
3,
NDHWGC,
GKZYXC,
NDHWGK,
ConvBwdWeightFilter1x1Stride1Pad0>{});
}
} // namespace instance

4
library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight_scale/CMakeLists.txt
View File

@@ -6,7 +6,9 @@ set(GROUPED_CONV3D_BWD_WEIGHT_SCALE
xdl/device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_f16_instance.cpp
xdl/device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_f32_instance.cpp
xdl/device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_f32_tf32_instance.cpp
xdl/device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_bf16_instance.cpp)
xdl/device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_bf16_instance.cpp
xdl/device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instance.cpp
)
if((DTYPES MATCHES "fp8" AND DTYPES MATCHES "bf8" AND DTYPES MATCHES "fp16") OR NOT DEFINED DTYPES)
list(APPEND GROUPED_CONV3D_BWD_WEIGHT_SCALE

51
library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight_scale/xdl/device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instance.cpp Normal file
View File

@@ -0,0 +1,51 @@
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
#include "ck/library/tensor_operation_instance/gpu/grouped_conv_bwd_weight/device_grouped_conv_bwd_weight_xdl_scale_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// Compilation parameters for in[n, hi, wi, g, c] * wei[g, k, y, x, c] = out[n, ho, wo, g, k]
void add_device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeightMultipleD<3,
NDHWGC,
GKZYXC,
NDHWGK,
Tuple<>,
BF16,
F32,
BF16,
Tuple<>,
PassThrough,
Scale,
PassThrough>>>& instances)
{
// 1. Default
add_device_operation_instances(
instances,
device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_f32_bf16_scale_instances<
3,
NDHWGC,
GKZYXC,
NDHWGK,
ConvBwdWeightDefault>{});
// 2. Filter1x1Stride1Pad0
add_device_operation_instances(
instances,
device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_f32_bf16_scale_instances<
3,
NDHWGC,
GKZYXC,
NDHWGK,
ConvBwdWeightFilter1x1Stride1Pad0>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck

15
library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight_scale/xdl/device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_bf16_instance.cpp
View File

@@ -10,21 +10,21 @@ namespace device {
namespace instance {
// Compilation parameters for in[n, hi, wi, g, c] * wei[g, k, y, x, c] = out[n, ho, wo, g, k]
void add_device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instances(
void add_device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_bf16_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeightMultipleD<3,
NDHWGC,
GKZYXC,
NDHWGK,
Tuple<>,
BF16,
F32,
BF16,
BF16,
Tuple<>,
PassThrough,
Scale,
PassThrough>>>& instances)
{
// 1. Default
// Default conv bwd weight
add_device_operation_instances(
instances,
device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_scale_instances<3,
@@ -32,15 +32,6 @@ void add_device_grouped_conv3d_bwd_weight_xdl_scale_ndhwgc_gkzyxc_ndhwgk_bf16_f3
GKZYXC,
NDHWGK,
ConvBwdWeightDefault>{});
// 2. Filter1x1Stride1Pad0
add_device_operation_instances(
instances,
device_grouped_conv_bwd_weight_xdl_c_shuffle_bf16_scale_instances<
3,
NDHWGC,
GKZYXC,
NDHWGK,
ConvBwdWeightFilter1x1Stride1Pad0>{});
}
} // namespace instance