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Commit 8f722700 authored by Chao Liu's avatar Chao Liu
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update ckprofiler for conv bwd data

parent a711f90b
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Showing with 829 additions and 16 deletions
example/17_convnd_bwd_data/CMakeLists.txt 0 → 100644
View file @ 8f722700
add_example_executable(example_convnd_bwd_data_xdl_fp16 convnd_bwd_data_xdl_fp16.cpp)
target_link_libraries(example_convnd_bwd_data_xdl_fp16 PRIVATE utility)
example/17_convnd_bwd_data_xdl/CMakeLists.txt deleted 100644 → 0
View file @ a711f90b
add_example_executable(example_convnd_bwd_data_xdl convnd_bwd_data_xdl.cpp)
target_link_libraries(example_convnd_bwd_data_xdl PRIVATE utility)
example/CMakeLists.txt
View file @ 8f722700
......@@ -33,10 +33,10 @@ add_subdirectory(13_pool2d_fwd)
add_subdirectory(14_gemm_xdl_requant_relu_requant)
add_subdirectory(15_grouped_gemm)
add_subdirectory(16_gemm_reduce)
add_subdirectory(17_convnd_bwd_data_xdl)
add_subdirectory(17_convnd_bwd_data)
add_subdirectory(18_batched_gemm_reduce)
add_subdirectory(19_binary_elementwise)
add_subdirectory(20_convnd_bwd_weight_xdl)
add_subdirectory(20_convnd_bwd_weight)
add_subdirectory(21_gemm_layernorm)
add_subdirectory(22_cgemm)
add_subdirectory(23_softmax)
......
include/ck/ck.hpp
View file @ 8f722700
......@@ -146,7 +146,7 @@
// workaround: verifaction failure, due to compiler regression, for conv bwd-data fp16 using some
// tuning parameter
#define CK_WORKAROUND_SWDEV_325164 1
#define CK_WORKAROUND_SWDEV_325164 0
namespace ck {
......
library/include/ck/library/tensor_operation_instance/gpu/convolution_backward_data.hpp 0 → 100644
View file @ 8f722700
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_conv_bwd_data.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// conv1d backward data
void add_device_conv1d_bwd_data_xdl_nwc_kxc_nwk_bf16_instances(
std::vector<std::unique_ptr<DeviceConvBwdData<1,
NWC,
KXC,
NWK,
BF16,
BF16,
BF16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f16_instances(
std::vector<std::unique_ptr<
DeviceConvBwdData<1, NWC, KXC, NWK, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
instances);
void add_device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f32_instances(
std::vector<std::unique_ptr<
DeviceConvBwdData<1, NWC, KXC, NWK, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
instances);
void add_device_conv1d_bwd_data_xdl_nwc_kxc_nwk_int8_instances(
std::vector<std::unique_ptr<DeviceConvBwdData<1,
NWC,
KXC,
NWK,
int8_t,
int8_t,
int8_t,
PassThrough,
PassThrough,
PassThrough>>>& instances);
// conv2d backward data
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_bf16_instances(
std::vector<std::unique_ptr<DeviceConvBwdData<2,
NHWC,
KYXC,
NHWK,
BF16,
BF16,
BF16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f16_instances(
std::vector<std::unique_ptr<DeviceConvBwdData<2,
NHWC,
KYXC,
NHWK,
F16,
F16,
F16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f32_instances(
std::vector<std::unique_ptr<DeviceConvBwdData<2,
NHWC,
KYXC,
NHWK,
F32,
F32,
F32,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_int8_instances(
std::vector<std::unique_ptr<DeviceConvBwdData<2,
NHWC,
KYXC,
NHWK,
int8_t,
int8_t,
int8_t,
PassThrough,
PassThrough,
PassThrough>>>& instances);
// conv3d backward data
void add_device_conv3d_bwd_data_xdl_ndhwc_kzyxc_ndhwk_bf16_instances(
std::vector<std::unique_ptr<DeviceConvBwdData<3,
NDHWC,
KZYXC,
NDHWK,
BF16,
BF16,
BF16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_conv3d_bwd_data_xdl_ndhwc_kzyxc_ndhwk_f16_instances(
std::vector<std::unique_ptr<DeviceConvBwdData<3,
NDHWC,
KZYXC,
NDHWK,
F16,
F16,
F16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_conv3d_bwd_data_xdl_ndhwc_kzyxc_ndhwk_f32_instances(
std::vector<std::unique_ptr<DeviceConvBwdData<3,
NDHWC,
KZYXC,
NDHWK,
F32,
F32,
F32,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_conv3d_bwd_data_xdl_ndhwc_kzyxc_ndhwk_int8_instances(
std::vector<std::unique_ptr<DeviceConvBwdData<3,
NDHWC,
KZYXC,
NDHWK,
int8_t,
int8_t,
int8_t,
PassThrough,
PassThrough,
PassThrough>>>& instances);
template <ck::index_t NumDimSpatial,
typename InLayout,
typename WeiLayout,
typename OutLayout,
typename InDataType,
typename WeiDataType,
typename OutDataType>
struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceConvBwdData<
NumDimSpatial,
InLayout,
WeiLayout,
OutLayout,
InDataType,
WeiDataType,
OutDataType,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough>>
{
using DeviceOp = DeviceConvBwdData<NumDimSpatial,
InLayout,
WeiLayout,
OutLayout,
InDataType,
WeiDataType,
OutDataType,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough>;
static auto GetInstances()
{
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
if constexpr(NumDimSpatial == 1 && is_same_v<InLayout, NWC> && is_same_v<WeiLayout, KXC> &&
is_same_v<OutLayout, NWK>)
{
if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> &&
is_same_v<OutDataType, float>)
{
add_device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f32_instances(op_ptrs);
}
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>)
{
add_device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f16_instances(op_ptrs);
}
else if constexpr(is_same_v<InDataType, ck::bhalf_t> &&
is_same_v<WeiDataType, ck::bhalf_t> &&
is_same_v<OutDataType, ck::bhalf_t>)
{
add_device_conv1d_bwd_data_xdl_nwc_kxc_nwk_bf16_instances(op_ptrs);
}
else if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> &&
is_same_v<OutDataType, int8_t>)
{
add_device_conv1d_bwd_data_xdl_nwc_kxc_nwk_int8_instances(op_ptrs);
}
}
else if constexpr(NumDimSpatial == 2 && is_same_v<InLayout, NHWC> &&
is_same_v<WeiLayout, KYXC> && is_same_v<OutLayout, NHWK>)
{
if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> &&
is_same_v<OutDataType, float>)
{
add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f32_instances(op_ptrs);
}
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>)
{
add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f16_instances(op_ptrs);
}
else if constexpr(is_same_v<InDataType, ck::bhalf_t> &&
is_same_v<WeiDataType, ck::bhalf_t> &&
is_same_v<OutDataType, ck::bhalf_t>)
{
add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_bf16_instances(op_ptrs);
}
else if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> &&
is_same_v<OutDataType, int8_t>)
{
add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_int8_instances(op_ptrs);
}
}
else if constexpr(NumDimSpatial == 3 && is_same_v<InLayout, NDHWC> &&
is_same_v<WeiLayout, KZYXC> && is_same_v<OutLayout, NDHWK>)
{
if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> &&
is_same_v<OutDataType, float>)
{
add_device_conv3d_bwd_data_xdl_ndhwc_kzyxc_ndhwk_f32_instances(op_ptrs);
}
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>)
{
add_device_conv3d_bwd_data_xdl_ndhwc_kzyxc_ndhwk_f16_instances(op_ptrs);
}
else if constexpr(is_same_v<InDataType, ck::bhalf_t> &&
is_same_v<WeiDataType, ck::bhalf_t> &&
is_same_v<OutDataType, ck::bhalf_t>)
{
add_device_conv3d_bwd_data_xdl_ndhwc_kzyxc_ndhwk_bf16_instances(op_ptrs);
}
else if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> &&
is_same_v<OutDataType, int8_t>)
{
add_device_conv3d_bwd_data_xdl_ndhwc_kzyxc_ndhwk_int8_instances(op_ptrs);
}
}
return op_ptrs;
}
};
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/CMakeLists.txt
View file @ 8f722700
......@@ -19,13 +19,14 @@ add_subdirectory(contraction_bilinear)
add_subdirectory(conv1d_fwd)
add_subdirectory(conv2d_fwd)
add_subdirectory(conv3d_fwd)
add_subdirectory(conv2d_fwd_bias_relu)
add_subdirectory(conv2d_fwd_bias_relu_add)
add_subdirectory(conv1d_bwd_data)
add_subdirectory(conv2d_bwd_data)
add_subdirectory(convnd_bwd_data)
add_subdirectory(conv3d_bwd_data)
add_subdirectory(conv1d_bwd_weight)
add_subdirectory(conv2d_bwd_weight)
add_subdirectory(conv3d_bwd_weight)
add_subdirectory(conv2d_fwd_bias_relu)
add_subdirectory(conv2d_fwd_bias_relu_add)
add_subdirectory(reduce)
add_subdirectory(normalization)
add_subdirectory(elementwise)
......@@ -44,13 +45,14 @@ add_library(device_operations STATIC
$<TARGET_OBJECTS:device_conv1d_fwd_instance>
$<TARGET_OBJECTS:device_conv2d_fwd_instance>
$<TARGET_OBJECTS:device_conv3d_fwd_instance>
$<TARGET_OBJECTS:device_conv2d_fwd_bias_relu_instance>
$<TARGET_OBJECTS:device_conv2d_fwd_bias_relu_add_instance>
$<TARGET_OBJECTS:device_conv1d_bwd_data_instance>
$<TARGET_OBJECTS:device_conv2d_bwd_data_instance>
$<TARGET_OBJECTS:device_convnd_bwd_data_instance>
$<TARGET_OBJECTS:device_conv3d_bwd_data_instance>
$<TARGET_OBJECTS:device_conv1d_bwd_weight_instance>
$<TARGET_OBJECTS:device_conv2d_bwd_weight_instance>
$<TARGET_OBJECTS:device_conv3d_bwd_weight_instance>
$<TARGET_OBJECTS:device_conv2d_fwd_bias_relu_instance>
$<TARGET_OBJECTS:device_conv2d_fwd_bias_relu_add_instance>
$<TARGET_OBJECTS:device_reduce_instance>
$<TARGET_OBJECTS:device_normalization_instance>
$<TARGET_OBJECTS:device_elementwise_instance>
......
library/src/tensor_operation_instance/gpu/conv1d_bwd_data/CMakeLists.txt 0 → 100644
View file @ 8f722700
# device_conv1d_bwd_data_instance
set(DEVICE_CONV1D_BWD_DATA_INSTANCE_SOURCE
device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f16_instance.cpp;
device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f32_instance.cpp;
device_conv1d_bwd_data_xdl_nwc_kxc_nwk_bf16_instance.cpp;
device_conv1d_bwd_data_xdl_nwc_kxc_nwk_int8_instance.cpp;
)
add_library(device_conv1d_bwd_data_instance OBJECT ${DEVICE_CONV1D_BWD_DATA_INSTANCE_SOURCE})
target_compile_features(device_conv1d_bwd_data_instance PUBLIC)
set_target_properties(device_conv1d_bwd_data_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
rocm_install(TARGETS device_conv1d_bwd_data_instance)
clang_tidy_check(device_conv1d_bwd_data_instance)
library/src/tensor_operation_instance/gpu/conv1d_bwd_data/device_conv1d_bwd_data_xdl_nwc_kxc_nwk_bf16_instance.cpp 0 → 100644
View file @ 8f722700
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_convnd_bwd_data_nwc_kxc_nwk_xdl.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using BF16 = bhalf_t;
using F32 = float;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using NWC = ck::tensor_layout::convolution::NWC;
using KXC = ck::tensor_layout::convolution::KXC;
using NWK = ck::tensor_layout::convolution::NWK;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto ConvBwdDataDefault =
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization::Default;
static constexpr auto ConvBwdDataFilter1x1Stride1Pad0 =
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization::Filter1x1Stride1Pad0;
// Compilation parameters for in[n, wi, c] * wei[k, x, c] = out[n, wo, k]
using device_conv1d_bwd_data_xdl_nwc_kxc_nwk_bf16_instances = std::tuple<
// clang-format off
//##############################| Num| InData| WeiData| OutData| AccData| 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| CThreadTransfer| CThreadTransfer|
//##############################| Dim| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
//##############################| Spatial| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
//##############################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>
// clang-format on
>;
using device_conv1d_bwd_data_xdl_nwc_kxc_nwk_1x1_s1_p0_bf16_instances = std::tuple<
// clang-format off
//##############################| Num| InData| WeiData| OutData| AccData| 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| CThreadTransfer| CThreadTransfer|
//##############################| Dim| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
//##############################| Spatial| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
//##############################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>
// clang-format on
>;
void add_device_conv1d_bwd_data_xdl_nwc_kxc_nwk_bf16_instances(
std::vector<std::unique_ptr<DeviceConvBwdData<1,
NWC,
KXC,
NWK,
BF16,
BF16,
BF16,
PassThrough,
PassThrough,
PassThrough>>>& instances)
{
add_device_operation_instances(instances,
device_conv1d_bwd_data_xdl_nwc_kxc_nwk_bf16_instances{});
add_device_operation_instances(
instances, device_conv1d_bwd_data_xdl_nwc_kxc_nwk_1x1_s1_p0_bf16_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/conv1d_bwd_data/device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f16_instance.cpp 0 → 100644
View file @ 8f722700
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_convnd_bwd_data_nwc_kxc_nwk_xdl.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using F16 = ck::half_t;
using F32 = float;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using NWC = ck::tensor_layout::convolution::NWC;
using KXC = ck::tensor_layout::convolution::KXC;
using NWK = ck::tensor_layout::convolution::NWK;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto ConvBwdDataDefault =
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization::Default;
static constexpr auto ConvBwdDataFilter1x1Stride1Pad0 =
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization::Filter1x1Stride1Pad0;
// Compilation parameters for in[n, wi, c] * wei[k, x, c] = out[n, wo, k]
using device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f16_instances = std::tuple<
// clang-format off
//##############################| Num| InData| WeiData| OutData| AccData| 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| CThreadTransfer| CThreadTransfer|
//##############################| Dim| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
//##############################| Spatial| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
//##############################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>
// clang-format on
>;
using device_conv1d_bwd_data_xdl_nwc_kxc_nwk_1x1_s1_p0_f16_instances = std::tuple<
// clang-format off
//##############################| Num| InData| WeiData| OutData| AccData| 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| CThreadTransfer| CThreadTransfer|
//##############################| Dim| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
//##############################| Spatial| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
//##############################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>
// clang-format on
>;
void add_device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f16_instances(
std::vector<std::unique_ptr<
DeviceConvBwdData<1, NWC, KXC, NWK, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
instances)
{
add_device_operation_instances(instances,
device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f16_instances{});
add_device_operation_instances(
instances, device_conv1d_bwd_data_xdl_nwc_kxc_nwk_1x1_s1_p0_f16_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/conv1d_bwd_data/device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f32_instance.cpp 0 → 100644
View file @ 8f722700
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_convnd_bwd_data_nwc_kxc_nwk_xdl.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using F32 = float;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using NWC = ck::tensor_layout::convolution::NWC;
using KXC = ck::tensor_layout::convolution::KXC;
using NWK = ck::tensor_layout::convolution::NWK;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto ConvBwdDataDefault =
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization::Default;
static constexpr auto ConvBwdDataFilter1x1Stride1Pad0 =
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization::Filter1x1Stride1Pad0;
// Compilation parameters for in[n, wi, c] * wei[k, x, c] = out[n, wo, k]
using device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f32_instances = std::tuple<
// clang-format off
//##############################| Num| InData| WeiData| OutData| AccData| 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| CThreadTransfer| CThreadTransfer|
//##############################| Dim| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
//##############################| Spatial| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
//##############################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 256, 128, 4, 4, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 256, 4, 4, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 128, 4, 4, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 128, 4, 4, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 64, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 64, 128, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 64, 4, 4, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 64, 4, 4, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 64, 128, 4, 4, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 32, 4, 4, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 32, 128, 4, 4, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 32, 4, 4, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 32, 64, 4, 4, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>
// clang-format on
>;
using device_conv1d_bwd_data_xdl_nwc_kxc_nwk_1x1_s1_p0_f32_instances = std::tuple<
// clang-format off
//##############################| Num| InData| WeiData| OutData| AccData| 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| CThreadTransfer| CThreadTransfer|
//##############################| Dim| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
//##############################| Spatial| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
//##############################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 256, 128, 4, 4, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 256, 4, 4, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 128, 4, 4, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 128, 4, 4, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 64, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 64, 128, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 64, 4, 4, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 64, 4, 4, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 64, 128, 4, 4, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 32, 4, 4, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 32, 128, 4, 4, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 32, 4, 4, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 32, 64, 4, 4, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>
// clang-format on
>;
void add_device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f32_instances(
std::vector<std::unique_ptr<
DeviceConvBwdData<1, NWC, KXC, NWK, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
instances)
{
add_device_operation_instances(instances,
device_conv1d_bwd_data_xdl_nwc_kxc_nwk_f32_instances{});
add_device_operation_instances(
instances, device_conv1d_bwd_data_xdl_nwc_kxc_nwk_1x1_s1_p0_f32_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/conv1d_bwd_data/device_conv1d_bwd_data_xdl_nwc_kxc_nwk_int8_instance.cpp 0 → 100644
View file @ 8f722700
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_convnd_bwd_data_nwc_kxc_nwk_xdl.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using NWC = ck::tensor_layout::convolution::NWC;
using KXC = ck::tensor_layout::convolution::KXC;
using NWK = ck::tensor_layout::convolution::NWK;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto ConvBwdDataDefault =
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization::Default;
static constexpr auto ConvBwdDataFilter1x1Stride1Pad0 =
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization::Filter1x1Stride1Pad0;
// Compilation parameters for in[n, wi, c] * wei[k, x, c] = out[n, wo, k]
using device_conv1d_bwd_data_xdl_nwc_kxc_nwk_int8_instances = std::tuple<
// clang-format off
//##############################| Num| InData| WeiData| OutData| AccData| 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| CThreadTransfer| CThreadTransfer|
//##############################| Dim| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
//##############################| Spatial| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
//##############################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 256, 4, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 128, 4, 16, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 256, 128, 4, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 128, 4, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 64, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 64, 128, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 64, 4, 16, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 64, 4, 16, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 64, 128, 4, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 32, 4, 16, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 32, 128, 4, 16, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 32, 4, 16, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 32, 64, 4, 16, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>
// clang-format on
>;
using device_conv1d_bwd_data_xdl_nwc_kxc_nwk_1x1_s1_p0_int8_instances = std::tuple<
// clang-format off
//##############################| Num| InData| WeiData| OutData| AccData| 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| CThreadTransfer| CThreadTransfer|
//##############################| Dim| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
//##############################| Spatial| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
//##############################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 256, 128, 4, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 256, 4, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 128, 4, 16, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 128, 4, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 64, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 64, 128, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 64, 4, 16, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 64, 4, 16, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 64, 128, 4, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 32, 4, 16, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 32, 128, 4, 16, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 32, 4, 16, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
DeviceConvNdBwdDataNwcKxcNwk_Xdl< 1, int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 32, 64, 4, 16, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>
// clang-format on
>;
void add_device_conv1d_bwd_data_xdl_nwc_kxc_nwk_int8_instances(
std::vector<std::unique_ptr<DeviceConvBwdData<1,
NWC,
KXC,
NWK,
int8_t,
int8_t,
int8_t,
PassThrough,
PassThrough,
PassThrough>>>& instances)
{
add_device_operation_instances(instances,
device_conv1d_bwd_data_xdl_nwc_kxc_nwk_int8_instances{});
add_device_operation_instances(
instances, device_conv1d_bwd_data_xdl_nwc_kxc_nwk_1x1_s1_p0_int8_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
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