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"src/include/utility.hpp" did not exist on "e43d7bc63c2df138c376412fa5b4aaebc26ca131"
Commit 0be1cf14 authored by Chao Liu's avatar Chao Liu
Browse files

update conv bwd weight

parent b054669b
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Showing with 177 additions and 519 deletions
include/ck/tensor_operation/gpu/device/convolution_backward_weight_specialization.hpp
View file @ 0be1cf14
......@@ -15,6 +15,19 @@ enum struct ConvolutionBackwardWeightSpecialization
OddC,
};
inline std::string
getConvBackwardWeightSpecializationString(const ConvolutionBackwardWeightSpecialization& s)
{
switch(s)
{
case ConvolutionBackwardWeightSpecialization::Default: return "Default";
case ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0:
return "Filter1x1Stride1Pad0";
case ConvolutionBackwardWeightSpecialization::Filter1x1Pad0: return "Filter1x1Pad0";
case ConvolutionBackwardWeightSpecialization::OddC: return "OddC";
default: return "Unrecognized specialization!";
}
}
} // namespace device
} // namespace tensor_operation
} // namespace ck
include/ck/tensor_operation/gpu/device/convolution_forward_specialization.hpp
View file @ 0be1cf14
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#ifndef CONVOLUTION_FORWARD_SPECIALIZATION
#define CONVOLUTION_FORWARD_SPECIALIZATION
#pragma once
#include <string>
......@@ -33,4 +32,3 @@ inline std::string getConvForwardSpecializationString(const ConvolutionForwardSp
} // namespace device
} // namespace tensor_operation
} // namespace ck
#endif
include/ck/tensor_operation/gpu/device/device_conv2d_backward_weight_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp
View file @ 0be1cf14
......@@ -10,7 +10,7 @@
#include "ck/tensor_description/tensor_descriptor.hpp"
#include "ck/tensor_description/tensor_descriptor_helper.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_conv_backward_weight.hpp"
#include "ck/tensor_operation/gpu/device/device_conv_bwd_weight.hpp"
#include "ck/tensor_operation/gpu/device/convolution_backward_weight_specialization.hpp"
#include "ck/tensor_operation/gpu/grid/gridwise_gemm_xdlops_bwd_weight.hpp"
#include "ck/tensor_operation/gpu/grid/gridwise_unary_elementwise_1d.hpp"
......@@ -57,7 +57,14 @@ template <typename InDataType,
typename CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
index_t CBlockTransferScalarPerVector_NWaveNPerXdl>
struct DeviceConv2dBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
: public DeviceConvBwdWeight<InElementwiseOperation,
: public DeviceConvBwdWeight<2,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK,
InDataType,
WeiDataType,
OutDataType,
InElementwiseOperation,
WeiElementwiseOperation,
OutElementwiseOperation>
{
......
include/ck/tensor_operation/gpu/device/device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk.hpp
View file @ 0be1cf14
......@@ -55,7 +55,14 @@ template <typename InDataType,
ck::index_t CThreadTransferSrcDstVectorDim,
ck::index_t CThreadTransferDstScalarPerVector>
struct DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
: public DeviceConvBwdData<InElementwiseOperation,
: public DeviceConvBwdData<2,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK,
InDataType,
WeiDataType,
OutDataType,
InElementwiseOperation,
WeiElementwiseOperation,
OutElementwiseOperation>
{
......
include/ck/tensor_operation/gpu/device/device_conv_bwd_data.hpp
View file @ 0be1cf14
......@@ -4,16 +4,21 @@
#pragma once
#include <vector>
#include <iostream>
#include "ck/tensor_operation/gpu/device/device_base.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
template <typename InElementwiseOperation,
template <ck::index_t NumDimSpatial,
typename InLayout,
typename WeiLayout,
typename OutLayout,
typename InDataType,
typename WeiDataType,
typename OutDataType,
typename InElementwiseOperation,
typename WeiElementwiseOperation,
typename OutElementwiseOperation>
struct DeviceConvBwdData : public BaseOperator
......@@ -39,12 +44,6 @@ struct DeviceConvBwdData : public BaseOperator
virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
};
template <typename InElementwiseOperation,
typename WeiElementwiseOperation,
typename OutElementwiseOperation>
using DeviceConvBwdDataPtr = std::unique_ptr<
DeviceConvBwdData<InElementwiseOperation, WeiElementwiseOperation, OutElementwiseOperation>>;
} // namespace device
} // namespace tensor_operation
} // namespace ck
include/ck/tensor_operation/gpu/device/device_conv_backward_weight.hpp → include/ck/tensor_operation/gpu/device/device_conv_bwd_weight.hpp
View file @ 0be1cf14
......@@ -4,7 +4,6 @@
#pragma once
#include <vector>
#include <iostream>
#include "ck/tensor_operation/gpu/device/device_base.hpp"
......@@ -12,7 +11,14 @@ namespace ck {
namespace tensor_operation {
namespace device {
template <typename InElementwiseOperation,
template <ck::index_t NumDimSpatial,
typename InLayout,
typename WeiLayout,
typename OutLayout,
typename InDataType,
typename WeiDataType,
typename OutDataType,
typename InElementwiseOperation,
typename WeiElementwiseOperation,
typename OutElementwiseOperation>
struct DeviceConvBwdWeight : public BaseOperator
......@@ -39,12 +45,6 @@ struct DeviceConvBwdWeight : public BaseOperator
virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
};
template <typename InElementwiseOperation,
typename WeiElementwiseOperation,
typename OutElementwiseOperation>
using DeviceConvBwdWeightPtr = std::unique_ptr<
DeviceConvBwdWeight<InElementwiseOperation, WeiElementwiseOperation, OutElementwiseOperation>>;
} // namespace device
} // namespace tensor_operation
} // namespace ck
include/ck/tensor_operation/gpu/device/device_conv_fwd.hpp
View file @ 0be1cf14
......@@ -3,7 +3,6 @@
#pragma once
#include <iostream>
#include <vector>
#include "ck/tensor_operation/gpu/device/device_base.hpp"
......@@ -12,7 +11,7 @@ namespace ck {
namespace tensor_operation {
namespace device {
template <ck::index_t NumDimSpatial,
template <ck::index_t NDimSpatial,
typename InLayout,
typename WeiLayout,
typename OutLayout,
......
include/ck/tensor_operation/gpu/device/device_convnd_bwd_data_xdl_ndhwc_kzyxc_ndhwk.hpp → include/ck/tensor_operation/gpu/device/device_convnd_bwd_data_nwc_kxc_nwk_xdl.hpp
View file @ 0be1cf14
......@@ -21,7 +21,8 @@ namespace tensor_operation {
namespace device {
// out[N, Ho, Wo, K] = in[N, Hi, Wi, C] * wei[K, Y, X, C]
template <typename InDataType,
template <ck::index_t NDimSpatial,
typename InDataType,
typename WeiDataType,
typename OutDataType,
typename AccDataType,
......@@ -29,7 +30,6 @@ template <typename InDataType,
typename WeiElementwiseOperation,
typename OutElementwiseOperation,
ConvolutionBackwardDataSpecialization ConvBackwardDataSpecialization,
ck::index_t NumDimSpatial,
ck::index_t BlockSize,
ck::index_t MPerBlock,
ck::index_t NPerBlock,
......@@ -55,12 +55,29 @@ template <typename InDataType,
bool BBlockLdsAddExtraN,
ck::index_t CThreadTransferSrcDstVectorDim,
ck::index_t CThreadTransferDstScalarPerVector>
struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_Wo_K
: public DeviceConvBwdData<InElementwiseOperation,
WeiElementwiseOperation,
OutElementwiseOperation>
struct DeviceConvNdBwdDataNwcKxcNwk_Xdl
: public DeviceConvBwdData<
NDimSpatial,
ck::tuple_element_t<NDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::NDHWC>>,
ck::tuple_element_t<NDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::KZYXC>>,
ck::tuple_element_t<NDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::NWK,
ck::tensor_layout::convolution::NHWK,
ck::tensor_layout::convolution::NDHWK>>,
InDataType,
WeiDataType,
OutDataType,
InElementwiseOperation,
WeiElementwiseOperation,
OutElementwiseOperation>
{
using DeviceOp = DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_Wo_K;
using DeviceOp = DeviceConvNdBwdDataNwcKxcNwk_Xdl;
using ADataType = OutDataType;
using BDataType = WeiDataType;
......@@ -950,7 +967,7 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
{0, 0, 0});
}
using ABCGridDescs = decltype(GetABCGridDesc<NumDimSpatial>());
using ABCGridDescs = decltype(GetABCGridDesc<NDimSpatial>());
using AGridDesc_K0_M_K1 = remove_cvref_t<decltype(ABCGridDescs{}[I0])>;
using BGridDesc_K0_N_K1 = remove_cvref_t<decltype(ABCGridDescs{}[I1])>;
......@@ -1037,7 +1054,7 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
input_left_pads_{input_left_pads},
input_right_pads_{input_right_pads}
{
CreateABCDesc<NumDimSpatial>();
CreateABCDesc<NDimSpatial>();
}
template <ck::index_t NDim, typename ck::enable_if<NDim == 1, bool>::type = false>
......@@ -1060,7 +1077,7 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
}
const auto descs =
DeviceOp::MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N<NumDimSpatial>(
DeviceOp::MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N<NDimSpatial>(
Conv_N_,
Conv_K_,
Conv_C_,
......@@ -1118,7 +1135,7 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
}
const auto descs =
DeviceOp::MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N<NumDimSpatial>(
DeviceOp::MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N<NDimSpatial>(
Conv_N_,
Conv_K_,
Conv_C_,
......@@ -1186,18 +1203,18 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
}
const auto descs =
DeviceOp::MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N<
NumDimSpatial>(Conv_N_,
Conv_K_,
Conv_C_,
input_spatial_lengths_,
filter_spatial_lengths_,
output_spatial_lengths_,
conv_filter_strides_,
conv_filter_dilations_,
input_left_pads_,
input_right_pads_,
{i_ztilde, i_ytilde, i_xtilde});
DeviceOp::MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N<NDimSpatial>(
Conv_N_,
Conv_K_,
Conv_C_,
input_spatial_lengths_,
filter_spatial_lengths_,
output_spatial_lengths_,
conv_filter_strides_,
conv_filter_dilations_,
input_left_pads_,
input_right_pads_,
{i_ztilde, i_ytilde, i_xtilde});
a_grid_desc_k0_m_k1_container_.push_back(descs[I0]);
b_grid_desc_k0_n_k1_container_.push_back(descs[I1]);
c_grid_desc_m_n_container_.push_back(descs[I2]);
......@@ -1398,7 +1415,7 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
ConvolutionBackwardDataSpecialization::Filter1x1Stride1Pad0)
{
// check if it's 1x1, stride=1 pad = 0 conv
for(int i = 0; i < NumDimSpatial; i++)
for(int i = 0; i < NDimSpatial; i++)
{
if(!(arg.filter_spatial_lengths_[i] == 1 && arg.conv_filter_strides_[i] == 1 &&
arg.input_left_pads_[i] == 0 && arg.input_right_pads_[i] == 0))
......@@ -1528,7 +1545,7 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
auto str = std::stringstream();
// clang-format off
str << "DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_Wo_K"
str << "DeviceConvNdBwdDataNwcKxcNwk_Xdl"
<< "<"
<< BlockSize << ", "
<< MPerBlock << ", "
......
include/ck/tensor_operation/gpu/device/device_convnd_fwd_nwc_kxc_nwk_xdl.hpp
View file @ 0be1cf14
......@@ -39,7 +39,7 @@ namespace device {
// 3D:
// out[N, Do, Ho, Wo, K] = in[N, Di, Hi, Wi, C] * wei[K, Z, Y, X, C]
//
template <ck::index_t NumDimSpatial,
template <ck::index_t NDimSpatial,
typename InDataType,
typename WeiDataType,
typename OutDataType,
......@@ -74,16 +74,16 @@ template <ck::index_t NumDimSpatial,
ck::index_t CThreadTransferSrcDstVectorDim,
ck::index_t CThreadTransferDstScalarPerVector>
struct DeviceConvNdFwdNwcKxcNwk_Xdl
: public DeviceConvFwd<NumDimSpatial,
ck::tuple_element_t<NumDimSpatial - 1,
: public DeviceConvFwd<NDimSpatial,
ck::tuple_element_t<NDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::NDHWC>>,
ck::tuple_element_t<NumDimSpatial - 1,
ck::tuple_element_t<NDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::KZYXC>>,
ck::tuple_element_t<NumDimSpatial - 1,
ck::tuple_element_t<NDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::NWK,
ck::tensor_layout::convolution::NHWK,
ck::tensor_layout::convolution::NDHWK>>,
......@@ -94,27 +94,6 @@ struct DeviceConvNdFwdNwcKxcNwk_Xdl
WeiElementwiseOperation,
OutElementwiseOperation>
{
using Base =
DeviceConvFwd<NumDimSpatial,
ck::tuple_element_t<NumDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::NDHWC>>,
ck::tuple_element_t<NumDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::KZYXC>>,
ck::tuple_element_t<NumDimSpatial - 1,
ck::Tuple<ck::tensor_layout::convolution::NWK,
ck::tensor_layout::convolution::NHWK,
ck::tensor_layout::convolution::NDHWK>>,
InDataType,
WeiDataType,
OutDataType,
InElementwiseOperation,
WeiElementwiseOperation,
OutElementwiseOperation>;
using DeviceOp = DeviceConvNdFwdNwcKxcNwk_Xdl;
using ADataType = InDataType;
......@@ -124,8 +103,6 @@ struct DeviceConvNdFwdNwcKxcNwk_Xdl
// TODO make A/B datatype different
using ABDataType = InDataType;
static constexpr index_t NDimSpatial = NumDimSpatial;
static constexpr auto I0 = Number<0>{};
static constexpr auto I1 = Number<1>{};
static constexpr auto I2 = Number<2>{};
......@@ -599,18 +576,18 @@ struct DeviceConvNdFwdNwcKxcNwk_Xdl
// C = A^T*B
// A:
const auto in_gemmk0_gemmm_gemmk1_grid_desc =
GetInputTensorDescriptor<NumDimSpatial>(N,
C,
GemmMRaw,
GemmK,
GemmMPad,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
input_right_pads);
GetInputTensorDescriptor<NDimSpatial>(N,
C,
GemmMRaw,
GemmK,
GemmMPad,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
input_right_pads);
// B:
const auto wei_gemmk0_gemmn_gemmk1_grid_desc = GetWeightTensorDescriptor(GemmN, GemmK);
// C:
......@@ -642,7 +619,7 @@ struct DeviceConvNdFwdNwcKxcNwk_Xdl
1, 1, 1, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1});
}
using ABCGridDescs = decltype(GetABCGridDesc<NumDimSpatial>());
using ABCGridDescs = decltype(GetABCGridDesc<NDimSpatial>());
using AGridDesc_K0_M_K1 = remove_cvref_t<decltype(ABCGridDescs{}[I0])>;
using BGridDesc_K0_N_K1 = remove_cvref_t<decltype(ABCGridDescs{}[I1])>;
......@@ -934,7 +911,7 @@ struct DeviceConvNdFwdNwcKxcNwk_Xdl
ConvolutionForwardSpecialization::Filter1x1Stride1Pad0)
{
// check if it's 1x1, stride=1 conv
for(ck::index_t i = 0; i < NumDimSpatial; ++i)
for(ck::index_t i = 0; i < NDimSpatial; ++i)
{
if(!(arg.filter_spatial_lengths_[i] == 1 && arg.conv_filter_strides_[i] == 1 &&
arg.input_left_pads_[i] == 0 && arg.input_right_pads_[i] == 0))
......@@ -947,7 +924,7 @@ struct DeviceConvNdFwdNwcKxcNwk_Xdl
ConvolutionForwardSpecialization::Filter1x1Pad0)
{
// check if it's 1x1 conv
for(ck::index_t i = 0; i < NumDimSpatial; ++i)
for(ck::index_t i = 0; i < NDimSpatial; ++i)
{
if(!(arg.filter_spatial_lengths_[i] == 1 && arg.input_left_pads_[i] == 0 &&
arg.input_right_pads_[i] == 0))
......
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