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Commit 7d658bbe authored by Jakub Piasecki's avatar Jakub Piasecki
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Merge remote-tracking branch 'origin/develop' into jakpiase/ck_tile_comp_gemm_uts

parents 86442822 261f1759
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Dockerfile
View file @ 7d658bbe
FROM ubuntu:20.04
ARG DEBIAN_FRONTEND=noninteractive
ARG ROCMVERSION=6.2
ARG ROCMVERSION=6.3
ARG compiler_version=""
ARG compiler_commit=""
ARG CK_SCCACHE=""
......@@ -13,17 +13,12 @@ RUN set -xe && \
apt-get update && apt-get install -y --allow-unauthenticated apt-utils wget gnupg2 curl && \
curl -fsSL https://repo.radeon.com/rocm/rocm.gpg.key | gpg --dearmor -o /etc/apt/trusted.gpg.d/rocm-keyring.gpg
RUN if [ "$ROCMVERSION" != "6.3" ]; then \
sh -c "wget https://repo.radeon.com/amdgpu-install/$ROCMVERSION/ubuntu/focal/amdgpu-install_6.2.60200-1_all.deb --no-check-certificate" && \
apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ./amdgpu-install_6.2.60200-1_all.deb && \
RUN if [ "$ROCMVERSION" != "6.4" ]; then \
sh -c "wget https://repo.radeon.com/amdgpu-install/$ROCMVERSION/ubuntu/focal/amdgpu-install_6.3.60300-1_all.deb --no-check-certificate" && \
apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ./amdgpu-install_6.3.60300-1_all.deb && \
wget -qO - http://repo.radeon.com/rocm/rocm.gpg.key | apt-key add - && \
sh -c "echo deb [arch=amd64 signed-by=/etc/apt/trusted.gpg.d/rocm-keyring.gpg] $DEB_ROCM_REPO focal main > /etc/apt/sources.list.d/rocm.list" && \
sh -c 'echo deb [arch=amd64 signed-by=/etc/apt/trusted.gpg.d/rocm-keyring.gpg] https://repo.radeon.com/amdgpu/$ROCMVERSION/ubuntu focal main > /etc/apt/sources.list.d/amdgpu.list'; \
elif [ "$ROCMVERSION" = "6.3" ] && [ "$compiler_version" = "rc1" ]; then \
sh -c "wget http://artifactory-cdn.amd.com/artifactory/list/amdgpu-deb/amdgpu-install-internal_6.3-20.04-1_all.deb --no-check-certificate" && \
apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install dialog libpopt0 rsync && DEBIAN_FRONTEND=noninteractive apt-get install ./amdgpu-install-internal_6.3-20.04-1_all.deb && \
sh -c 'echo deb [arch=amd64 trusted=yes] http://compute-artifactory.amd.com/artifactory/list/rocm-release-archive-20.04-deb/ 6.3 rel-20 > /etc/apt/sources.list.d/rocm-build.list' && \
amdgpu-repo --amdgpu-build=2074281; \
fi
RUN sh -c "echo deb http://mirrors.kernel.org/ubuntu focal main universe | tee -a /etc/apt/sources.list" && \
......
Dockerfile.compiler
View file @ 7d658bbe
ARG BASE_DOCKER="rocm/composable_kernel:ck_ub20.04_rocm6.2"
ARG BASE_DOCKER="rocm/composable_kernel:ck_ub20.04_rocm6.3"
FROM $BASE_DOCKER
ARG compiler_version=""
ARG compiler_commit=""
......
Jenkinsfile
View file @ 7d658bbe
......@@ -38,13 +38,14 @@ def getBaseDockerImageName(){
img = "${params.USE_CUSTOM_DOCKER}"
}
else{
if (params.ROCMVERSION != "6.3"){
img = "${env.CK_DOCKERHUB}:ck_ub20.04_rocm${params.ROCMVERSION}"
}
else{
img = "${env.CK_DOCKERHUB_PRIVATE}:ck_ub20.04_rocm${params.ROCMVERSION}"
def ROCM_numeric = "${params.ROCMVERSION}" as float
if ( ROCM_numeric < 6.4 ){
img = "${env.CK_DOCKERHUB}:ck_ub20.04_rocm${params.ROCMVERSION}"
}
else{
img = "${env.CK_DOCKERHUB_PRIVATE}:ck_ub20.04_rocm${params.ROCMVERSION}"
}
}
}
return img
}
......@@ -739,8 +740,8 @@ def process_results(Map conf=[:]){
}
//launch develop branch daily at 23:00 UT in FULL_QA mode and at 19:00 UT with latest staging compiler version
CRON_SETTINGS = BRANCH_NAME == "develop" ? '''0 23 * * * % RUN_FULL_QA=true;ROCMVERSION=6.2;RUN_CK_TILE_FMHA_TESTS=true;RUN_CK_TILE_GEMM_TESTS=true
0 21 * * * % ROCMVERSION=6.2;hipTensor_test=true;RUN_CODEGEN_TESTS=true
CRON_SETTINGS = BRANCH_NAME == "develop" ? '''0 23 * * * % RUN_FULL_QA=true;ROCMVERSION=6.3;RUN_CK_TILE_FMHA_TESTS=true;RUN_CK_TILE_GEMM_TESTS=true
0 21 * * * % ROCMVERSION=6.3;hipTensor_test=true;RUN_CODEGEN_TESTS=true
0 19 * * * % BUILD_DOCKER=true;DL_KERNELS=true;COMPILER_VERSION=amd-staging;BUILD_COMPILER=/llvm-project/build/bin/clang++;BUILD_GFX12=true;USE_SCCACHE=false;NINJA_BUILD_TRACE=true
0 17 * * * % BUILD_DOCKER=true;DL_KERNELS=true;COMPILER_VERSION=amd-mainline;BUILD_COMPILER=/llvm-project/build/bin/clang++;BUILD_GFX12=true;USE_SCCACHE=false;NINJA_BUILD_TRACE=true
0 15 * * * % BUILD_INSTANCES_ONLY=true;RUN_PERFORMANCE_TESTS=false;USE_SCCACHE=false
......@@ -765,8 +766,8 @@ pipeline {
description: 'If you want to use a custom docker image, please specify it here (default: leave blank).')
string(
name: 'ROCMVERSION',
defaultValue: '6.2',
description: 'Specify which ROCM version to use: 6.2 (default).')
defaultValue: '6.3',
description: 'Specify which ROCM version to use: 6.3 (default).')
string(
name: 'COMPILER_VERSION',
defaultValue: '',
......
example/62_convnd_activ/convscale/convnd_fwd_convscale_common.hpp
View file @ 7d658bbe
......@@ -172,12 +172,13 @@ bool run_grouped_conv_fwd(bool do_verification,
{
case 0: break;
case 1:
in.GenerateTensorValue(GeneratorTensor_2<InDataType>{-5, 5});
wei.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-5, 5});
// values generated: -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5
in.GenerateTensorValue(GeneratorTensor_2<InDataType>{-5, 6});
wei.GenerateTensorValue(GeneratorTensor_3<WeiDataType>{-1.0, 1.0});
break;
default:
in.GenerateTensorValue(GeneratorTensor_3<InDataType>{0.0, 1.0});
wei.GenerateTensorValue(GeneratorTensor_3<WeiDataType>{-0.5, 0.5});
in.GenerateTensorValue(GeneratorTensor_3<InDataType>{-5.0, 5.0});
wei.GenerateTensorValue(GeneratorTensor_3<WeiDataType>{-1.0, 1.0});
}
DeviceMem in_device_buf(sizeof(InDataType) * in.mDesc.GetElementSpaceSize());
......
include/ck/tensor_operation/gpu/device/impl/device_grouped_conv_bwd_data_multiple_d_wmma_cshuffle.hpp
View file @ 7d658bbe
// SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -106,89 +106,35 @@ struct DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle
static constexpr auto I3 = Number<3>{};
static constexpr index_t KPerBlock = K0PerBlock * K1;
static constexpr auto transform_conv_to_gemm =
TransformConvBwdDataToGemm_v1<NDimSpatial,
ConvBackwardDataSpecialization,
K1,
K1,
MPerBlock,
NPerBlock,
KPerBlock,
true /* DoPadGemmM */,
true /* DoPadGemmN */>{};
static auto GetDummyABDsEGridDescriptor()
{
const std::array<index_t, NDimSpatial + 3> dummy_tensor_lengths = {1};
const std::array<index_t, NDimSpatial + 3> dummy_tensor_strides = {1};
const std::array<index_t, NDimSpatial> dummy_spatial_lengths = {1};
const auto a_grid_desc_ak0_m_ak1 =
transform_conv_to_gemm.template MakeADescriptor_AK0_M_AK1<ALayout>(
dummy_tensor_lengths,
dummy_tensor_strides,
dummy_tensor_lengths,
dummy_tensor_strides,
dummy_tensor_lengths,
dummy_tensor_strides,
dummy_spatial_lengths,
dummy_spatial_lengths,
dummy_spatial_lengths,
dummy_spatial_lengths,
dummy_spatial_lengths);
const auto b_grid_desc_bk0_n_bk1 =
transform_conv_to_gemm.template MakeBDescriptor_BK0_N_BK1<BLayout>(
dummy_tensor_lengths,
dummy_tensor_strides,
dummy_tensor_lengths,
dummy_tensor_strides,
dummy_tensor_lengths,
dummy_tensor_strides,
dummy_spatial_lengths,
dummy_spatial_lengths,
dummy_spatial_lengths,
dummy_spatial_lengths,
dummy_spatial_lengths);
const auto ds_grid_desc_m_n = generate_tuple(
[&](auto i) {
using DLayout = remove_cvref_t<tuple_element_t<i.value, DsLayout>>;
return transform_conv_to_gemm.template MakeCDescriptor_M_N<DLayout>(
dummy_tensor_lengths,
dummy_tensor_strides,
dummy_tensor_lengths,
dummy_tensor_strides,
dummy_tensor_lengths,
dummy_tensor_strides,
dummy_spatial_lengths,
dummy_spatial_lengths,
dummy_spatial_lengths,
dummy_spatial_lengths,
dummy_spatial_lengths);
},
Number<NumDTensor>{});
const auto e_grid_desc_m_n =
transform_conv_to_gemm.template MakeCDescriptor_M_N<ELayout>(dummy_tensor_lengths,
dummy_tensor_strides,
dummy_tensor_lengths,
dummy_tensor_strides,
dummy_tensor_lengths,
dummy_tensor_strides,
dummy_spatial_lengths,
dummy_spatial_lengths,
dummy_spatial_lengths,
dummy_spatial_lengths,
dummy_spatial_lengths);
using ConvToGemmBwdDataTransform = TransformConvBwdDataToGemm_v1<NDimSpatial,
ConvBackwardDataSpecialization,
K1,
K1,
MPerBlock,
NPerBlock,
KPerBlock,
true /* DoPadGemmM */,
true /* DoPadGemmN */,
ALayout,
BLayout,
ELayout>;
static auto
GetDummyABDsEGridDescriptor(const ConvToGemmBwdDataTransform& conv_to_gemm_transform)
{
const auto a_grid_desc_ak0_m_ak1 = conv_to_gemm_transform.MakeADescriptor_AK0_M_AK1();
const auto b_grid_desc_bk0_n_bk1 = conv_to_gemm_transform.MakeBDescriptor_BK0_N_BK1();
const auto ds_grid_desc_m_n =
generate_tuple([&](auto) { return conv_to_gemm_transform.MakeCDescriptor_M_N(); },
Number<NumDTensor>{});
const auto e_grid_desc_m_n = conv_to_gemm_transform.MakeCDescriptor_M_N();
return make_tuple(
a_grid_desc_ak0_m_ak1, b_grid_desc_bk0_n_bk1, ds_grid_desc_m_n, e_grid_desc_m_n);
}
// desc
using ABDsEGridDesc = decltype(GetDummyABDsEGridDescriptor());
constexpr static ConvToGemmBwdDataTransform dummy_conv_to_gemm_transform;
using ABDsEGridDesc = decltype(GetDummyABDsEGridDescriptor(dummy_conv_to_gemm_transform));
using AGridDesc_AK0_M_AK1 = remove_cvref_t<tuple_element_t<0, ABDsEGridDesc>>;
using BGridDesc_BK0_N_BK1 = remove_cvref_t<tuple_element_t<1, ABDsEGridDesc>>;
......@@ -270,7 +216,7 @@ struct DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_lengths,
const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_strides,
const std::array<std::array<index_t, NDimSpatial + 3>, NumDTensor>&
ds_g_n_c_wis_lengths,
/*ds_g_n_c_wis_lengths*/,
const std::array<std::array<index_t, NDimSpatial + 3>, NumDTensor>&
ds_g_n_c_wis_strides,
const std::array<index_t, NDimSpatial + 3>& e_g_n_c_wis_lengths,
......@@ -291,15 +237,8 @@ struct DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle
b_element_op_{b_element_op},
cde_element_op_{cde_element_op},
a_g_n_k_wos_lengths_{a_g_n_k_wos_lengths},
a_g_n_k_wos_strides_{a_g_n_k_wos_strides},
b_g_k_c_xs_lengths_{b_g_k_c_xs_lengths},
b_g_k_c_xs_strides_{b_g_k_c_xs_strides},
ds_g_n_c_wis_lengths_{ds_g_n_c_wis_lengths},
ds_g_n_c_wis_strides_{ds_g_n_c_wis_strides},
e_g_n_c_wis_lengths_{e_g_n_c_wis_lengths},
e_g_n_c_wis_strides_{e_g_n_c_wis_strides},
conv_filter_strides_{conv_filter_strides},
conv_filter_dilations_{conv_filter_dilations},
input_left_pads_{input_left_pads},
input_right_pads_{input_right_pads}
{
......@@ -382,68 +321,47 @@ struct DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle
tildes = {i_ztilde, i_ytilde, i_xtilde};
}
ConvToGemmBwdDataTransform conv_to_gemm_transform_{a_g_n_k_wos_lengths,
a_g_n_k_wos_strides,
b_g_k_c_xs_lengths,
b_g_k_c_xs_strides,
e_g_n_c_wis_lengths,
e_g_n_c_wis_strides,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
input_right_pads,
tildes};
const auto a_grid_desc_ak0_m_ak1 =
transform_conv_to_gemm.template MakeADescriptor_AK0_M_AK1<ALayout>(
a_g_n_k_wos_lengths,
a_g_n_k_wos_strides,
b_g_k_c_xs_lengths,
b_g_k_c_xs_strides,
e_g_n_c_wis_lengths,
e_g_n_c_wis_strides,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
input_right_pads,
tildes);
conv_to_gemm_transform_.MakeADescriptor_AK0_M_AK1();
const auto b_grid_desc_bk0_n_bk1 =
transform_conv_to_gemm.template MakeBDescriptor_BK0_N_BK1<BLayout>(
a_g_n_k_wos_lengths,
a_g_n_k_wos_strides,
b_g_k_c_xs_lengths,
b_g_k_c_xs_strides,
e_g_n_c_wis_lengths,
e_g_n_c_wis_strides,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
input_right_pads,
tildes);
conv_to_gemm_transform_.MakeBDescriptor_BK0_N_BK1();
DsGridDesc_M_N ds_grid_desc_m_n;
// populate Ds desc
static_for<0, NumDTensor, 1>{}([&](auto i) {
using DLayout = remove_cvref_t<tuple_element_t<i.value, DsLayout>>;
ds_grid_desc_m_n(i) =
transform_conv_to_gemm.template MakeCDescriptor_M_N<DLayout>(
a_g_n_k_wos_lengths,
a_g_n_k_wos_strides,
b_g_k_c_xs_lengths,
b_g_k_c_xs_strides,
ds_g_n_c_wis_lengths[i],
ds_g_n_c_wis_strides[i],
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
input_right_pads,
tildes);
});
const auto e_grid_desc_m_n =
transform_conv_to_gemm.template MakeCDescriptor_M_N<ELayout>(
static_assert(is_same_v<DLayout, ELayout>);
ConvToGemmBwdDataTransform conv_to_gemm_transform_d{
a_g_n_k_wos_lengths,
a_g_n_k_wos_strides,
b_g_k_c_xs_lengths,
b_g_k_c_xs_strides,
e_g_n_c_wis_lengths,
e_g_n_c_wis_strides,
ds_g_n_c_wis_strides[i],
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
input_right_pads,
tildes);
tildes};
ds_grid_desc_m_n(i) = conv_to_gemm_transform_d.MakeCDescriptor_M_N();
});
const auto e_grid_desc_m_n = conv_to_gemm_transform_.MakeCDescriptor_M_N();
// for check validity
ds_grid_desc_m_n_container_.push_back(ds_grid_desc_m_n);
......@@ -522,17 +440,9 @@ struct DeviceGroupedConvBwdDataMultipleD_Wmma_CShuffle
BElementwiseOp b_element_op_;
CDEElementwiseOp cde_element_op_;
// for checking IsSupportedArgument()
std::array<index_t, NDimSpatial + 3> a_g_n_k_wos_lengths_;
std::array<index_t, NDimSpatial + 3> a_g_n_k_wos_strides_;
std::array<index_t, NDimSpatial + 3> b_g_k_c_xs_lengths_;
std::array<index_t, NDimSpatial + 3> b_g_k_c_xs_strides_;
std::array<std::array<index_t, NDimSpatial + 3>, NumDTensor> ds_g_n_c_wis_lengths_;
std::array<std::array<index_t, NDimSpatial + 3>, NumDTensor> ds_g_n_c_wis_strides_;
std::array<index_t, NDimSpatial + 3> e_g_n_c_wis_lengths_;
std::array<index_t, NDimSpatial + 3> e_g_n_c_wis_strides_;
std::array<index_t, NDimSpatial> conv_filter_strides_;
std::array<index_t, NDimSpatial> conv_filter_dilations_;
std::array<index_t, NDimSpatial> input_left_pads_;
std::array<index_t, NDimSpatial> input_right_pads_;
};
......
include/ck_tile/ops/fmha/kernel/fmha_fwd_kernel.hpp
View file @ 7d658bbe
......@@ -998,14 +998,14 @@ struct FmhaFwdKernel
return pad_tensor_view(
q_dram_naive,
make_tuple(number<FmhaPipeline::kM0>{}, number<FmhaPipeline::kSubQKHeaddim>{}),
sequence<false, kPadHeadDimQ>{});
sequence<kPadSeqLenQ, kPadHeadDimQ>{});
}
else
{
return pad_tensor_view(
q_dram_naive,
make_tuple(number<FmhaPipeline::kM0>{}, number<FmhaPipeline::kK0>{}),
sequence<false, kPadHeadDimQ>{});
sequence<kPadSeqLenQ, kPadHeadDimQ>{});
}
}();
const auto k_dram = [&]() {
......@@ -1019,7 +1019,7 @@ struct FmhaFwdKernel
return pad_tensor_view(
k_dram_naive,
make_tuple(number<FmhaPipeline::kN0>{}, number<FmhaPipeline::kK0>{}),
sequence<false, kPadHeadDimQ>{});
sequence<kPadSeqLenK, kPadHeadDimQ>{});
}();
const auto v_dram = [&]() {
if constexpr(std::is_same_v<VLayout, ck_tile::tensor_layout::gemm::RowMajor>)
......@@ -1041,7 +1041,7 @@ struct FmhaFwdKernel
return pad_tensor_view(
v_dram_transposed,
make_tuple(number<FmhaPipeline::kN1>{}, number<FmhaPipeline::kK1>{}),
sequence<kPadHeadDimV, false>{});
sequence<kPadHeadDimV, kPadSeqLenK>{});
}
else
{
......@@ -1055,7 +1055,7 @@ struct FmhaFwdKernel
return pad_tensor_view(
v_dram_naive,
make_tuple(number<FmhaPipeline::kN1>{}, number<FmhaPipeline::kK1>{}),
sequence<false, kPadSeqLenK>{});
sequence<kPadHeadDimV, kPadSeqLenK>{});
}
}();
......@@ -1097,8 +1097,9 @@ struct FmhaFwdKernel
number<FmhaPipeline::kAlignmentBias>{},
number<1>{});
return pad_tensor_view(
bias_dram_naive, bias_dram_window_lengths, sequence<false, kPadSeqLenK>{});
return pad_tensor_view(bias_dram_naive,
bias_dram_window_lengths,
sequence<kPadSeqLenQ, kPadSeqLenK>{});
}();
return make_tile_window(bias_dram, bias_dram_window_lengths, {i_m0, 0});
......
test/grouped_convnd_bwd_data/CMakeLists.txt
View file @ 7d658bbe
add_gtest_executable(test_grouped_convnd_bwd_data test_grouped_convnd_bwd_data_xdl_wmma.cpp)
add_gtest_executable(test_grouped_convnd_bwd_data_xdl test_grouped_convnd_bwd_data_xdl.cpp)
if(result EQUAL 0)
target_link_libraries(test_grouped_convnd_bwd_data PRIVATE utility device_grouped_conv2d_bwd_data_instance device_grouped_conv3d_bwd_data_instance)
target_link_libraries(test_grouped_convnd_bwd_data_xdl PRIVATE utility device_grouped_conv2d_bwd_data_instance device_grouped_conv3d_bwd_data_instance)
endif()
add_gtest_executable(test_grouped_convnd_bwd_data_wmma test_grouped_convnd_bwd_data_wmma.cpp)
if(result EQUAL 0)
target_link_libraries(test_grouped_convnd_bwd_data_wmma PRIVATE utility device_grouped_conv2d_bwd_data_instance device_grouped_conv3d_bwd_data_instance)
endif()
add_gtest_executable(test_grouped_convnd_bwd_data_interface_xdl test_grouped_convnd_bwd_data_interface_xdl.cpp)
if(result EQUAL 0)
......
test/grouped_convnd_bwd_data/test_grouped_convnd_bwd_data_wmma.cpp 0 → 100644
View file @ 7d658bbe
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include <iostream>
#include <initializer_list>
#include <tuple>
#include <vector>
#include <gtest/gtest.h>
#include "profiler/profile_grouped_conv_bwd_data_impl.hpp"
template <typename Tuple>
class TestGroupedConvndBwdDataWmma : public ::testing::Test
{
protected:
using DataType = std::tuple_element_t<0, Tuple>;
using OutLayout = std::tuple_element_t<1, Tuple>;
using WeiLayout = std::tuple_element_t<2, Tuple>;
using InLayout = std::tuple_element_t<3, Tuple>;
std::vector<ck::utils::conv::ConvParam> conv_params;
template <ck::index_t NDimSpatial>
void Run()
{
EXPECT_FALSE(conv_params.empty());
bool pass = true;
for(auto& param : conv_params)
{
pass = pass && ck::profiler::profile_grouped_conv_bwd_data_impl<NDimSpatial,
OutLayout,
WeiLayout,
InLayout,
DataType,
DataType,
DataType>(
true, // do_verification
1, // init_method: integer value
false, // do_log
false, // time_kernel
param);
}
EXPECT_TRUE(pass);
}
};
using namespace ck::tensor_layout::convolution;
using KernelTypes2d = ::testing::Types<std::tuple<ck::half_t, GNHWK, GKYXC, GNHWC>,
std::tuple<int8_t, GNHWK, GKYXC, GNHWC>,
std::tuple<ck::half_t, NHWGK, GKYXC, NHWGC>,
std::tuple<int8_t, NHWGK, GKYXC, NHWGC>>;
using KernelTypes3d = ::testing::Types<std::tuple<ck::half_t, GNDHWK, GKZYXC, GNDHWC>,
std::tuple<int8_t, GNDHWK, GKZYXC, GNDHWC>,
std::tuple<ck::half_t, NDHWGK, GKZYXC, NDHWGC>,
std::tuple<int8_t, NDHWGK, GKZYXC, NDHWGC>>;
template <typename Tuple>
class TestGroupedConvndBwdDataWmma2d : public TestGroupedConvndBwdDataWmma<Tuple>
{
};
template <typename Tuple>
class TestGroupedConvndBwdDataWmma3d : public TestGroupedConvndBwdDataWmma<Tuple>
{
};
TYPED_TEST_SUITE(TestGroupedConvndBwdDataWmma2d, KernelTypes2d);
TYPED_TEST_SUITE(TestGroupedConvndBwdDataWmma3d, KernelTypes3d);
TYPED_TEST(TestGroupedConvndBwdDataWmma2d, Test2D)
{
this->conv_params.clear();
this->conv_params.push_back(
{2, 2, 4, 192, 192, {3, 3}, {28, 28}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
this->conv_params.push_back(
{2, 2, 128, 128, 256, {3, 3}, {14, 14}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
this->conv_params.push_back(
{2, 2, 128, 128, 256, {1, 1}, {7, 7}, {2, 2}, {1, 1}, {0, 0}, {0, 0}});
this->conv_params.push_back(
{2, 2, 128, 128, 256, {1, 1}, {3, 3}, {1, 1}, {1, 1}, {0, 0}, {0, 0}});
this->conv_params.push_back({2, 1, 1, 1, 32, {8, 8}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
this->conv_params.push_back({2, 1, 1, 64, 3, {8, 8}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
this->conv_params.push_back({2, 1, 1, 1, 1, {8, 8}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
this->template Run<2>();
}
TYPED_TEST(TestGroupedConvndBwdDataWmma3d, Test3D)
{
this->conv_params.clear();
this->conv_params.push_back(
{3, 2, 16, 128, 256, {1, 1, 1}, {7, 7, 7}, {2, 2, 2}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
this->conv_params.push_back(
{3, 2, 2, 128, 256, {3, 3, 3}, {14, 14, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
this->conv_params.push_back(
{3, 2, 32, 128, 256, {1, 1, 1}, {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
this->conv_params.push_back(
{3, 1, 1, 1, 32, {3, 3, 3}, {32, 32, 32}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
this->conv_params.push_back(
{3, 1, 1, 64, 3, {3, 3, 3}, {32, 32, 32}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
this->conv_params.push_back(
{3, 1, 1, 1, 1, {3, 3, 3}, {32, 32, 32}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
this->template Run<3>();
}
test/grouped_convnd_bwd_data/test_grouped_convnd_bwd_data_xdl_wmma.cpp → test/grouped_convnd_bwd_data/test_grouped_convnd_bwd_data_xdl.cpp
View file @ 7d658bbe
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include <iostream>
......@@ -12,7 +12,7 @@
#include "profiler/profile_grouped_conv_bwd_data_impl.hpp"
template <typename Tuple>
class TestGroupedConvndBwdData : public ::testing::Test
class TestGroupedConvndBwdDataXdl : public ::testing::Test
{
protected:
using DataType = std::tuple_element_t<0, Tuple>;
......@@ -51,35 +51,31 @@ using namespace ck::tensor_layout::convolution;
using KernelTypes2d = ::testing::Types<std::tuple<float, GNHWK, GKYXC, GNHWC>,
std::tuple<ck::half_t, GNHWK, GKYXC, GNHWC>,
std::tuple<ck::bhalf_t, GNHWK, GKYXC, GNHWC>,
std::tuple<int8_t, GNHWK, GKYXC, GNHWC>,
std::tuple<float, NHWGK, GKYXC, NHWGC>,
std::tuple<ck::half_t, NHWGK, GKYXC, NHWGC>,
std::tuple<ck::bhalf_t, NHWGK, GKYXC, NHWGC>,
std::tuple<int8_t, NHWGK, GKYXC, NHWGC>>;
std::tuple<ck::bhalf_t, NHWGK, GKYXC, NHWGC>>;
using KernelTypes3d = ::testing::Types<std::tuple<float, GNDHWK, GKZYXC, GNDHWC>,
std::tuple<ck::half_t, GNDHWK, GKZYXC, GNDHWC>,
std::tuple<ck::bhalf_t, GNDHWK, GKZYXC, GNDHWC>,
std::tuple<int8_t, GNDHWK, GKZYXC, GNDHWC>,
std::tuple<float, NDHWGK, GKZYXC, NDHWGC>,
std::tuple<ck::half_t, NDHWGK, GKZYXC, NDHWGC>,
std::tuple<ck::bhalf_t, NDHWGK, GKZYXC, NDHWGC>,
std::tuple<int8_t, NDHWGK, GKZYXC, NDHWGC>>;
std::tuple<ck::bhalf_t, NDHWGK, GKZYXC, NDHWGC>>;
template <typename Tuple>
class TestGroupedConvndBwdData2d : public TestGroupedConvndBwdData<Tuple>
class TestGroupedConvndBwdDataXdl2d : public TestGroupedConvndBwdDataXdl<Tuple>
{
};
template <typename Tuple>
class TestGroupedConvndBwdData3d : public TestGroupedConvndBwdData<Tuple>
class TestGroupedConvndBwdDataXdl3d : public TestGroupedConvndBwdDataXdl<Tuple>
{
};
TYPED_TEST_SUITE(TestGroupedConvndBwdData2d, KernelTypes2d);
TYPED_TEST_SUITE(TestGroupedConvndBwdData3d, KernelTypes3d);
TYPED_TEST_SUITE(TestGroupedConvndBwdDataXdl2d, KernelTypes2d);
TYPED_TEST_SUITE(TestGroupedConvndBwdDataXdl3d, KernelTypes3d);
TYPED_TEST(TestGroupedConvndBwdData2d, Test2D)
TYPED_TEST(TestGroupedConvndBwdDataXdl2d, Test2D)
{
this->conv_params.clear();
......@@ -94,10 +90,13 @@ TYPED_TEST(TestGroupedConvndBwdData2d, Test2D)
this->conv_params.push_back({2, 1, 1, 1, 32, {8, 8}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
this->conv_params.push_back({2, 1, 1, 64, 3, {8, 8}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
this->conv_params.push_back({2, 1, 1, 1, 1, {8, 8}, {32, 32}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
// SplitN case
this->conv_params.push_back(
{2, 1, 128, 4, 192, {2, 2}, {224, 224}, {224, 224}, {1, 1}, {0, 0}, {0, 0}});
this->template Run<2>();
}
TYPED_TEST(TestGroupedConvndBwdData3d, Test3D)
TYPED_TEST(TestGroupedConvndBwdDataXdl3d, Test3D)
{
this->conv_params.clear();
this->conv_params.push_back(
......@@ -112,5 +111,17 @@ TYPED_TEST(TestGroupedConvndBwdData3d, Test3D)
{3, 1, 1, 64, 3, {3, 3, 3}, {32, 32, 32}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
this->conv_params.push_back(
{3, 1, 1, 1, 1, {3, 3, 3}, {32, 32, 32}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
// SplitN case
this->conv_params.push_back({3,
1,
128,
4,
192,
{2, 2, 2},
{2, 224, 224},
{1, 224, 224},
{1, 1, 1},
{0, 0, 0},
{0, 0, 0}});
this->template Run<3>();
}
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