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add conv1d/3d bwd weight instances (#318)

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* add conv1d/3d bwd weight instances

* add profiler code

[ROCm/composable_kernel commit: 763ca61581]
This commit is contained in:
Shaojie WANG
2022-07-09 04:42:20 +08:00
committed by GitHub
parent 7a98e9fa34
commit 4513fb2e77
19 changed files with 1907 additions and 30 deletions
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1
test/CMakeLists.txt
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@@ -44,6 +44,7 @@ add_subdirectory(grouped_gemm)
add_subdirectory(convnd_fwd)
add_subdirectory(reduce)
add_subdirectory(conv2d_bwd_weight)
add_subdirectory(convnd_bwd_weight)
add_subdirectory(convnd_bwd_data)
add_subdirectory(block_to_ctile_map)
add_subdirectory(softmax)

2
test/convnd_bwd_weight/CMakeLists.txt Normal file
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@@ -0,0 +1,2 @@
add_test_executable(test_convnd_bwd_weight convnd_bwd_weight.cpp)
target_link_libraries(test_convnd_bwd_weight PRIVATE host_tensor device_convnd_bwd_weight_instance conv_util)

283
test/convnd_bwd_weight/convnd_bwd_weight.cpp Normal file
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@@ -0,0 +1,283 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <iostream>
#include <numeric>
#include <initializer_list>
#include <cstdlib>
#include <vector>
#include "test/convnd_fwd/conv_util.hpp"
#include "profiler/include/profile_convnd_bwd_weight_impl.hpp"
int test_self()
{
bool pass = true;
std::vector<ck::utils::conv::ConvParams> params;
params.push_back({1, 128, 256, 256, {1}, {7}, {2}, {1}, {0}, {0}});
params.push_back({1, 128, 256, 256, {3}, {14}, {1}, {1}, {1}, {1}});
params.push_back({1, 128, 256, 256, {1}, {3}, {1}, {1}, {0}, {0}});
for(auto& param : params)
{
// f32
pass &= ck::profiler::profile_convnd_bwd_weight_impl<1,
float,
float,
float,
ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK>(
true, // do_verification
1, // init_method
false, // do_log
true, // time_kernel
param.N_,
param.K_,
param.C_,
param.input_spatial_lengths_,
param.filter_spatial_lengths_,
param.GetOutputSpatialLengths(),
param.conv_filter_strides_,
param.conv_filter_dilations_,
param.input_left_pads_,
param.input_right_pads_,
2);
// fp16
pass &= ck::profiler::profile_convnd_bwd_weight_impl<1,
ck::half_t,
ck::half_t,
ck::half_t,
ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK>(
true, // do_verification
1, // init_method
false, // do_log
true, // time_kernel
param.N_,
param.K_,
param.C_,
param.input_spatial_lengths_,
param.filter_spatial_lengths_,
param.GetOutputSpatialLengths(),
param.conv_filter_strides_,
param.conv_filter_dilations_,
param.input_left_pads_,
param.input_right_pads_,
2);
// bf16
pass &= ck::profiler::profile_convnd_bwd_weight_impl<1,
ck::bhalf_t,
ck::bhalf_t,
ck::bhalf_t,
ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK>(
true, // do_verification
1, // init_method
false, // do_log
true, // time_kernel
param.N_,
param.K_,
param.C_,
param.input_spatial_lengths_,
param.filter_spatial_lengths_,
param.GetOutputSpatialLengths(),
param.conv_filter_strides_,
param.conv_filter_dilations_,
param.input_left_pads_,
param.input_right_pads_,
2);
}
// check 2d
params.clear();
params.push_back({2, 128, 256, 256, {1, 1}, {7, 7}, {2, 2}, {1, 1}, {0, 0}, {0, 0}});
params.push_back({2, 128, 256, 256, {3, 3}, {14, 14}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
params.push_back({2, 128, 256, 256, {1, 1}, {3, 3}, {1, 1}, {1, 1}, {0, 0}, {0, 0}});
for(auto& param : params)
{
// f32
pass &= ck::profiler::profile_convnd_bwd_weight_impl<2,
float,
float,
float,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK>(
true, // do_verification
1, // init_method
false, // do_log
true, // time_kernel
param.N_,
param.K_,
param.C_,
param.input_spatial_lengths_,
param.filter_spatial_lengths_,
param.GetOutputSpatialLengths(),
param.conv_filter_strides_,
param.conv_filter_dilations_,
param.input_left_pads_,
param.input_right_pads_,
2);
// fp16
pass &= ck::profiler::profile_convnd_bwd_weight_impl<2,
ck::half_t,
ck::half_t,
ck::half_t,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK>(
true, // do_verification
1, // init_method
false, // do_log
true, // time_kernel
param.N_,
param.K_,
param.C_,
param.input_spatial_lengths_,
param.filter_spatial_lengths_,
param.GetOutputSpatialLengths(),
param.conv_filter_strides_,
param.conv_filter_dilations_,
param.input_left_pads_,
param.input_right_pads_,
2);
// bf16
pass &= ck::profiler::profile_convnd_bwd_weight_impl<2,
ck::bhalf_t,
ck::bhalf_t,
ck::bhalf_t,
ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK>(
true, // do_verification
1, // init_method
false, // do_log
true, // time_kernel
param.N_,
param.K_,
param.C_,
param.input_spatial_lengths_,
param.filter_spatial_lengths_,
param.GetOutputSpatialLengths(),
param.conv_filter_strides_,
param.conv_filter_dilations_,
param.input_left_pads_,
param.input_right_pads_,
2);
}
// check 2d
params.clear();
params.push_back(
{3, 128, 256, 256, {1, 1, 1}, {4, 4, 4}, {2, 2, 2}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
params.push_back(
{3, 128, 256, 256, {3, 3, 3}, {4, 4, 8}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
params.push_back(
{3, 128, 256, 256, {1, 1, 1}, {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
for(auto& param : params)
{
// f32
pass &= ck::profiler::profile_convnd_bwd_weight_impl<3,
float,
float,
float,
ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC,
ck::tensor_layout::convolution::NDHWK>(
true, // do_verification
1, // init_method
false, // do_log
true, // time_kernel
param.N_,
param.K_,
param.C_,
param.input_spatial_lengths_,
param.filter_spatial_lengths_,
param.GetOutputSpatialLengths(),
param.conv_filter_strides_,
param.conv_filter_dilations_,
param.input_left_pads_,
param.input_right_pads_,
2);
// fp16
pass &= ck::profiler::profile_convnd_bwd_weight_impl<3,
ck::half_t,
ck::half_t,
ck::half_t,
ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC,
ck::tensor_layout::convolution::NDHWK>(
true, // do_verification
1, // init_method
false, // do_log
true, // time_kernel
param.N_,
param.K_,
param.C_,
param.input_spatial_lengths_,
param.filter_spatial_lengths_,
param.GetOutputSpatialLengths(),
param.conv_filter_strides_,
param.conv_filter_dilations_,
param.input_left_pads_,
param.input_right_pads_,
2);
// bf16
pass &= ck::profiler::profile_convnd_bwd_weight_impl<3,
ck::bhalf_t,
ck::bhalf_t,
ck::bhalf_t,
ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC,
ck::tensor_layout::convolution::NDHWK>(
true, // do_verification
1, // init_method
false, // do_log
true, // time_kernel
param.N_,
param.K_,
param.C_,
param.input_spatial_lengths_,
param.filter_spatial_lengths_,
param.GetOutputSpatialLengths(),
param.conv_filter_strides_,
param.conv_filter_dilations_,
param.input_left_pads_,
param.input_right_pads_,
2);
}
return pass;
}
int main()
{
// int data_type = 1;
// int init_method = 1;
bool pass = true;
pass = test_self();
if(pass)
{
std::cout << "test conv2d bwd weight : Pass" << std::endl;
return 0;
}
else
{
std::cout << "test conv2d bwd weight: Fail " << std::endl;
return -1;
}
}