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Commit 92a0945d authored by Chao Liu's avatar Chao Liu
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convnd_fwd fp16 example

parent 63914743
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library/include/ck/library/utility/io.hpp 0 → 100644
View file @ 92a0945d
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <cstdlib>
#include <iostream>
#include <vector>
template <typename T>
std::ostream& operator<<(std::ostream& os, const std::vector<T>& v)
{
std::copy(std::begin(v), std::end(v), std::ostream_iterator<T>(os, " "));
return os;
}
library/src/host_tensor/CMakeLists.txt deleted 100644 → 0
View file @ 63914743
## host_tensor
set(HOST_TENSOR_SOURCE
device_memory.cpp
host_tensor.cpp
)
add_library(host_tensor STATIC ${HOST_TENSOR_SOURCE})
add_library(composable_kernel::host_tensor ALIAS host_tensor)
target_compile_features(host_tensor PUBLIC)
set_target_properties(host_tensor PROPERTIES POSITION_INDEPENDENT_CODE ON)
target_include_directories(host_tensor SYSTEM PUBLIC $<BUILD_INTERFACE:${HALF_INCLUDE_DIR}>)
target_include_directories(host_tensor PUBLIC
"$<INSTALL_INTERFACE:${CMAKE_INSTALL_INCLUDEDIR}/ck>"
"$<INSTALL_INTERFACE:${CMAKE_INSTALL_INCLUDEDIR}/ck/utility>"
"$<INSTALL_INTERFACE:${CMAKE_INSTALL_INCLUDEDIR}/ck/library/host_tensor>"
)
rocm_install(
TARGETS host_tensor
EXPORT host_tensorTargets
)
rocm_install(
EXPORT host_tensorTargets
FILE composable_kernelhost_tensorTargets.cmake
NAMESPACE composable_kernel::
DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/composable_kernel
)
clang_tidy_check(host_tensor)
library/src/utility/CMakeLists.txt
View file @ 92a0945d
set(CONV_UTIL_SOURCE
conv_util.cpp
## utility
set(UTILITY_SOURCE
device_memory.cpp
host_tensor.cpp
convolution_parameter.cpp
)
add_library(conv_util SHARED ${CONV_UTIL_SOURCE})
target_link_libraries(conv_util PRIVATE host_tensor)
target_compile_features(conv_util PUBLIC)
set_target_properties(conv_util PROPERTIES POSITION_INDEPENDENT_CODE ON)
target_include_directories(conv_util SYSTEM PUBLIC $<BUILD_INTERFACE:${HALF_INCLUDE_DIR}>)
add_library(utility STATIC ${UTILITY_SOURCE})
add_library(composable_kernel::utility ALIAS utility)
clang_tidy_check(conv_util)
target_compile_features(utility PUBLIC)
set_target_properties(utility PROPERTIES POSITION_INDEPENDENT_CODE ON)
target_include_directories(utility PUBLIC
"$<INSTALL_INTERFACE:${CMAKE_INSTALL_INCLUDEDIR}/ck>"
"$<INSTALL_INTERFACE:${CMAKE_INSTALL_INCLUDEDIR}/ck/library/utility>"
)
rocm_install(
TARGETS utility
EXPORT utilityTargets
)
rocm_install(
EXPORT utilityTargets
FILE composable_kernelutilityTargets.cmake
NAMESPACE composable_kernel::
DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/composable_kernel
)
clang_tidy_check(utility)
library/src/utility/conv_util.cpp deleted 100644 → 0
View file @ 63914743
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/utility/conv_util.hpp"
namespace ck {
namespace utils {
namespace conv {
/**
* @brief Calculate number of FLOPs for Convolution
*
* @param[in] N Batch size.
* @param[in] C Number of input channels.
* @param[in] K Number of output channels.
* @param[in] filter_spatial_lengths Filter spatial dimensions lengths.
* @param[in] output_spatial_lengths Convolution output spatial dimensions
* lengths.
*
* @return The number of flops.
*/
std::size_t get_flops(ck::index_t N,
ck::index_t C,
ck::index_t K,
const std::vector<ck::index_t>& filter_spatial_lengths,
const std::vector<ck::index_t>& output_spatial_lengths)
{
// 2 * N * K * <output spatial lengths product> * C * <filter spatial lengths product>
return static_cast<std::size_t>(2) * N * K *
std::accumulate(std::begin(output_spatial_lengths),
std::end(output_spatial_lengths),
static_cast<std::size_t>(1),
std::multiplies<std::size_t>()) *
C *
std::accumulate(std::begin(filter_spatial_lengths),
std::end(filter_spatial_lengths),
static_cast<std::size_t>(1),
std::multiplies<std::size_t>());
}
ConvParams::ConvParams()
: num_dim_spatial_(2),
N_(128),
K_(256),
C_(192),
filter_spatial_lengths_(2, 3),
input_spatial_lengths_(2, 71),
conv_filter_strides_(2, 2),
conv_filter_dilations_(2, 1),
input_left_pads_(2, 1),
input_right_pads_(2, 1)
{
}
ConvParams::ConvParams(ck::index_t n_dim,
ck::index_t n_batch,
ck::index_t n_out_channels,
ck::index_t n_in_channels,
const std::vector<ck::index_t>& filters_len,
const std::vector<ck::index_t>& input_len,
const std::vector<ck::index_t>& strides,
const std::vector<ck::index_t>& dilations,
const std::vector<ck::index_t>& left_pads,
const std::vector<ck::index_t>& right_pads)
: num_dim_spatial_(n_dim),
N_(n_batch),
K_(n_out_channels),
C_(n_in_channels),
filter_spatial_lengths_(filters_len),
input_spatial_lengths_(input_len),
conv_filter_strides_(strides),
conv_filter_dilations_(dilations),
input_left_pads_(left_pads),
input_right_pads_(right_pads)
{
if(ck::type_convert<ck::index_t>(filter_spatial_lengths_.size()) != num_dim_spatial_ ||
ck::type_convert<ck::index_t>(input_spatial_lengths_.size()) != num_dim_spatial_ ||
ck::type_convert<ck::index_t>(conv_filter_strides_.size()) != num_dim_spatial_ ||
ck::type_convert<ck::index_t>(conv_filter_dilations_.size()) != num_dim_spatial_ ||
ck::type_convert<ck::index_t>(input_left_pads_.size()) != num_dim_spatial_ ||
ck::type_convert<ck::index_t>(input_right_pads_.size()) != num_dim_spatial_)
{
throw(
std::runtime_error("ConvParams::GetOutputSpatialLengths: "
"parameter size is different from number of declared dimensions!"));
}
}
std::vector<ck::index_t> ConvParams::GetOutputSpatialLengths() const
{
if(ck::type_convert<ck::index_t>(filter_spatial_lengths_.size()) != num_dim_spatial_ ||
ck::type_convert<ck::index_t>(input_spatial_lengths_.size()) != num_dim_spatial_ ||
ck::type_convert<ck::index_t>(conv_filter_strides_.size()) != num_dim_spatial_ ||
ck::type_convert<ck::index_t>(conv_filter_dilations_.size()) != num_dim_spatial_ ||
ck::type_convert<ck::index_t>(input_left_pads_.size()) != num_dim_spatial_ ||
ck::type_convert<ck::index_t>(input_right_pads_.size()) != num_dim_spatial_)
{
throw(
std::runtime_error("ConvParams::GetOutputSpatialLengths: "
"parameter size is different from number of declared dimensions!"));
}
std::vector<ck::index_t> out_spatial_len(num_dim_spatial_, 0);
for(ck::index_t i = 0; i < num_dim_spatial_; ++i)
{
// XEff = (X - 1) * conv_dilation_w + 1;
// Wo = (Wi + in_left_pad_w + in_right_pad_w - XEff) / conv_stride_w + 1;
const ck::index_t idx_eff =
(filter_spatial_lengths_[i] - 1) * conv_filter_dilations_[i] + 1;
out_spatial_len[i] =
(input_spatial_lengths_[i] + input_left_pads_[i] + input_right_pads_[i] - idx_eff) /
conv_filter_strides_[i] +
1;
}
return out_spatial_len;
}
ConvParams parse_conv_params(int num_dim_spatial, int arg_idx, char* const argv[])
{
ck::utils::conv::ConvParams params;
params.num_dim_spatial_ = num_dim_spatial;
params.N_ = std::stoi(argv[arg_idx++]);
params.K_ = std::stoi(argv[arg_idx++]);
params.C_ = std::stoi(argv[arg_idx++]);
params.filter_spatial_lengths_.resize(num_dim_spatial);
for(int i = 0; i < num_dim_spatial; ++i)
{
params.filter_spatial_lengths_[i] = std::stoi(argv[arg_idx++]);
}
params.input_spatial_lengths_.resize(num_dim_spatial);
for(int i = 0; i < num_dim_spatial; ++i)
{
params.input_spatial_lengths_[i] = std::stoi(argv[arg_idx++]);
}
params.conv_filter_strides_.resize(num_dim_spatial);
for(int i = 0; i < num_dim_spatial; ++i)
{
params.conv_filter_strides_[i] = std::stoi(argv[arg_idx++]);
}
params.conv_filter_dilations_.resize(num_dim_spatial);
for(int i = 0; i < num_dim_spatial; ++i)
{
params.conv_filter_dilations_[i] = std::stoi(argv[arg_idx++]);
}
params.input_left_pads_.resize(num_dim_spatial);
for(int i = 0; i < num_dim_spatial; ++i)
{
params.input_left_pads_[i] = std::stoi(argv[arg_idx++]);
}
params.input_right_pads_.resize(num_dim_spatial);
for(int i = 0; i < num_dim_spatial; ++i)
{
params.input_right_pads_[i] = std::stoi(argv[arg_idx++]);
}
return params;
}
HostTensorDescriptor get_output_host_tensor_descriptor(const std::vector<std::size_t>& dims,
int num_dim_spatial)
{
namespace tl = ck::tensor_layout::convolution;
switch(num_dim_spatial)
{
case 3: {
return ck::utils::conv::get_host_tensor_descriptor(dims, tl::NDHWK{});
}
case 2: {
return ck::utils::conv::get_host_tensor_descriptor(dims, tl::NHWK{});
}
case 1: {
return ck::utils::conv::get_host_tensor_descriptor(dims, tl::NWK{});
}
default: {
throw std::runtime_error("Unsupported number of spatial dimensions provided!");
}
}
}
HostTensorDescriptor get_filters_host_tensor_descriptor(const std::vector<std::size_t>& dims,
int num_dim_spatial)
{
namespace tl = ck::tensor_layout::convolution;
switch(num_dim_spatial)
{
case 3: {
return ck::utils::conv::get_host_tensor_descriptor(dims, tl::KZYXC{});
}
case 2: {
return ck::utils::conv::get_host_tensor_descriptor(dims, tl::KYXC{});
}
case 1: {
return ck::utils::conv::get_host_tensor_descriptor(dims, tl::KXC{});
}
default: {
throw std::runtime_error("Unsupported number of spatial dimensions provided!");
}
}
}
HostTensorDescriptor get_input_host_tensor_descriptor(const std::vector<std::size_t>& dims,
int num_dim_spatial)
{
namespace tl = ck::tensor_layout::convolution;
switch(num_dim_spatial)
{
case 3: {
return ck::utils::conv::get_host_tensor_descriptor(dims, tl::NDHWC{});
}
case 2: {
return ck::utils::conv::get_host_tensor_descriptor(dims, tl::NHWC{});
}
case 1: {
return ck::utils::conv::get_host_tensor_descriptor(dims, tl::NWC{});
}
default: {
throw std::runtime_error("Unsupported number of spatial dimensions provided!");
}
}
}
} // namespace conv
} // namespace utils
} // namespace ck
std::ostream& operator<<(std::ostream& os, const ck::utils::conv::ConvParams& p)
{
os << "ConvParams {"
<< "\nnum_dim_spatial: " << p.num_dim_spatial_ << "\nN: " << p.N_ << "\nK: " << p.K_
<< "\nC: " << p.C_ << "\nfilter_spatial_lengths: " << p.filter_spatial_lengths_
<< "\ninput_spatial_lengths: " << p.input_spatial_lengths_
<< "\nconv_filter_strides: " << p.conv_filter_strides_
<< "\nconv_filter_dilations: " << p.conv_filter_dilations_
<< "\ninput_left_pads: " << p.input_left_pads_
<< "\ninput_right_pads: " << p.input_right_pads_;
return os;
}
library/src/utility/convolution_parameter.cpp 0 → 100644
View file @ 92a0945d
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/utility/convolution_parameter.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
ConvParams::ConvParams(ck::index_t n_dim,
ck::index_t n_batch,
ck::index_t n_out_channels,
ck::index_t n_in_channels,
const std::vector<ck::index_t>& filters_len,
const std::vector<ck::index_t>& input_len,
const std::vector<ck::index_t>& strides,
const std::vector<ck::index_t>& dilations,
const std::vector<ck::index_t>& left_pads,
const std::vector<ck::index_t>& right_pads)
: num_dim_spatial_(n_dim),
N_(n_batch),
K_(n_out_channels),
C_(n_in_channels),
filter_spatial_lengths_(filters_len),
input_spatial_lengths_(input_len),
output_spatial_lengths_(num_dim_spatial_),
conv_filter_strides_(strides),
conv_filter_dilations_(dilations),
input_left_pads_(left_pads),
input_right_pads_(right_pads)
{
if(static_cast<ck::index_t>(filter_spatial_lengths_.size()) != num_dim_spatial_ ||
static_cast<ck::index_t>(input_spatial_lengths_.size()) != num_dim_spatial_ ||
static_cast<ck::index_t>(conv_filter_strides_.size()) != num_dim_spatial_ ||
static_cast<ck::index_t>(conv_filter_dilations_.size()) != num_dim_spatial_ ||
static_cast<ck::index_t>(input_left_pads_.size()) != num_dim_spatial_ ||
static_cast<ck::index_t>(input_right_pads_.size()) != num_dim_spatial_)
{
throw(
std::runtime_error("ConvParams::ConvParams: "
"parameter size is different from number of declared dimensions!"));
}
for(ck::index_t i = 0; i < num_dim_spatial_; ++i)
{
// XEff = (X - 1) * conv_dilation_w + 1;
// Wo = (Wi + in_left_pad_w + in_right_pad_w - XEff) / conv_stride_w + 1;
const ck::index_t idx_eff =
(filter_spatial_lengths_[i] - 1) * conv_filter_dilations_[i] + 1;
output_spatial_lengths_[i] =
(input_spatial_lengths_[i] + input_left_pads_[i] + input_right_pads_[i] - idx_eff) /
conv_filter_strides_[i] +
1;
}
}
ConvParams::ConvParams()
: ConvParams::ConvParams(2, 128, 256, 192, {3, 3}, {71, 71}, {2, 2}, {1, 1}, {2, 2}, {2, 2})
{
}
std::vector<ck::index_t> ConvParams::GetOutputSpatialLengths() const
{
return output_spatial_lengths_;
}
std::size_t ConvParams::GetFlops() const
{
// 2 * N * K * C * <output spatial lengths product> * <filter spatial lengths product>
return static_cast<std::size_t>(2) * N_ * K_ * C_ *
std::accumulate(std::begin(output_spatial_lengths_),
std::end(output_spatial_lengths_),
static_cast<std::size_t>(1),
std::multiplies<std::size_t>()) *
std::accumulate(std::begin(filter_spatial_lengths_),
std::end(filter_spatial_lengths_),
static_cast<std::size_t>(1),
std::multiplies<std::size_t>());
}
} // namespace device
} // namespace tensor_operation
} // namespace ck
std::ostream& operator<<(std::ostream& os, const ck::tensor_operation::device::ConvParams& p)
{
os << "ConvParams {"
<< "\nnum_dim_spatial: " << p.num_dim_spatial_ << "\nN: " << p.N_ << "\nK: " << p.K_
<< "\nC: " << p.C_ << "\nfilter_spatial_lengths: " << p.filter_spatial_lengths_
<< "\ninput_spatial_lengths: " << p.input_spatial_lengths_
<< "\nconv_filter_strides: " << p.conv_filter_strides_
<< "\nconv_filter_dilations: " << p.conv_filter_dilations_
<< "\ninput_left_pads: " << p.input_left_pads_
<< "\ninput_right_pads: " << p.input_right_pads_;
return os;
}
library/src/host_tensor/device_memory.cpp → library/src/utility/device_memory.cpp
View file @ 92a0945d
......@@ -2,7 +2,7 @@
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/device_utility/hip_check_error.hpp"
#include "ck/library/host_tensor/device_memory.hpp"
#include "ck/library/utility/device_memory.hpp"
DeviceMem::DeviceMem(std::size_t mem_size) : mMemSize(mem_size)
{
......
library/src/host_tensor/host_tensor.cpp → library/src/utility/host_tensor.cpp
View file @ 92a0945d
......@@ -3,7 +3,7 @@
#include <cassert>
#include "ck/library/host_tensor/host_tensor.hpp"
#include "ck/library/utility/host_tensor.hpp"
void HostTensorDescriptor::CalculateStrides()
{
......
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