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/*
* Copyright (c) 2017-2022 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "src/cpu/kernels/CpuWinogradConv2dKernel.h"
namespace arm_compute
{
namespace cpu
{
CpuWinogradConv2dTransformInputKernel::CpuWinogradConv2dTransformInputKernel(arm_conv::winograd::WinogradImpl &w_impl,
arm_conv::ConvolutionArgs &_c_args,
uint32_t nthreads)
: _winograd_impl{w_impl}, _conv_args{_c_args}, _nthreads{nthreads}
{
}
void CpuWinogradConv2dTransformInputKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(window);
const ITensor *input_nhwc = tensors.get_const_tensor(TensorType::ACL_SRC);
const ITensor *winograd_input_transform = tensors.get_const_tensor(TensorType::ACL_DST);
const ITensor *workspace = tensors.get_const_tensor(TensorType::ACL_INT);
const unsigned int width_idx = 1;
const unsigned int height_idx = 2;
const unsigned int batch_idx = 3;
int element_size_in_bytes = input_nhwc->info()->element_size();
const auto src_strides = input_nhwc->info()->strides_in_bytes();
const size_t input_row_stride = src_strides[height_idx] / element_size_in_bytes;
const size_t input_col_stride = src_strides[width_idx] / element_size_in_bytes;
const size_t input_batch_stride = src_strides[batch_idx] / element_size_in_bytes;
const auto input_nhwc_ptr =
reinterpret_cast<const void *>(input_nhwc->buffer() + input_nhwc->info()->offset_first_element_in_bytes());
auto win_transf_ptr = reinterpret_cast<void *>(winograd_input_transform->buffer() +
winograd_input_transform->info()->offset_first_element_in_bytes());
_winograd_impl.input_transform->execute(_conv_args, input_nhwc_ptr, input_batch_stride, input_row_stride,
input_col_stride, win_transf_ptr, _winograd_impl.winograd_spec,
workspace->buffer(), info.thread_id, _nthreads);
}
CpuWinogradConv2dTransformOutputKernel::CpuWinogradConv2dTransformOutputKernel(arm_conv::winograd::WinogradImpl &w_impl,
arm_conv::ConvolutionArgs &_c_args,
uint32_t nthreads)
: _winograd_impl{w_impl}, _conv_args{_c_args}, _nthreads{nthreads}
{
}
// Inherited methods overridden:
void CpuWinogradConv2dTransformOutputKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(window);
const ITensor *dst_nhwc = tensors.get_const_tensor(TensorType::ACL_DST);
const ITensor *winograd_output_transform = tensors.get_const_tensor(TensorType::ACL_SRC_0);
const ITensor *biases = tensors.get_const_tensor(TensorType::ACL_SRC_1);
const ITensor *workspace = tensors.get_tensor(TensorType::ACL_INT);
const unsigned int width_idx = 1;
const unsigned int height_idx = 2;
const unsigned int batch_idx = 3;
const int element_size_in_bytes = dst_nhwc->info()->element_size();
const auto dst_strides = dst_nhwc->info()->strides_in_bytes();
const size_t out_row_stride = dst_strides[height_idx] / element_size_in_bytes;
const size_t out_col_stride = dst_strides[width_idx] / element_size_in_bytes;
const size_t out_batch_stride = dst_strides[batch_idx] / element_size_in_bytes;
const auto wout_transf_ptr = reinterpret_cast<const void *>(
winograd_output_transform->buffer() + winograd_output_transform->info()->offset_first_element_in_bytes());
auto dst_nhwc_ptr =
reinterpret_cast<void *>(dst_nhwc->buffer() + dst_nhwc->info()->offset_first_element_in_bytes());
void *biases_data_ptr = nullptr;
if (biases != nullptr)
{
biases_data_ptr = reinterpret_cast<void *>(biases->buffer() + biases->info()->offset_first_element_in_bytes());
}
// Output transform
_winograd_impl.output_transform->execute(_conv_args, wout_transf_ptr, _winograd_impl.winograd_spec, biases_data_ptr,
dst_nhwc_ptr, out_batch_stride, out_row_stride, out_col_stride,
workspace->buffer(), info.thread_id, _nthreads);
}
} // namespace cpu
} // namespace arm_compute
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