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author | Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com> | 2023-09-27 17:46:17 +0100 |
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committer | felixjohnny.thomasmathibalan <felixjohnny.thomasmathibalan@arm.com> | 2023-09-28 12:08:05 +0000 |
commit | afd38f0c617d6f89b2b4532c6c44f116617e2b6f (patch) | |
tree | 03bc7d5a762099989b16a656fa8d397b490ed70e /src/cpu/kernels/CpuWinogradConv2dKernel.cpp | |
parent | bdcb4c148ee2fdeaaddf4cf1e57bbb0de02bb894 (diff) | |
download | ComputeLibrary-afd38f0c617d6f89b2b4532c6c44f116617e2b6f.tar.gz |
Apply clang-format on repository
Code is formatted as per a revised clang format configuration
file(not part of this delivery). Version 14.0.6 is used.
Exclusion List:
- files with .cl extension
- files that are not strictly C/C++ (e.g. Android.bp, Sconscript ...)
And the following directories
- compute_kernel_writer/validation/
- tests/
- include/
- src/core/NEON/kernels/convolution/
- src/core/NEON/kernels/arm_gemm/
- src/core/NEON/kernels/arm_conv/
- data/
There will be a follow up for formatting of .cl files and the
files under tests/ and compute_kernel_writer/validation/.
Signed-off-by: Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>
Change-Id: Ib7eb1fcf4e7537b9feaefcfc15098a804a3fde0a
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10391
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Diffstat (limited to 'src/cpu/kernels/CpuWinogradConv2dKernel.cpp')
-rw-r--r-- | src/cpu/kernels/CpuWinogradConv2dKernel.cpp | 59 |
1 files changed, 25 insertions, 34 deletions
diff --git a/src/cpu/kernels/CpuWinogradConv2dKernel.cpp b/src/cpu/kernels/CpuWinogradConv2dKernel.cpp index 818d878119..52e3f2549c 100644 --- a/src/cpu/kernels/CpuWinogradConv2dKernel.cpp +++ b/src/cpu/kernels/CpuWinogradConv2dKernel.cpp @@ -28,8 +28,10 @@ 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 } +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} { } @@ -49,24 +51,20 @@ void CpuWinogradConv2dTransformInputKernel::run_op(ITensorPack &tensors, const W 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()); + 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); + _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 } +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} { } @@ -88,28 +86,21 @@ void CpuWinogradConv2dTransformOutputKernel::run_op(ITensorPack &tensors, const 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) + 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); + _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
\ No newline at end of file +} // namespace arm_compute |