diff options
Diffstat (limited to 'src/core/NEON/kernels/convolution/winograd/winograd.cpp')
| -rw-r--r-- | src/core/NEON/kernels/convolution/winograd/winograd.cpp | 182 |
1 files changed, 0 insertions, 182 deletions
diff --git a/src/core/NEON/kernels/convolution/winograd/winograd.cpp b/src/core/NEON/kernels/convolution/winograd/winograd.cpp deleted file mode 100644 index d556112853..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd.cpp +++ /dev/null @@ -1,182 +0,0 @@ -/* - * Copyright (c) 2017-2019 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 <cstring> -#include "utils.hpp" -#include "winograd.hpp" - -using namespace winograd; -using array2 = std::pair<unsigned int, unsigned int>; - -#define MEMBERFN(RTYPE) \ - template <int output_tile_rows, int output_tile_cols, int kernel_rows, \ - int kernel_cols, WinogradRoots roots> \ - template <typename TOut, typename TIn, typename TGEMMIn, typename TGEMMOut> \ - RTYPE WinogradGEMM<output_tile_rows, output_tile_cols, kernel_rows, \ - kernel_cols, \ - roots>::Convolution<TOut, TIn, TGEMMIn, TGEMMOut> - -/** Get the output shape of a convolution. */ -MEMBERFN(array2) -::get_output_shape(const std::pair<unsigned int, unsigned int> input_shape, - const bool padding_same) { - const unsigned int n_rows = - padding_same ? input_shape.first : input_shape.first - (kernel_rows - 1); - const unsigned int n_cols = padding_same - ? input_shape.second - : input_shape.second - (kernel_cols - 1); - return {n_rows, n_cols}; -} - -/** Get the memory required to store the kernel transformed into the - * Winograd domain. - */ -MEMBERFN(size_t) -::get_kernel_storage_size(const unsigned int n_input_channels, - const unsigned int n_output_channels) { - return N_GEMMS * get_kernel_matrix_size(n_input_channels, n_output_channels); -} - -MEMBERFN(size_t) -::get_input_storage_size(const unsigned int n_batches, - const unsigned int n_rows, const unsigned int n_cols, - const unsigned int n_channels, - const bool same_padding) { - return N_GEMMS * get_input_matrix_size(n_batches, n_rows, n_cols, n_channels, - same_padding); -} - -MEMBERFN(size_t) -::get_output_storage_size(const unsigned int n_batches, - const unsigned int n_rows, const unsigned int n_cols, - const unsigned int n_channels) { - return N_GEMMS * - get_output_matrix_size(n_batches, n_rows, n_cols, n_channels); -} - -/** Get the memory required to apply a Winograd operator to some input. - */ -MEMBERFN(size_t) -::get_working_space_size(const unsigned int n_batches, - const unsigned int n_rows, const unsigned int n_cols, - const unsigned int n_input_channels, - const unsigned int n_output_channels, - const bool padding_same) { - const auto output_shape = get_output_shape({n_rows, n_cols}, padding_same); - - // Get the memory required to store the matrices - const size_t matrix_sizes = - N_GEMMS * - (get_input_matrix_size(n_batches, n_rows, n_cols, n_input_channels, - padding_same) + - get_output_matrix_size(n_batches, output_shape.first, - output_shape.second, n_output_channels)); - return matrix_sizes; -} - -/* Get the memory required by a single "input" matrix. - */ -MEMBERFN(size_t) -::get_input_matrix_size(const unsigned int n_batches, const unsigned int n_rows, - const unsigned int n_cols, - const unsigned int n_channels, - const bool same_padding) { - return get_input_matrix_stride(n_batches, n_rows, n_cols, n_channels, - same_padding) * - sizeof(TGEMMIn); -} - -MEMBERFN(int) -::get_input_matrix_stride(const unsigned int n_batches, const unsigned int n_rows, - const unsigned int n_cols, - const unsigned int n_channels, - const bool same_padding) { - const auto output_shape = get_output_shape({n_rows, n_cols}, same_padding); - const unsigned int tile_rows = iceildiv(output_shape.first, output_tile_rows); - const unsigned int tile_cols = - iceildiv(output_shape.second, output_tile_cols); - const unsigned int M = - roundup<unsigned int>(n_batches * tile_rows * tile_cols, M_BLOCK); - const unsigned int K = n_channels; - - return M * K; -} - -/* Get the memory required by a single "output" matrix. - */ -MEMBERFN(size_t) -::get_output_matrix_size(const unsigned int n_batches, - const unsigned int n_rows, const unsigned int n_cols, - const unsigned int n_channels) { - return get_output_matrix_stride(n_batches, n_rows, n_cols, n_channels) * - sizeof(TGEMMOut); -} - -MEMBERFN(int) -::get_output_matrix_stride(const unsigned int n_batches, - const unsigned int n_rows, const unsigned int n_cols, - const unsigned int n_channels) { - // Compute shape for the GEMM - const int tile_rows = iceildiv(n_rows, output_tile_rows); - const int tile_cols = iceildiv(n_cols, output_tile_cols); - const int M = roundup<int>(tile_rows * tile_cols, M_BLOCK); - const int N = roundup<int>(n_channels, N_BLOCK); - - return n_batches * M * N; -} - - -/* Get the memory required by a single "kernel" matrix. - */ -MEMBERFN(size_t) -::get_kernel_matrix_size(const unsigned int n_input_channels, - const unsigned int n_output_channels) { - return sizeof(TGEMMIn) * - get_kernel_matrix_stride(n_input_channels, n_output_channels); -} - -MEMBERFN(int) -::get_kernel_matrix_stride(const unsigned int n_input_channels, - const unsigned int n_output_channels) { - return n_input_channels * roundup<int>(n_output_channels, N_BLOCK); -} - -// Instantiate required implementations -template class WinogradGEMM<2, 2, 3, 3, WinogradRoots::Integers>::Convolution<float, float, float, float>; -template class WinogradGEMM<4, 4, 3, 3, WinogradRoots::Integers>::Convolution<float, float, float, float>; - -template class WinogradGEMM<1, 6, 1, 3, WinogradRoots::Integers>::Convolution<float, float, float, float>; -template class WinogradGEMM<6, 1, 3, 1, WinogradRoots::Integers>::Convolution<float, float, float, float>; - -template class WinogradGEMM<2, 2, 5, 5, WinogradRoots::Integers>::Convolution<float, float, float, float>; - -template class WinogradGEMM<1, 4, 1, 5, WinogradRoots::Integers>::Convolution<float, float, float, float>; -template class WinogradGEMM<4, 1, 5, 1, WinogradRoots::Integers>::Convolution<float, float, float, float>; - -template class WinogradGEMM<1, 2, 1, 7, WinogradRoots::Integers>::Convolution<float, float, float, float>; -template class WinogradGEMM<2, 1, 7, 1, WinogradRoots::Integers>::Convolution<float, float, float, float>; - -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC -template class WinogradGEMM<4, 4, 3, 3, WinogradRoots::Integers>::Convolution<__fp16, __fp16, __fp16, __fp16>; -#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |