| /* |
| * 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. |
| */ |
| |
| #pragma once |
| |
| #include <algorithm> |
| |
| #include "padding.hpp" |
| #include "utils.hpp" |
| #include "winograd.hpp" |
| |
| #define MEMBERFN(RTYPE) template <\ |
| int InnerTileRows, int InnerTileCols,\ |
| typename TIn, typename TOut, WinogradRoots Roots\ |
| > RTYPE InputTransform<InnerTileRows, InnerTileCols, TIn, TOut, Roots> |
| |
| |
| #define Nx1MEMBERFN(RTYPE) template <\ |
| int InnerTileRows, typename TIn, typename TOut, WinogradRoots Roots\ |
| > RTYPE InputTransform<InnerTileRows, 1, TIn, TOut, Roots> |
| |
| namespace winograd |
| { |
| |
| MEMBERFN()::InputTransform( |
| const int kernel_rows, |
| const int kernel_cols, |
| const int n_batches, |
| const int n_rows, |
| const int n_cols, |
| const int n_channels, |
| const int padding_top, |
| const int padding_left, |
| const int padding_bottom, |
| const int padding_right |
| ) : _n_batches(n_batches), _n_rows(n_rows), _n_cols(n_cols), _n_channels(n_channels), |
| _inptr(nullptr), _outptr(nullptr), |
| _overlap_rows(kernel_rows - 1), _overlap_cols(kernel_cols - 1), |
| _padding_top(padding_top), _padding_left(padding_left), _padding_bottom(padding_bottom), _padding_right(padding_right), |
| _tiles_M(iceildiv(padding_top + n_rows + padding_bottom - kernel_rows + 1, InnerTileRows - kernel_rows + 1)), |
| _tiles_N(iceildiv(padding_left + n_cols + padding_right - kernel_cols + 1, InnerTileCols - kernel_cols + 1)), |
| _matrix_stride(0), _matrix_row_stride(0), _matrix_batch_stride(0), |
| _in_col_stride(0), _in_row_stride(0), _in_batch_stride(0), |
| _working_space_col_stride(n_channels), |
| _working_space_row_stride(InnerTileCols * _working_space_col_stride), |
| _working_space(nullptr) |
| { |
| } |
| |
| MEMBERFN(void)::set_input_tensor(const void* const inptr) |
| { |
| set_input_tensor(inptr, _n_channels); |
| } |
| |
| MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldcol) |
| { |
| set_input_tensor(inptr, _n_cols * ldcol, ldcol); |
| } |
| |
| MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldrow, const int ldcol) |
| { |
| set_input_tensor(inptr, _n_rows * ldrow, ldrow, ldcol); |
| } |
| |
| MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldbatch, const int ldrow, const int ldcol) |
| { |
| _inptr = static_cast<const TIn *>(inptr); |
| _in_batch_stride = ldbatch; |
| _in_row_stride = ldrow; |
| _in_col_stride = ldcol; |
| } |
| |
| MEMBERFN(void)::set_output_matrices(void * const mptr, const int ldmatrix, const int ldrow) |
| { |
| _outptr = static_cast<TOut *>(mptr); |
| _matrix_stride = ldmatrix; |
| _matrix_row_stride = ldrow; |
| _matrix_batch_stride = _tiles_M * _tiles_N * ldrow; |
| } |
| |
| Nx1MEMBERFN()::InputTransform( |
| const int kernel_rows, |
| const int kernel_cols, |
| const int n_batches, |
| const int n_rows, |
| const int n_cols, |
| const int n_channels, |
| const int padding_top, |
| const int padding_left, |
| const int padding_bottom, |
| const int padding_right |
| ) : InputTransform<1, InnerTileRows, TIn, TOut, Roots>::InputTransform( |
| /* Transpose rows and columns */ |
| kernel_cols, kernel_rows, n_batches, n_cols, n_rows, n_channels, |
| padding_left, padding_top, padding_right, padding_bottom |
| ) |
| { |
| } |
| |
| Nx1MEMBERFN(void)::set_input_tensor(const void* const inptr) |
| { |
| set_input_tensor(inptr, this->_n_channels); |
| } |
| |
| Nx1MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldcol) |
| { |
| set_input_tensor(inptr, this->_n_cols * ldcol, ldcol); |
| } |
| |
| Nx1MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldrow, const int ldcol) |
| { |
| set_input_tensor(inptr, this->_n_rows * ldrow, ldrow, ldcol); |
| } |
| |
| Nx1MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldbatch, const int ldrow, const int ldcol) |
| { |
| // Transpose row and column strides |
| Base::set_input_tensor(inptr, ldbatch, ldcol, ldrow); |
| } |
| |
| MEMBERFN(size_t)::get_working_space_size(const unsigned int nthreads) const |
| { |
| return sizeof(TIn) * InnerTileRows * _working_space_row_stride * nthreads; |
| } |
| |
| MEMBERFN(void)::set_working_space(void * const buffer) |
| { |
| _working_space = static_cast<TIn *>(buffer); |
| } |
| |
| MEMBERFN(unsigned int)::get_window(void) const |
| { |
| return iceildiv(_n_channels, WINDOW_BLOCK); |
| } |
| |
| MEMBERFN(void)::run( |
| const unsigned int start, |
| const unsigned int stop, |
| const unsigned int threadid |
| ) |
| { |
| // Determine the channels on which to work |
| if (start >= get_window()) |
| { |
| return; // No work to do beyond the end of the window |
| } |
| const unsigned int start_channel = start * WINDOW_BLOCK; |
| const unsigned int stop_channel = std::min<unsigned int>(_n_channels , stop * WINDOW_BLOCK); |
| const unsigned int n_channels = stop_channel - start_channel; |
| |
| // Loop over batches |
| for (int batch = 0; batch < _n_batches; batch++) |
| { |
| const TIn* const inptr_batch = _inptr + start_channel + batch*_in_batch_stride; |
| TOut* const outptr_batch = _outptr + start_channel + batch*_matrix_batch_stride; |
| |
| // Loop over rows of tiles |
| for (int tile_i = 0; tile_i < _tiles_M; tile_i++) |
| { |
| // Compute the starting and ending row of pixels within the row of tiles, |
| // hence compute the padding to apply to the top and bottom of each tile. |
| const int row_top = tile_i * (InnerTileRows - _overlap_rows) - _padding_top; |
| const int row_bottom = row_top + InnerTileRows; |
| const int row_pad_top = std::max(0, _padding_top - tile_i * (InnerTileRows - _overlap_rows)); |
| const int row_pad_bottom = std::max(0, row_bottom - _n_rows); |
| |
| // Get a pointer to the start of the row. |
| const int row_offset = std::min(0, row_pad_top - _padding_top); |
| const TIn* const inptr_row = inptr_batch + _in_row_stride*(row_offset + tile_i*(InnerTileRows - _overlap_rows)); |
| TOut* const outptr_row = outptr_batch + tile_i*_tiles_N*_matrix_row_stride; |
| |
| // Loop over tiles within the row |
| for (int tile_j = 0; tile_j < _tiles_N; tile_j++) |
| { |
| // Compute the starting and ending column of pixels within the tile, |
| // hence compute the padding to apply to the left and right of the |
| // tile. |
| const int tile_left = tile_j * (InnerTileCols - _overlap_cols) - _padding_left; |
| const int tile_right = tile_left + InnerTileCols; |
| const int tile_pad_left = std::max(0, _padding_left - tile_j * (InnerTileCols - _overlap_cols)); |
| const int tile_pad_right = std::max(0, tile_right - _n_cols); |
| |
| // Get a pointer to the start of the tile. |
| const int col_offset = std::min(0, tile_pad_left - _padding_left); |
| const TIn* const inptr_tile = inptr_row + _in_col_stride*(col_offset + tile_j*(InnerTileCols - _overlap_cols)); |
| TOut* const outptr_tile = outptr_row + tile_j * _matrix_row_stride; |
| |
| // Transform the tile, applying padding if necessary. |
| if (row_pad_top || tile_pad_left || row_pad_bottom || tile_pad_right) |
| { |
| transform_padded_tile( |
| threadid, n_channels, outptr_tile, inptr_tile, |
| row_pad_top, tile_pad_left, row_pad_bottom, tile_pad_right |
| ); |
| } |
| else |
| { |
| transform_unpadded_tile(threadid, n_channels, outptr_tile, inptr_tile); |
| } |
| } |
| } |
| } |
| } |
| |
| MEMBERFN(void)::transform_unpadded_tile( |
| const unsigned int /* threadid unused */, |
| const int n_channels, |
| TOut * const outptr, |
| const TIn * const inptr |
| ) |
| { |
| transform_tile( |
| n_channels, inptr, _in_row_stride, _in_col_stride, outptr, _matrix_stride |
| ); |
| } |
| |
| MEMBERFN(void)::transform_padded_tile( |
| const unsigned int threadid, |
| const int n_channels, |
| TOut * const outptr, |
| const TIn * const inptr, |
| const int padding_top, |
| const int padding_left, |
| const int padding_bottom, |
| const int padding_right |
| ) |
| { |
| padding::copy_and_pad_tile( |
| InnerTileRows, InnerTileCols, n_channels, |
| inptr, _in_row_stride, _in_col_stride, |
| static_cast<TIn *>(get_working_space(threadid)), _working_space_row_stride, _working_space_col_stride, |
| padding_top, padding_left, padding_bottom, padding_right |
| ); |
| |
| transform_tile( |
| n_channels, static_cast<const TIn *>(get_working_space(threadid)), |
| _working_space_row_stride, _working_space_col_stride, |
| outptr, _matrix_stride |
| ); |
| } |
| |
| MEMBERFN(void *)::get_working_space(const unsigned int threadid) const |
| { |
| return _working_space + InnerTileRows * _working_space_row_stride * threadid; |
| } |
| |
| } // namespace winograd |