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Diffstat (limited to 'src/core/NEON/kernels/convolution/winograd/winograd_transforms/input.hpp')
-rw-r--r-- | src/core/NEON/kernels/convolution/winograd/winograd_transforms/input.hpp | 265 |
1 files changed, 265 insertions, 0 deletions
diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input.hpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input.hpp new file mode 100644 index 0000000000..fcbd21fcd0 --- /dev/null +++ b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input.hpp @@ -0,0 +1,265 @@ +/* + * Copyright (c) 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 "winograd.hpp" +#include "padding.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 |