diff options
Diffstat (limited to 'arm_compute/core/NEON/kernels/convolution/winograd/winograd_input_transform.hpp')
| -rw-r--r-- | arm_compute/core/NEON/kernels/convolution/winograd/winograd_input_transform.hpp | 271 |
1 files changed, 0 insertions, 271 deletions
diff --git a/arm_compute/core/NEON/kernels/convolution/winograd/winograd_input_transform.hpp b/arm_compute/core/NEON/kernels/convolution/winograd/winograd_input_transform.hpp deleted file mode 100644 index 995554d7f2..0000000000 --- a/arm_compute/core/NEON/kernels/convolution/winograd/winograd_input_transform.hpp +++ /dev/null @@ -1,271 +0,0 @@ -/* - * Copyright (c) 2018 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 - -namespace winograd -{ - -namespace -{ - -template <int KernelRows, int KernelCols, int InnerTileRows, int InnerTileCols, typename T> -class InputTransformImplTiles -{ - public: - /** Method to transform a tile of the input tensor into the Winograd domain. */ - typedef void (*TileFn)( - const int n_channels, /** @param[in] Number of channels in the tensor. */ - const T* const inptr_base, /** @param[in] Pointer to the base of the input tile. */ - const int input_row_stride, /** @param[in] Stride between rows of the input tensor. */ - const int input_col_stride, /** @param[in] Stride between columns of the input tensor. */ - T* const mptr_base, /** @param[out] Base pointer to transformed input matrices. */ - const int matrix_stride, /** @param[in] Stride between matrices in the input space. */ - const int _pad_top, /** @param[in] Top padding for unspecialised tiles. */ - const int _pad_left, /** @param[in] Left padding for unspecialised tiles. */ - const int _pad_bottom, /** @param[in] Bottom padding for unspecialised tiles. */ - const int _pad_right /** @param[in] Right padding for unspecialised tiles. */ - ); - - static TileFn get_tile_specialization( - const int pad_top, - const int pad_left, - const int pad_bottom, - const int pad_right - ); - - // Tile overlaps - static constexpr int overlap_rows = KernelRows - 1; - static constexpr int overlap_cols = KernelCols - 1; - - private: - - // Maximum padding and number of distinct paddings - static constexpr int max_pad_top = KernelRows / 2; - static constexpr int min_pad_top = KernelRows % (InnerTileRows - overlap_rows); - static constexpr int n_pad_top = iceildiv(max_pad_top, InnerTileRows - overlap_rows); - - static constexpr int max_pad_left = KernelCols / 2; - static constexpr int min_pad_left = KernelCols % (InnerTileCols - overlap_cols); - static constexpr int n_pad_left = iceildiv(max_pad_left, InnerTileCols - overlap_cols); - - static constexpr int n_pad_bottom = InnerTileRows; - static constexpr int n_pad_right = InnerTileCols; - - // Pointers to methods implementing a generically padded tile and a totally unpadded tile. - static const TileFn tilefn_generic; /** Generic tile processing function. */ - static const TileFn tilefn_unpadded; /** Tile processor for unpadded tiles. */ - - // Arrays of methods covering tiles which are padded only on a single side. - static const TileFn tilefn_top_padded[n_pad_top]; - static const TileFn tilefn_left_padded[n_pad_left]; - static const TileFn tilefn_bottom_padded[n_pad_bottom]; - static const TileFn tilefn_right_padded[n_pad_right]; -}; - - -template < int KernelCols, int InnerTileCols, typename T> -class InputTransformImplTiles<1, KernelCols, 1, InnerTileCols, T> -{ - public: - /** Method to transform a tile of the input tensor into the Winograd domain. */ - typedef void (*TileFn)( - const int n_channels, /** @param[in] Number of channels in the tensor. */ - const T* const inptr_base, /** @param[in] Pointer to the base of the input tile. */ - const int input_row_stride, /** @param[in] Stride between rows of the input tensor. */ - const int input_col_stride, /** @param[in] Stride between columns of the input tensor. */ - T* const mptr_base, /** @param[out] Base pointer to transformed input matrices. */ - const int matrix_stride, /** @param[in] Stride between matrices in the input space. */ - const int _pad_top, /** @param[in] Top padding for unspecialised tiles. */ - const int _pad_left, /** @param[in] Left padding for unspecialised tiles. */ - const int _pad_bottom, /** @param[in] Bottom padding for unspecialised tiles. */ - const int _pad_right /** @param[in] Right padding for unspecialised tiles. */ - ); - - static TileFn get_tile_specialization( - const int pad_top, - const int pad_left, - const int pad_bottom, - const int pad_right - ); - - // Tile overlaps - static constexpr int overlap_rows = 0; - static constexpr int overlap_cols = KernelCols - 1; - - private: - // Maximum padding and number of distinct paddings - static constexpr int max_pad_left = KernelCols / 2; - static constexpr int min_pad_left = KernelCols % (InnerTileCols - overlap_cols); - static constexpr int n_pad_left = iceildiv(max_pad_left, InnerTileCols - overlap_cols); - - static constexpr int n_pad_right = InnerTileCols; - - // Pointers to methods implementing a generically padded tile and a totally unpadded tile. - static const TileFn tilefn_generic; /** Generic tile processing function. */ - static const TileFn tilefn_unpadded; /** Tile processor for unpadded tiles. */ - - // Arrays of methods covering tiles which are padded only on a single side. - static const TileFn tilefn_left_padded[n_pad_left]; - static const TileFn tilefn_right_padded[n_pad_right]; -}; - - - -template <int KernelRows, int KernelCols, int InnerTileRows, int InnerTileCols, typename T> -class InputTransformImpl -{ - public: - /** Apply the transform to a tensor. */ - static void execute( - const T* const input, /** Input tensor data */ - const int n_batches, /** Number of batches in input tensor. */ - const int in_batch_stride, /** Stride between batches of the input. */ - const int n_rows, /** Number of rows in input tensor. */ - const int in_row_stride, /** Stride between rows of the input. */ - const int n_cols, /** Number of columns in input tensor. */ - const int in_col_stride, /** Stride between columns of the input. */ - const int n_channels, /** Number of channels in input tensor. */ - const PaddingType padding, /** Padding type. */ - const int tile_M, - const int tile_N, - T* const output, /** Base of output matrices. */ - const int matrix_stride, /** Stride between output matrices. */ - const int matrix_batch_stride, /** Stride between batches within the matrix. */ - const int matrix_row_stride /** Stride within matrices. */ - ); - - private: - static void process_tile_row( - const int tile_N, - int n_channels, - const T* const input_base, - const int input_row_stride, - const int input_col_stride, - T* const matrix_base, - const int matrix_stride, - const int matrix_row_stride, - const int row_pad_top, - const int row_pad_left, - const int row_pad_bottom, - const int n_cols - ); - - using Tiles = InputTransformImplTiles<KernelRows, KernelCols, InnerTileRows, InnerTileCols, T>; - - static constexpr int overlap_rows = Tiles::overlap_rows; - static constexpr int overlap_cols = Tiles::overlap_cols; - - - }; - - -template <int KernelRows, int InnerTileRows, typename T> -class InputTransformImpl<KernelRows, 1, InnerTileRows, 1, T> -{ - public: - /** Apply the transform to a tensor. */ - static void execute( - const T* const input, /** Input tensor data */ - const int n_batches, /** Number of batches in input tensor. */ - const int in_batch_stride, /** Stride between batches of the input. */ - const int n_rows, /** Number of rows in input tensor. */ - const int in_row_stride, /** Stride between rows of the input. */ - const int n_cols, /** Number of columns in input tensor. */ - const int in_col_stride, /** Stride between columns of the input. */ - const int n_channels, /** Number of channels in input tensor. */ - const PaddingType padding, /** Padding type. */ - const int tile_M, - const int tile_N, - T* const output, /** Base of output matrices. */ - const int matrix_stride, /** Stride between output matrices. */ - const int matrix_batch_stride, /** Stride between batches within the matrix. */ - const int matrix_row_stride /** Stride within matrices. */ - ); -}; - -} // namespace (anonymous) - -template <int KernelRows, int KernelCols, int InnerTileRows, int InnerTileCols, typename T> -class InputTransform -{ - public: - /***********************************************************************/ - /** Create an InputTransform operator fixed on a given problem and set of - * pointers. - */ - InputTransform( - const T* const input, /** Input tensor data */ - const int n_batches, /** Number of batches in input tensor. */ - const int n_rows, /** Number of rows in input tensor. */ - const int n_cols, /** Number of columns in input tensor. */ - const int n_channels, /** Number of channels in input tensor. */ - const PaddingType padding, /** Padding type. */ - T* const output, /** Base of output matrices. */ - const int matrix_stride, /** Stride between output matrices. */ - const int matrix_row_stride, /** Stride within matrices. */ - const int in_batch_stride=0, /** Stride between input batches. */ - const int in_row_stride=0, /** Stride between input rows. */ - const int in_col_stride=0 /** Stride between input columns. */ - ); - - /** Get the window of work a given operator can perform. */ - unsigned int get_window() const; - static constexpr unsigned int WINDOW_BLOCK = 16; // Base size of window - - /** Perform work upon a window of the input. */ - void run(const unsigned int start, const unsigned int stop); - - /** Apply the transform to a tensor. */ - static void execute( - const T* const input, /** Input tensor data */ - const int n_batches, /** Number of batches in input tensor. */ - const int in_batch_stride, /** Stride between batches of the input. */ - const int n_rows, /** Number of rows in input tensor. */ - const int in_row_stride, /** Stride between rows of the input. */ - const int n_cols, /** Number of columns in input tensor. */ - const int in_col_stride, /** Stride between columns of the input. */ - const int n_channels, /** Number of channels in input tensor. */ - const PaddingType padding, /** Padding type. */ - const int tile_M, - const int tile_N, - T* const output, /** Base of output matrices. */ - const int matrix_stride, /** Stride between output matrices. */ - const int matrix_batch_stride, /** Stride between batches within the matrix. */ - const int matrix_row_stride /** Stride within matrices. */ - ); - - protected: - using Transform = InputTransformImpl<KernelRows, KernelCols, InnerTileRows, InnerTileCols, T>; - - /* Member values for instance-based API. */ - const T* const _inptr; - T* const _outptr; - const int _n_batches, _n_rows, _n_cols, _n_channels, _matrix_stride, - _matrix_row_stride, _tiles_M, _tiles_N; - const int _in_col_stride, _in_row_stride, _in_batch_stride; - const PaddingType _padding_type; -}; - -} // namespace winograd |