diff options
Diffstat (limited to 'arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp')
| -rw-r--r-- | arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp | 123 |
1 files changed, 7 insertions, 116 deletions
diff --git a/arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp b/arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp index 7098fc48a1..31aee35fab 100644 --- a/arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp +++ b/arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp @@ -30,7 +30,7 @@ #include "arm_compute/core/NEON/kernels/convolution/common/shims.hpp" #include "arm_compute/core/NEON/kernels/convolution/common/tensor.hpp" #include "arm_compute/core/NEON/kernels/convolution/common/utils.hpp" - +#include "winograd_input_transform.hpp" #include <thread> #include <utility> @@ -114,121 +114,12 @@ class WinogradGEMM /** Transform input feature maps from the spatial to the Winograd domain. */ template <typename T> - struct InputTransform - { - /** Get the bytes read during the transform. */ - static size_t bytes_read(const Tensor4DShape &shape) - { - return shape.size() * sizeof(T); - } - - /** Get the bytes written during the transform. */ - static size_t bytes_written(const Tensor4DShape &shape) - { - const int M = iceildiv(shape.n_rows, inner_tile_rows) * - iceildiv(shape.n_cols, inner_tile_cols); - const int K = shape.n_channels; - return inner_tile_rows * inner_tile_cols * M * K * sizeof(T); - } - - /** Get the count of operations performed by the transform. */ - static int ops_performed(const Tensor4DShape &shape); - - /** 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. */ - ); - - /***********************************************************************/ - /** 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); - /***********************************************************************/ - - 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 - ); - - // Tile overlaps - static constexpr int overlap_rows = kernel_rows - 1; - static constexpr int overlap_cols = kernel_cols - 1; - - // Maximum padding and number of distinct paddings - static constexpr int max_pad_top = kernel_rows / 2; - static constexpr int n_pad_top = 1 + iceildiv(max_pad_top, inner_tile_rows - overlap_rows); - - static constexpr int max_pad_left = kernel_cols / 2; - static constexpr int n_pad_left = 1 + iceildiv(max_pad_left, inner_tile_cols - overlap_cols); - - static constexpr int n_pad_bottom = inner_tile_rows; - static constexpr int n_pad_right = inner_tile_cols; - - - - /** Process a single tile of the input tensor. */ - template <int pad_top, int pad_left, int pad_bottom, int pad_right> - static void process_tile(int, const T*, int, int, T*, int); - - // Array of methods to transform tiles of the input tensor. - typedef void (*TileFn)(int, const T*, int, int, T*, int); - static const TileFn - tile_fns[n_pad_top][n_pad_left][n_pad_bottom][n_pad_right]; - - /* 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; - }; + using InputTransform = InputTransform< + KernelRows, KernelCols, + (OutputTileRows + KernelRows - 1), + (OutputTileCols + KernelCols - 1), + T + >; /** Transform output feature maps from the Winograd to the spatial domain. */ |