Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 1 | /* |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 2 | * Copyright (c) 2017-2019 ARM Limited. |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 3 | * |
| 4 | * SPDX-License-Identifier: MIT |
| 5 | * |
| 6 | * Permission is hereby granted, free of charge, to any person obtaining a copy |
| 7 | * of this software and associated documentation files (the "Software"), to |
| 8 | * deal in the Software without restriction, including without limitation the |
| 9 | * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| 10 | * sell copies of the Software, and to permit persons to whom the Software is |
| 11 | * furnished to do so, subject to the following conditions: |
| 12 | * |
| 13 | * The above copyright notice and this permission notice shall be included in all |
| 14 | * copies or substantial portions of the Software. |
| 15 | * |
| 16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| 17 | * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| 18 | * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| 19 | * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| 20 | * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| 21 | * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| 22 | * SOFTWARE. |
| 23 | */ |
| 24 | |
| 25 | #pragma once |
| 26 | |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 27 | #include "arm_compute/core/NEON/kernels/assembly/arm_gemm.hpp" |
| 28 | |
| 29 | #include <cstddef> |
| 30 | #include <utility> |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 31 | |
| 32 | namespace winograd |
| 33 | { |
| 34 | |
| 35 | class ITransform |
| 36 | { |
| 37 | public: |
| 38 | virtual ~ITransform() = default; |
| 39 | |
| 40 | /** |
| 41 | * Get the working space required to perform the transformation. |
| 42 | * |
| 43 | * Note, the working space is only required when performing the |
| 44 | * transformation - hence it can be reused whenever the transformation is |
| 45 | * not running. |
| 46 | * |
| 47 | * @param nthreads The greatest number of threads that will be used to execute the transform. |
| 48 | * @return Size of working space required in bytes. |
| 49 | */ |
| 50 | virtual size_t get_working_space_size(unsigned int nthreads=1) const = 0; |
| 51 | |
| 52 | /** |
| 53 | * Set the working space to be used by the transformation. |
| 54 | * |
| 55 | * Note, the working space is only required when performing the |
| 56 | * transformation - hence it can be reused whenever the transformation is |
| 57 | * not running. |
| 58 | * |
| 59 | * @param Pointer to the working space. |
| 60 | */ |
| 61 | virtual void set_working_space(void *buffer) = 0; |
| 62 | |
| 63 | /** |
| 64 | * Get the window of work a given operator can perform. |
| 65 | */ |
| 66 | virtual unsigned int get_window() const = 0; |
| 67 | |
| 68 | /** |
| 69 | * Perform work upon a window of the transform. |
| 70 | */ |
| 71 | virtual void run(unsigned int start, unsigned int stop, unsigned int threadid=0) = 0; |
| 72 | }; |
| 73 | |
| 74 | class IInputTransform : public ITransform |
| 75 | { |
| 76 | public: |
| 77 | virtual ~IInputTransform() = default; |
| 78 | |
| 79 | /** |
| 80 | * Set the pointer to the (NHWC-ordered) tensor to be transformed. |
| 81 | */ |
| 82 | virtual void set_input_tensor(const void *input) = 0; |
| 83 | |
| 84 | /** |
| 85 | * Set the pointer to the (NHWC-ordered) tensor to be transformed. |
| 86 | * @param col_stride Stride between columns of the tensor, measured in elements (not bytes). |
| 87 | */ |
| 88 | virtual void set_input_tensor(const void *input, int col_stride) = 0; |
| 89 | |
| 90 | /** |
| 91 | * Set the pointer to the (NHWC-ordered) tensor to be transformed. |
| 92 | * @param row_stride Stride between rows of the tensor, measured in elements (not bytes). |
| 93 | * @param col_stride Stride between columns of the tensor, measured in elements (not bytes). |
| 94 | */ |
| 95 | virtual void set_input_tensor(const void *input, int row_stride, int col_stride) = 0; |
| 96 | |
| 97 | /** |
| 98 | * Set the pointer to the (NHWC-ordered) tensor to be transformed. |
| 99 | * @param batch_stride Stride between batches of the tensor, measured in elements (not bytes). |
| 100 | * @param row_stride Stride between rows of the tensor, measured in elements (not bytes). |
| 101 | * @param col_stride Stride between columns of the tensor, measured in elements (not bytes). |
| 102 | */ |
| 103 | virtual void set_input_tensor(const void *input, int batch_stride, int row_stride, int col_stride) = 0; |
| 104 | |
| 105 | /** |
| 106 | * Set pointers to the matrices written by the transform. |
| 107 | * @param matrices Pointer to the start of the first matrix representing the transformed input. |
| 108 | * @param inter_matrix_stride Stride (in elements) between matrices. |
| 109 | * @param matrix_row_stride Stride (in elements) between the rows within a single matrix. |
| 110 | */ |
| 111 | virtual void set_output_matrices(void *matrices, int inter_matrix_stride, int matrix_row_stride) = 0; |
| 112 | }; |
| 113 | |
| 114 | class IOutputTransform : public ITransform |
| 115 | { |
| 116 | public: |
| 117 | virtual ~IOutputTransform() = default; |
| 118 | |
| 119 | /** |
| 120 | * Set pointers to the matrices written by the transform. |
| 121 | * @param matrices Pointer to the start of the first matrix representing the input to the transform. |
| 122 | * @param inter_matrix_stride Stride (in elements) between matrices. |
| 123 | * @param matrix_row_stride Stride (in elements) between the rows within a single matrix. |
| 124 | */ |
| 125 | virtual void set_input_matrices(const void *matrices, int inter_matrix_stride, int matrix_row_stride) = 0; |
| 126 | |
| 127 | /** |
| 128 | * Set pointer to the bias tensor (can be ignored or called with nullptr for no bias. |
| 129 | */ |
| 130 | virtual void set_bias(const void *bias=nullptr) = 0; |
| 131 | |
| 132 | /** |
| 133 | * Set pointer to the output tensor produced by the transform. |
| 134 | */ |
| 135 | virtual void set_output_tensor(void *output) = 0; |
| 136 | |
| 137 | /** |
| 138 | * Set pointer to the output tensor produced by the transform. |
| 139 | * @param col_stride Stride between columns of the tensor, measured in elements (not bytes). |
| 140 | */ |
| 141 | virtual void set_output_tensor(void *output, int col_stride) = 0; |
| 142 | |
| 143 | /** |
| 144 | * Set pointer to the output tensor produced by the transform. |
| 145 | * @param row_stride Stride between rows of the tensor, measured in elements (not bytes). |
| 146 | * @param col_stride Stride between columns of the tensor, measured in elements (not bytes). |
| 147 | */ |
| 148 | virtual void set_output_tensor(void *output, int row_stride, int col_stride) = 0; |
| 149 | |
| 150 | /** |
| 151 | * Set pointer to the output tensor produced by the transform. |
| 152 | * @param batch_stride Stride between batches of the tensor, measured in elements (not bytes). |
| 153 | * @param row_stride Stride between rows of the tensor, measured in elements (not bytes). |
| 154 | * @param col_stride Stride between columns of the tensor, measured in elements (not bytes). |
| 155 | */ |
| 156 | virtual void set_output_tensor(void *output, int batch_stride, int row_stride, int col_stride) = 0; |
| 157 | }; |
| 158 | |
| 159 | class IWeightTransform : public ITransform |
| 160 | { |
| 161 | public: |
| 162 | virtual ~IWeightTransform() = default; |
| 163 | |
| 164 | /** Set pointer to the weight tensor read by the transform. */ |
| 165 | virtual void set_weight_tensor(const void *weights) = 0; |
| 166 | |
| 167 | /** |
| 168 | * Set pointers to the matrices written by the transform. |
| 169 | * @param matrices Pointer to the start of the first matrix representing the transformed input. |
| 170 | * @param inter_matrix_stride Stride (in elements) between matrices. |
| 171 | * @param matrix_row_stride Stride (in elements) between the rows within a single matrix. |
| 172 | */ |
| 173 | virtual void set_output_matrices(void *matrices, int inter_matrix_stride, int matrix_row_stride) = 0; |
| 174 | }; |
| 175 | |
| 176 | enum class WinogradRoots |
| 177 | { |
| 178 | Integers, |
| 179 | }; |
| 180 | |
| 181 | template <int InnerTileRows, int InnerTileCols, typename TIn, typename TOut, WinogradRoots Roots> |
| 182 | class InputTransform : public IInputTransform |
| 183 | { |
| 184 | public: |
| 185 | /** Create an InputTransform operator fixed on a given problem and set of |
| 186 | * pointers. |
| 187 | */ |
| 188 | InputTransform( |
| 189 | int kernel_rows, /**< Number of rows in the kernel */ |
| 190 | int kernel_cols, /**< Number of columns in the kernel */ |
| 191 | int n_batches, /**< Number of batches in input tensor. */ |
| 192 | int n_rows, /**< Number of rows in input tensor. */ |
| 193 | int n_cols, /**< Number of columns in input tensor. */ |
| 194 | int n_channels, /**< Number of channels in input tensor. */ |
| 195 | int padding_top, /**< Padding to apply to the top of the image. */ |
| 196 | int padding_left, /**< Padding to apply to the left of the image. */ |
| 197 | int padding_bottom, /**< Padding to apply to the bottom of the image. */ |
| 198 | int padding_right /**< Padding to apply to the right of the image. */ |
| 199 | ); |
| 200 | |
| 201 | InputTransform(InputTransform&) = delete; |
| 202 | InputTransform operator=(InputTransform&) = delete; |
| 203 | |
| 204 | /** Set pointers to the input tensor read by the transform. */ |
| 205 | void set_input_tensor(const void *input) override; |
| 206 | void set_input_tensor(const void *input, int col_stride) override; |
| 207 | void set_input_tensor(const void *input, int row_stride, int col_stride) override; |
| 208 | void set_input_tensor(const void *input, int batch_stride, int row_stride, int col_stride) override; |
| 209 | |
| 210 | /** Set pointers to the matrices written by the transform. */ |
| 211 | void set_output_matrices(void *matrices, int iter_matrix_stride, int matrix_row_stride) override; |
| 212 | |
| 213 | /** Get the working space required to perform the transformation. */ |
| 214 | size_t get_working_space_size(unsigned int nthreads=1) const override; |
| 215 | void set_working_space(void *buffer) override; |
| 216 | |
| 217 | /** Get the window of work a given operator can perform. */ |
| 218 | unsigned int get_window() const override; |
| 219 | static constexpr unsigned int WINDOW_BLOCK = 16; // Base size of window |
| 220 | |
| 221 | /** Perform work upon a window of the input. */ |
| 222 | void run(unsigned int start, unsigned int stop, unsigned int threadid=0) override; |
| 223 | |
| 224 | protected: |
| 225 | const int _n_batches, _n_rows, _n_cols, _n_channels; |
| 226 | |
| 227 | private: |
| 228 | void transform_unpadded_tile( |
| 229 | unsigned int threadid, |
| 230 | int n_channels, |
| 231 | TOut *outptr, |
| 232 | const TIn *inptr |
| 233 | ); |
| 234 | |
| 235 | void transform_padded_tile( |
| 236 | unsigned int threadid, |
| 237 | int n_channels, |
| 238 | TOut *outptr, |
| 239 | const TIn *inptr, |
| 240 | int padding_top, |
| 241 | int padding_left, |
| 242 | int padding_bottom, |
| 243 | int padding_right |
| 244 | ); |
| 245 | |
| 246 | /* Tile implementation */ |
| 247 | static void transform_tile( |
| 248 | int n_channels, /** @param[in] Number of channels in the tensor. */ |
| 249 | const TIn* inptr_base, /** @param[in] Pointer to the base of the input tile. */ |
| 250 | int input_row_stride, /** @param[in] Stride between rows of the input tensor. */ |
| 251 | int input_col_stride, /** @param[in] Stride between columns of the input tensor. */ |
| 252 | TOut* mptr_base, /** @param[out] Base pointer to transformed input matrices. */ |
| 253 | int matrix_stride /** @param[in] Stride between matrices in the input space. */ |
| 254 | ); |
| 255 | |
| 256 | /** Get the working space for a thread. */ |
| 257 | void * get_working_space(unsigned int threadid) const; |
| 258 | |
| 259 | const TIn* _inptr; |
| 260 | TOut* _outptr; |
| 261 | |
| 262 | const int _overlap_rows, _overlap_cols; |
| 263 | const int _padding_top, _padding_left, _padding_bottom, _padding_right; |
| 264 | const int _tiles_M, _tiles_N; |
| 265 | int _matrix_stride, _matrix_row_stride, _matrix_batch_stride; |
| 266 | int _in_col_stride, _in_row_stride, _in_batch_stride; |
| 267 | |
| 268 | const int _working_space_col_stride, _working_space_row_stride; |
| 269 | TIn *_working_space; |
| 270 | }; |
| 271 | |
| 272 | template <int InnerTileRows, typename TIn, typename TOut, WinogradRoots Roots> |
| 273 | class InputTransform<InnerTileRows, 1, TIn, TOut, Roots> : |
| 274 | public InputTransform<1, InnerTileRows, TIn, TOut, Roots> |
| 275 | { |
| 276 | using Base = InputTransform<1, InnerTileRows, TIn, TOut, Roots>; |
| 277 | |
| 278 | public: |
| 279 | InputTransform( |
| 280 | int kernel_rows, /**< Number of rows in the kernel. */ |
| 281 | int kernel_cols, /**< Number of columns in the kernel. */ |
| 282 | int n_batches, /**< Number of batches in input tensor. */ |
| 283 | int n_rows, /**< Number of rows in input tensor. */ |
| 284 | int n_cols, /**< Number of columns in input tensor. */ |
| 285 | int n_channels, /**< Number of channels in input tensor. */ |
| 286 | int padding_top, /**< Padding to apply to the top of the image. */ |
| 287 | int padding_left, /**< Padding to apply to the left of the image. */ |
| 288 | int padding_bottom, /**< Padding to apply to the bottom of the image. */ |
| 289 | int padding_right /**< Padding to apply to the right of the image. */ |
| 290 | ); |
| 291 | |
| 292 | /** Set pointers to the input tensor read by the transform. */ |
| 293 | void set_input_tensor(const void *input) override; |
| 294 | void set_input_tensor(const void *input, int col_stride) override; |
| 295 | void set_input_tensor(const void *input, int row_stride, int col_stride) override; |
| 296 | void set_input_tensor(const void *input, int batch_stride, int row_stride, int col_stride) override; |
| 297 | }; |
| 298 | |
| 299 | template < |
| 300 | int KernelRows, int KernelCols, |
| 301 | int InnerTileRows, int InnerTileCols, |
| 302 | typename TIn, typename TOut, |
| 303 | WinogradRoots Roots |
| 304 | > |
| 305 | class OutputTransform : public IOutputTransform |
| 306 | { |
| 307 | public: |
| 308 | OutputTransform( |
| 309 | int n_batches, /**< Number of batches in output tensor. */ |
| 310 | int n_rows, /**< Number of rows in output tensor. */ |
| 311 | int n_cols, /**< Number of columns in output tensor. */ |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 312 | int n_channels, /**< Number of channels in output tensor. */ |
| 313 | const arm_gemm::Activation &activation |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 314 | ); |
| 315 | |
| 316 | OutputTransform(OutputTransform&) = delete; |
| 317 | OutputTransform operator=(OutputTransform&) = delete; |
| 318 | |
| 319 | /** Set pointers to the matrices read by the transform. */ |
| 320 | void set_input_matrices(const void *matrices, int iter_matrix_stride, int matrix_row_stride) override; |
| 321 | |
| 322 | /** Set pointer to the bias tensor (can be ignored or called with nullptr for no bias */ |
| 323 | void set_bias(const void *bias=nullptr) override; |
| 324 | |
| 325 | /** Set pointers to the output tensor written by the transform. */ |
| 326 | void set_output_tensor(void *output) override; |
| 327 | void set_output_tensor(void *output, int col_stride) override; |
| 328 | void set_output_tensor(void *output, int row_stride, int col_stride) override; |
| 329 | void set_output_tensor(void *output, int batch_stride, int row_stride, int col_stride) override; |
| 330 | |
| 331 | /** Get the working space required to perform the transformation. */ |
| 332 | size_t get_working_space_size(unsigned int nthreads=1) const override; |
| 333 | void set_working_space(void *buffer) override; |
| 334 | |
| 335 | /** Get the window of work a given operator can perform. */ |
| 336 | unsigned int get_window() const override; |
| 337 | static constexpr unsigned int WINDOW_BLOCK = 16; // Base size of window |
| 338 | |
| 339 | /** Perform work upon a window of the input. */ |
| 340 | void run(unsigned int start, unsigned int stop, unsigned int threadid=0) override; |
| 341 | |
| 342 | protected: |
| 343 | static constexpr int inner_tile_rows = InnerTileRows; |
| 344 | static constexpr int inner_tile_cols = InnerTileCols; |
| 345 | static constexpr int output_tile_rows = InnerTileRows - KernelRows + 1; |
| 346 | static constexpr int output_tile_cols = InnerTileCols - KernelCols + 1; |
| 347 | |
| 348 | const int _n_batches, _n_rows, _n_cols, _n_channels; |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 349 | const TOut _output_min, _output_max; |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 350 | |
| 351 | private: |
| 352 | void transform_uncropped_tile( |
| 353 | unsigned int threadid, |
| 354 | int n_channels, |
| 355 | TOut *outptr, |
| 356 | const TIn *inptr, |
| 357 | const TOut *biases |
| 358 | ); |
| 359 | |
| 360 | void transform_cropped_tile( |
| 361 | unsigned int threadid, |
| 362 | int n_channels, |
| 363 | TOut *outptr, |
| 364 | const TIn *inptr, |
| 365 | const TOut *biases, |
| 366 | int pad_bottom, |
| 367 | int pad_right |
| 368 | ); |
| 369 | |
| 370 | /** Implementation of the tile transformation method. */ |
| 371 | static void transform_tile( |
| 372 | int n_channels, |
| 373 | const TIn* matrix_base, |
| 374 | int matrix_stride, |
| 375 | const TOut* biases, |
| 376 | TOut* output, |
| 377 | int output_row_stride, |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 378 | int output_col_stride, |
| 379 | TOut output_min, |
| 380 | TOut output_max |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 381 | ); |
| 382 | |
| 383 | /** Get the working space for a thread. */ |
| 384 | void * get_working_space(unsigned int threadid) const; |
| 385 | |
| 386 | const TIn* _matrix_base; |
| 387 | const TOut* _biases; |
| 388 | int _matrix_stride, _matrix_row_stride, _matrix_batch_stride; |
| 389 | TOut* _outptr; |
| 390 | const int _tiles_M, _tiles_N; |
| 391 | int _out_col_stride, _out_row_stride, _out_batch_stride; |
| 392 | |
| 393 | const int _working_space_col_stride, _working_space_row_stride; |
| 394 | TOut *_working_space; |
| 395 | }; |
| 396 | |
| 397 | template < |
| 398 | int KernelRows, |
| 399 | int InnerTileRows, |
| 400 | typename TIn, typename TOut, |
| 401 | WinogradRoots Roots |
| 402 | > |
| 403 | class OutputTransform<KernelRows, 1, InnerTileRows, 1, TIn, TOut, Roots> : |
| 404 | public OutputTransform<1, KernelRows, 1, InnerTileRows, TIn, TOut, Roots> |
| 405 | { |
| 406 | using Base = OutputTransform<1, KernelRows, 1, InnerTileRows, TIn, TOut, Roots>; |
| 407 | |
| 408 | public: |
| 409 | OutputTransform( |
| 410 | int n_batches, /**< Number of batches in output tensor. */ |
| 411 | int n_rows, /**< Number of rows in output tensor. */ |
| 412 | int n_cols, /**< Number of columns in output tensor. */ |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 413 | int n_channels, /**< Number of channels in output tensor. */ |
| 414 | const arm_gemm::Activation &activation |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 415 | ); |
| 416 | |
| 417 | /** Set pointers to the output tensor written by the transform. */ |
| 418 | void set_output_tensor(void *output) override; |
| 419 | void set_output_tensor(void *output, int col_stride) override; |
| 420 | void set_output_tensor(void *output, int row_stride, int col_stride) override; |
| 421 | void set_output_tensor(void *output, int batch_stride, int row_stride, int col_stride) override; |
| 422 | }; |
| 423 | |
| 424 | template < |
| 425 | int KernelRows, int KernelCols, |
| 426 | int InnerTileRows, int InnerTileCols, |
| 427 | typename TIn, typename TOut, |
| 428 | WinogradRoots Roots |
| 429 | > |
| 430 | class WeightTransform : public IWeightTransform |
| 431 | { |
| 432 | public: |
| 433 | WeightTransform( |
| 434 | int n_output_channels, /**< Number of output channels in the kernel. */ |
| 435 | int n_input_channels /**< Number of input channels in the kernel. */ |
| 436 | ); |
| 437 | |
| 438 | WeightTransform(WeightTransform&) = delete; |
| 439 | WeightTransform operator=(WeightTransform&) = delete; |
| 440 | |
| 441 | /** Set pointer to the weight tensor read by the transform. */ |
| 442 | void set_weight_tensor(const void *weights) override; |
| 443 | |
| 444 | /** Set pointer to the matrices written by the transform. */ |
| 445 | void set_output_matrices(void *matrices, int inter_matrix_stride, int matrix_row_stride) override; |
| 446 | |
| 447 | /** Get the working space required to perform the transformation. */ |
| 448 | size_t get_working_space_size(unsigned int nthreads=1) const override; |
| 449 | void set_working_space(void *buffer) override; |
| 450 | |
| 451 | /** Get the window of work a given operator can perform. */ |
| 452 | unsigned int get_window() const override; |
| 453 | static constexpr unsigned int WINDOW_BLOCK = 16; // Base size of window |
| 454 | |
| 455 | /** Perform work upon a window of the input. */ |
| 456 | void run(unsigned int start, unsigned int stop, unsigned int threadid=0) override; |
| 457 | |
| 458 | protected: |
| 459 | static const int kernel_rows = KernelRows; |
| 460 | static const int kernel_cols = KernelCols; |
| 461 | static const int inner_tile_rows = InnerTileRows; |
| 462 | static const int inner_tile_cols = InnerTileCols; |
| 463 | |
| 464 | private: |
| 465 | /** Apply the transform to a tensor. */ |
| 466 | static void execute( |
| 467 | int n_output_channels, |
| 468 | int n_input_channels, |
| 469 | const TIn* input, |
| 470 | TOut* output, |
| 471 | int matrix_stride, |
| 472 | int matrix_row_stride |
| 473 | ); |
| 474 | |
| 475 | const int _n_output_channels, _n_input_channels; |
| 476 | TOut *_matrices; |
| 477 | int _matrix_stride, _matrix_row_stride; |
| 478 | const TIn *_weights; |
| 479 | }; |
| 480 | |
| 481 | template <int KernelRows, int InnerTileRows, typename TIn, typename TOut, WinogradRoots Roots> |
| 482 | class WeightTransform<KernelRows, 1, InnerTileRows, 1, TIn, TOut, Roots> : |
| 483 | public WeightTransform<1, KernelRows, 1, InnerTileRows, TIn, TOut, Roots> |
| 484 | { |
| 485 | public: |
| 486 | using WeightTransform<1, KernelRows, 1, InnerTileRows, TIn, TOut, Roots>::WeightTransform; |
| 487 | }; |
| 488 | |
| 489 | template <int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols, WinogradRoots Roots> |
| 490 | class WinogradGEMM |
| 491 | { |
| 492 | public: |
| 493 | // Information about the specific Winograd instance |
| 494 | static constexpr int output_tile_rows = OutputTileRows; |
| 495 | static constexpr int output_tile_cols = OutputTileCols; |
| 496 | static constexpr int kernel_rows = KernelRows; |
| 497 | static constexpr int kernel_cols = KernelCols; |
| 498 | static constexpr int inner_tile_rows = output_tile_rows + kernel_rows - 1; |
| 499 | static constexpr int inner_tile_cols = output_tile_cols + kernel_cols - 1; |
| 500 | static constexpr int N_GEMMS = inner_tile_rows * inner_tile_cols; |
| 501 | |
| 502 | /** Transform weights from the spatial to the Winograd domain. */ |
| 503 | template <typename TIn, typename TOut> |
| 504 | using WeightsTransform = WeightTransform< |
| 505 | KernelRows, KernelCols, inner_tile_rows, inner_tile_cols, |
| 506 | TIn, TOut, Roots |
| 507 | >; |
| 508 | |
| 509 | /** Transform input feature maps from the spatial to the Winograd domain. |
| 510 | */ |
| 511 | template <typename TIn, typename TOut> |
| 512 | using InputTransform = InputTransform< |
| 513 | inner_tile_rows, inner_tile_cols, TIn, TOut, Roots |
| 514 | >; |
| 515 | |
| 516 | /** Transform output feature maps from the Winograd to the spatial domain. |
| 517 | */ |
| 518 | template <typename TIn, typename TOut> |
| 519 | using OutputTransform = OutputTransform< |
| 520 | KernelRows, KernelCols, inner_tile_rows, inner_tile_cols, |
| 521 | TIn, TOut, Roots |
| 522 | >; |
| 523 | |
| 524 | /** Perform a convolution. |
| 525 | */ |
| 526 | template <typename TOut, typename TIn, typename TInGEMM=TIn, typename TOutGEMM=TOut> |
| 527 | class Convolution |
| 528 | { |
| 529 | public: |
| 530 | // Information about the typed Winograd instance |
| 531 | typedef TOut OutputType; |
| 532 | typedef TOutGEMM GemmOutputType; |
| 533 | typedef TInGEMM GemmInputType; |
| 534 | typedef TIn InputType; |
| 535 | |
| 536 | /** Get the output shape of a convolution. */ |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 537 | static std::pair<unsigned int, unsigned int> get_output_shape( |
| 538 | const std::pair<unsigned int, unsigned int> input_shape, |
| 539 | bool padding_same); |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 540 | |
| 541 | /** Get the memory required to store the kernel transformed into the |
| 542 | * Winograd domain. |
| 543 | */ |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 544 | static size_t get_kernel_storage_size(unsigned int n_input_channels, |
| 545 | unsigned int n_output_channels); |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 546 | |
| 547 | /** Get the memory required to store the input tensor transformed into |
| 548 | * the Winograd domain. |
| 549 | */ |
| 550 | static size_t get_input_storage_size( |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 551 | unsigned int n_batches, // Number of batches |
| 552 | unsigned int n_rows, // Number of input rows |
| 553 | unsigned int n_cols, // Number of input columns |
| 554 | unsigned int n_channels, // Number of input channels |
| 555 | bool padding_same); |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 556 | |
| 557 | /** Get the memory required to store the output tensor in the Winograd |
| 558 | * domain. |
| 559 | */ |
| 560 | static size_t get_output_storage_size( |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 561 | unsigned int n_batches, // Number of batches |
| 562 | unsigned int n_rows, // Number of output rows |
| 563 | unsigned int n_cols, // Number of output columns |
| 564 | unsigned int n_channels // Number of output channels |
| 565 | ); |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 566 | |
| 567 | /** Get the memory required to apply a Winograd operator to some input. |
| 568 | */ |
| 569 | static size_t get_working_space_size( |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 570 | unsigned int n_batches, |
| 571 | unsigned int n_rows, // Number of input rows |
| 572 | unsigned int n_cols, // Number of input columns |
| 573 | unsigned int n_input_channels, // Number of input channels |
| 574 | unsigned int n_output_channels, // Number of output channels |
| 575 | bool padding_same); |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 576 | |
| 577 | /* Get the memory required by a single "input" matrix. |
| 578 | */ |
| 579 | static size_t get_input_matrix_size( |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 580 | unsigned int n_batches, // Number of batches |
| 581 | unsigned int n_rows, // Number of input rows |
| 582 | unsigned int n_cols, // Number of input columns |
| 583 | unsigned int n_channels, // Number of input channels |
| 584 | bool padding_same); |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 585 | |
| 586 | static int get_input_matrix_stride( |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 587 | unsigned int n_batches, // Number of batches |
| 588 | unsigned int n_rows, // Number of input rows |
| 589 | unsigned int n_cols, // Number of input columns |
| 590 | unsigned int n_channels, // Number of input channels |
| 591 | bool padding_same); |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 592 | |
| 593 | /* Get the memory required by a single "output" matrix. |
| 594 | */ |
| 595 | static size_t get_output_matrix_size( |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 596 | unsigned int n_batches, // Number of batches |
| 597 | unsigned int n_rows, // Number of output rows |
| 598 | unsigned int n_cols, // Number of output columns |
| 599 | unsigned int n_channels // Number of output channels |
| 600 | ); |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 601 | |
| 602 | static int get_output_matrix_stride( |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 603 | unsigned int n_batches, // Number of batches |
| 604 | unsigned int n_rows, // Number of output rows |
| 605 | unsigned int n_cols, // Number of output columns |
| 606 | unsigned int n_channels // Number of output channels |
| 607 | ); |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 608 | |
| 609 | /* Get the memory required by a single "kernel" matrix. |
| 610 | */ |
Pablo Tello | 5264b7d | 2019-10-21 14:25:41 +0100 | [diff] [blame] | 611 | static size_t get_kernel_matrix_size(unsigned int n_input_channels, |
| 612 | unsigned int n_output_channels); |
| 613 | static int get_kernel_matrix_stride(unsigned int n_input_channels, |
| 614 | unsigned int n_output_channels); |
Pablo Tello | 8f43d74 | 2019-03-27 09:28:32 +0000 | [diff] [blame] | 615 | |
| 616 | static constexpr int M_BLOCK = 4; /** Size of block used by GEMM. */ |
| 617 | static constexpr int N_BLOCK = 16; /** Size of block used by GEMM. */ |
| 618 | }; |
| 619 | }; |
| 620 | |
| 621 | } // namespace winograd |