Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2016, 2017 ARM Limited. |
| 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 | #include "arm_compute/core/TensorInfo.h" |
| 25 | |
| 26 | #include "arm_compute/core/Error.h" |
| 27 | #include "arm_compute/core/HOGInfo.h" |
| 28 | #include "arm_compute/core/Helpers.h" |
Michel Iwaniec | 0063380 | 2017-10-12 14:14:15 +0100 | [diff] [blame] | 29 | #include "arm_compute/core/TensorInfo.h" |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 30 | #include "arm_compute/core/Validate.h" |
Georgios Pinitas | 283c179 | 2017-11-10 18:14:06 +0000 | [diff] [blame] | 31 | #include "support/ToolchainSupport.h" |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 32 | |
| 33 | using namespace arm_compute; |
| 34 | |
| 35 | TensorInfo::TensorInfo() |
| 36 | : _total_size(0), _fixed_point_position(0), _offset_first_element_in_bytes(0), _strides_in_bytes(), _num_channels(0), _tensor_shape(), _data_type(DataType::UNKNOWN), _format(Format::UNKNOWN), |
Michel Iwaniec | 0063380 | 2017-10-12 14:14:15 +0100 | [diff] [blame] | 37 | _is_resizable{ true }, _valid_region{ Coordinates(), _tensor_shape }, _padding{ 0 }, _quantization_info() |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 38 | { |
| 39 | } |
| 40 | |
| 41 | TensorInfo::TensorInfo(const ITensorInfo &info) |
| 42 | : TensorInfo() |
| 43 | { |
| 44 | _total_size = info.total_size(); |
| 45 | _fixed_point_position = info.fixed_point_position(); |
| 46 | _offset_first_element_in_bytes = info.offset_first_element_in_bytes(); |
| 47 | _strides_in_bytes = info.strides_in_bytes(); |
| 48 | _num_channels = info.num_channels(); |
| 49 | _tensor_shape = info.tensor_shape(); |
| 50 | _data_type = info.data_type(); |
| 51 | _format = info.format(); |
| 52 | _is_resizable = info.is_resizable(); |
| 53 | _valid_region = info.valid_region(); |
| 54 | _padding = info.padding(); |
| 55 | } |
| 56 | |
| 57 | TensorInfo::TensorInfo(Format format) |
| 58 | : TensorInfo(TensorShape(), format) |
| 59 | { |
| 60 | } |
| 61 | |
| 62 | TensorInfo::TensorInfo(unsigned int width, unsigned int height, Format format) |
| 63 | : TensorInfo(TensorShape(width, height), format) |
| 64 | { |
| 65 | } |
| 66 | |
| 67 | TensorInfo::TensorInfo(const TensorShape &tensor_shape, Format format) |
| 68 | : TensorInfo() |
| 69 | { |
| 70 | init(tensor_shape, format); |
| 71 | } |
| 72 | |
| 73 | TensorInfo::TensorInfo(size_t num_channels, DataType data_type, size_t fixed_point_position) |
| 74 | : TensorInfo() |
| 75 | { |
| 76 | init(TensorShape(), num_channels, data_type, fixed_point_position); |
| 77 | } |
| 78 | |
| 79 | TensorInfo::TensorInfo(const TensorShape &tensor_shape, size_t num_channels, DataType data_type, int fixed_point_position) |
| 80 | : TensorInfo() |
| 81 | { |
| 82 | init(tensor_shape, num_channels, data_type, fixed_point_position); |
| 83 | } |
| 84 | |
Michel Iwaniec | 0063380 | 2017-10-12 14:14:15 +0100 | [diff] [blame] | 85 | TensorInfo::TensorInfo(const TensorShape &tensor_shape, size_t num_channels, DataType data_type, QuantizationInfo quantization_info) |
| 86 | : TensorInfo() |
| 87 | { |
| 88 | init(tensor_shape, num_channels, data_type, 0); |
| 89 | _quantization_info = quantization_info; |
| 90 | } |
| 91 | |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 92 | TensorInfo::TensorInfo(const HOGInfo &hog_info, unsigned int width, unsigned int height) |
| 93 | : TensorInfo() |
| 94 | { |
| 95 | init(hog_info, width, height); |
| 96 | } |
| 97 | |
| 98 | void TensorInfo::init(Format format) |
| 99 | { |
| 100 | init(TensorShape(), format); |
| 101 | } |
| 102 | |
| 103 | void TensorInfo::init(const TensorShape &tensor_shape, Format format) |
| 104 | { |
| 105 | size_t num_channels = num_channels_from_format(format); |
| 106 | const DataType type = data_type_from_format(format); |
| 107 | |
| 108 | init(tensor_shape, num_channels, type); |
| 109 | |
| 110 | _format = format; |
| 111 | } |
| 112 | |
| 113 | void TensorInfo::init(const TensorShape &tensor_shape, Format format, |
| 114 | const Strides &strides_in_bytes, size_t offset_first_element_in_bytes, |
| 115 | size_t total_size_in_bytes) |
| 116 | { |
| 117 | size_t num_channels = num_channels_from_format(format); |
| 118 | const DataType type = data_type_from_format(format); |
| 119 | |
| 120 | init(tensor_shape, num_channels, type, strides_in_bytes, offset_first_element_in_bytes, total_size_in_bytes); |
| 121 | |
| 122 | _format = format; |
| 123 | } |
| 124 | |
| 125 | void TensorInfo::init(size_t num_channels, DataType data_type, size_t fixed_point_position) |
| 126 | { |
| 127 | init(TensorShape(), num_channels, data_type, fixed_point_position); |
| 128 | } |
| 129 | |
| 130 | void TensorInfo::init(const TensorShape &tensor_shape, size_t num_channels, DataType data_type, int fixed_point_position) |
| 131 | { |
| 132 | ARM_COMPUTE_ERROR_ON(num_channels == 0); |
| 133 | ARM_COMPUTE_ERROR_ON(data_type == DataType::QS8 && (fixed_point_position < 1 || fixed_point_position > 6)); |
| 134 | ARM_COMPUTE_ERROR_ON(data_type == DataType::QS16 && (fixed_point_position < 1 || fixed_point_position > 14)); |
| 135 | |
| 136 | _fixed_point_position = fixed_point_position; |
| 137 | _data_type = data_type; |
| 138 | _num_channels = num_channels; |
| 139 | _format = Format::UNKNOWN; |
| 140 | |
| 141 | set_tensor_shape(tensor_shape); |
| 142 | } |
| 143 | |
| 144 | void TensorInfo::init(const TensorShape &tensor_shape, size_t num_channels, DataType data_type, |
| 145 | const Strides &strides_in_bytes, size_t offset_first_element_in_bytes, |
| 146 | size_t total_size_in_bytes, int fixed_point_position) |
| 147 | { |
| 148 | ARM_COMPUTE_ERROR_ON(num_channels == 0); |
| 149 | ARM_COMPUTE_ERROR_ON(data_type == DataType::QS8 && (fixed_point_position < 1 || fixed_point_position > 6)); |
| 150 | ARM_COMPUTE_ERROR_ON(data_type == DataType::QS16 && (fixed_point_position < 1 || fixed_point_position > 14)); |
| 151 | |
| 152 | _fixed_point_position = fixed_point_position; |
| 153 | _data_type = data_type; |
| 154 | _num_channels = num_channels; |
| 155 | _format = Format::UNKNOWN; |
| 156 | _tensor_shape = tensor_shape; |
| 157 | _offset_first_element_in_bytes = offset_first_element_in_bytes; |
| 158 | _strides_in_bytes = strides_in_bytes; |
| 159 | _total_size = total_size_in_bytes; |
| 160 | |
| 161 | Coordinates coordinates; |
| 162 | coordinates.set_num_dimensions(_tensor_shape.num_dimensions()); |
| 163 | _valid_region = ValidRegion{ coordinates, _tensor_shape }; |
| 164 | } |
| 165 | |
| 166 | void TensorInfo::init(const HOGInfo &hog_info, unsigned int width, unsigned int height) |
| 167 | { |
| 168 | // Number of cells for each block |
| 169 | const Size2D num_cells_per_block = hog_info.num_cells_per_block(); |
| 170 | |
| 171 | // Tensor Size = (Number of horizontal blocks) * (Number of vertical blocks ) |
| 172 | const Size2D num_blocks_per_img = hog_info.num_blocks_per_image(Size2D(width, height)); |
| 173 | |
| 174 | // Number of tensor channels = (Number of cells per block) * (Number of bins per cell) |
| 175 | const size_t num_channels = num_cells_per_block.area() * hog_info.num_bins(); |
| 176 | |
| 177 | init(TensorShape(num_blocks_per_img.width, num_blocks_per_img.height), num_channels, DataType::F32); |
| 178 | } |
| 179 | |
| 180 | size_t TensorInfo::init_auto_padding(const TensorShape &tensor_shape, Format format) |
| 181 | { |
| 182 | const size_t num_channels = num_channels_from_format(format); |
| 183 | const DataType type = data_type_from_format(format); |
| 184 | size_t total_size = init_auto_padding(tensor_shape, num_channels, type); |
| 185 | |
| 186 | _format = format; |
| 187 | |
| 188 | return total_size; |
| 189 | } |
| 190 | |
| 191 | size_t TensorInfo::init_auto_padding(const TensorShape &tensor_shape, size_t num_channels, DataType data_type, int fixed_point_position) |
| 192 | { |
| 193 | ARM_COMPUTE_ERROR_ON(num_channels == 0); |
| 194 | ARM_COMPUTE_ERROR_ON(data_type == DataType::QS8 && (fixed_point_position < 1 || fixed_point_position > 6)); |
| 195 | ARM_COMPUTE_ERROR_ON(data_type == DataType::QS16 && (fixed_point_position < 1 || fixed_point_position > 14)); |
| 196 | |
| 197 | _fixed_point_position = fixed_point_position; |
| 198 | _data_type = data_type; |
| 199 | _num_channels = num_channels; |
| 200 | _format = Format::UNKNOWN; |
| 201 | _tensor_shape = tensor_shape; |
| 202 | |
| 203 | Coordinates coordinates; |
| 204 | coordinates.set_num_dimensions(_tensor_shape.num_dimensions()); |
| 205 | _valid_region = ValidRegion{ coordinates, _tensor_shape }; |
| 206 | |
| 207 | auto_padding(); |
| 208 | |
| 209 | return _total_size; |
| 210 | } |
| 211 | |
| 212 | size_t TensorInfo::init_auto_padding(const HOGInfo &hog_info, unsigned int width, unsigned int height) |
| 213 | { |
| 214 | // Number of cells for each block |
| 215 | const Size2D num_cells_per_block = hog_info.num_cells_per_block(); |
| 216 | |
| 217 | // Tensor Size = (Number of horizontal blocks) * (Number of vertical blocks ) |
| 218 | const Size2D num_blocks_per_img = hog_info.num_blocks_per_image(Size2D(width, height)); |
| 219 | |
| 220 | // Number of tensor channels = (Number of cells per block) * (Number of bins per cell) |
| 221 | const size_t num_channels = num_cells_per_block.area() * hog_info.num_bins(); |
| 222 | |
| 223 | return init_auto_padding(TensorShape(num_blocks_per_img.width, num_blocks_per_img.height), num_channels, DataType::F32); |
| 224 | } |
| 225 | |
| 226 | bool TensorInfo::auto_padding() |
| 227 | { |
| 228 | ARM_COMPUTE_ERROR_ON(!_is_resizable); |
| 229 | |
| 230 | // Some kernels compute 32 elements at the time, worst case scenario they |
| 231 | // will read 32 values after the last element |
| 232 | const size_t extra_pad_x = _tensor_shape.num_dimensions() < 1 ? 0 : 32; |
| 233 | const size_t pad_x = _tensor_shape.num_dimensions() < 1 ? 0 : 4; |
| 234 | const size_t pad_y = _tensor_shape.num_dimensions() < 2 ? 0 : 4; |
| 235 | |
| 236 | return extend_padding(PaddingSize(pad_y, pad_x + extra_pad_x, pad_y, pad_x)); |
| 237 | } |
| 238 | |
| 239 | std::tuple<Strides, size_t, size_t> TensorInfo::calculate_padding_requirements(const PaddingSize &padding) |
| 240 | { |
| 241 | // Calculate resulting stride for the X, Y and Z dimension |
| 242 | const size_t stride_x = element_size(); |
| 243 | const size_t stride_y = (padding.left + _tensor_shape[0] + padding.right) * stride_x; |
| 244 | const size_t stride_z = (padding.top + _tensor_shape[1] + padding.bottom) * stride_y; |
| 245 | |
| 246 | Strides required_strides; |
| 247 | size_t required_total_size = 0; |
| 248 | const size_t required_offset_first_element = padding.left * stride_x + padding.top * stride_y; |
| 249 | |
| 250 | switch(_tensor_shape.num_dimensions()) |
| 251 | { |
| 252 | case 0: |
| 253 | { |
| 254 | if(_tensor_shape.total_size() > 0) |
| 255 | { |
Gian Marco Iodice | ee94f6a | 2017-09-11 17:38:02 +0100 | [diff] [blame] | 256 | required_strides = Strides(stride_x, stride_x); |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 257 | required_total_size = stride_z; |
| 258 | } |
| 259 | break; |
| 260 | } |
| 261 | case 1: |
Gian Marco Iodice | ee94f6a | 2017-09-11 17:38:02 +0100 | [diff] [blame] | 262 | required_strides = compute_strides(*this, stride_x, stride_y); |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 263 | required_total_size = stride_z; |
| 264 | break; |
| 265 | case 2: |
| 266 | required_strides = compute_strides(*this, stride_x, stride_y); |
| 267 | required_total_size = stride_z; |
| 268 | break; |
| 269 | default: |
| 270 | { |
| 271 | required_strides = compute_strides(*this, stride_x, stride_y, stride_z); |
| 272 | |
| 273 | const unsigned int idx_last_dimension = _tensor_shape.num_dimensions() - 1; |
| 274 | |
| 275 | required_total_size = _tensor_shape[idx_last_dimension] * required_strides[idx_last_dimension]; |
| 276 | break; |
| 277 | } |
| 278 | } |
| 279 | |
| 280 | return std::make_tuple(required_strides, required_offset_first_element, required_total_size); |
| 281 | } |
| 282 | |
| 283 | bool TensorInfo::extend_padding(const PaddingSize &padding) |
| 284 | { |
| 285 | ARM_COMPUTE_ERROR_ON(!_is_resizable); |
| 286 | |
| 287 | bool updated = false; |
| 288 | |
| 289 | if(padding.top > _padding.top) |
| 290 | { |
| 291 | _padding.top = padding.top; |
| 292 | updated = true; |
| 293 | } |
| 294 | |
| 295 | if(padding.right > _padding.right) |
| 296 | { |
| 297 | _padding.right = padding.right; |
| 298 | updated = true; |
| 299 | } |
| 300 | |
| 301 | if(padding.bottom > _padding.bottom) |
| 302 | { |
| 303 | _padding.bottom = padding.bottom; |
| 304 | updated = true; |
| 305 | } |
| 306 | |
| 307 | if(padding.left > _padding.left) |
| 308 | { |
| 309 | _padding.left = padding.left; |
| 310 | updated = true; |
| 311 | } |
| 312 | |
| 313 | std::tie(_strides_in_bytes, _offset_first_element_in_bytes, _total_size) = calculate_padding_requirements(_padding); |
| 314 | |
| 315 | return updated; |
| 316 | } |
| 317 | |
Georgios Pinitas | 283c179 | 2017-11-10 18:14:06 +0000 | [diff] [blame] | 318 | std::unique_ptr<ITensorInfo> TensorInfo::clone() const |
| 319 | { |
| 320 | return support::cpp14::make_unique<TensorInfo>(*this); |
| 321 | } |
| 322 | |
| 323 | ITensorInfo &TensorInfo::set_data_type(DataType data_type) |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 324 | { |
| 325 | _data_type = data_type; |
| 326 | _format = Format::UNKNOWN; |
Georgios Pinitas | 283c179 | 2017-11-10 18:14:06 +0000 | [diff] [blame] | 327 | return *this; |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 328 | } |
| 329 | |
Georgios Pinitas | 283c179 | 2017-11-10 18:14:06 +0000 | [diff] [blame] | 330 | ITensorInfo &TensorInfo::set_num_channels(int num_channels) |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 331 | { |
| 332 | _num_channels = num_channels; |
| 333 | _format = Format::UNKNOWN; |
Georgios Pinitas | 283c179 | 2017-11-10 18:14:06 +0000 | [diff] [blame] | 334 | return *this; |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 335 | } |
| 336 | |
Georgios Pinitas | 283c179 | 2017-11-10 18:14:06 +0000 | [diff] [blame] | 337 | ITensorInfo &TensorInfo::set_format(Format format) |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 338 | { |
| 339 | _format = format; |
| 340 | |
| 341 | if(_data_type == DataType::UNKNOWN) |
| 342 | { |
| 343 | _num_channels = num_channels_from_format(format); |
| 344 | _data_type = data_type_from_format(format); |
| 345 | } |
| 346 | else |
| 347 | { |
| 348 | ARM_COMPUTE_ERROR_ON(num_channels_from_format(format) != _num_channels); |
| 349 | ARM_COMPUTE_ERROR_ON(data_type_from_format(format) != _data_type); |
| 350 | } |
Georgios Pinitas | 283c179 | 2017-11-10 18:14:06 +0000 | [diff] [blame] | 351 | return *this; |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 352 | } |
| 353 | |
Georgios Pinitas | 283c179 | 2017-11-10 18:14:06 +0000 | [diff] [blame] | 354 | ITensorInfo &TensorInfo::set_tensor_shape(TensorShape shape) |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 355 | { |
| 356 | _tensor_shape = shape; |
| 357 | _offset_first_element_in_bytes = 0; |
| 358 | _strides_in_bytes = compute_strides(*this); |
| 359 | |
| 360 | if(_tensor_shape.num_dimensions() == 0) |
| 361 | { |
| 362 | _total_size = _strides_in_bytes[0]; |
| 363 | } |
| 364 | else |
| 365 | { |
| 366 | const unsigned int idx_last_dimension = _tensor_shape.num_dimensions() - 1; |
| 367 | _total_size = _tensor_shape[idx_last_dimension] * _strides_in_bytes[idx_last_dimension]; |
| 368 | } |
| 369 | |
| 370 | Coordinates coordinates; |
| 371 | coordinates.set_num_dimensions(_tensor_shape.num_dimensions()); |
| 372 | _valid_region = ValidRegion{ coordinates, _tensor_shape }; |
Georgios Pinitas | 283c179 | 2017-11-10 18:14:06 +0000 | [diff] [blame] | 373 | return *this; |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 374 | } |
| 375 | |
Georgios Pinitas | 283c179 | 2017-11-10 18:14:06 +0000 | [diff] [blame] | 376 | ITensorInfo &TensorInfo::set_fixed_point_position(int fixed_point_position) |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 377 | { |
| 378 | ARM_COMPUTE_ERROR_ON(_data_type == DataType::QS8 && (fixed_point_position < 1 || fixed_point_position > 6)); |
| 379 | ARM_COMPUTE_ERROR_ON(_data_type == DataType::QS16 && (fixed_point_position < 1 || fixed_point_position > 14)); |
| 380 | _fixed_point_position = fixed_point_position; |
Georgios Pinitas | 283c179 | 2017-11-10 18:14:06 +0000 | [diff] [blame] | 381 | return *this; |
| 382 | } |
| 383 | |
| 384 | ITensorInfo &TensorInfo::set_quantization_info(QuantizationInfo quantization_info) |
| 385 | { |
| 386 | _quantization_info = quantization_info; |
| 387 | return *this; |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 388 | } |
| 389 | |
| 390 | size_t TensorInfo::offset_element_in_bytes(const Coordinates &pos) const |
| 391 | { |
| 392 | ARM_COMPUTE_ERROR_ON_COORDINATES_DIMENSIONS_GTE(pos, _tensor_shape.num_dimensions()); |
| 393 | |
| 394 | size_t offset = _offset_first_element_in_bytes; |
| 395 | |
| 396 | for(size_t i = 0; i < _tensor_shape.num_dimensions(); ++i) |
| 397 | { |
| 398 | offset += pos[i] * _strides_in_bytes[i]; |
| 399 | } |
| 400 | |
| 401 | return offset; |
| 402 | } |