Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 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 | #ifndef __ARM_COMPUTE_TEST_REFERENCE_REFERENCE_H__ |
| 25 | #define __ARM_COMPUTE_TEST_REFERENCE_REFERENCE_H__ |
| 26 | |
| 27 | #include "RawTensor.h" |
| 28 | #include "Types.h" |
Giorgio Arena | 2ca209e | 2017-06-13 15:49:37 +0100 | [diff] [blame] | 29 | #include "arm_compute/runtime/Array.h" |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 30 | |
Isabella Gottardi | b797fa2 | 2017-06-23 15:02:11 +0100 | [diff] [blame] | 31 | #include <map> |
Georgios Pinitas | d4f8c27 | 2017-06-30 16:16:19 +0100 | [diff] [blame] | 32 | #include <vector> |
| 33 | |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 34 | namespace arm_compute |
| 35 | { |
| 36 | namespace test |
| 37 | { |
| 38 | namespace validation |
| 39 | { |
| 40 | /** Interface for reference implementations. */ |
| 41 | class Reference |
| 42 | { |
| 43 | public: |
Giorgio Arena | 50f9fd7 | 2017-06-19 17:05:30 +0100 | [diff] [blame] | 44 | /** Compute reference sobel 3x3. |
| 45 | * |
| 46 | * @param[in] shape Shape of the input and output tensors. |
| 47 | * @param[in] border_mode Border mode to use for input tensor |
| 48 | * @param[in] constant_border_value Constant value to use if @p border_mode is constant |
| 49 | * |
| 50 | * @return Computed raw tensors along x and y axis. |
| 51 | */ |
| 52 | static std::pair<RawTensor, RawTensor> compute_reference_sobel_3x3(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value); |
| 53 | /** Compute reference sobel 5x5. |
| 54 | * |
| 55 | * @param[in] shape Shape of the input and output tensors. |
| 56 | * @param[in] border_mode Border mode to use for input tensor |
| 57 | * @param[in] constant_border_value Constant value to use if @p border_mode is constant |
| 58 | * |
| 59 | * @return Computed raw tensors along x and y axis. |
| 60 | */ |
| 61 | static std::pair<RawTensor, RawTensor> compute_reference_sobel_5x5(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value); |
Giorgio Arena | fc2817d | 2017-06-27 17:26:37 +0100 | [diff] [blame] | 62 | /** Compute reference Harris corners. |
| 63 | * |
| 64 | * @param[in] shape Shape of input tensor |
| 65 | * @param[in] threshold Minimum threshold with which to eliminate Harris Corner scores (computed using the normalized Sobel kernel). |
| 66 | * @param[in] min_dist Radial Euclidean distance for the euclidean distance stage |
| 67 | * @param[in] sensitivity Sensitivity threshold k from the Harris-Stephens equation |
| 68 | * @param[in] gradient_size The gradient window size to use on the input. The implementation supports 3, 5, and 7 |
| 69 | * @param[in] block_size The block window size used to compute the Harris Corner score. The implementation supports 3, 5, and 7. |
| 70 | * @param[in] border_mode Border mode to use |
| 71 | * @param[in] constant_border_value Constant value to use for borders if border_mode is set to CONSTANT. |
| 72 | * |
| 73 | * @return Computed corners' keypoints. |
| 74 | */ |
| 75 | static KeyPointArray compute_reference_harris_corners(const TensorShape &shape, float threshold, float min_dist, float sensitivity, |
| 76 | int32_t gradient_size, int32_t block_size, BorderMode border_mode, uint8_t constant_border_value); |
Giorgio Arena | 2ca209e | 2017-06-13 15:49:37 +0100 | [diff] [blame] | 77 | /** Compute min max location. |
| 78 | * |
| 79 | * @param[in] shape Shape of the input tensors. |
| 80 | * @param[in] dt_in Data type of input tensor. |
| 81 | * @param[out] min Minimum value of tensor |
| 82 | * @param[out] max Maximum value of tensor |
| 83 | * @param[out] min_loc Array with locations of minimum values |
| 84 | * @param[out] max_loc Array with locations of maximum values |
| 85 | * @param[out] min_count Number of minimum values found |
| 86 | * @param[out] max_count Number of maximum values found |
| 87 | * |
| 88 | * @return Computed minimum, maximum values and their locations. |
| 89 | */ |
Michele Di Giorgio | ef4b4ae | 2017-07-04 17:19:43 +0100 | [diff] [blame] | 90 | static void compute_reference_min_max_location(const TensorShape &shape, DataType dt_in, void *min, void *max, IArray<Coordinates2D> &min_loc, IArray<Coordinates2D> &max_loc, |
Giorgio Arena | 935deee | 2017-06-14 13:40:36 +0100 | [diff] [blame] | 91 | uint32_t &min_count, |
Giorgio Arena | 2ca209e | 2017-06-13 15:49:37 +0100 | [diff] [blame] | 92 | uint32_t &max_count); |
Giorgio Arena | f795986 | 2017-06-13 15:19:51 +0100 | [diff] [blame] | 93 | /** Compute reference mean and standard deviation. |
| 94 | * |
| 95 | * @param[in] shape Shape of the input tensors. |
| 96 | * |
| 97 | * @return Computed mean and standard deviation. |
| 98 | */ |
| 99 | static std::pair<float, float> compute_reference_mean_and_standard_deviation(const TensorShape &shape); |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 100 | /** Compute reference integral image. |
| 101 | * |
| 102 | * @param[in] shape Shape of the input and output tensors. |
| 103 | * |
| 104 | * @return Computed raw tensor. |
| 105 | */ |
| 106 | static RawTensor compute_reference_integral_image(const TensorShape &shape); |
| 107 | /** Compute reference absolute difference. |
| 108 | * |
| 109 | * @param[in] shape Shape of the input and output tensors. |
| 110 | * @param[in] dt_in0 Data type of first input tensor. |
| 111 | * @param[in] dt_in1 Data type of second input tensor. |
| 112 | * @param[in] dt_out Data type of the output tensor. |
| 113 | * |
| 114 | * @return Computed raw tensor. |
| 115 | */ |
| 116 | static RawTensor compute_reference_absolute_difference(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out); |
| 117 | /** Compute reference accumulate. |
| 118 | * |
| 119 | * @param[in] shape Shape of the input and output tensors. |
| 120 | * |
| 121 | * @return Computed raw tensor. |
| 122 | */ |
| 123 | static RawTensor compute_reference_accumulate(const TensorShape &shape); |
| 124 | /** Compute reference accumulate. |
| 125 | * |
| 126 | * @param[in] shape Shape of the input and output tensors. |
| 127 | * @param[in] shift A uint32_t value within the range of [0, 15] |
| 128 | * |
| 129 | * @return Computed raw tensor. |
| 130 | */ |
| 131 | static RawTensor compute_reference_accumulate_squared(const TensorShape &shape, uint32_t shift); |
| 132 | /** Compute reference accumulate. |
| 133 | * |
| 134 | * @param[in] shape Shape of the input and output tensors. |
| 135 | * @param[in] alpha A float value within the range of [0, 1] |
| 136 | * |
| 137 | * @return Computed raw tensor. |
| 138 | */ |
| 139 | static RawTensor compute_reference_accumulate_weighted(const TensorShape &shape, float alpha); |
| 140 | /** Compute reference arithmetic addition. |
| 141 | * |
Michele Di Giorgio | 81f0d15 | 2017-07-11 15:00:52 +0100 | [diff] [blame] | 142 | * @param[in] shape Shape of the input and output tensors. |
| 143 | * @param[in] dt_in0 Data type of first input tensor. |
| 144 | * @param[in] dt_in1 Data type of second input tensor. |
| 145 | * @param[in] dt_out Data type of the output tensor. |
| 146 | * @param[in] convert_policy Overflow policy of the operation. |
| 147 | * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 148 | * |
| 149 | * @return Computed raw tensor. |
| 150 | */ |
Michele Di Giorgio | 81f0d15 | 2017-07-11 15:00:52 +0100 | [diff] [blame] | 151 | static RawTensor compute_reference_arithmetic_addition(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, ConvertPolicy convert_policy, int fixed_point_position = 0); |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 152 | /** Compute reference arithmetic subtraction. |
| 153 | * |
Michele Di Giorgio | 81f0d15 | 2017-07-11 15:00:52 +0100 | [diff] [blame] | 154 | * @param[in] shape Shape of the input and output tensors. |
| 155 | * @param[in] dt_in0 Data type of first input tensor. |
| 156 | * @param[in] dt_in1 Data type of second input tensor. |
| 157 | * @param[in] dt_out Data type of the output tensor. |
| 158 | * @param[in] convert_policy Overflow policy of the operation. |
| 159 | * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 160 | * |
| 161 | * @return Computed raw tensor. |
| 162 | */ |
Michele Di Giorgio | 81f0d15 | 2017-07-11 15:00:52 +0100 | [diff] [blame] | 163 | static RawTensor compute_reference_arithmetic_subtraction(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, ConvertPolicy convert_policy, int fixed_point_position = 0); |
SiCong Li | bacaf9a | 2017-06-19 13:41:45 +0100 | [diff] [blame] | 164 | /** Compute reference box3x3 filter. |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 165 | * |
SiCong Li | bacaf9a | 2017-06-19 13:41:45 +0100 | [diff] [blame] | 166 | * @param[in] shape Shape of the input and output tensors. |
| 167 | * @param[in] border_mode BorderMode used by the input tensor. |
| 168 | * @param[in] constant_border_value Constant to use if @p border_mode == CONSTANT. |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 169 | * |
| 170 | * @return Computed raw tensor. |
| 171 | */ |
SiCong Li | bacaf9a | 2017-06-19 13:41:45 +0100 | [diff] [blame] | 172 | static RawTensor compute_reference_box3x3(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value); |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 173 | /** Compute reference depth convert. |
| 174 | * |
Georgios Pinitas | e222941 | 2017-07-12 12:30:40 +0100 | [diff] [blame] | 175 | * @param[in] shape Shape of the input and output tensors. |
| 176 | * @param[in] dt_in Data type of input tensor. |
| 177 | * @param[in] dt_out Data type of the output tensor. |
| 178 | * @param[in] policy Overflow policy of the operation. |
| 179 | * @param[in] shift Value for down/up conversions. Must be 0 <= shift < 8. |
| 180 | * @param[in] fixed_point_position_in (Optional) Fixed point position for the input tensor. |
| 181 | * @param[in] fixed_point_position_out (Optional) Fixed point position for the output tensor. |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 182 | * |
| 183 | * @return Computed raw tensor. |
| 184 | */ |
Georgios Pinitas | e222941 | 2017-07-12 12:30:40 +0100 | [diff] [blame] | 185 | static RawTensor compute_reference_depth_convert(const TensorShape &shape, DataType dt_in, DataType dt_out, ConvertPolicy policy, |
| 186 | uint32_t shift, uint32_t fixed_point_position_in = 0, uint32_t fixed_point_position_out = 0); |
SiCong Li | 5a53664 | 2017-06-19 14:47:05 +0100 | [diff] [blame] | 187 | /** Compute reference gaussian3x3 filter. |
| 188 | * |
| 189 | * @param[in] shape Shape of the input and output tensors. |
| 190 | * @param[in] border_mode BorderMode used by the input tensor |
| 191 | * @param[in] constant_border_value Constant to use if @p border_mode == CONSTANT |
| 192 | * |
| 193 | * @return Computed raw tensor. |
| 194 | */ |
| 195 | static RawTensor compute_reference_gaussian3x3(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value); |
SiCong Li | 3eb263e | 2017-06-19 15:31:43 +0100 | [diff] [blame] | 196 | /** Compute reference gaussian5x5 filter. |
| 197 | * |
| 198 | * @param[in] shape Shape of the input and output tensors. |
| 199 | * @param[in] border_mode BorderMode used by the input tensor. |
| 200 | * @param[in] constant_border_value Constant to use if @p border_mode == CONSTANT. |
| 201 | * |
| 202 | * @return Computed raw tensor. |
| 203 | */ |
| 204 | static RawTensor compute_reference_gaussian5x5(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value); |
Isabella Gottardi | 3b77e9d | 2017-06-22 11:05:41 +0100 | [diff] [blame] | 205 | /** Compute reference non linear filter function |
| 206 | * |
| 207 | * @param[in] shape Shape of the input and output tensors.Data type supported: U8 |
| 208 | * @param[in] function Non linear function to perform |
| 209 | * @param[in] mask_size Mask size. Supported sizes: 3, 5 |
| 210 | * @param[in] pattern Matrix pattern |
| 211 | * @param[in] mask The given mask. Will be used only if pattern is specified to PATTERN_OTHER |
| 212 | * @param[in] border_mode Strategy to use for borders. |
| 213 | * @param[in] constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT. |
| 214 | * |
| 215 | * @return Computed raw tensor. |
| 216 | */ |
| 217 | static RawTensor compute_reference_non_linear_filter(const TensorShape &shape, NonLinearFilterFunction function, unsigned int mask_size, |
| 218 | MatrixPattern pattern, const uint8_t *mask, BorderMode border_mode, uint8_t constant_border_value = 0); |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 219 | /** Compute reference pixel-wise multiplication |
| 220 | * |
| 221 | * @param[in] shape Shape of the input and output tensors. |
| 222 | * @param[in] dt_in0 Data type of first input tensor. |
| 223 | * @param[in] dt_in1 Data type of second input tensor. |
| 224 | * @param[in] dt_out Data type of the output tensor. |
| 225 | * @param[in] scale Non-negative scale. |
| 226 | * @param[in] convert_policy Overflow policy of the operation. |
| 227 | * @param[in] rounding_policy Rounding policy of the operation. |
| 228 | * |
| 229 | * @return Computed raw tensor. |
| 230 | */ |
| 231 | static RawTensor compute_reference_pixel_wise_multiplication(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, float scale, ConvertPolicy convert_policy, |
| 232 | RoundingPolicy rounding_policy); |
| 233 | /** Compute reference pixel-wise multiplication. |
| 234 | * |
| 235 | * @param[in] shape Shape of the input and output tensors. |
| 236 | * @param[in] dt_in0 Data type of first input tensor. |
| 237 | * @param[in] dt_in1 Data type of second input tensor. |
| 238 | * @param[in] dt_out Data type of the output tensor. |
| 239 | * @param[in] scale Scale to apply after multiplication. Must be positive. |
| 240 | * @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number. |
| 241 | * @param[in] convert_policy Overflow policy of the operation. |
| 242 | * @param[in] rounding_policy Rounding policy of the operation. |
| 243 | * |
| 244 | * @return Computed raw tensor. |
| 245 | */ |
| 246 | static RawTensor compute_reference_fixed_point_pixel_wise_multiplication(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, float scale, int fixed_point_position, |
| 247 | ConvertPolicy convert_policy, RoundingPolicy rounding_policy); |
Isabella Gottardi | b797fa2 | 2017-06-23 15:02:11 +0100 | [diff] [blame] | 248 | /** Compute reference Table Lookup. |
| 249 | * |
| 250 | * @param[in] shape Shape of the input and output tensors. |
| 251 | * @param[in] dt_inout Data type of input/output tensor. |
| 252 | * @param[in] lut Input lookup table. |
| 253 | * |
| 254 | * @return Computed raw tensor. |
| 255 | */ |
| 256 | template <typename T> |
| 257 | static RawTensor compute_reference_table_lookup(const TensorShape &shape, DataType dt_inout, std::map<T, T> &lut); |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 258 | /** Compute reference threshold. |
| 259 | * |
| 260 | * @param[in] shape Shape of the input and output tensors. |
| 261 | * @param[in] threshold Threshold. When the threshold type is RANGE, this is used as the lower threshold. |
| 262 | * @param[in] false_value value to set when the condition is not respected. |
| 263 | * @param[in] true_value value to set when the condition is respected. |
| 264 | * @param[in] type Thresholding type. Either RANGE or BINARY. |
| 265 | * @param[in] upper Upper threshold. Only used when the thresholding type is RANGE. |
| 266 | * |
| 267 | * @return Computed raw tensor. |
| 268 | */ |
| 269 | static RawTensor compute_reference_threshold(const TensorShape &shape, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper); |
Isabella Gottardi | 6203153 | 2017-07-04 11:21:28 +0100 | [diff] [blame] | 270 | |
| 271 | /** Compute reference Warp Perspective. |
| 272 | * |
| 273 | * @param[in] shape Shape of the input and output tensors. |
| 274 | * @param[out] valid_mask Valid mask tensor. |
| 275 | * @param[in] matrix The perspective matrix. Must be 3x3 of type float. |
| 276 | * @param[in] policy The interpolation type. |
| 277 | * @param[in] border_mode Strategy to use for borders. |
| 278 | * @param[in] constant_border_value Constant value to use for borders if border_mode is set to CONSTANT. |
| 279 | * |
| 280 | * @return Computed raw tensor. |
| 281 | */ |
| 282 | static RawTensor compute_reference_warp_perspective(const TensorShape &shape, RawTensor &valid_mask, const float *matrix, InterpolationPolicy policy, BorderMode border_mode, |
| 283 | uint8_t constant_border_value); |
| 284 | |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 285 | /** Compute reference batch normalization layer. |
| 286 | * |
| 287 | * @param[in] shape0 Shape of the input and output tensors. |
| 288 | * @param[in] shape1 Shape of the vector tensors. |
| 289 | * @param[in] dt Data type of all input and output tensors. |
| 290 | * @param[in] epsilon Small value to avoid division with zero. |
| 291 | * @param[in] fixed_point_position Fixed point position. |
| 292 | * |
| 293 | * @return Computed raw tensor. |
| 294 | */ |
| 295 | static RawTensor compute_reference_batch_normalization_layer(const TensorShape &shape0, const TensorShape &shape1, DataType dt, float epsilon, int fixed_point_position = 0); |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 296 | /** Compute reference pooling layer. |
| 297 | * |
| 298 | * @param[in] shape_in Shape of the input tensor. |
| 299 | * @param[in] shape_out Shape of the output tensor. |
| 300 | * @param[in] dt Data type of input and output tensors. |
| 301 | * @param[in] pool_info Pooling Layer information. |
| 302 | * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers. |
| 303 | * |
| 304 | * @return Computed raw tensor. |
| 305 | */ |
| 306 | static RawTensor compute_reference_pooling_layer(const TensorShape &shape_in, const TensorShape &shape_out, DataType dt, PoolingLayerInfo pool_info, int fixed_point_position = 0); |
Georgios Pinitas | 7b7858d | 2017-06-21 16:44:24 +0100 | [diff] [blame] | 307 | /** Compute reference roi pooling layer. |
| 308 | * |
| 309 | * @param[in] shape Shape of the input tensor. |
| 310 | * @param[in] dt Data type of input and output tensors. |
| 311 | * @param[in] rois Region of interest vector. |
| 312 | * @param[in] pool_info ROI Pooling Layer information. |
| 313 | */ |
| 314 | static RawTensor compute_reference_roi_pooling_layer(const TensorShape &shape, DataType dt, const std::vector<ROI> &rois, const ROIPoolingLayerInfo &pool_info); |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 315 | /** Compute reference fixed point operation. |
| 316 | * |
| 317 | * @param[in] shape Shape of the input and output tensors. |
| 318 | * @param[in] dt_in Data type of the input tensor. |
| 319 | * @param[in] dt_out Data type of the output tensor. |
| 320 | * @param[in] op Fixed point operation to perform. |
| 321 | * @param[in] fixed_point_position Number of bits for the fractional part of the fixed point numbers |
| 322 | * |
| 323 | * @return Computed raw tensor. |
| 324 | */ |
| 325 | static RawTensor compute_reference_fixed_point_operation(const TensorShape &shape, DataType dt_in, DataType dt_out, FixedPointOp op, int fixed_point_position); |
| 326 | |
| 327 | protected: |
| 328 | Reference() = default; |
| 329 | ~Reference() = default; |
| 330 | }; |
| 331 | } // namespace validation |
| 332 | } // namespace test |
| 333 | } // namespace arm_compute |
Anthony Barbier | ac69aa1 | 2017-07-03 17:39:37 +0100 | [diff] [blame] | 334 | #endif /* __ARM_COMPUTE_TEST_REFERENCE_REFERENCE_H__ */ |