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 | #include "ReferenceCPP.h" |
| 25 | |
| 26 | #include "TensorFactory.h" |
| 27 | #include "TensorOperations.h" |
| 28 | #include "TensorVisitors.h" |
| 29 | #include "TypePrinter.h" |
| 30 | |
| 31 | #include "arm_compute/core/Coordinates.h" |
| 32 | #include "arm_compute/core/Error.h" |
| 33 | #include "arm_compute/core/TensorInfo.h" |
| 34 | #include "arm_compute/core/TensorShape.h" |
| 35 | #include "arm_compute/runtime/Tensor.h" |
| 36 | |
| 37 | #include "boost_wrapper.h" |
| 38 | |
| 39 | #include <functional> |
| 40 | #include <numeric> |
| 41 | #include <vector> |
| 42 | |
| 43 | using namespace arm_compute::test::validation::tensor_visitors; |
| 44 | |
| 45 | namespace arm_compute |
| 46 | { |
| 47 | namespace test |
| 48 | { |
| 49 | namespace validation |
| 50 | { |
Giorgio Arena | 50f9fd7 | 2017-06-19 17:05:30 +0100 | [diff] [blame] | 51 | // Sobel 3x3 |
| 52 | void ReferenceCPP::sobel_3x3(RawTensor &src, RawTensor &dst_x, RawTensor &dst_y, BorderMode border_mode, uint8_t constant_border_value) |
| 53 | { |
| 54 | ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst_x.data_type() != DataType::S16 || dst_y.data_type() != DataType::S16); |
| 55 | Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data())); |
| 56 | Tensor<int16_t> dx(dst_x.shape(), dst_x.data_type(), dst_x.fixed_point_position(), reinterpret_cast<int16_t *>(dst_x.data())); |
| 57 | Tensor<int16_t> dy(dst_y.shape(), dst_y.data_type(), dst_y.fixed_point_position(), reinterpret_cast<int16_t *>(dst_y.data())); |
| 58 | tensor_operations::sobel_3x3(s, dx, dy, border_mode, constant_border_value); |
| 59 | } |
| 60 | |
| 61 | // Sobel 5x5 |
| 62 | void ReferenceCPP::sobel_5x5(RawTensor &src, RawTensor &dst_x, RawTensor &dst_y, BorderMode border_mode, uint8_t constant_border_value) |
| 63 | { |
| 64 | ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst_x.data_type() != DataType::S16 || dst_y.data_type() != DataType::S16); |
| 65 | Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data())); |
| 66 | Tensor<int16_t> dx(dst_x.shape(), dst_x.data_type(), dst_x.fixed_point_position(), reinterpret_cast<int16_t *>(dst_x.data())); |
| 67 | Tensor<int16_t> dy(dst_y.shape(), dst_y.data_type(), dst_y.fixed_point_position(), reinterpret_cast<int16_t *>(dst_y.data())); |
| 68 | tensor_operations::sobel_5x5(s, dx, dy, border_mode, constant_border_value); |
| 69 | } |
| 70 | |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 71 | // Absolute difference |
| 72 | void ReferenceCPP::absolute_difference(const RawTensor &src1, const RawTensor &src2, RawTensor &dst) |
| 73 | { |
| 74 | const TensorVariant s1 = TensorFactory::get_tensor(src1); |
| 75 | const TensorVariant s2 = TensorFactory::get_tensor(src2); |
| 76 | TensorVariant d = TensorFactory::get_tensor(dst); |
| 77 | boost::apply_visitor(absolute_difference_visitor(), s1, s2, d); |
| 78 | } |
Giorgio Arena | f795986 | 2017-06-13 15:19:51 +0100 | [diff] [blame] | 79 | |
| 80 | // Mean and standard deviation |
| 81 | void ReferenceCPP::mean_and_standard_deviation(const RawTensor &src, float &mean, float &std_dev) |
| 82 | { |
| 83 | ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8); |
| 84 | const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data())); |
| 85 | tensor_operations::mean_and_standard_deviation(s, mean, std_dev); |
| 86 | } |
| 87 | |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 88 | // Integral image |
| 89 | void ReferenceCPP::integral_image(const RawTensor &src, RawTensor &dst) |
| 90 | { |
| 91 | ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U32); |
| 92 | const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data())); |
| 93 | Tensor<uint32_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint32_t *>(dst.data())); |
| 94 | tensor_operations::integral_image(s, d); |
| 95 | } |
Giorgio Arena | f795986 | 2017-06-13 15:19:51 +0100 | [diff] [blame] | 96 | |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 97 | // Accumulate |
| 98 | void ReferenceCPP::accumulate(const RawTensor &src, RawTensor &dst) |
| 99 | { |
| 100 | ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::S16); |
| 101 | const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data())); |
| 102 | Tensor<int16_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<int16_t *>(dst.data())); |
| 103 | tensor_operations::accumulate(s, d); |
| 104 | } |
| 105 | |
| 106 | // Accumulate squared |
| 107 | void ReferenceCPP::accumulate_squared(const RawTensor &src, RawTensor &dst, uint32_t shift) |
| 108 | { |
| 109 | ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::S16); |
| 110 | const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data())); |
| 111 | Tensor<int16_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<int16_t *>(dst.data())); |
| 112 | tensor_operations::accumulate_squared(s, d, shift); |
| 113 | } |
| 114 | |
| 115 | // Accumulate weighted |
| 116 | void ReferenceCPP::accumulate_weighted(const RawTensor &src, RawTensor &dst, float alpha) |
| 117 | { |
| 118 | ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8); |
| 119 | const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data())); |
| 120 | Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data())); |
| 121 | tensor_operations::accumulate_weighted(s, d, alpha); |
| 122 | } |
| 123 | |
| 124 | // Arithmetic addition |
| 125 | void ReferenceCPP::arithmetic_addition(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, ConvertPolicy convert_policy) |
| 126 | { |
| 127 | const TensorVariant s1 = TensorFactory::get_tensor(src1); |
| 128 | const TensorVariant s2 = TensorFactory::get_tensor(src2); |
| 129 | TensorVariant d = TensorFactory::get_tensor(dst); |
| 130 | boost::apply_visitor(arithmetic_addition_visitor(convert_policy), s1, s2, d); |
| 131 | } |
| 132 | |
| 133 | // Arithmetic subtraction |
| 134 | void ReferenceCPP::arithmetic_subtraction(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, ConvertPolicy convert_policy) |
| 135 | { |
| 136 | const TensorVariant s1 = TensorFactory::get_tensor(src1); |
| 137 | const TensorVariant s2 = TensorFactory::get_tensor(src2); |
| 138 | TensorVariant d = TensorFactory::get_tensor(dst); |
| 139 | boost::apply_visitor(arithmetic_subtraction_visitor(convert_policy), s1, s2, d); |
| 140 | } |
| 141 | |
| 142 | // Bitwise and |
| 143 | void ReferenceCPP::bitwise_and(const RawTensor &src1, const RawTensor &src2, RawTensor &dst) |
| 144 | { |
| 145 | ARM_COMPUTE_ERROR_ON(src1.data_type() != DataType::U8 || src2.data_type() != DataType::U8 || dst.data_type() != DataType::U8); |
| 146 | const Tensor<uint8_t> s1(src1.shape(), src1.data_type(), src1.fixed_point_position(), reinterpret_cast<const uint8_t *>(src1.data())); |
| 147 | const Tensor<uint8_t> s2(src2.shape(), src2.data_type(), src2.fixed_point_position(), reinterpret_cast<const uint8_t *>(src2.data())); |
| 148 | Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data())); |
| 149 | tensor_operations::bitwise_and(s1, s2, d); |
| 150 | } |
| 151 | |
| 152 | // Bitwise or |
| 153 | void ReferenceCPP::bitwise_or(const RawTensor &src1, const RawTensor &src2, RawTensor &dst) |
| 154 | { |
| 155 | ARM_COMPUTE_ERROR_ON(src1.data_type() != DataType::U8 || src2.data_type() != DataType::U8 || dst.data_type() != DataType::U8); |
| 156 | const Tensor<uint8_t> s1(src1.shape(), src1.data_type(), src1.fixed_point_position(), reinterpret_cast<const uint8_t *>(src1.data())); |
| 157 | const Tensor<uint8_t> s2(src2.shape(), src2.data_type(), src2.fixed_point_position(), reinterpret_cast<const uint8_t *>(src2.data())); |
| 158 | Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data())); |
| 159 | tensor_operations::bitwise_or(s1, s2, d); |
| 160 | } |
| 161 | |
| 162 | // Bitwise xor |
| 163 | void ReferenceCPP::bitwise_xor(const RawTensor &src1, const RawTensor &src2, RawTensor &dst) |
| 164 | { |
| 165 | ARM_COMPUTE_ERROR_ON(src1.data_type() != DataType::U8 || src2.data_type() != DataType::U8 || dst.data_type() != DataType::U8); |
| 166 | const Tensor<uint8_t> s1(src1.shape(), src1.data_type(), src1.fixed_point_position(), reinterpret_cast<const uint8_t *>(src1.data())); |
| 167 | const Tensor<uint8_t> s2(src2.shape(), src2.data_type(), src2.fixed_point_position(), reinterpret_cast<const uint8_t *>(src2.data())); |
| 168 | Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data())); |
| 169 | tensor_operations::bitwise_xor(s1, s2, d); |
| 170 | } |
| 171 | |
| 172 | // Bitwise not |
| 173 | void ReferenceCPP::bitwise_not(const RawTensor &src, RawTensor &dst) |
| 174 | { |
| 175 | ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8); |
| 176 | const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data())); |
| 177 | Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data())); |
| 178 | tensor_operations::bitwise_not(s, d); |
| 179 | } |
| 180 | |
SiCong Li | bacaf9a | 2017-06-19 13:41:45 +0100 | [diff] [blame] | 181 | // Box3x3 filter |
| 182 | void ReferenceCPP::box3x3(const RawTensor &src, RawTensor &dst, BorderMode border_mode, uint8_t constant_border_value) |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 183 | { |
| 184 | ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8); |
| 185 | const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data())); |
| 186 | Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data())); |
SiCong Li | bacaf9a | 2017-06-19 13:41:45 +0100 | [diff] [blame] | 187 | tensor_operations::box3x3(s, d, border_mode, constant_border_value); |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 188 | } |
| 189 | |
| 190 | // Depth conversion |
| 191 | void ReferenceCPP::depth_convert(const RawTensor &src, RawTensor &dst, ConvertPolicy policy, uint32_t shift) |
| 192 | { |
| 193 | const TensorVariant s = TensorFactory::get_tensor(src); |
| 194 | TensorVariant d = TensorFactory::get_tensor(dst); |
| 195 | boost::apply_visitor(tensor_visitors::depth_convert_visitor(policy, shift), s, d); |
| 196 | } |
| 197 | |
SiCong Li | 5a53664 | 2017-06-19 14:47:05 +0100 | [diff] [blame] | 198 | // Gaussian3x3 filter |
| 199 | void ReferenceCPP::gaussian3x3(const RawTensor &src, RawTensor &dst, BorderMode border_mode, uint8_t constant_border_value) |
| 200 | { |
| 201 | ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8); |
| 202 | const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data())); |
| 203 | Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data())); |
| 204 | tensor_operations::gaussian3x3(s, d, border_mode, constant_border_value); |
| 205 | } |
| 206 | |
Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 207 | // GEMM |
| 208 | void ReferenceCPP::gemm(const RawTensor &src1, const RawTensor &src2, const RawTensor &src3, |
| 209 | RawTensor &dst, float alpha, float beta) |
| 210 | { |
| 211 | const TensorVariant s1 = TensorFactory::get_tensor(src1); |
| 212 | const TensorVariant s2 = TensorFactory::get_tensor(src2); |
| 213 | const TensorVariant s3 = TensorFactory::get_tensor(src3); |
| 214 | TensorVariant d = TensorFactory::get_tensor(dst); |
| 215 | |
| 216 | boost::apply_visitor(tensor_visitors::gemm_visitor(s1, s2, s3, alpha, beta), d); |
| 217 | } |
| 218 | |
| 219 | // Pixel-wise multiplication |
| 220 | void ReferenceCPP::pixel_wise_multiplication(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, float scale, ConvertPolicy convert_policy, RoundingPolicy rounding_policy) |
| 221 | { |
| 222 | const TensorVariant s1 = TensorFactory::get_tensor(src1); |
| 223 | const TensorVariant s2 = TensorFactory::get_tensor(src2); |
| 224 | TensorVariant d = TensorFactory::get_tensor(dst); |
| 225 | boost::apply_visitor(pixel_wise_multiplication_visitor(scale, convert_policy, rounding_policy), s1, s2, d); |
| 226 | } |
| 227 | |
| 228 | // Fixed-point Pixel-wise multiplication |
| 229 | void ReferenceCPP::fixed_point_pixel_wise_multiplication(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, float scale, ConvertPolicy convert_policy, RoundingPolicy rounding_policy) |
| 230 | { |
| 231 | const TensorVariant s1 = TensorFactory::get_tensor(src1); |
| 232 | const TensorVariant s2 = TensorFactory::get_tensor(src2); |
| 233 | TensorVariant d = TensorFactory::get_tensor(dst); |
| 234 | boost::apply_visitor(tensor_visitors::fixed_point_pixel_wise_multiplication_visitor(s1, s2, scale, convert_policy, rounding_policy), d); |
| 235 | } |
| 236 | |
| 237 | // Threshold |
| 238 | void ReferenceCPP::threshold(const RawTensor &src, RawTensor &dst, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper) |
| 239 | { |
| 240 | ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8); |
| 241 | const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data())); |
| 242 | Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data())); |
| 243 | threshold_operation(s, d, threshold, false_value, true_value, type, upper); |
| 244 | } |
| 245 | |
| 246 | // Activation layer |
| 247 | void ReferenceCPP::activation_layer(const RawTensor &input, RawTensor &output, ActivationLayerInfo act_info) |
| 248 | { |
| 249 | const TensorVariant s = TensorFactory::get_tensor(input); |
| 250 | TensorVariant d = TensorFactory::get_tensor(output); |
| 251 | boost::apply_visitor(tensor_visitors::activation_layer_visitor(s, act_info), d); |
| 252 | } |
| 253 | |
| 254 | // Batch Normalization Layer |
| 255 | void ReferenceCPP::batch_normalization_layer(const RawTensor &src, RawTensor &dst, const RawTensor &mean, const RawTensor &var, const RawTensor &beta, const RawTensor &gamma, float epsilon, |
| 256 | int fixed_point_position) |
| 257 | { |
| 258 | const TensorVariant s = TensorFactory::get_tensor(src); |
| 259 | TensorVariant d = TensorFactory::get_tensor(dst); |
| 260 | const TensorVariant m = TensorFactory::get_tensor(mean); |
| 261 | const TensorVariant v = TensorFactory::get_tensor(var); |
| 262 | const TensorVariant b = TensorFactory::get_tensor(beta); |
| 263 | const TensorVariant g = TensorFactory::get_tensor(gamma); |
| 264 | boost::apply_visitor(tensor_visitors::batch_normalization_layer_visitor(s, m, v, b, g, epsilon, fixed_point_position), d); |
| 265 | } |
| 266 | |
| 267 | // Convolution Layer |
| 268 | void ReferenceCPP::convolution_layer(const RawTensor &src, const RawTensor &weights, const RawTensor &bias, RawTensor &dst, const PadStrideInfo &conv_info) |
| 269 | { |
| 270 | const TensorVariant s = TensorFactory::get_tensor(src); |
| 271 | const TensorVariant w = TensorFactory::get_tensor(weights); |
| 272 | const TensorVariant b = TensorFactory::get_tensor(bias); |
| 273 | TensorVariant d = TensorFactory::get_tensor(dst); |
| 274 | boost::apply_visitor(tensor_visitors::convolution_layer_visitor(s, w, b, conv_info), d); |
| 275 | } |
| 276 | |
| 277 | // Fully connected layer |
| 278 | void ReferenceCPP::fully_connected_layer(const RawTensor &src, const RawTensor &weights, const RawTensor &bias, RawTensor &dst) |
| 279 | { |
| 280 | const TensorVariant s = TensorFactory::get_tensor(src); |
| 281 | const TensorVariant w = TensorFactory::get_tensor(weights); |
| 282 | const TensorVariant b = TensorFactory::get_tensor(bias); |
| 283 | TensorVariant d = TensorFactory::get_tensor(dst); |
| 284 | boost::apply_visitor(tensor_visitors::fully_connected_layer_visitor(s, w, b), d); |
| 285 | } |
| 286 | |
| 287 | // Normalization Layer |
| 288 | void ReferenceCPP::normalization_layer(const RawTensor &src, RawTensor &dst, NormalizationLayerInfo norm_info) |
| 289 | { |
| 290 | const TensorVariant s = TensorFactory::get_tensor(src); |
| 291 | TensorVariant d = TensorFactory::get_tensor(dst); |
| 292 | boost::apply_visitor(tensor_visitors::normalization_layer_visitor(s, norm_info), d); |
| 293 | } |
| 294 | |
| 295 | // Pooling Layer |
| 296 | void ReferenceCPP::pooling_layer(const RawTensor &src, RawTensor &dst, PoolingLayerInfo pool_info, int fixed_point_position) |
| 297 | { |
| 298 | const TensorVariant s = TensorFactory::get_tensor(src); |
| 299 | TensorVariant d = TensorFactory::get_tensor(dst); |
| 300 | boost::apply_visitor(tensor_visitors::pooling_layer_visitor(s, pool_info, fixed_point_position), d); |
| 301 | } |
| 302 | |
| 303 | // Softmax Layer |
| 304 | void ReferenceCPP::softmax_layer(const RawTensor &src, RawTensor &dst) |
| 305 | { |
| 306 | const TensorVariant s = TensorFactory::get_tensor(src); |
| 307 | TensorVariant d = TensorFactory::get_tensor(dst); |
| 308 | boost::apply_visitor(tensor_visitors::softmax_layer_visitor(s), d); |
| 309 | } |
| 310 | |
| 311 | // Fixed point operation |
| 312 | void ReferenceCPP::fixed_point_operation(const RawTensor &src, RawTensor &dst, FixedPointOp op) |
| 313 | { |
| 314 | const TensorVariant s = TensorFactory::get_tensor(src); |
| 315 | TensorVariant d = TensorFactory::get_tensor(dst); |
| 316 | boost::apply_visitor(tensor_visitors::fixed_point_operation_visitor(s, op), d); |
| 317 | } |
| 318 | |
| 319 | } // namespace validation |
| 320 | } // namespace test |
| 321 | } // namespace arm_compute |