Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 1 | // |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 2 | // Copyright © 2019,2021-2023 Arm Ltd and Contributors. All rights reserved. |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 6 | #include <armnn/Types.hpp> |
| 7 | |
Matteo Martincigh | e011d20 | 2019-11-28 11:35:47 +0000 | [diff] [blame] | 8 | #include <armnnUtils/TensorUtils.hpp> |
| 9 | |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 10 | #include <doctest/doctest.h> |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 11 | |
| 12 | using namespace armnn; |
| 13 | using namespace armnnUtils; |
| 14 | |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 15 | TEST_SUITE("TensorUtilsSuite") |
| 16 | { |
| 17 | TEST_CASE("ExpandDimsAxis0Test") |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 18 | { |
| 19 | armnn::TensorShape inputShape({ 2, 3, 4 }); |
| 20 | |
| 21 | // Expand dimension 0 |
| 22 | armnn::TensorShape outputShape = ExpandDims(inputShape, 0); |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 23 | CHECK(outputShape.GetNumDimensions() == 4); |
| 24 | CHECK(outputShape[0] == 1); |
| 25 | CHECK(outputShape[1] == 2); |
| 26 | CHECK(outputShape[2] == 3); |
| 27 | CHECK(outputShape[3] == 4); |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 28 | } |
| 29 | |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 30 | TEST_CASE("ExpandDimsAxis1Test") |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 31 | { |
| 32 | armnn::TensorShape inputShape({ 2, 3, 4 }); |
| 33 | |
| 34 | // Expand dimension 1 |
| 35 | armnn::TensorShape outputShape = ExpandDims(inputShape, 1); |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 36 | CHECK(outputShape.GetNumDimensions() == 4); |
| 37 | CHECK(outputShape[0] == 2); |
| 38 | CHECK(outputShape[1] == 1); |
| 39 | CHECK(outputShape[2] == 3); |
| 40 | CHECK(outputShape[3] == 4); |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 41 | } |
| 42 | |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 43 | TEST_CASE("ExpandDimsAxis2Test") |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 44 | { |
| 45 | armnn::TensorShape inputShape({ 2, 3, 4 }); |
| 46 | |
| 47 | // Expand dimension 2 |
| 48 | armnn::TensorShape outputShape = ExpandDims(inputShape, 2); |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 49 | CHECK(outputShape.GetNumDimensions() == 4); |
| 50 | CHECK(outputShape[0] == 2); |
| 51 | CHECK(outputShape[1] == 3); |
| 52 | CHECK(outputShape[2] == 1); |
| 53 | CHECK(outputShape[3] == 4); |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 54 | } |
| 55 | |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 56 | TEST_CASE("ExpandDimsAxis3Test") |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 57 | { |
| 58 | armnn::TensorShape inputShape({ 2, 3, 4 }); |
| 59 | |
| 60 | // Expand dimension 3 |
| 61 | armnn::TensorShape outputShape = ExpandDims(inputShape, 3); |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 62 | CHECK(outputShape.GetNumDimensions() == 4); |
| 63 | CHECK(outputShape[0] == 2); |
| 64 | CHECK(outputShape[1] == 3); |
| 65 | CHECK(outputShape[2] == 4); |
| 66 | CHECK(outputShape[3] == 1); |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 67 | } |
| 68 | |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 69 | TEST_CASE("ExpandDimsNegativeAxis1Test") |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 70 | { |
| 71 | armnn::TensorShape inputShape({ 2, 3, 4 }); |
| 72 | |
| 73 | // Expand dimension -1 |
| 74 | armnn::TensorShape outputShape = ExpandDims(inputShape, -1); |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 75 | CHECK(outputShape.GetNumDimensions() == 4); |
| 76 | CHECK(outputShape[0] == 2); |
| 77 | CHECK(outputShape[1] == 3); |
| 78 | CHECK(outputShape[2] == 4); |
| 79 | CHECK(outputShape[3] == 1); |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 80 | } |
| 81 | |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 82 | TEST_CASE("ExpandDimsNegativeAxis2Test") |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 83 | { |
| 84 | armnn::TensorShape inputShape({ 2, 3, 4 }); |
| 85 | |
| 86 | // Expand dimension -2 |
| 87 | armnn::TensorShape outputShape = ExpandDims(inputShape, -2); |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 88 | CHECK(outputShape.GetNumDimensions() == 4); |
| 89 | CHECK(outputShape[0] == 2); |
| 90 | CHECK(outputShape[1] == 3); |
| 91 | CHECK(outputShape[2] == 1); |
| 92 | CHECK(outputShape[3] == 4); |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 93 | } |
| 94 | |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 95 | TEST_CASE("ExpandDimsNegativeAxis3Test") |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 96 | { |
| 97 | armnn::TensorShape inputShape({ 2, 3, 4 }); |
| 98 | |
| 99 | // Expand dimension -3 |
| 100 | armnn::TensorShape outputShape = ExpandDims(inputShape, -3); |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 101 | CHECK(outputShape.GetNumDimensions() == 4); |
| 102 | CHECK(outputShape[0] == 2); |
| 103 | CHECK(outputShape[1] == 1); |
| 104 | CHECK(outputShape[2] == 3); |
| 105 | CHECK(outputShape[3] == 4); |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 106 | } |
| 107 | |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 108 | TEST_CASE("ExpandDimsNegativeAxis4Test") |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 109 | { |
| 110 | armnn::TensorShape inputShape({ 2, 3, 4 }); |
| 111 | |
| 112 | // Expand dimension -4 |
| 113 | armnn::TensorShape outputShape = ExpandDims(inputShape, -4); |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 114 | CHECK(outputShape.GetNumDimensions() == 4); |
| 115 | CHECK(outputShape[0] == 1); |
| 116 | CHECK(outputShape[1] == 2); |
| 117 | CHECK(outputShape[2] == 3); |
| 118 | CHECK(outputShape[3] == 4); |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 119 | } |
| 120 | |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 121 | TEST_CASE("ExpandDimsInvalidAxisTest") |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 122 | { |
| 123 | armnn::TensorShape inputShape({ 2, 3, 4 }); |
| 124 | |
| 125 | // Invalid expand dimension 4 |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 126 | CHECK_THROWS_AS(ExpandDims(inputShape, 4), armnn::InvalidArgumentException); |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 127 | } |
| 128 | |
Ryan OShea | a544f0f | 2023-01-25 18:10:20 +0000 | [diff] [blame] | 129 | TEST_CASE("ExpandDimsInvalidNegativeAxisTest") |
| 130 | { |
| 131 | armnn::TensorShape inputShape({ 2, 3, 4 }); |
| 132 | |
| 133 | // Invalid expand dimension -5 |
| 134 | CHECK_THROWS_AS(ExpandDims(inputShape, -5), armnn::InvalidArgumentException); |
| 135 | } |
| 136 | |
| 137 | TEST_CASE("ExpandDimsBy1Rank") |
| 138 | { |
| 139 | armnn::TensorShape inputShape({ 2, 3, 4 }); |
| 140 | |
| 141 | // Expand by 1 dimension |
| 142 | armnn::TensorShape outputShape = ExpandDimsToRank(inputShape, 4); |
| 143 | CHECK(outputShape.GetNumDimensions() == 4); |
| 144 | CHECK(outputShape[0] == 1); |
| 145 | CHECK(outputShape[1] == 2); |
| 146 | CHECK(outputShape[2] == 3); |
| 147 | CHECK(outputShape[3] == 4); |
| 148 | } |
| 149 | |
| 150 | TEST_CASE("ExpandDimsBy2Ranks") |
| 151 | { |
| 152 | armnn::TensorShape inputShape({ 3, 4 }); |
| 153 | |
| 154 | // Expand 2 dimensions |
| 155 | armnn::TensorShape outputShape = ExpandDimsToRank(inputShape, 4); |
| 156 | CHECK(outputShape.GetNumDimensions() == 4); |
| 157 | CHECK(outputShape[0] == 1); |
| 158 | CHECK(outputShape[1] == 1); |
| 159 | CHECK(outputShape[2] == 3); |
| 160 | CHECK(outputShape[3] == 4); |
| 161 | } |
| 162 | |
| 163 | TEST_CASE("ExpandDimsBy3Ranks") |
| 164 | { |
| 165 | armnn::TensorShape inputShape({ 4 }); |
| 166 | |
| 167 | // Expand 3 dimensions |
| 168 | armnn::TensorShape outputShape = ExpandDimsToRank(inputShape, 4); |
| 169 | CHECK(outputShape.GetNumDimensions() == 4); |
| 170 | CHECK(outputShape[0] == 1); |
| 171 | CHECK(outputShape[1] == 1); |
| 172 | CHECK(outputShape[2] == 1); |
| 173 | CHECK(outputShape[3] == 4); |
| 174 | } |
| 175 | |
| 176 | TEST_CASE("ExpandDimsInvalidRankAmount") |
| 177 | { |
| 178 | armnn::TensorShape inputShape({ 2, 3, 4 }); |
| 179 | |
| 180 | // Don't expand because target rank is smaller than current rank |
| 181 | armnn::TensorShape outputShape = ExpandDimsToRank(inputShape, 2); |
| 182 | CHECK(outputShape.GetNumDimensions() == 3); |
| 183 | CHECK(outputShape[0] == 2); |
| 184 | CHECK(outputShape[1] == 3); |
| 185 | CHECK(outputShape[2] == 4); |
| 186 | } |
| 187 | |
| 188 | TEST_CASE("ExpandDimsToRankInvalidTensorShape") |
| 189 | { |
| 190 | armnn::TensorShape inputShape({ 2, 3, 4 }); |
| 191 | |
| 192 | // Throw exception because rank 6 tensors are unsupported by armnn |
| 193 | CHECK_THROWS_AS(ExpandDimsToRank(inputShape, 6), armnn::InvalidArgumentException); |
| 194 | } |
| 195 | |
| 196 | |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 197 | TEST_CASE("ReduceDimsShapeAll1s") |
| 198 | { |
| 199 | armnn::TensorShape inputShape({ 1, 1, 1 }); |
| 200 | |
Ryan OShea | a544f0f | 2023-01-25 18:10:20 +0000 | [diff] [blame] | 201 | // Reduce dimension 2 |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 202 | armnn::TensorShape outputShape = ReduceDims(inputShape, 2); |
| 203 | CHECK(outputShape.GetNumDimensions() == 2); |
| 204 | CHECK(outputShape[0] == 1); |
| 205 | CHECK(outputShape[1] == 1); |
| 206 | } |
| 207 | |
| 208 | TEST_CASE("ReduceDimsShapeNotEnough1s") |
| 209 | { |
| 210 | armnn::TensorShape inputShape({ 1, 2, 1 }); |
| 211 | |
Ryan OShea | a544f0f | 2023-01-25 18:10:20 +0000 | [diff] [blame] | 212 | // Reduce dimension 1 |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 213 | armnn::TensorShape outputShape = ReduceDims(inputShape, 1); |
| 214 | CHECK(outputShape.GetNumDimensions() == 2); |
| 215 | CHECK(outputShape[0] == 2); |
| 216 | CHECK(outputShape[1] == 1); |
| 217 | } |
| 218 | |
| 219 | TEST_CASE("ReduceDimsInfoAll1s") |
| 220 | { |
| 221 | armnn::TensorInfo inputInfo({ 1, 1, 1 }, DataType::Float32); |
| 222 | |
Ryan OShea | a544f0f | 2023-01-25 18:10:20 +0000 | [diff] [blame] | 223 | // Reduce dimension 2 |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 224 | armnn::TensorInfo outputInfo = ReduceDims(inputInfo, 2); |
| 225 | CHECK(outputInfo.GetShape().GetNumDimensions() == 2); |
| 226 | CHECK(outputInfo.GetShape()[0] == 1); |
| 227 | CHECK(outputInfo.GetShape()[1] == 1); |
| 228 | } |
| 229 | |
| 230 | TEST_CASE("ReduceDimsInfoNotEnough1s") |
| 231 | { |
| 232 | armnn::TensorInfo inputInfo({ 1, 2, 1 }, DataType::Float32); |
| 233 | |
Ryan OShea | a544f0f | 2023-01-25 18:10:20 +0000 | [diff] [blame] | 234 | // Reduce dimension 1 |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 235 | armnn::TensorInfo outputInfo = ReduceDims(inputInfo, 1); |
| 236 | CHECK(outputInfo.GetNumDimensions() == 2); |
| 237 | CHECK(outputInfo.GetShape()[0] == 2); |
| 238 | CHECK(outputInfo.GetShape()[1] == 1); |
| 239 | } |
| 240 | |
| 241 | TEST_CASE("ReduceDimsShapeDimensionGreaterThanSize") |
| 242 | { |
| 243 | armnn::TensorShape inputShape({ 1, 1, 1 }); |
| 244 | |
Ryan OShea | a544f0f | 2023-01-25 18:10:20 +0000 | [diff] [blame] | 245 | // Do not reduce because dimension does not exist |
Mike Kelly | 0e3fe10 | 2023-01-23 19:32:06 +0000 | [diff] [blame] | 246 | armnn::TensorShape outputShape = ReduceDims(inputShape, 4); |
| 247 | CHECK(outputShape.GetNumDimensions() == 3); |
| 248 | CHECK(outputShape[0] == 1); |
| 249 | CHECK(outputShape[1] == 1); |
| 250 | CHECK(outputShape[2] == 1); |
| 251 | } |
| 252 | |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 253 | |
Mike Kelly | 0506ef0 | 2023-01-03 16:29:44 +0000 | [diff] [blame] | 254 | TEST_CASE("ToFloatArrayInvalidDataType") |
| 255 | { |
| 256 | armnn::TensorInfo info({ 2, 3, 4 }, armnn::DataType::BFloat16); |
| 257 | std::vector<uint8_t> data {1,2,3,4,5,6,7,8,9,10}; |
| 258 | |
| 259 | // Invalid argument |
| 260 | CHECK_THROWS_AS(ToFloatArray(data, info), armnn::InvalidArgumentException); |
| 261 | } |
| 262 | |
| 263 | TEST_CASE("ToFloatArrayQSymmS8PerAxis") |
| 264 | { |
| 265 | std::vector<float> quantizationScales { 0.1f, 0.2f, 0.3f, 0.4f }; |
| 266 | unsigned int quantizationDim = 1; |
| 267 | |
| 268 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::QSymmS8, quantizationScales, quantizationDim); |
| 269 | std::vector<uint8_t> data { 100, 120, 130, 140, 150, 160, 170 ,180, 190, 200, 210, 220 }; |
| 270 | float expected[] { 10.0f, 24.0f, -37.8f, -46.4f, -10.6f, -19.2f, -25.8f, -30.4f, -6.6f, -11.2f, -13.8f, -14.4f }; |
| 271 | |
| 272 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 273 | |
| 274 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 275 | { |
| 276 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 277 | } |
| 278 | } |
| 279 | |
| 280 | TEST_CASE("ToFloatArrayQSymmS8") |
| 281 | { |
| 282 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::QSymmS8, 0.1f); |
| 283 | std::vector<uint8_t> data { 100, 120, 130, 140, 150, 160, 170 ,180, 190, 200, 210, 220 }; |
| 284 | float expected[] { 10.0f, 12.0f, -12.6f, -11.6f, -10.6f, -9.6f, -8.6f, -7.6f, -6.6f, -5.6f, -4.6f, -3.6f }; |
| 285 | |
| 286 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 287 | |
| 288 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 289 | { |
| 290 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 291 | } |
| 292 | } |
| 293 | |
| 294 | TEST_CASE("ToFloatArrayQAsymmS8PerAxis") |
| 295 | { |
| 296 | std::vector<float> quantizationScales { 0.1f, 0.2f, 0.3f, 0.4f }; |
| 297 | unsigned int quantizationDim = 1; |
| 298 | |
| 299 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::QAsymmS8, quantizationScales, quantizationDim); |
| 300 | std::vector<uint8_t> data { 100, 120, 130, 140, 150, 160, 170 ,180, 190, 200, 210, 220 }; |
| 301 | float expected[] { 10.0f, 24.0f, -37.8f, -46.4f, -10.6f, -19.2f, -25.8f, -30.4f, -6.6f, -11.2f, -13.8f, -14.4f }; |
| 302 | |
| 303 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 304 | |
| 305 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 306 | { |
| 307 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 308 | } |
| 309 | } |
| 310 | |
| 311 | TEST_CASE("ToFloatArrayQAsymmS8") |
| 312 | { |
| 313 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::QAsymmS8, 0.1f); |
| 314 | std::vector<uint8_t> data { 100, 120, 130, 140, 150, 160, 170 ,180, 190, 200, 210, 220 }; |
| 315 | float expected[] { 10.0f, 12.0f, -12.6f, -11.6f, -10.6f, -9.6f, -8.6f, -7.6f, -6.6f, -5.6f, -4.6f, -3.6f }; |
| 316 | |
| 317 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 318 | |
| 319 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 320 | { |
| 321 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 322 | } |
| 323 | } |
| 324 | |
| 325 | TEST_CASE("ToFloatArrayQASymmU8PerAxis") |
| 326 | { |
| 327 | std::vector<float> quantizationScales { 0.1f, 0.2f, 0.3f, 0.4f }; |
| 328 | unsigned int quantizationDim = 1; |
| 329 | |
| 330 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::QAsymmU8, quantizationScales, quantizationDim); |
| 331 | std::vector<uint8_t> data { 100, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220 }; |
| 332 | float expected[] { 10.0f, 24.0f, 39.0f, 56.0f, 15.0f, 32.0f, 51.0f, 72.0f, 19.0f, 40.0f, 63.0f, 88.0f }; |
| 333 | |
| 334 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 335 | |
| 336 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 337 | { |
| 338 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 339 | } |
| 340 | } |
| 341 | |
| 342 | TEST_CASE("ToFloatArrayQAsymmU8") |
| 343 | { |
| 344 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::QAsymmU8, 0.1f); |
| 345 | std::vector<uint8_t> data { 100, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220 }; |
| 346 | float expected[] { 10.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f }; |
| 347 | |
| 348 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 349 | |
| 350 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 351 | { |
| 352 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 353 | } |
| 354 | } |
| 355 | |
| 356 | TEST_CASE("ToFloatArraySigned32PerAxis") |
| 357 | { |
| 358 | std::vector<float> quantizationScales { 0.1f, 0.2f, 0.3f, 0.4f }; |
| 359 | unsigned int quantizationDim = 1; |
| 360 | |
| 361 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::Signed32, quantizationScales, quantizationDim); |
| 362 | std::vector<uint8_t> data { 100, 0, 0, 0, 120, 0, 0, 0, 130, 0, 0, 0, 140, 0, 0, 0, 150, 0, 0, 0, 160, 0, 0, 0, |
| 363 | 170, 0, 0, 0, 180, 0, 0, 0, 190, 0, 0, 0, 200, 0, 0, 0, 210, 0, 0, 0, 220, 0, 0, 0 }; |
| 364 | float expected[] { 10.0f, 24.0f, 39.0f, 56.0f, 15.0f, 32.0f, 51.0f, 72.0f, 19.0f, 40.0f, 63.0f, 88.0f }; |
| 365 | |
| 366 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 367 | |
| 368 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 369 | { |
| 370 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 371 | } |
| 372 | } |
| 373 | |
| 374 | TEST_CASE("ToFloatArraySigned32") |
| 375 | { |
| 376 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::Signed32, 0.1f); |
| 377 | std::vector<uint8_t> data { 100, 0, 0, 0, 120, 0, 0, 0, 130, 0, 0, 0, 140, 0, 0, 0, 150, 0, 0, 0, 160, 0, 0, 0, |
| 378 | 170, 0, 0, 0, 180, 0, 0, 0, 190, 0, 0, 0, 200, 0, 0, 0, 210, 0, 0, 0, 220, 0, 0, 0 }; |
| 379 | float expected[] { 10.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f }; |
| 380 | |
| 381 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 382 | |
| 383 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 384 | { |
| 385 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 386 | } |
| 387 | } |
| 388 | |
| 389 | TEST_CASE("ToFloatArraySigned64PerAxis") |
| 390 | { |
| 391 | std::vector<float> quantizationScales { 0.1f, 0.2f, 0.3f, 0.4f }; |
| 392 | unsigned int quantizationDim = 1; |
| 393 | |
| 394 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::Signed64, quantizationScales, quantizationDim); |
| 395 | std::vector<uint8_t> data { 100, 0, 0, 0, 0, 0, 0, 0, 120, 0, 0, 0, 0, 0, 0, 0, 130, 0, 0, 0, 0, 0, 0, 0, |
| 396 | 140, 0, 0, 0, 0, 0, 0, 0, 150, 0, 0, 0, 0, 0, 0, 0, 160, 0, 0, 0, 0, 0, 0, 0, |
| 397 | 170, 0, 0, 0, 0, 0, 0, 0, 180, 0, 0, 0, 0, 0, 0, 0, 190, 0, 0, 0, 0, 0, 0, 0, |
| 398 | 200, 0, 0, 0, 0, 0, 0, 0, 210, 0, 0, 0, 0, 0, 0, 0, 220, 0, 0, 0, 0, 0, 0, 0 }; |
| 399 | float expected[] { 10.0f, 24.0f, 39.0f, 56.0f, 15.0f, 32.0f, 51.0f, 72.0f, 19.0f, 40.0f, 63.0f, 88.0f }; |
| 400 | |
| 401 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 402 | |
| 403 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 404 | { |
| 405 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 406 | } |
| 407 | } |
| 408 | |
| 409 | TEST_CASE("ToFloatArraySigned64") |
| 410 | { |
| 411 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::Signed64, 0.1f); |
| 412 | std::vector<uint8_t> data { 100, 0, 0, 0, 0, 0, 0, 0, 120, 0, 0, 0, 0, 0, 0, 0, 130, 0, 0, 0, 0, 0, 0, 0, |
| 413 | 140, 0, 0, 0, 0, 0, 0, 0, 150, 0, 0, 0, 0, 0, 0, 0, 160, 0, 0, 0, 0, 0, 0, 0, |
| 414 | 170, 0, 0, 0, 0, 0, 0, 0, 180, 0, 0, 0, 0, 0, 0, 0, 190, 0, 0, 0, 0, 0, 0, 0, |
| 415 | 200, 0, 0, 0, 0, 0, 0, 0, 210, 0, 0, 0, 0, 0, 0, 0, 220, 0, 0, 0, 0, 0, 0, 0 }; |
| 416 | float expected[] { 10.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f }; |
| 417 | |
| 418 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 419 | |
| 420 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 421 | { |
| 422 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 423 | } |
| 424 | } |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 425 | } |