Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 1 | // |
Mike Kelly | 0506ef0 | 2023-01-03 16:29:44 +0000 | [diff] [blame^] | 2 | // Copyright © 2019,2021-2022 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 | |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 129 | TEST_CASE("ExpandDimsInvalidNegativeAxisTest") |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 130 | { |
| 131 | armnn::TensorShape inputShape({ 2, 3, 4 }); |
| 132 | |
| 133 | // Invalid expand dimension -5 |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 134 | CHECK_THROWS_AS(ExpandDims(inputShape, -5), armnn::InvalidArgumentException); |
Narumol Prangnawarat | 0280785 | 2019-09-11 16:43:09 +0100 | [diff] [blame] | 135 | } |
| 136 | |
Mike Kelly | 0506ef0 | 2023-01-03 16:29:44 +0000 | [diff] [blame^] | 137 | TEST_CASE("ToFloatArrayInvalidDataType") |
| 138 | { |
| 139 | armnn::TensorInfo info({ 2, 3, 4 }, armnn::DataType::BFloat16); |
| 140 | std::vector<uint8_t> data {1,2,3,4,5,6,7,8,9,10}; |
| 141 | |
| 142 | // Invalid argument |
| 143 | CHECK_THROWS_AS(ToFloatArray(data, info), armnn::InvalidArgumentException); |
| 144 | } |
| 145 | |
| 146 | TEST_CASE("ToFloatArrayQSymmS8PerAxis") |
| 147 | { |
| 148 | std::vector<float> quantizationScales { 0.1f, 0.2f, 0.3f, 0.4f }; |
| 149 | unsigned int quantizationDim = 1; |
| 150 | |
| 151 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::QSymmS8, quantizationScales, quantizationDim); |
| 152 | std::vector<uint8_t> data { 100, 120, 130, 140, 150, 160, 170 ,180, 190, 200, 210, 220 }; |
| 153 | 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 }; |
| 154 | |
| 155 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 156 | |
| 157 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 158 | { |
| 159 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 160 | } |
| 161 | } |
| 162 | |
| 163 | TEST_CASE("ToFloatArrayQSymmS8") |
| 164 | { |
| 165 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::QSymmS8, 0.1f); |
| 166 | std::vector<uint8_t> data { 100, 120, 130, 140, 150, 160, 170 ,180, 190, 200, 210, 220 }; |
| 167 | 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 }; |
| 168 | |
| 169 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 170 | |
| 171 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 172 | { |
| 173 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 174 | } |
| 175 | } |
| 176 | |
| 177 | TEST_CASE("ToFloatArrayQAsymmS8PerAxis") |
| 178 | { |
| 179 | std::vector<float> quantizationScales { 0.1f, 0.2f, 0.3f, 0.4f }; |
| 180 | unsigned int quantizationDim = 1; |
| 181 | |
| 182 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::QAsymmS8, quantizationScales, quantizationDim); |
| 183 | std::vector<uint8_t> data { 100, 120, 130, 140, 150, 160, 170 ,180, 190, 200, 210, 220 }; |
| 184 | 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 }; |
| 185 | |
| 186 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 187 | |
| 188 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 189 | { |
| 190 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 191 | } |
| 192 | } |
| 193 | |
| 194 | TEST_CASE("ToFloatArrayQAsymmS8") |
| 195 | { |
| 196 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::QAsymmS8, 0.1f); |
| 197 | std::vector<uint8_t> data { 100, 120, 130, 140, 150, 160, 170 ,180, 190, 200, 210, 220 }; |
| 198 | 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 }; |
| 199 | |
| 200 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 201 | |
| 202 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 203 | { |
| 204 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 205 | } |
| 206 | } |
| 207 | |
| 208 | TEST_CASE("ToFloatArrayQASymmU8PerAxis") |
| 209 | { |
| 210 | std::vector<float> quantizationScales { 0.1f, 0.2f, 0.3f, 0.4f }; |
| 211 | unsigned int quantizationDim = 1; |
| 212 | |
| 213 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::QAsymmU8, quantizationScales, quantizationDim); |
| 214 | std::vector<uint8_t> data { 100, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220 }; |
| 215 | 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 }; |
| 216 | |
| 217 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 218 | |
| 219 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 220 | { |
| 221 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 222 | } |
| 223 | } |
| 224 | |
| 225 | TEST_CASE("ToFloatArrayQAsymmU8") |
| 226 | { |
| 227 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::QAsymmU8, 0.1f); |
| 228 | std::vector<uint8_t> data { 100, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220 }; |
| 229 | 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 }; |
| 230 | |
| 231 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 232 | |
| 233 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 234 | { |
| 235 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 236 | } |
| 237 | } |
| 238 | |
| 239 | TEST_CASE("ToFloatArraySigned32PerAxis") |
| 240 | { |
| 241 | std::vector<float> quantizationScales { 0.1f, 0.2f, 0.3f, 0.4f }; |
| 242 | unsigned int quantizationDim = 1; |
| 243 | |
| 244 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::Signed32, quantizationScales, quantizationDim); |
| 245 | 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, |
| 246 | 170, 0, 0, 0, 180, 0, 0, 0, 190, 0, 0, 0, 200, 0, 0, 0, 210, 0, 0, 0, 220, 0, 0, 0 }; |
| 247 | 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 }; |
| 248 | |
| 249 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 250 | |
| 251 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 252 | { |
| 253 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 254 | } |
| 255 | } |
| 256 | |
| 257 | TEST_CASE("ToFloatArraySigned32") |
| 258 | { |
| 259 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::Signed32, 0.1f); |
| 260 | 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, |
| 261 | 170, 0, 0, 0, 180, 0, 0, 0, 190, 0, 0, 0, 200, 0, 0, 0, 210, 0, 0, 0, 220, 0, 0, 0 }; |
| 262 | 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 }; |
| 263 | |
| 264 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 265 | |
| 266 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 267 | { |
| 268 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 269 | } |
| 270 | } |
| 271 | |
| 272 | TEST_CASE("ToFloatArraySigned64PerAxis") |
| 273 | { |
| 274 | std::vector<float> quantizationScales { 0.1f, 0.2f, 0.3f, 0.4f }; |
| 275 | unsigned int quantizationDim = 1; |
| 276 | |
| 277 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::Signed64, quantizationScales, quantizationDim); |
| 278 | 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, |
| 279 | 140, 0, 0, 0, 0, 0, 0, 0, 150, 0, 0, 0, 0, 0, 0, 0, 160, 0, 0, 0, 0, 0, 0, 0, |
| 280 | 170, 0, 0, 0, 0, 0, 0, 0, 180, 0, 0, 0, 0, 0, 0, 0, 190, 0, 0, 0, 0, 0, 0, 0, |
| 281 | 200, 0, 0, 0, 0, 0, 0, 0, 210, 0, 0, 0, 0, 0, 0, 0, 220, 0, 0, 0, 0, 0, 0, 0 }; |
| 282 | 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 }; |
| 283 | |
| 284 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 285 | |
| 286 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 287 | { |
| 288 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 289 | } |
| 290 | } |
| 291 | |
| 292 | TEST_CASE("ToFloatArraySigned64") |
| 293 | { |
| 294 | armnn::TensorInfo info({ 3, 4 }, armnn::DataType::Signed64, 0.1f); |
| 295 | 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, |
| 296 | 140, 0, 0, 0, 0, 0, 0, 0, 150, 0, 0, 0, 0, 0, 0, 0, 160, 0, 0, 0, 0, 0, 0, 0, |
| 297 | 170, 0, 0, 0, 0, 0, 0, 0, 180, 0, 0, 0, 0, 0, 0, 0, 190, 0, 0, 0, 0, 0, 0, 0, |
| 298 | 200, 0, 0, 0, 0, 0, 0, 0, 210, 0, 0, 0, 0, 0, 0, 0, 220, 0, 0, 0, 0, 0, 0, 0 }; |
| 299 | 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 }; |
| 300 | |
| 301 | std::unique_ptr<float[]> result = ToFloatArray(data, info); |
| 302 | |
| 303 | for (uint i = 0; i < info.GetNumElements(); ++i) |
| 304 | { |
| 305 | CHECK_EQ(result[i], doctest::Approx(expected[i])); |
| 306 | } |
| 307 | } |
Sadik Armagan | 1625efc | 2021-06-10 18:24:34 +0100 | [diff] [blame] | 308 | } |