Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2021 Arm Ltd and Contributors. All rights reserved. |
| 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #include "ReductionTestImpl.hpp" |
| 7 | |
| 8 | #include <backendsCommon/test/DataTypeUtils.hpp> |
| 9 | #include <backendsCommon/test/TensorCopyUtils.hpp> |
| 10 | #include <backendsCommon/test/WorkloadTestUtils.hpp> |
| 11 | |
| 12 | #include <test/TensorHelpers.hpp> |
| 13 | |
| 14 | #include <iostream> |
| 15 | |
| 16 | namespace |
| 17 | { |
| 18 | |
| 19 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 20 | LayerTestResult<float, 4> ReductionTestCommon( |
| 21 | armnn::IWorkloadFactory& workloadFactory, |
| 22 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 23 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 24 | const armnn::TensorInfo inputTensorInfo, |
| 25 | const armnn::TensorInfo outputTensorInfo, |
| 26 | const std::vector<float>& inputData, |
| 27 | const std::vector<float>& outputData, |
| 28 | const std::vector<int32_t> vAxis, |
| 29 | const armnn::ReduceOperation reduceOperation, |
| 30 | bool keepDims = false) |
| 31 | { |
| 32 | IgnoreUnused(memoryManager); |
| 33 | auto inputTensor = MakeTensor<T, 4>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputData, inputTensorInfo)); |
| 34 | |
| 35 | LayerTestResult<float, 4> result(outputTensorInfo); |
| 36 | result.outputExpected = MakeTensor<float, 4>(outputTensorInfo, outputData); |
| 37 | |
| 38 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 39 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 40 | |
| 41 | armnn::ReduceQueueDescriptor descriptor; |
| 42 | std::vector<uint32_t> updated_idx; |
| 43 | uint32_t resolvedAxis = 0; |
| 44 | for (uint32_t i = 0; i < vAxis.size(); ++i) |
| 45 | { |
| 46 | if (vAxis[i] < 0) |
| 47 | { |
| 48 | resolvedAxis = inputTensorInfo.GetNumDimensions() + static_cast<uint32_t>(vAxis[i]); |
| 49 | } else |
| 50 | { |
| 51 | resolvedAxis = static_cast<uint32_t>(vAxis[i]); |
| 52 | } |
| 53 | |
| 54 | updated_idx.push_back(resolvedAxis); |
| 55 | } |
| 56 | |
| 57 | descriptor.m_Parameters.m_vAxis = updated_idx; |
| 58 | descriptor.m_Parameters.m_ReduceOperation = reduceOperation; |
| 59 | descriptor.m_Parameters.m_KeepDims = keepDims; |
| 60 | armnn::WorkloadInfo info; |
| 61 | |
| 62 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 63 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 64 | |
| 65 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateReduce(descriptor, info); |
| 66 | |
| 67 | inputHandle->Allocate(); |
| 68 | outputHandle->Allocate(); |
| 69 | |
| 70 | CopyDataToITensorHandle(inputHandle.get(), inputTensor.origin()); |
| 71 | |
| 72 | workload->Execute(); |
| 73 | |
| 74 | CopyDataFromITensorHandle(result.output.origin(), outputHandle.get()); |
| 75 | |
| 76 | return result; |
| 77 | } |
| 78 | |
| 79 | } // namespace |
| 80 | |
| 81 | template<armnn::DataType ArmnnType, typename T> |
| 82 | LayerTestResult<float, 4> ReduceMaxSimpleTest( |
| 83 | armnn::IWorkloadFactory& workloadFactory, |
| 84 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 85 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
| 86 | { |
| 87 | const armnn::TensorShape inputShape{ 1, 1, 2, 3 }; |
| 88 | const armnn::TensorShape outputShape{ 1, 1, 1, 3}; |
| 89 | |
| 90 | armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); |
| 91 | |
| 92 | if (armnn::IsQuantizedType<T>()) |
| 93 | { |
| 94 | inputTensorInfo.SetQuantizationScale(1.0f); |
| 95 | inputTensorInfo.SetQuantizationOffset(0); |
| 96 | } |
| 97 | |
| 98 | armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); |
| 99 | |
| 100 | std::vector<float> inputValues |
| 101 | ({ |
| 102 | 1001.0f, 11.0f, 1003.0f, |
| 103 | 10.0f, 1002.0f, 12.0f |
| 104 | }); |
| 105 | std::vector<float> outputValues |
| 106 | ({ |
| 107 | 1001.0f, 1002.0f, 1003.0f |
| 108 | }); |
| 109 | |
| 110 | return ReductionTestCommon<ArmnnType>(workloadFactory, |
| 111 | memoryManager, |
| 112 | tensorHandleFactory, |
| 113 | inputTensorInfo, |
| 114 | outputTensorInfo, |
| 115 | inputValues, |
| 116 | outputValues, |
| 117 | { 2 }, |
| 118 | armnn::ReduceOperation::Max); |
| 119 | } |
| 120 | |
| 121 | template<armnn::DataType ArmnnType, typename T> |
| 122 | LayerTestResult<float, 4> ReduceMaxNegativeAxisTest( |
| 123 | armnn::IWorkloadFactory& workloadFactory, |
| 124 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 125 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
| 126 | { |
| 127 | const armnn::TensorShape inputShape{ 1, 1, 2, 3 }; |
| 128 | const armnn::TensorShape outputShape{ 1, 1, 2, 1}; |
| 129 | |
| 130 | armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); |
| 131 | |
| 132 | if (armnn::IsQuantizedType<T>()) |
| 133 | { |
| 134 | inputTensorInfo.SetQuantizationScale(1.0f); |
| 135 | inputTensorInfo.SetQuantizationOffset(0); |
| 136 | } |
| 137 | |
| 138 | armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); |
| 139 | |
| 140 | std::vector<float> inputValues |
| 141 | ({ |
| 142 | 1001.0f, 11.0f, 1003.0f, |
| 143 | 10.0f, 1002.0f, 12.0f |
| 144 | }); |
| 145 | std::vector<float> outputValues |
| 146 | ({ |
| 147 | 1003.0f, 1002.0f |
| 148 | }); |
| 149 | |
| 150 | return ReductionTestCommon<ArmnnType>(workloadFactory, |
| 151 | memoryManager, |
| 152 | tensorHandleFactory, |
| 153 | inputTensorInfo, |
| 154 | outputTensorInfo, |
| 155 | inputValues, |
| 156 | outputValues, |
| 157 | { -1 }, |
| 158 | armnn::ReduceOperation::Max, |
| 159 | true); |
| 160 | } |
| 161 | |
| 162 | template<armnn::DataType ArmnnType, typename T> |
| 163 | LayerTestResult<float, 4> ReduceMaxSimpleTest2( |
| 164 | armnn::IWorkloadFactory& workloadFactory, |
| 165 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 166 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
| 167 | { |
| 168 | const armnn::TensorShape inputShape{ 1, 1, 2, 3 }; |
| 169 | const armnn::TensorShape outputShape{ 1, 1, 2, 1 }; |
| 170 | |
| 171 | armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); |
| 172 | |
| 173 | if (armnn::IsQuantizedType<T>()) |
| 174 | { |
| 175 | inputTensorInfo.SetQuantizationScale(1.0f); |
| 176 | inputTensorInfo.SetQuantizationOffset(0); |
| 177 | } |
| 178 | |
| 179 | armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); |
| 180 | |
| 181 | std::vector<float> inputValues |
| 182 | ({ |
| 183 | 1.0f, 3.0f, 2.0f, |
| 184 | 6.0f, 4.0f, 5.0f |
| 185 | }); |
| 186 | |
| 187 | std::vector<float> outputValues |
| 188 | ({ |
| 189 | 3.0f, 6.0f |
| 190 | }); |
| 191 | |
| 192 | return ReductionTestCommon<ArmnnType>(workloadFactory, |
| 193 | memoryManager, |
| 194 | tensorHandleFactory, |
| 195 | inputTensorInfo, |
| 196 | outputTensorInfo, |
| 197 | inputValues, |
| 198 | outputValues, |
| 199 | { 3 }, |
| 200 | armnn::ReduceOperation::Max, |
| 201 | true); |
| 202 | } |
| 203 | |
| 204 | template<armnn::DataType ArmnnType, typename T> |
| 205 | LayerTestResult<float, 4> ReduceMinSimpleTest( |
| 206 | armnn::IWorkloadFactory& workloadFactory, |
| 207 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 208 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
| 209 | { |
| 210 | const armnn::TensorShape inputShape { 1, 1, 2, 3 }; |
| 211 | const armnn::TensorShape outputShape { 1, 1, 1, 3}; |
| 212 | |
| 213 | armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); |
| 214 | |
| 215 | if (armnn::IsQuantizedType<T>()) |
| 216 | { |
| 217 | inputTensorInfo.SetQuantizationScale(1.0f); |
| 218 | inputTensorInfo.SetQuantizationOffset(0); |
| 219 | } |
| 220 | |
| 221 | armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); |
| 222 | |
| 223 | std::vector<float> inputValues |
| 224 | ({ |
| 225 | 1001.0f, 11.0f, 1003.0f, |
| 226 | 10.0f, 1002.0f, 12.0f |
| 227 | }); |
| 228 | std::vector<float> outputValues |
| 229 | ({ |
| 230 | 10.0f, 11.0f, 12.0f |
| 231 | }); |
| 232 | |
| 233 | return ReductionTestCommon<ArmnnType>(workloadFactory, |
| 234 | memoryManager, |
| 235 | tensorHandleFactory, |
| 236 | inputTensorInfo, |
| 237 | outputTensorInfo, |
| 238 | inputValues, |
| 239 | outputValues, |
| 240 | { 2 }, |
| 241 | armnn::ReduceOperation::Min); |
| 242 | } |
| 243 | |
| 244 | template<armnn::DataType ArmnnType, typename T> |
| 245 | LayerTestResult<float, 4> ReduceMinNegativeAxisTest( |
| 246 | armnn::IWorkloadFactory& workloadFactory, |
| 247 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 248 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
| 249 | { |
| 250 | const armnn::TensorShape inputShape{ 1, 1, 2, 3 }; |
| 251 | const armnn::TensorShape outputShape{ 1, 1, 2, 1}; |
| 252 | |
| 253 | armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); |
| 254 | |
| 255 | if (armnn::IsQuantizedType<T>()) |
| 256 | { |
| 257 | inputTensorInfo.SetQuantizationScale(1.0f); |
| 258 | inputTensorInfo.SetQuantizationOffset(0); |
| 259 | } |
| 260 | |
| 261 | armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); |
| 262 | |
| 263 | std::vector<float> inputValues |
| 264 | ({ |
| 265 | 1001.0f, 11.0f, 1003.0f, |
| 266 | 10.0f, 1002.0f, 12.0f |
| 267 | }); |
| 268 | std::vector<float> outputValues |
| 269 | ({ |
| 270 | 11.0f, 10.0f |
| 271 | }); |
| 272 | |
| 273 | return ReductionTestCommon<ArmnnType>(workloadFactory, |
| 274 | memoryManager, |
| 275 | tensorHandleFactory, |
| 276 | inputTensorInfo, |
| 277 | outputTensorInfo, |
| 278 | inputValues, |
| 279 | outputValues, |
| 280 | { -1 }, |
| 281 | armnn::ReduceOperation::Min, |
| 282 | true); |
| 283 | } |
| 284 | |
| 285 | // Explicit template specializations |
| 286 | template LayerTestResult<float, 4> |
| 287 | ReduceMaxSimpleTest<armnn::DataType::Float32>( |
| 288 | armnn::IWorkloadFactory& workloadFactory, |
| 289 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 290 | const armnn::ITensorHandleFactory& tensorHandleFactory); |
| 291 | |
| 292 | template LayerTestResult<float, 4> |
| 293 | ReduceMaxNegativeAxisTest<armnn::DataType::Float32>( |
| 294 | armnn::IWorkloadFactory& workloadFactory, |
| 295 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 296 | const armnn::ITensorHandleFactory& tensorHandleFactory); |
| 297 | |
| 298 | template LayerTestResult<float, 4> |
| 299 | ReduceMaxSimpleTest2<armnn::DataType::Float32>( |
| 300 | armnn::IWorkloadFactory& workloadFactory, |
| 301 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 302 | const armnn::ITensorHandleFactory& tensorHandleFactory); |
| 303 | |
| 304 | template LayerTestResult<float, 4> |
| 305 | ReduceMinSimpleTest<armnn::DataType::Float32>( |
| 306 | armnn::IWorkloadFactory& workloadFactory, |
| 307 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 308 | const armnn::ITensorHandleFactory& tensorHandleFactory); |
| 309 | |
| 310 | template LayerTestResult<float, 4> |
| 311 | ReduceMinNegativeAxisTest<armnn::DataType::Float32>( |
| 312 | armnn::IWorkloadFactory& workloadFactory, |
| 313 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 314 | const armnn::ITensorHandleFactory& tensorHandleFactory); |
| 315 | |