telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2017 Arm Ltd. All rights reserved. |
David Beck | ecb56cd | 2018-09-05 12:52:57 +0100 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4 | // |
| 5 | #pragma once |
| 6 | |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 7 | #include "ActivationFixture.hpp" |
| 8 | #include "QuantizeHelper.hpp" |
| 9 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 10 | #include <armnn/ArmNN.hpp> |
| 11 | #include <armnn/Tensor.hpp> |
| 12 | #include <armnn/TypesUtils.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 13 | |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 14 | #include <backendsCommon/CpuTensorHandle.hpp> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 15 | #include <backendsCommon/IBackendInternal.hpp> |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 16 | #include <backendsCommon/WorkloadFactory.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 17 | |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 18 | #include <test/TensorHelpers.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 19 | |
| 20 | #include <algorithm> |
| 21 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 22 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 23 | LayerTestResult<T, 4> BoundedReLuTestCommon( |
| 24 | armnn::IWorkloadFactory& workloadFactory, |
| 25 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 26 | float upperBound, |
| 27 | float lowerBound, |
| 28 | float inputScale, |
| 29 | int32_t inputOffset, |
| 30 | float outputScale, |
| 31 | int32_t outputOffset, |
| 32 | const std::vector<T>& inputData, |
| 33 | const std::vector<T>& outputExpectedData, |
| 34 | unsigned int inputWidth, |
| 35 | unsigned int inputHeight, |
| 36 | unsigned int inputChannels, |
| 37 | unsigned int inputBatchSize) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 38 | { |
| 39 | unsigned int outputWidth = inputWidth; |
| 40 | unsigned int outputHeight = inputHeight; |
| 41 | unsigned int outputChannels = inputChannels; |
| 42 | unsigned int outputBatchSize = inputBatchSize; |
| 43 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 44 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 45 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 46 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 47 | |
| 48 | if(armnn::IsQuantizedType<T>()) |
| 49 | { |
| 50 | inputTensorInfo.SetQuantizationScale(inputScale); |
| 51 | inputTensorInfo.SetQuantizationOffset(inputOffset); |
| 52 | |
| 53 | outputTensorInfo.SetQuantizationScale(outputScale); |
| 54 | outputTensorInfo.SetQuantizationOffset(outputOffset); |
| 55 | } |
| 56 | |
| 57 | LayerTestResult<T, 4> result(inputTensorInfo); |
| 58 | |
| 59 | auto input = MakeTensor<T, 4>(inputTensorInfo, inputData); |
| 60 | |
| 61 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 62 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 63 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 64 | // Setup bounded ReLu. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 65 | armnn::ActivationQueueDescriptor descriptor; |
| 66 | armnn::WorkloadInfo workloadInfo; |
| 67 | AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get()); |
| 68 | AddOutputToWorkload(descriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| 69 | |
| 70 | descriptor.m_Parameters.m_Function = armnn::ActivationFunction::BoundedReLu; |
| 71 | descriptor.m_Parameters.m_A = upperBound; |
| 72 | descriptor.m_Parameters.m_B = lowerBound; |
| 73 | |
| 74 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateActivation(descriptor, workloadInfo); |
| 75 | |
| 76 | inputHandle->Allocate(); |
| 77 | outputHandle->Allocate(); |
| 78 | |
| 79 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 80 | |
| 81 | workload->Execute(); |
| 82 | |
| 83 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 84 | |
| 85 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, outputExpectedData); |
| 86 | |
| 87 | return result; |
| 88 | } |
| 89 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 90 | LayerTestResult<float, 4> BoundedReLuUpperAndLowerBoundTest( |
| 91 | armnn::IWorkloadFactory& workloadFactory, |
| 92 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 93 | { |
| 94 | unsigned int inputWidth = 4u; |
| 95 | unsigned int inputHeight = 5u; |
| 96 | unsigned int inputChannels = 1u; |
| 97 | unsigned int inputBatchSize = 1; |
| 98 | |
| 99 | std::vector<float> input = std::vector<float>{ |
| 100 | -2.0f, 0.1f, 0.5f, 1.25f, |
| 101 | 0.786f, 0.9875f, -1.5f, 0.384f, |
| 102 | 1.0001f, 3.5f, 7.5f, 0.896f, |
| 103 | 2.126f, 2.0f, 0.3f, 0.15f, |
| 104 | 0.999f, 1.2f, 0.89f, 6.1f, |
| 105 | }; |
| 106 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 107 | // Calculated manually. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 108 | std::vector<float> output = std::vector<float>{ |
| 109 | -1.0f, 0.1f, 0.5f, 1.0f, |
| 110 | 0.786f, 0.9875f, -1.0f, 0.384f, |
| 111 | 1.0f, 1.0f, 1.0f, 0.896f, |
| 112 | 1.0f, 1.0f, 0.3f, 0.15f, |
| 113 | 0.999f, 1.0f, 0.89f, 1.0f, |
| 114 | }; |
| 115 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 116 | return BoundedReLuTestCommon<armnn::DataType::Float32>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 117 | workloadFactory, memoryManager, 1.0f, -1.0f, 1.0f, 0, 1.0f, 0, input, output, |
| 118 | inputWidth, inputHeight, inputChannels, inputBatchSize); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 119 | } |
| 120 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 121 | LayerTestResult<float, 4> BoundedReLuUpperBoundOnlyTest( |
| 122 | armnn::IWorkloadFactory& workloadFactory, |
| 123 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 124 | { |
| 125 | unsigned int inputWidth = 4u; |
| 126 | unsigned int inputHeight = 5u; |
| 127 | unsigned int inputChannels = 1u; |
| 128 | unsigned int inputBatchSize = 1; |
| 129 | |
| 130 | std::vector<float> input = std::vector<float>{ |
| 131 | -1.0f, 0.1f, 0.5f, 6.25f, |
| 132 | 0.786f, 5.9875f, -0.5f, 0.384f, |
| 133 | 6.0001f, 3.5f, 7.5f, 0.896f, |
| 134 | 2.126f, 12.0f, 0.3f, 0.15f, |
| 135 | 0.999f, 1.2f, 0.89f, 6.1f, |
| 136 | }; |
| 137 | |
David Beck | ac42efd | 2018-09-26 17:41:13 +0100 | [diff] [blame] | 138 | // Calculated manually. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 139 | std::vector<float> output = std::vector<float>{ |
| 140 | 0.0f, 0.1f, 0.5f, 6.0f, |
| 141 | 0.786f, 5.9875f, 0.0f, 0.384f, |
| 142 | 6.0f, 3.5f, 6.0f, 0.896f, |
| 143 | 2.126f, 6.0f, 0.3f, 0.15f, |
| 144 | 0.999f, 1.2f, 0.89f, 6.0f, |
| 145 | }; |
| 146 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 147 | return BoundedReLuTestCommon<armnn::DataType::Float32>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 148 | workloadFactory, memoryManager, 6.0f, 0.0f, 1.0f, 0, 1.0f, 0, input, output, |
| 149 | inputWidth, inputHeight, inputChannels, inputBatchSize); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 150 | } |
| 151 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 152 | LayerTestResult<uint8_t, 4> BoundedReLuUint8UpperBoundOnlyTest( |
| 153 | armnn::IWorkloadFactory& workloadFactory, |
| 154 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 155 | { |
| 156 | unsigned int inputWidth = 3u; |
| 157 | unsigned int inputHeight = 2u; |
| 158 | unsigned int inputChannels = 1u; |
| 159 | unsigned int inputBatchSize = 1; |
| 160 | |
| 161 | std::vector<uint8_t> input = std::vector<uint8_t>{ |
| 162 | 51, 124, 28, |
| 163 | 251, 8, 92 |
| 164 | }; |
| 165 | |
David Beck | ac42efd | 2018-09-26 17:41:13 +0100 | [diff] [blame] | 166 | // Calculated manually. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 167 | std::vector<uint8_t> output = std::vector<uint8_t>{ |
| 168 | 0, 122, 0, |
| 169 | 255, 0, 58 |
| 170 | }; |
| 171 | |
| 172 | float inputScale = 12.0f / 255.0f; |
| 173 | int32_t inputOffset = 63; |
| 174 | float outputScale = 6.0f / 255.0f; |
| 175 | int32_t outputOffset = 0; |
| 176 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 177 | return BoundedReLuTestCommon<armnn::DataType::QuantisedAsymm8>( |
| 178 | workloadFactory, memoryManager, 6.0f, 0.0f, |
| 179 | inputScale, inputOffset, outputScale, outputOffset, |
| 180 | input, output, inputWidth, inputHeight, inputChannels, inputBatchSize); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 181 | } |
| 182 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 183 | LayerTestResult<uint8_t, 4> BoundedReLuUint8UpperAndLowerBoundTest( |
| 184 | armnn::IWorkloadFactory& workloadFactory, |
| 185 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 186 | { |
| 187 | unsigned int inputWidth = 3u; |
| 188 | unsigned int inputHeight = 2u; |
| 189 | unsigned int inputChannels = 1u; |
| 190 | unsigned int inputBatchSize = 1; |
| 191 | |
| 192 | std::vector<uint8_t> input = std::vector<uint8_t>{ |
| 193 | 51, 230, 28, |
| 194 | 251, 8, 92 |
| 195 | }; |
| 196 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 197 | // Calculated manually. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 198 | std::vector<uint8_t> output = std::vector<uint8_t>{ |
| 199 | 51, 192, 32, |
| 200 | 192, 32, 92 |
| 201 | }; |
| 202 | |
| 203 | int32_t inputOffset = 112; |
| 204 | float inputScale = 0.0125f; |
| 205 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 206 | return BoundedReLuTestCommon<armnn::DataType::QuantisedAsymm8>( |
| 207 | workloadFactory, memoryManager, 1.0f, -1.0f, |
| 208 | inputScale, inputOffset, inputScale, inputOffset, // Input/output scale & offset same. |
| 209 | input, output, inputWidth, inputHeight, inputChannels, inputBatchSize); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 210 | } |
| 211 | |
| 212 | namespace |
| 213 | { |
| 214 | |
| 215 | struct BoundedReLuRandomInputTestTraits |
| 216 | { |
| 217 | constexpr static unsigned int inputHeight = 31u; |
| 218 | constexpr static unsigned int inputWidth = 19u; |
| 219 | constexpr static unsigned int inputChannels = 4u; |
| 220 | constexpr static unsigned int inputBatchSize = 2; |
| 221 | |
| 222 | constexpr static unsigned int outputHeight = inputHeight; |
| 223 | constexpr static unsigned int outputWidth = inputWidth; |
| 224 | constexpr static unsigned int outputChannels = inputChannels; |
| 225 | constexpr static unsigned int outputBatchSize = inputBatchSize; |
| 226 | |
| 227 | static armnn::TensorInfo GetInputTensorInfo() |
| 228 | { |
| 229 | return armnn::TensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| 230 | armnn::DataType::Float32); |
| 231 | } |
| 232 | |
| 233 | static armnn::TensorInfo GetOutputTensorInfo() |
| 234 | { |
| 235 | return armnn::TensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| 236 | armnn::DataType::Float32); |
| 237 | } |
| 238 | }; |
| 239 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 240 | boost::multi_array<float, 4> BoundedReLuRandomInputTest( |
| 241 | armnn::IWorkloadFactory& workloadFactory, |
| 242 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 243 | float lowerBound, |
| 244 | float upperBound, |
| 245 | const armnn::ActivationDescriptor& activationDescriptor) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 246 | { |
| 247 | const armnn::TensorInfo inputTensorInfo = BoundedReLuRandomInputTestTraits::GetInputTensorInfo(); |
| 248 | const armnn::TensorInfo outputTensorInfo = BoundedReLuRandomInputTestTraits::GetOutputTensorInfo(); |
| 249 | |
| 250 | boost::multi_array<float, 4> output(GetTensorShapeAsArray<4>(outputTensorInfo)); |
| 251 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 252 | // Min/max random values passed to MakeRandomTensor are purposely outside of the ReLu |
| 253 | // range [lowerBound, upperBound]. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 254 | auto input = MakeRandomTensor<float, 4>(inputTensorInfo, 4605828, lowerBound - 5.0f, upperBound * 2.0f); |
| 255 | |
| 256 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 257 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 258 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 259 | // Set up bounded ReLu. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 260 | armnn::ActivationQueueDescriptor descriptor; |
| 261 | armnn::WorkloadInfo workloadInfo; |
| 262 | AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get()); |
| 263 | AddOutputToWorkload(descriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| 264 | descriptor.m_Parameters = activationDescriptor; |
| 265 | |
| 266 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateActivation(descriptor, workloadInfo); |
| 267 | |
| 268 | inputHandle->Allocate(); |
| 269 | outputHandle->Allocate(); |
| 270 | |
| 271 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 272 | |
| 273 | workload->Execute(); |
| 274 | |
| 275 | CopyDataFromITensorHandle(&output[0][0][0][0], outputHandle.get()); |
| 276 | |
| 277 | return output; |
| 278 | } |
| 279 | |
| 280 | } // namespace |
| 281 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 282 | LayerTestResult<float, 4> CompareBoundedReLuTest( |
| 283 | armnn::IWorkloadFactory& workloadFactory, |
| 284 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 285 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 286 | float upperBound, |
| 287 | float lowerBound) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 288 | { |
| 289 | LayerTestResult<float, 4> result(BoundedReLuRandomInputTestTraits::GetOutputTensorInfo()); |
| 290 | |
| 291 | armnn::ActivationDescriptor activationDescriptor; |
| 292 | activationDescriptor.m_Function = armnn::ActivationFunction::BoundedReLu; |
| 293 | activationDescriptor.m_A = upperBound; |
| 294 | activationDescriptor.m_B = lowerBound; |
| 295 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 296 | result.output = BoundedReLuRandomInputTest( |
| 297 | workloadFactory, memoryManager, 0.0f, upperBound, activationDescriptor); |
| 298 | result.outputExpected = BoundedReLuRandomInputTest( |
| 299 | refWorkloadFactory, nullptr, 0.0f, upperBound, activationDescriptor); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 300 | |
| 301 | return result; |
| 302 | } |
| 303 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 304 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 305 | LayerTestResult<T,4> ConstantLinearActivationTestCommon( |
| 306 | armnn::IWorkloadFactory& workloadFactory, |
| 307 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 308 | float qScale = 0.0f, |
| 309 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 310 | { |
| 311 | unsigned int inputHeight = 20; |
| 312 | unsigned int inputWidth = 17; |
| 313 | unsigned int inputChannels = 3; |
| 314 | unsigned int batchSize = 5; |
| 315 | |
| 316 | armnn::TensorInfo inputTensorInfo; |
| 317 | armnn::TensorInfo outputTensorInfo; |
| 318 | |
| 319 | unsigned int shape[] = {batchSize, inputChannels, inputHeight, inputWidth}; |
| 320 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 321 | inputTensorInfo = armnn::TensorInfo(4, shape, ArmnnType); |
| 322 | outputTensorInfo = armnn::TensorInfo(4, shape, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 323 | |
| 324 | // Set quantization parameters if the requested type is a quantized type. |
| 325 | if(armnn::IsQuantizedType<T>()) |
| 326 | { |
| 327 | inputTensorInfo.SetQuantizationScale(qScale); |
| 328 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 329 | outputTensorInfo.SetQuantizationScale(qScale); |
| 330 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 331 | } |
| 332 | |
| 333 | LayerTestResult<T, 4> ret(outputTensorInfo); |
| 334 | |
| 335 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 336 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 337 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 338 | // Do linear activation that should leave the tensor unchanged. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 339 | armnn::ActivationQueueDescriptor data; |
| 340 | armnn::WorkloadInfo info; |
| 341 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 342 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 343 | data.m_Parameters.m_A = 1.0f; |
| 344 | data.m_Parameters.m_B = 0.0f; |
| 345 | data.m_Parameters.m_Function = armnn::ActivationFunction::Linear; |
| 346 | |
| 347 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateActivation(data, info); |
| 348 | |
| 349 | inputHandle->Allocate(); |
| 350 | outputHandle->Allocate(); |
| 351 | |
| 352 | boost::multi_array<T, 4> input = MakeRandomTensor<T, 4>(inputTensorInfo, 7123561); |
| 353 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 354 | |
| 355 | workload->Execute(); |
| 356 | |
| 357 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 358 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 359 | // Ensure output equals input. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 360 | ret.outputExpected = input; |
| 361 | |
| 362 | return ret; |
| 363 | } |
| 364 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 365 | LayerTestResult<float, 4> ConstantLinearActivationTest( |
| 366 | armnn::IWorkloadFactory& workloadFactory, |
| 367 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 368 | { |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 369 | return ConstantLinearActivationTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 370 | } |
| 371 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 372 | LayerTestResult<uint8_t, 4> ConstantLinearActivationUint8Test( |
| 373 | armnn::IWorkloadFactory& workloadFactory, |
| 374 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 375 | { |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 376 | return ConstantLinearActivationTestCommon<armnn::DataType::QuantisedAsymm8>( |
| 377 | workloadFactory, memoryManager, 4.0f, 3); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 378 | } |
| 379 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 380 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 381 | LayerTestResult<T, 4> SimpleActivationTest( |
| 382 | armnn::IWorkloadFactory& workloadFactory, |
| 383 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 384 | armnn::ActivationFunction activationFunction, |
| 385 | float activationParameterA, |
| 386 | float activationParameterB, |
| 387 | float qScale, |
| 388 | int32_t qOffset, |
| 389 | const std::vector<float>& inputData, |
| 390 | const std::vector<float>& outputExpectedData) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 391 | { |
| 392 | constexpr static unsigned int inputWidth = 16u; |
| 393 | constexpr static unsigned int inputHeight = 1u; |
| 394 | constexpr static unsigned int inputChannels = 1u; |
| 395 | constexpr static unsigned int inputBatchSize = 1u; |
| 396 | |
| 397 | constexpr static unsigned int outputWidth = inputWidth; |
| 398 | constexpr static unsigned int outputHeight = inputHeight; |
| 399 | constexpr static unsigned int outputChannels = inputChannels; |
| 400 | constexpr static unsigned int outputBatchSize = inputBatchSize; |
| 401 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 402 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, ArmnnType); |
| 403 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 404 | |
| 405 | // Set quantization parameters if the requested type is a quantized type. |
| 406 | if(armnn::IsQuantizedType<T>()) |
| 407 | { |
| 408 | inputTensorInfo.SetQuantizationScale(qScale); |
| 409 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 410 | outputTensorInfo.SetQuantizationScale(qScale); |
| 411 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 412 | } |
| 413 | |
| 414 | LayerTestResult<T, 4> result(inputTensorInfo); |
| 415 | |
| 416 | auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, inputData)); |
| 417 | |
| 418 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 419 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 420 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 421 | // Setup bounded ReLu. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 422 | armnn::ActivationQueueDescriptor descriptor; |
| 423 | armnn::WorkloadInfo workloadInfo; |
| 424 | AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get()); |
| 425 | AddOutputToWorkload(descriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| 426 | |
| 427 | descriptor.m_Parameters.m_Function = activationFunction; |
| 428 | descriptor.m_Parameters.m_A = activationParameterA; |
| 429 | descriptor.m_Parameters.m_B = activationParameterB; |
| 430 | |
| 431 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateActivation(descriptor, workloadInfo); |
| 432 | |
| 433 | inputHandle->Allocate(); |
| 434 | outputHandle->Allocate(); |
| 435 | |
| 436 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 437 | |
| 438 | workload->Execute(); |
| 439 | |
| 440 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 441 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 442 | // Calculated manually. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 443 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, outputExpectedData)); |
| 444 | |
| 445 | return result; |
| 446 | } |
| 447 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 448 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 449 | LayerTestResult<T, 4> SimpleSigmoidTestCommon( |
| 450 | armnn::IWorkloadFactory& workloadFactory, |
| 451 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 452 | float qScale, |
| 453 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 454 | { |
| 455 | std::vector<float> inputData = { |
| 456 | -0.1f, -0.2f, -0.3f, -0.4f, |
| 457 | 0.1f, 0.2f, 0.3f, 0.4f, |
| 458 | -1.0f, -2.0f, -3.0f, -4.0f, |
| 459 | 1.0f, 2.0f, 3.0f, 4.0f |
| 460 | }; |
| 461 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 462 | // Calculate output values for input. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 463 | auto f = [](float value) |
| 464 | { |
| 465 | return 1.0f / (1.0f + std::exp(-value)); |
| 466 | }; |
| 467 | std::vector<float> outputExpectedData(inputData.size()); |
| 468 | std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f); |
| 469 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 470 | return SimpleActivationTest<ArmnnType>(workloadFactory, |
| 471 | memoryManager, |
| 472 | armnn::ActivationFunction::Sigmoid, |
| 473 | 0.f, |
| 474 | 0.f, |
| 475 | qScale, |
| 476 | qOffset, |
| 477 | inputData, |
| 478 | outputExpectedData); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 479 | } |
| 480 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 481 | LayerTestResult<float, 4> SimpleSigmoidTest( |
| 482 | armnn::IWorkloadFactory& workloadFactory, |
| 483 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 484 | { |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 485 | return SimpleSigmoidTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 486 | } |
| 487 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 488 | LayerTestResult<uint8_t, 4> SimpleSigmoidUint8Test( |
| 489 | armnn::IWorkloadFactory& workloadFactory, |
| 490 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 491 | { |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 492 | return SimpleSigmoidTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.1f, 50); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 493 | } |
| 494 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 495 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 496 | LayerTestResult<T,4> CompareActivationTestImpl( |
| 497 | armnn::IWorkloadFactory& workloadFactory, |
| 498 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 499 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 500 | armnn::ActivationFunction f, |
| 501 | unsigned int batchSize = 5, |
| 502 | float qScale = 0.0f, |
| 503 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 504 | { |
| 505 | unsigned int width = 17; |
| 506 | unsigned int height = 29; |
| 507 | unsigned int channels = 2; |
| 508 | |
| 509 | float a = 0.234f; |
| 510 | float b = -12.345f; |
| 511 | |
| 512 | armnn::TensorInfo inputTensorInfo; |
| 513 | armnn::TensorInfo outputTensorInfo; |
| 514 | |
| 515 | unsigned int shape[] = {batchSize, channels, height, width}; |
| 516 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 517 | inputTensorInfo = armnn::TensorInfo(4, shape, ArmnnType); |
| 518 | outputTensorInfo = armnn::TensorInfo(4, shape, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 519 | |
| 520 | // Set quantization parameters if the requested type is a quantized type. |
| 521 | if(armnn::IsQuantizedType<T>()) |
| 522 | { |
| 523 | inputTensorInfo.SetQuantizationScale(qScale); |
| 524 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 525 | outputTensorInfo.SetQuantizationScale(qScale); |
| 526 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 527 | } |
| 528 | |
| 529 | float minVal = -10.f; |
| 530 | if (f == armnn::ActivationFunction::Sqrt) |
| 531 | { |
| 532 | minVal = 0.f; |
| 533 | } |
| 534 | |
| 535 | boost::multi_array<T, 4> input = MakeRandomTensor<T, 4>(inputTensorInfo, 21453, minVal, 10.f); |
| 536 | |
| 537 | |
| 538 | LayerTestResult<T,4> ret(outputTensorInfo); |
| 539 | auto boostArrayExtents = boost::extents |
| 540 | [boost::numeric_cast<boost::multi_array_types::extent_gen::index>(batchSize)] |
| 541 | [boost::numeric_cast<boost::multi_array_types::extent_gen::index>(channels)] |
| 542 | [boost::numeric_cast<boost::multi_array_types::extent_gen::index>(height)] |
| 543 | [boost::numeric_cast<boost::multi_array_types::extent_gen::index>(width)]; |
| 544 | ret.output.resize(boostArrayExtents); |
| 545 | ret.outputExpected.resize(boostArrayExtents); |
| 546 | |
| 547 | |
| 548 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 549 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 550 | |
| 551 | std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refWorkloadFactory.CreateTensorHandle(inputTensorInfo); |
| 552 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refWorkloadFactory.CreateTensorHandle(outputTensorInfo); |
| 553 | |
| 554 | armnn::ActivationQueueDescriptor data; |
| 555 | armnn::WorkloadInfo info; |
| 556 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 557 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 558 | data.m_Parameters.m_A = a; |
| 559 | data.m_Parameters.m_B = b; |
| 560 | data.m_Parameters.m_Function = f; |
| 561 | |
| 562 | armnn::ActivationQueueDescriptor refData = data; |
| 563 | armnn::WorkloadInfo refInfo = info; |
| 564 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get()); |
| 565 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 566 | |
| 567 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateActivation(data, info); |
| 568 | BOOST_ASSERT(workload != nullptr); |
| 569 | std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateActivation(refData, refInfo); |
| 570 | BOOST_ASSERT(workloadRef != nullptr); |
| 571 | |
| 572 | inputHandle->Allocate(); |
| 573 | outputHandle->Allocate(); |
| 574 | inputHandleRef->Allocate(); |
| 575 | outputHandleRef->Allocate(); |
| 576 | |
| 577 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 578 | CopyDataToITensorHandle(inputHandleRef.get(), &input[0][0][0][0]); |
| 579 | |
| 580 | workload->Execute(); |
| 581 | workloadRef->Execute(); |
| 582 | |
| 583 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 584 | CopyDataFromITensorHandle(&ret.outputExpected[0][0][0][0], outputHandleRef.get()); |
| 585 | |
| 586 | return ret; |
| 587 | } |
| 588 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 589 | LayerTestResult<float,4> CompareActivationTest( |
| 590 | armnn::IWorkloadFactory& workloadFactory, |
| 591 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 592 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 593 | armnn::ActivationFunction f, |
| 594 | unsigned int batchSize) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 595 | { |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 596 | return CompareActivationTestImpl<armnn::DataType::Float32>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 597 | workloadFactory, memoryManager, refWorkloadFactory, f, batchSize); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 598 | } |
| 599 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 600 | LayerTestResult<uint8_t,4> CompareActivationUint8Test( |
| 601 | armnn::IWorkloadFactory& workloadFactory, |
| 602 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 603 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 604 | armnn::ActivationFunction f) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 605 | { |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 606 | return CompareActivationTestImpl<armnn::DataType::QuantisedAsymm8>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 607 | workloadFactory, memoryManager, refWorkloadFactory, f, 5, 0.1f, 50); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 608 | } |