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 | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7 | #include "WorkloadTestUtils.hpp" |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 8 | #include "TensorUtils.hpp" |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 9 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 10 | #include "QuantizeHelper.hpp" |
| 11 | |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 12 | #include <armnn/ArmNN.hpp> |
| 13 | |
| 14 | #include <Permute.hpp> |
| 15 | |
| 16 | #include <backendsCommon/CpuTensorHandle.hpp> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 17 | #include <backendsCommon/IBackendInternal.hpp> |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 18 | #include <backendsCommon/WorkloadFactory.hpp> |
| 19 | #include <backendsCommon/WorkloadInfo.hpp> |
| 20 | |
| 21 | #include <test/TensorHelpers.hpp> |
| 22 | |
Matteo Martincigh | 2135015 | 2018-11-28 16:22:22 +0000 | [diff] [blame] | 23 | #include <DataLayoutIndexed.hpp> |
| 24 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 25 | #include <boost/numeric/conversion/cast.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 26 | |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 27 | #include <algorithm> |
| 28 | #include <string> |
| 29 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 30 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 31 | LayerTestResult<T, 4> SimplePooling2dTestImpl( |
| 32 | armnn::IWorkloadFactory& workloadFactory, |
| 33 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 34 | armnn::Pooling2dDescriptor descriptor, |
| 35 | float qScale, |
| 36 | int32_t qOffset, |
| 37 | const boost::multi_array<T, 4>& input, |
| 38 | const boost::multi_array<T, 4>& outputExpected) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 39 | { |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 40 | const armnn::DataLayout dataLayout = descriptor.m_DataLayout; |
Matteo Martincigh | 2135015 | 2018-11-28 16:22:22 +0000 | [diff] [blame] | 41 | const armnnUtils::DataLayoutIndexed dimensionIndices = dataLayout; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 42 | auto heightIndex = dimensionIndices.GetHeightIndex(); |
| 43 | auto widthIndex = dimensionIndices.GetWidthIndex(); |
| 44 | auto channelsIndex = dimensionIndices.GetChannelsIndex(); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 45 | |
James Conroy | 6948227 | 2018-10-19 10:41:35 +0100 | [diff] [blame] | 46 | unsigned int inputHeight = boost::numeric_cast<unsigned int>(input.shape()[heightIndex]); |
| 47 | unsigned int inputWidth = boost::numeric_cast<unsigned int>(input.shape()[widthIndex]); |
| 48 | unsigned int inputChannels = boost::numeric_cast<unsigned int>(input.shape()[channelsIndex]); |
| 49 | unsigned int inputBatchSize = boost::numeric_cast<unsigned int>(input.shape()[0]); |
| 50 | |
| 51 | unsigned int outputHeight = boost::numeric_cast<unsigned int>(outputExpected.shape()[heightIndex]); |
| 52 | unsigned int outputWidth = boost::numeric_cast<unsigned int>(outputExpected.shape()[widthIndex]); |
| 53 | unsigned int outputChannels = boost::numeric_cast<unsigned int>(outputExpected.shape()[channelsIndex]); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 54 | unsigned int outputBatchSize = boost::numeric_cast<unsigned int>(outputExpected.shape()[0]); |
| 55 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 56 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( |
| 57 | inputBatchSize, inputChannels, inputHeight, inputWidth, dataLayout, ArmnnType); |
| 58 | |
| 59 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( |
| 60 | outputBatchSize, outputChannels, outputHeight, outputWidth, dataLayout, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 61 | |
| 62 | // Set quantization parameters if the requested type is a quantized type. |
| 63 | if(armnn::IsQuantizedType<T>()) |
| 64 | { |
| 65 | inputTensorInfo.SetQuantizationScale(qScale); |
| 66 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 67 | outputTensorInfo.SetQuantizationScale(qScale); |
| 68 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 69 | } |
| 70 | |
| 71 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 72 | |
| 73 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 74 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 75 | |
| 76 | armnn::Pooling2dQueueDescriptor queueDescriptor; |
| 77 | queueDescriptor.m_Parameters = descriptor; |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 78 | queueDescriptor.m_Parameters.m_DataLayout = dataLayout; |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 79 | |
| 80 | armnn::WorkloadInfo workloadInfo; |
| 81 | AddInputToWorkload(queueDescriptor, workloadInfo, inputTensorInfo, inputHandle.get()); |
| 82 | AddOutputToWorkload(queueDescriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| 83 | |
| 84 | // Don't execute if Pooling is not supported, as an exception will be raised. |
David Beck | 79141b9 | 2018-10-23 16:09:36 +0100 | [diff] [blame] | 85 | armnn::BackendId backend = workloadFactory.GetBackendId(); |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 86 | const size_t reasonIfUnsupportedMaxLen = 255; |
| 87 | char reasonIfUnsupported[reasonIfUnsupportedMaxLen+1]; |
David Beck | 79141b9 | 2018-10-23 16:09:36 +0100 | [diff] [blame] | 88 | result.supported = armnn::IsPooling2dSupported(backend, inputTensorInfo, outputTensorInfo, |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 89 | queueDescriptor.m_Parameters, |
| 90 | reasonIfUnsupported, reasonIfUnsupportedMaxLen); |
| 91 | if (!result.supported) |
| 92 | { |
| 93 | return result; |
| 94 | } |
| 95 | |
| 96 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePooling2d(queueDescriptor, workloadInfo); |
| 97 | |
| 98 | inputHandle->Allocate(); |
| 99 | outputHandle->Allocate(); |
| 100 | |
| 101 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 102 | |
| 103 | workload->Execute(); |
| 104 | |
| 105 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 106 | |
| 107 | result.outputExpected = outputExpected; |
| 108 | |
| 109 | return result; |
| 110 | } |
| 111 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 112 | // |
| 113 | // Tests max pooling with the following parameters: |
| 114 | // |
| 115 | // Pooling size: 3x3 |
| 116 | // Stride: (2,4) |
| 117 | // input size: 8x13 |
| 118 | // channels: 2 |
| 119 | // batch size: 2 |
| 120 | // |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 121 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 122 | LayerTestResult<T, 4> SimpleMaxPooling2dSize3x3Stride2x4TestCommon( |
| 123 | armnn::IWorkloadFactory& workloadFactory, |
| 124 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 125 | bool forceNoPadding, |
| 126 | float qScale = 1.0f, |
| 127 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 128 | { |
| 129 | armnn::Pooling2dDescriptor descriptor; |
| 130 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 131 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 132 | descriptor.m_StrideX = 2; |
| 133 | descriptor.m_StrideY = 4; |
| 134 | // forceNoPadding is mainly used for compatibility with ARM Compute. |
| 135 | // As of 16/05/2017, it errors if padX or padY are equal to or greater than the pool size. |
| 136 | descriptor.m_PadLeft = descriptor.m_PadRight = forceNoPadding ? 0 : 3; |
| 137 | descriptor.m_PadTop = descriptor.m_PadBottom = 0; |
| 138 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 139 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 140 | |
| 141 | unsigned int inputWidth = 8; |
| 142 | unsigned int inputHeight = 13; |
| 143 | unsigned int outputWidth = |
| 144 | (inputWidth + descriptor.m_PadLeft + descriptor.m_PadRight + descriptor.m_StrideX - descriptor.m_PoolWidth) / |
| 145 | descriptor.m_StrideX; |
| 146 | unsigned int outputHeight = |
| 147 | (inputHeight + descriptor.m_PadTop + descriptor.m_PadBottom + descriptor.m_StrideY - descriptor.m_PoolHeight) / |
| 148 | descriptor.m_StrideY; |
| 149 | unsigned int channels = 2; |
| 150 | unsigned int batchSize = 2; |
| 151 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 152 | armnn::TensorInfo inputTensorInfo({ batchSize, channels, inputHeight, inputWidth }, ArmnnType); |
| 153 | armnn::TensorInfo outputTensorInfo({ batchSize, channels, outputHeight, outputWidth }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 154 | |
| 155 | // Set quantization parameters if the requested type is a quantized type. |
| 156 | if(armnn::IsQuantizedType<T>()) |
| 157 | { |
| 158 | inputTensorInfo.SetQuantizationScale(qScale); |
| 159 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 160 | outputTensorInfo.SetQuantizationScale(qScale); |
| 161 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 162 | } |
| 163 | |
| 164 | std::vector<float> singleChannelData({ |
| 165 | 0.0f, 4.0f, 8.0f, 1.0f, 6.0f, 4.0f, 5.0f, 8.0f, |
| 166 | 1.0f, 1.0f, 6.0f, 0.0f, 3.0f, 7.0f, 4.0f, 7.0f, |
| 167 | 8.0f, 5.0f, 0.0f, 0.0f, 8.0f, 3.0f, 4.0f, 3.0f, |
| 168 | 8.0f, 2.0f, 5.0f, 4.0f, 1.0f, 9.0f, 2.0f, 0.0f, |
| 169 | 5.0f, 4.0f, 5.0f, 0.0f, 0.0f, 0.0f, 7.0f, 2.0f, |
| 170 | 1.0f, 2.0f, 6.0f, 2.0f, 7.0f, 9.0f, 5.0f, 2.0f, |
| 171 | 9.0f, 7.0f, 3.0f, 1.0f, 3.0f, 4.0f, 8.0f, 3.0f, |
| 172 | 1.0f, 0.0f, 0.0f, 5.0f, 5.0f, 4.0f, 2.0f, 0.0f, |
| 173 | 6.0f, 4.0f, 3.0f, 6.0f, 9.0f, 5.0f, 5.0f, 6.0f, |
| 174 | 8.0f, 7.0f, 9.0f, 6.0f, 1.0f, 4.0f, 1.0f, 9.0f, |
| 175 | 7.0f, 1.0f, 9.0f, 2.0f, 9.0f, 9.0f, 8.0f, 1.0f, |
| 176 | 4.0f, 4.0f, 5.0f, 9.0f, 2.0f, 6.0f, 6.0f, 4.0f, |
| 177 | 3.0f, 5.0f, 4.0f, 0.0f, 1.0f, 5.0f, 9.0f, 7.0f, |
| 178 | }); |
| 179 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 180 | // Constructs input data. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 181 | std::vector<float> inputData; |
| 182 | auto negator = [](float f) { return -f; }; |
| 183 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 184 | // First image (two channels where the second channel is the negative of the first one). |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 185 | inputData.insert(inputData.end(), singleChannelData.begin(), singleChannelData.end()); |
| 186 | std::transform(singleChannelData.begin(), singleChannelData.end(), std::back_inserter(inputData), negator); |
| 187 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 188 | // Second image (same as first image). |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 189 | inputData.insert(inputData.end(), singleChannelData.begin(), singleChannelData.end()); |
| 190 | std::transform(singleChannelData.begin(), singleChannelData.end(), std::back_inserter(inputData), negator); |
| 191 | |
| 192 | auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, inputData)); |
| 193 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 194 | // These were calculated manually. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 195 | auto shape(GetTensorShapeAsArray<4>(outputTensorInfo)); |
| 196 | boost::multi_array<T, 4> outputExpected(shape); |
| 197 | if (forceNoPadding) |
| 198 | { |
| 199 | outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 200 | QuantizedVector<T>(qScale, qOffset, { |
| 201 | 8.0f, 8.0f, 8.0f, |
| 202 | 9.0f, 7.0f, 9.0f, |
| 203 | 9.0f, 9.0f, 9.0f, |
| 204 | |
| 205 | 0.0f, 0.0f, -3.0f, |
| 206 | -1.0f, 0.0f, 0.0f, |
| 207 | -1.0f, -1.0f, -1.0f, |
| 208 | |
| 209 | 8.0f, 8.0f, 8.0f, |
| 210 | 9.0f, 7.0f, 9.0f, |
| 211 | 9.0f, 9.0f, 9.0f, |
| 212 | |
| 213 | 0.0f, 0.0f, -3.0f, |
| 214 | -1.0f, 0.0f, 0.0f, |
| 215 | -1.0f, -1.0f, -1.0f |
| 216 | })); |
| 217 | } |
| 218 | else |
| 219 | { |
| 220 | outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 221 | QuantizedVector<T>(qScale, qOffset, { |
| 222 | 0.0f, 8.0f, 8.0f, 8.0f, 8.0f, 8.0f, |
| 223 | 0.0f, 9.0f, 7.0f, 9.0f, 9.0f, 3.0f, |
| 224 | 0.0f, 8.0f, 9.0f, 9.0f, 9.0f, 9.0f, |
| 225 | |
| 226 | 0.0f, 0.0f, 0.0f, 0.0f,-3.0f, 0.0f, |
| 227 | 0.0f,-1.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 228 | 0.0f,-1.0f,-1.0f,-1.0f,-1.0f, 0.0f, |
| 229 | |
| 230 | 0.0f, 8.0f, 8.0f, 8.0f, 8.0f, 8.0f, |
| 231 | 0.0f, 9.0f, 7.0f, 9.0f, 9.0f, 3.0f, |
| 232 | 0.0f, 8.0f, 9.0f, 9.0f, 9.0f, 9.0f, |
| 233 | |
| 234 | 0.0f, 0.0f, 0.0f, 0.0f,-3.0f, 0.0f, |
| 235 | 0.0f,-1.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 236 | 0.0f,-1.0f,-1.0f,-1.0f,-1.0f, 0.0f |
| 237 | })); |
| 238 | } |
| 239 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 240 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 241 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 242 | } |
| 243 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 244 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 245 | LayerTestResult<T, 4> SimpleMaxPooling2dTestCommon( |
| 246 | armnn::IWorkloadFactory& workloadFactory, |
| 247 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 248 | const armnn::DataLayout dataLayout = armnn::DataLayout::NCHW, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 249 | float qScale = 1.0f, |
| 250 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 251 | { |
| 252 | armnn::Pooling2dDescriptor descriptor; |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 253 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 254 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| 255 | descriptor.m_StrideX = descriptor.m_StrideY = 2; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 256 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
James Conroy | 6948227 | 2018-10-19 10:41:35 +0100 | [diff] [blame] | 257 | descriptor.m_DataLayout = dataLayout; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 258 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 259 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo(1, 2, 4, 4, dataLayout, ArmnnType); |
| 260 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo(1, 2, 2, 2, dataLayout, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 261 | |
| 262 | // Set quantization parameters if the requested type is a quantized type. |
| 263 | if(armnn::IsQuantizedType<T>()) |
| 264 | { |
| 265 | inputTensorInfo.SetQuantizationScale(qScale); |
| 266 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 267 | outputTensorInfo.SetQuantizationScale(qScale); |
| 268 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 269 | } |
| 270 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 271 | std::vector<T> inputData( |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 272 | QuantizedVector<T>(qScale, qOffset, { |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 273 | 1.0f, 2.0f, 5.0f, 6.0f, |
| 274 | 3.0f, 4.0f, 7.0f, 8.0f, |
| 275 | 9.0f, 10.0f, 13.0f, 14.0f, |
| 276 | 11.0f, 12.0f, 15.0f, 16.0f, |
| 277 | |
| 278 | 17.0f, 18.0f, 21.0f, 22.0f, |
| 279 | 19.0f, 20.0f, 23.0f, 24.0f, |
| 280 | 25.0f, 26.0f, 29.0f, 30.0f, |
| 281 | 27.0f, 28.0f, 31.0f, 32.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 282 | })); |
| 283 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 284 | std::vector<T> outputData( |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 285 | QuantizedVector<T>(qScale, qOffset, { |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 286 | 4.0f, 8.0f, |
| 287 | 12.0f, 16.0f, |
| 288 | |
| 289 | 20.0f, 24.0f, |
| 290 | 28.0f, 32.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 291 | })); |
| 292 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 293 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 294 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 295 | { |
| 296 | std::vector<T> tmp(inputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 297 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(T)); |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 298 | inputData = tmp; |
| 299 | |
| 300 | std::vector<T> tmp1(outputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 301 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(T)); |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 302 | outputData = tmp1; |
| 303 | } |
| 304 | |
| 305 | auto input = MakeTensor<T, 4>(inputTensorInfo, inputData); |
| 306 | |
| 307 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, outputData); |
| 308 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 309 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 310 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 311 | } |
| 312 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 313 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 314 | LayerTestResult<T, 4> SimpleAveragePooling2dTestCommon( |
| 315 | armnn::IWorkloadFactory& workloadFactory, |
| 316 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 317 | armnn::DataLayout dataLayout = armnn::DataLayout::NCHW, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 318 | float qScale = 1.0f, |
| 319 | int32_t qOffset = 0) |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 320 | { |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 321 | armnn::Pooling2dDescriptor descriptor; |
| 322 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 323 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| 324 | descriptor.m_StrideX = descriptor.m_StrideY = 2; |
| 325 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 326 | descriptor.m_DataLayout = dataLayout; |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 327 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 328 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo(1, 2, 4, 4, dataLayout, ArmnnType); |
| 329 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo(1, 2, 2, 2, dataLayout, ArmnnType); |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 330 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 331 | // Set quantization parameters if the requested type is a quantized type. |
| 332 | if(armnn::IsQuantizedType<T>()) |
| 333 | { |
| 334 | inputTensorInfo.SetQuantizationScale(qScale); |
| 335 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 336 | outputTensorInfo.SetQuantizationScale(qScale); |
| 337 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 338 | } |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 339 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 340 | std::vector<T> inputData( |
| 341 | QuantizedVector<T>(qScale, qOffset, { |
| 342 | 2.0f, 2.0f, 6.0f, 6.0f, |
| 343 | 4.0f, 4.0f, 8.0f, 8.0f, |
| 344 | 10.0f, 12.0f, 14.0f, 16.0f, |
| 345 | 10.0f, 12.0f, 16.0f, 14.0f, |
| 346 | |
| 347 | 18.0f, 20.0f, 24.0f, 22.0f, |
| 348 | 20.0f, 18.0f, 22.0f, 24.0f, |
| 349 | 26.0f, 28.0f, 0.0f, 0.0f, |
| 350 | 26.0f, 28.0f, 0.0f, 0.0f, |
| 351 | })); |
| 352 | |
| 353 | std::vector<T> outputData( |
| 354 | QuantizedVector<T>(qScale, qOffset, { |
| 355 | 3.0f, 7.0f, |
| 356 | 11.0f, 15.0f, |
| 357 | |
| 358 | 19.0f, 23.0f, |
| 359 | 27.0f, 0.0f, |
| 360 | })); |
| 361 | |
| 362 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 363 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 364 | { |
| 365 | std::vector<T> tmp(inputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 366 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(T)); |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 367 | inputData = tmp; |
| 368 | |
| 369 | std::vector<T> tmp1(outputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 370 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(T)); |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 371 | outputData = tmp1; |
| 372 | } |
| 373 | |
| 374 | auto input = MakeTensor<T, 4>(inputTensorInfo, inputData); |
| 375 | |
| 376 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, outputData); |
| 377 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 378 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 379 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 380 | } |
| 381 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 382 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 383 | LayerTestResult<T, 4> LargeTensorsAveragePooling2dTestCommon( |
| 384 | armnn::IWorkloadFactory& workloadFactory, |
| 385 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 386 | float qScale = 1.0f, |
| 387 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 388 | { |
| 389 | armnn::Pooling2dDescriptor descriptor; |
| 390 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 391 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 100; |
| 392 | descriptor.m_StrideX = descriptor.m_StrideY = 5; |
| 393 | descriptor.m_PadLeft = 50; |
| 394 | descriptor.m_PadRight = 50; |
| 395 | descriptor.m_PadTop = 50; |
| 396 | descriptor.m_PadBottom = 50; |
| 397 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 398 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 399 | armnn::TensorInfo inputTensorInfo({ 5, 3, 52, 60 }, ArmnnType); |
| 400 | armnn::TensorInfo outputTensorInfo({ 5, 3, 11, 13 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 401 | |
| 402 | // Set quantization parameters if the requested type is a quantized type. |
| 403 | if(armnn::IsQuantizedType<T>()) |
| 404 | { |
| 405 | inputTensorInfo.SetQuantizationScale(qScale); |
| 406 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 407 | outputTensorInfo.SetQuantizationScale(qScale); |
| 408 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 409 | } |
| 410 | |
| 411 | std::vector<T> inputVec; |
| 412 | |
| 413 | for (unsigned int i = 0 ; i < inputTensorInfo.GetShape().GetNumElements(); ++i) |
| 414 | { |
| 415 | inputVec.push_back(1); |
| 416 | } |
| 417 | |
| 418 | auto input = MakeTensor<T, 4>(inputTensorInfo, inputVec); |
| 419 | |
| 420 | std::vector<T> outputVec; |
| 421 | |
| 422 | for (unsigned int i = 0 ; i < outputTensorInfo.GetShape().GetNumElements(); ++i) |
| 423 | { |
| 424 | outputVec.push_back(1); |
| 425 | } |
| 426 | |
| 427 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, outputVec); |
| 428 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 429 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 430 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 431 | } |
| 432 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 433 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 434 | LayerTestResult<T, 4> SimpleL2Pooling2dTestCommon( |
| 435 | armnn::IWorkloadFactory& workloadFactory, |
| 436 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 437 | armnn::DataLayout dataLayout = armnn::DataLayout::NCHW, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 438 | float qScale = 1.0f, |
| 439 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 440 | { |
| 441 | armnn::Pooling2dDescriptor descriptor; |
| 442 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 443 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| 444 | descriptor.m_StrideX = descriptor.m_StrideY = 2; |
| 445 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 446 | descriptor.m_DataLayout = dataLayout; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 447 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 448 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo(1, 2, 4, 4, dataLayout, ArmnnType); |
| 449 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo(1, 2, 2, 2, dataLayout, ArmnnType); |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 450 | |
| 451 | std::vector<T> inputData( |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 452 | QuantizedVector<T>(qScale, qOffset, { |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 453 | 1.0f, 7.0f, 5.0f, 5.0f, |
| 454 | 1.0f, 7.0f, 5.0f, 5.0f, |
| 455 | 3.0f, 3.0f, 1.0f, 1.0f, |
| 456 | 3.0f, 3.0f, 1.0f, 1.0f, |
| 457 | |
| 458 | 1.0f, 7.0f, 0.0f, 0.0f, |
| 459 | 1.0f, 7.0f, 2.0f, 0.0f, |
| 460 | 0.0f, 2.0f, 1.0f, 1.0f, |
| 461 | 0.0f, 0.0f, 1.0f, 1.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 462 | })); |
| 463 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 464 | std::vector<T> outputData( |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 465 | QuantizedVector<T>(qScale, qOffset, { |
| 466 | 5.0f, 5.0f, |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 467 | 3.0f, 1.0f, |
| 468 | |
| 469 | 5.0f, 1.0f, |
| 470 | 1.0f, 1.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 471 | })); |
| 472 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 473 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 474 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 475 | { |
| 476 | std::vector<T> tmp(inputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 477 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(T)); |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 478 | inputData = tmp; |
| 479 | |
| 480 | std::vector<T> tmp1(outputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 481 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(T)); |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 482 | outputData = tmp1; |
| 483 | } |
| 484 | |
| 485 | auto input = MakeTensor<T, 4>(inputTensorInfo, inputData); |
| 486 | |
| 487 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, outputData); |
| 488 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 489 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 490 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 491 | } |
| 492 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 493 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 494 | LayerTestResult<T, 4> L2Pooling2dSize3Stride1TestCommon( |
| 495 | armnn::IWorkloadFactory& workloadFactory, |
| 496 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 497 | float qScale = 1.0f, |
| 498 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 499 | { |
| 500 | armnn::Pooling2dDescriptor descriptor; |
| 501 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 502 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 503 | descriptor.m_StrideX = descriptor.m_StrideY = 1; |
| 504 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 505 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 506 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 507 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 508 | QuantizedVector<T>(qScale, qOffset, { |
| 509 | 2.0f, 1.0f, 5.0f, 2.0f, |
| 510 | 1.0f, 2.0f, 2.0f, 1.0f, |
| 511 | 5.0f, 4.0f, 1.0f, 5.0f, |
| 512 | 2.0f, 1.0f, 5.0f, 2.0f, |
| 513 | })); |
| 514 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 515 | armnn::TensorInfo outputTensorInfo({ 1, 1, 2, 2 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 516 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 517 | QuantizedVector<T>(qScale, qOffset, { |
| 518 | 3.0f, 3.0f, |
| 519 | 3.0f, 3.0f, |
| 520 | })); |
| 521 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 522 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 523 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 524 | } |
| 525 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 526 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 527 | LayerTestResult<T, 4> L2Pooling2dSize3Stride3TestCommon( |
| 528 | armnn::IWorkloadFactory& workloadFactory, |
| 529 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 530 | float qScale = 1.0f, |
| 531 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 532 | { |
| 533 | armnn::Pooling2dDescriptor descriptor; |
| 534 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 535 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 536 | descriptor.m_StrideX = descriptor.m_StrideY = 3; |
| 537 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 538 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 539 | armnn::TensorInfo inputTensorInfo({ 1, 1, 9, 9 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 540 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 541 | QuantizedVector<T>(qScale, qOffset, { |
| 542 | 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, |
| 543 | 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, |
| 544 | 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, |
| 545 | 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, |
| 546 | 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, |
| 547 | 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, |
| 548 | 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, |
| 549 | 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, |
| 550 | 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, |
| 551 | })); |
| 552 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 553 | armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 554 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 555 | QuantizedVector<T>(qScale, qOffset, { |
| 556 | 3.0f, 3.0f, 3.0f, |
| 557 | 3.0f, 3.0f, 3.0f, |
| 558 | 3.0f, 3.0f, 3.0f, |
| 559 | })); |
| 560 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 561 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 562 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 563 | } |
| 564 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 565 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 566 | LayerTestResult<T, 4> L2Pooling2dSize3Stride4TestCommon( |
| 567 | armnn::IWorkloadFactory& workloadFactory, |
| 568 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 569 | float qScale = 1.0f, |
| 570 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 571 | { |
| 572 | armnn::Pooling2dDescriptor descriptor; |
| 573 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 574 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 575 | descriptor.m_StrideX = descriptor.m_StrideY = 4; |
| 576 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 577 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 578 | armnn::TensorInfo inputTensorInfo({ 1, 1, 7, 7 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 579 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 580 | QuantizedVector<T>(qScale, qOffset, { |
| 581 | 2.0f, 1.0f, 5.0f, 0.0f, 2.0f, 1.0f, 5.0f, |
| 582 | 1.0f, 2.0f, 2.0f, 0.0f, 1.0f, 2.0f, 2.0f, |
| 583 | 5.0f, 4.0f, 1.0f, 0.0f, 5.0f, 4.0f, 1.0f, |
| 584 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 585 | 2.0f, 1.0f, 5.0f, 0.0f, 2.0f, 1.0f, 5.0f, |
| 586 | 1.0f, 2.0f, 2.0f, 0.0f, 1.0f, 2.0f, 2.0f, |
| 587 | 5.0f, 4.0f, 1.0f, 0.0f, 5.0f, 4.0f, 1.0f, |
| 588 | })); |
| 589 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 590 | armnn::TensorInfo outputTensorInfo({ 1, 1, 2, 2 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 591 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 592 | QuantizedVector<T>(qScale, qOffset, { |
| 593 | 3.0f, 3.0f, |
| 594 | 3.0f, 3.0f, |
| 595 | })); |
| 596 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 597 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 598 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 599 | } |
| 600 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 601 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 602 | LayerTestResult<T, 4> L2Pooling2dSize7TestCommon( |
| 603 | armnn::IWorkloadFactory& workloadFactory, |
| 604 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 605 | float qScale = 1.0f, |
| 606 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 607 | { |
| 608 | armnn::Pooling2dDescriptor descriptor; |
| 609 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 610 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 7; |
| 611 | descriptor.m_StrideX = descriptor.m_StrideY = 7; |
| 612 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 613 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 614 | armnn::TensorInfo inputTensorInfo({ 1, 1, 7, 7 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 615 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 616 | QuantizedVector<T>(qScale, qOffset, { |
| 617 | 1.0f, 0.0f, 2.0f, 0.0f, 3.0f, 0.0f, 4.0f, |
| 618 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 619 | 0.0f, 5.0f, 0.0f, 6.0f, 0.0f, 7.0f, 0.0f, |
| 620 | 8.0f, 0.0f, 9.0f, 0.0f, 10.0f, 0.0f, 5.0f, |
| 621 | 0.0f, 5.0f, 0.0f, 2.0f, 0.0f, 1.0f, 1.0f, |
| 622 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 623 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 624 | })); |
| 625 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 626 | armnn::TensorInfo outputTensorInfo({ 1, 1, 1, 1 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 627 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 628 | QuantizedVector<T>(qScale, qOffset, { |
| 629 | 3.0f, |
| 630 | })); |
| 631 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 632 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 633 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 634 | } |
| 635 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 636 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 637 | LayerTestResult<T, 4> L2Pooling2dSize9TestCommon( |
| 638 | armnn::IWorkloadFactory& workloadFactory, |
| 639 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 640 | float qScale = 1.0f, |
| 641 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 642 | { |
| 643 | armnn::Pooling2dDescriptor descriptor; |
| 644 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 645 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 9; |
| 646 | descriptor.m_StrideX = descriptor.m_StrideY = 9; |
| 647 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 648 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 649 | armnn::TensorInfo inputTensorInfo({ 1, 1, 9, 9 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 650 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 651 | QuantizedVector<T>(qScale, qOffset, { |
| 652 | 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, |
| 653 | 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, |
| 654 | 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, |
| 655 | 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, |
| 656 | 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, |
| 657 | 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, |
| 658 | 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, |
| 659 | 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, |
| 660 | 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, |
| 661 | })); |
| 662 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 663 | armnn::TensorInfo outputTensorInfo({ 1, 1, 1, 1 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 664 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 665 | QuantizedVector<T>(qScale, qOffset, { |
| 666 | 3.0f, |
| 667 | })); |
| 668 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 669 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 670 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 671 | } |
| 672 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 673 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 674 | LayerTestResult<T, 4> AsymmetricNonSquarePooling2dTestCommon( |
| 675 | armnn::IWorkloadFactory& workloadFactory, |
| 676 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 677 | float qScale = 1.0f, |
| 678 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 679 | { |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 680 | armnn::TensorInfo inputTensorInfo({ 1, 1, 1, 3 }, ArmnnType); |
| 681 | armnn::TensorInfo outputTensorInfo({ 1, 1, 2, 2 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 682 | |
| 683 | armnn::Pooling2dDescriptor descriptor; |
| 684 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 685 | descriptor.m_PoolWidth = 2; |
| 686 | descriptor.m_PoolHeight = 3; |
| 687 | descriptor.m_StrideX = 2; |
| 688 | descriptor.m_StrideY = 1; |
| 689 | descriptor.m_PadLeft = 2; |
| 690 | descriptor.m_PadRight = 0; |
| 691 | descriptor.m_PadTop = 1; |
| 692 | descriptor.m_PadBottom = 2; |
| 693 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 694 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 695 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 696 | // Construct input data. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 697 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 698 | QuantizedVector<T>(qScale, qOffset, { |
| 699 | 1.0f, 3.0f, 4.0f, |
| 700 | })); |
| 701 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 702 | // These were calculated manually. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 703 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 704 | QuantizedVector<T>(qScale, qOffset, { |
| 705 | 0.0f, 3.0f, 0.0f, 3.0f, |
| 706 | })); |
| 707 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 708 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 709 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 710 | } |
| 711 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 712 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 713 | LayerTestResult<T, 4> ComparePooling2dTestCommon( |
| 714 | armnn::IWorkloadFactory& workloadFactory, |
| 715 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 716 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 717 | armnn::PoolingAlgorithm poolingType, |
| 718 | float qScale = 1.0f, |
| 719 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 720 | { |
| 721 | const unsigned int inputWidth = 16; |
| 722 | const unsigned int inputHeight = 32; |
| 723 | const unsigned int channelCount = 2; |
| 724 | const unsigned int batchSize = 5; |
| 725 | |
| 726 | const unsigned int poolSize = 3; |
| 727 | const unsigned int strideX = 2; |
| 728 | const unsigned int strideY = 4; |
| 729 | const unsigned int padX = 0; |
| 730 | const unsigned int padY = 0; |
| 731 | |
| 732 | const unsigned int outputWidth = (inputWidth + 2 * padX + strideX - poolSize) / strideX; |
| 733 | const unsigned int outputHeight = (inputHeight + 2 * padY + strideY - poolSize) / strideY; |
| 734 | |
| 735 | armnn::TensorInfo inputTensorInfo; |
| 736 | armnn::TensorInfo outputTensorInfo; |
| 737 | |
| 738 | unsigned int inputShape[] = { batchSize, channelCount, inputHeight, inputWidth }; |
| 739 | unsigned int outputShape[] = { batchSize, channelCount, outputHeight, outputWidth }; |
| 740 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 741 | inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType); |
| 742 | outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 743 | |
| 744 | // Set quantization parameters if the requested type is a quantized type. |
| 745 | if(armnn::IsQuantizedType<T>()) |
| 746 | { |
| 747 | inputTensorInfo.SetQuantizationScale(qScale); |
| 748 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 749 | outputTensorInfo.SetQuantizationScale(qScale); |
| 750 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 751 | } |
| 752 | |
| 753 | boost::multi_array<T, 4> input = MakeRandomTensor<T, 4>(inputTensorInfo, 81715); |
| 754 | |
| 755 | LayerTestResult<T, 4> comparisonResult(outputTensorInfo); |
| 756 | |
| 757 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 758 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 759 | |
| 760 | armnn::Pooling2dQueueDescriptor data; |
| 761 | armnn::WorkloadInfo info; |
| 762 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 763 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 764 | data.m_Parameters.m_PoolType = poolingType; |
| 765 | data.m_Parameters.m_PoolWidth = poolSize; |
| 766 | data.m_Parameters.m_PoolHeight = poolSize; |
| 767 | data.m_Parameters.m_StrideX = strideX; |
| 768 | data.m_Parameters.m_StrideY = strideY; |
| 769 | data.m_Parameters.m_PadLeft = padX; |
| 770 | data.m_Parameters.m_PadRight = padX; |
| 771 | data.m_Parameters.m_PadTop = padY; |
| 772 | data.m_Parameters.m_PadBottom = padY; |
| 773 | data.m_Parameters.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 774 | |
| 775 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refWorkloadFactory.CreateTensorHandle(outputTensorInfo); |
| 776 | std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refWorkloadFactory.CreateTensorHandle(inputTensorInfo); |
| 777 | |
| 778 | // Don't execute if Pooling is not supported, as an exception will be raised. |
David Beck | 79141b9 | 2018-10-23 16:09:36 +0100 | [diff] [blame] | 779 | armnn::BackendId backend = workloadFactory.GetBackendId(); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 780 | const size_t reasonIfUnsupportedMaxLen = 255; |
| 781 | char reasonIfUnsupported[reasonIfUnsupportedMaxLen+1]; |
David Beck | 79141b9 | 2018-10-23 16:09:36 +0100 | [diff] [blame] | 782 | comparisonResult.supported = armnn::IsPooling2dSupported(backend, inputTensorInfo, outputTensorInfo, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 783 | data.m_Parameters, |
| 784 | reasonIfUnsupported, reasonIfUnsupportedMaxLen); |
| 785 | if (!comparisonResult.supported) |
| 786 | { |
| 787 | return comparisonResult; |
| 788 | } |
| 789 | |
| 790 | armnn::Pooling2dQueueDescriptor refData = data; |
| 791 | armnn::WorkloadInfo refInfo = info; |
| 792 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get()); |
| 793 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 794 | |
| 795 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePooling2d(data, info); |
| 796 | std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreatePooling2d(refData, refInfo); |
| 797 | |
| 798 | outputHandleRef->Allocate(); |
| 799 | inputHandleRef->Allocate(); |
| 800 | inputHandle->Allocate(); |
| 801 | outputHandle->Allocate(); |
| 802 | |
| 803 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 804 | CopyDataToITensorHandle(inputHandleRef.get(), &input[0][0][0][0]); |
| 805 | |
| 806 | workload->Execute(); |
| 807 | workloadRef->Execute(); |
| 808 | |
| 809 | CopyDataFromITensorHandle(&comparisonResult.output[0][0][0][0], outputHandle.get()); |
| 810 | CopyDataFromITensorHandle(&comparisonResult.outputExpected[0][0][0][0], outputHandleRef.get()); |
| 811 | |
| 812 | return comparisonResult; |
| 813 | } |
| 814 | |
| 815 | // |
| 816 | // Tests max pooling with the following parameters: |
| 817 | // |
| 818 | // Pooling size: 2x2 |
| 819 | // Stride: (2,2) |
| 820 | // input size: 4x4 |
| 821 | // channels: 1 |
| 822 | // batch size: 1 |
| 823 | // |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 824 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 825 | LayerTestResult<T, 4> SimpleMaxPooling2dSize2x2Stride2x2TestCommon( |
| 826 | armnn::IWorkloadFactory& workloadFactory, |
| 827 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 828 | bool forceNoPadding, |
| 829 | float qScale = 1.0f, |
| 830 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 831 | { |
| 832 | armnn::Pooling2dDescriptor descriptor; |
| 833 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 834 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| 835 | descriptor.m_StrideX = 2; |
| 836 | descriptor.m_StrideY = 2; |
| 837 | descriptor.m_PadLeft = descriptor.m_PadRight = forceNoPadding ? 0 : 3; |
| 838 | descriptor.m_PadTop = descriptor.m_PadBottom = 0; |
| 839 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 840 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 841 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 842 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 843 | unsigned int inputWidth = 4; |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 844 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 845 | unsigned int inputHeight = 4; |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 846 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 847 | unsigned int outputWidth = |
| 848 | (inputWidth + descriptor.m_PadLeft + descriptor.m_PadRight + descriptor.m_StrideX - descriptor.m_PoolWidth) / |
| 849 | descriptor.m_StrideX; |
| 850 | unsigned int outputHeight = |
| 851 | (inputHeight + descriptor.m_PadTop + descriptor.m_PadBottom + descriptor.m_StrideY - descriptor.m_PoolHeight) / |
| 852 | descriptor.m_StrideY; |
| 853 | unsigned int channels = 1; |
| 854 | unsigned int batchSize = 1; |
| 855 | |
| 856 | std::vector<float> inputData = { |
| 857 | 510.0f, 222.0f, 780.0f, 654.0f, |
| 858 | 141.0f, 276.0f, 15.0f, 546.0f, |
| 859 | 303.0f, 618.0f, 582.0f, 339.0f, |
| 860 | 438.0f, 564.0f, 573.0f, 402.0f |
| 861 | }; |
| 862 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 863 | // Note that left and right edges will be 0.f, due to the 2x2 max pooling only accessing zeros here. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 864 | std::vector<float> expectedOutputDataWithPadding = { |
| 865 | 0.0f, 510.0f, 780.0f, 654.0f, 0.0f, |
| 866 | 0.0f, 438.0f, 618.0f, 402.0f, 0.0f |
| 867 | }; |
| 868 | |
| 869 | std::vector<float> expectedOutputDataNoPadding = { |
| 870 | 510.0f, 780.0f, |
| 871 | 618.0f, 582.0f |
| 872 | }; |
| 873 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 874 | armnn::TensorInfo inputTensorInfo({ batchSize, channels, inputHeight, inputWidth }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 875 | |
| 876 | // Scale and offset should match input - we're just calculating maximum values. |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 877 | armnn::TensorInfo outputTensorInfo({ batchSize, channels, outputHeight, outputWidth }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 878 | |
| 879 | // Set quantization parameters if the requested type is a quantized type. |
| 880 | if(armnn::IsQuantizedType<T>()) |
| 881 | { |
| 882 | inputTensorInfo.SetQuantizationScale(qScale); |
| 883 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 884 | outputTensorInfo.SetQuantizationScale(qScale); |
| 885 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 886 | } |
| 887 | |
| 888 | auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, inputData)); |
| 889 | |
| 890 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 891 | forceNoPadding ? QuantizedVector<T>(qScale, qOffset, expectedOutputDataNoPadding) : |
| 892 | QuantizedVector<T>(qScale, qOffset, expectedOutputDataWithPadding)); |
| 893 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 894 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 895 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 896 | } |
| 897 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 898 | // |
| 899 | // Tests max pooling with the following parameters: |
| 900 | // |
| 901 | // Pooling size: 3x2 |
| 902 | // Stride: (2,2) |
| 903 | // input size: 3x2 |
| 904 | // channels: 1 |
| 905 | // batch size: 1 |
| 906 | // |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 907 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 908 | LayerTestResult<T, 4> IgnorePaddingAveragePooling2dSize3x2Stride2x2TestCommon( |
| 909 | armnn::IWorkloadFactory& workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 910 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 911 | bool forceNoPadding, |
| 912 | float qScale = 1.0f, |
| 913 | int32_t qOffset = 0) |
| 914 | { |
| 915 | armnn::Pooling2dDescriptor descriptor; |
| 916 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 917 | descriptor.m_PoolWidth = 3; |
| 918 | descriptor.m_PoolHeight = 2; |
| 919 | descriptor.m_StrideX = 2; |
| 920 | descriptor.m_StrideY = 2; |
| 921 | descriptor.m_PadLeft = (forceNoPadding) ? 0 : 1; |
| 922 | descriptor.m_PadRight = descriptor.m_PadLeft; |
| 923 | descriptor.m_PadTop = 0; |
| 924 | descriptor.m_PadBottom = 0; |
| 925 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 926 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 927 | |
| 928 | unsigned int inputWidth = 3; |
| 929 | unsigned int inputHeight = 2; |
| 930 | unsigned int outputWidth = |
| 931 | (inputWidth + descriptor.m_PadLeft + descriptor.m_PadRight + descriptor.m_StrideX - descriptor.m_PoolWidth) / |
| 932 | descriptor.m_StrideX; |
| 933 | unsigned int outputHeight = |
| 934 | (inputHeight + descriptor.m_PadTop + descriptor.m_PadBottom + descriptor.m_StrideY - descriptor.m_PoolHeight) / |
| 935 | descriptor.m_StrideY; |
| 936 | unsigned int channels = 1; |
| 937 | unsigned int batchSize = 1; |
| 938 | |
| 939 | std::vector<float> inputData = { |
| 940 | 3.0f, 6.0f, 9.0f, |
| 941 | 12.0f, 15.0f, 18.0f, |
| 942 | }; |
| 943 | |
| 944 | std::vector<float> expectedOutputDataWithPadding = { |
| 945 | 6.0f, 8.0f, |
| 946 | }; |
| 947 | |
| 948 | std::vector<float> expectedOutputDataNoPadding = { |
| 949 | 10.5f, |
| 950 | }; |
| 951 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 952 | armnn::TensorInfo inputTensorInfo({ batchSize, channels, inputHeight, inputWidth }, ArmnnType); |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 953 | |
| 954 | // Scale and offset should match input - we're just calculating average values. |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 955 | armnn::TensorInfo outputTensorInfo({ batchSize, channels, outputHeight, outputWidth }, ArmnnType); |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 956 | |
| 957 | // Set quantization parameters if the requested type is a quantized type. |
| 958 | if(armnn::IsQuantizedType<T>()) |
| 959 | { |
| 960 | inputTensorInfo.SetQuantizationScale(qScale); |
| 961 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 962 | outputTensorInfo.SetQuantizationScale(qScale); |
| 963 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 964 | } |
| 965 | |
| 966 | auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, inputData)); |
| 967 | |
| 968 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 969 | forceNoPadding ? QuantizedVector<T>(qScale, qOffset, expectedOutputDataNoPadding) : |
| 970 | QuantizedVector<T>(qScale, qOffset, expectedOutputDataWithPadding)); |
| 971 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 972 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 973 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 974 | } |
| 975 | |
| 976 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 977 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 978 | LayerTestResult<T, 4> IgnorePaddingSimpleMaxPooling2dTestCommon( |
| 979 | armnn::IWorkloadFactory& workloadFactory, |
| 980 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 981 | float qScale = 1.0f, |
| 982 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 983 | { |
| 984 | armnn::Pooling2dDescriptor descriptor; |
| 985 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 986 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| 987 | descriptor.m_StrideX = descriptor.m_StrideY = 2; |
| 988 | descriptor.m_PadLeft = 1; |
| 989 | descriptor.m_PadRight = 1; |
| 990 | descriptor.m_PadTop = 1; |
| 991 | descriptor.m_PadBottom = 1; |
| 992 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 993 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 994 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
| 995 | armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 996 | |
| 997 | // Set quantization parameters if the requested type is a quantized type. |
| 998 | if(armnn::IsQuantizedType<T>()) |
| 999 | { |
| 1000 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1001 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1002 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1003 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1004 | } |
| 1005 | |
| 1006 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 1007 | QuantizedVector<T>(qScale, qOffset, { |
| 1008 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 1009 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 1010 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 1011 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 1012 | })); |
| 1013 | |
| 1014 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 1015 | QuantizedVector<T>(qScale, qOffset, { |
| 1016 | -1.0f, 3.0f, 4.0f, |
| 1017 | 1.0f, 3.0f, 4.0f, |
| 1018 | 1.0f, 2.0f, -4.0f, |
| 1019 | })); |
| 1020 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1021 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1022 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1023 | } |
| 1024 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1025 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1026 | LayerTestResult<T, 4> IgnorePaddingMaxPooling2dSize3TestCommon( |
| 1027 | armnn::IWorkloadFactory& workloadFactory, |
| 1028 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1029 | float qScale = 1.0f, |
| 1030 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1031 | { |
| 1032 | armnn::Pooling2dDescriptor descriptor; |
| 1033 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 1034 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 1035 | descriptor.m_StrideX = descriptor.m_StrideY = 1; |
| 1036 | descriptor.m_PadLeft = 1; |
| 1037 | descriptor.m_PadRight = 1; |
| 1038 | descriptor.m_PadTop = 1; |
| 1039 | descriptor.m_PadBottom = 1; |
| 1040 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 1041 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1042 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
| 1043 | armnn::TensorInfo outputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1044 | |
| 1045 | // Set quantization parameters if the requested type is a quantized type. |
| 1046 | if(armnn::IsQuantizedType<T>()) |
| 1047 | { |
| 1048 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1049 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1050 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1051 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1052 | } |
| 1053 | |
| 1054 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 1055 | QuantizedVector<T>(qScale, qOffset, { |
| 1056 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 1057 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 1058 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 1059 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 1060 | })); |
| 1061 | |
| 1062 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 1063 | QuantizedVector<T>(qScale, qOffset, { |
| 1064 | -1.0f, 3.0f, 4.0f, 4.0f, |
| 1065 | 2.0f, 3.0f, 4.0f, 4.0f, |
| 1066 | 2.0f, 3.0f, 4.0f, 4.0f, |
| 1067 | 2.0f, 2.0f, 2.0f, -3.0f, |
| 1068 | })); |
| 1069 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1070 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1071 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1072 | } |
| 1073 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1074 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1075 | LayerTestResult<T, 4> IgnorePaddingSimpleAveragePooling2dTestCommon( |
| 1076 | armnn::IWorkloadFactory& workloadFactory, |
| 1077 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1078 | float qScale = 1.0f, |
| 1079 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1080 | { |
| 1081 | armnn::Pooling2dDescriptor descriptor; |
| 1082 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 1083 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| 1084 | descriptor.m_StrideX = descriptor.m_StrideY = 2; |
| 1085 | descriptor.m_PadLeft = 1; |
| 1086 | descriptor.m_PadRight = 1; |
| 1087 | descriptor.m_PadTop = 1; |
| 1088 | descriptor.m_PadBottom = 1; |
| 1089 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 1090 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1091 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
| 1092 | armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1093 | |
| 1094 | // Set quantization parameters if the requested type is a quantized type. |
| 1095 | if(armnn::IsQuantizedType<T>()) |
| 1096 | { |
| 1097 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1098 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1099 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1100 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1101 | } |
| 1102 | |
| 1103 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 1104 | QuantizedVector<T>(qScale, qOffset, { |
| 1105 | 12.0f, 20.0f, 32.0f, 40.0f, |
| 1106 | 12.0f, 20.0f, 32.0f, 40.0f, |
| 1107 | 12.0f, 20.0f, 32.0f, 40.0f, |
| 1108 | 12.0f, 20.0f, 32.0f, 40.0f, |
| 1109 | })); |
| 1110 | |
| 1111 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 1112 | QuantizedVector<T>(qScale, qOffset, { |
| 1113 | 3.0f, 13.0f, 10.0f, |
| 1114 | 6.0f, 26.0f, 20.0f, |
| 1115 | 3.0f, 13.0f, 10.0f, |
| 1116 | })); |
| 1117 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1118 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1119 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1120 | } |
| 1121 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1122 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1123 | LayerTestResult<T, 4> IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon( |
| 1124 | armnn::IWorkloadFactory& workloadFactory, |
| 1125 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1126 | float qScale = 1.0f, |
| 1127 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1128 | { |
| 1129 | armnn::Pooling2dDescriptor descriptor; |
| 1130 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 1131 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 1132 | descriptor.m_StrideX = descriptor.m_StrideY = 2; |
| 1133 | descriptor.m_PadLeft = 0; |
| 1134 | descriptor.m_PadRight = 0; |
| 1135 | descriptor.m_PadTop = 0; |
| 1136 | descriptor.m_PadBottom = 0; |
| 1137 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 1138 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Ceiling; |
| 1139 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1140 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4}, ArmnnType); |
| 1141 | armnn::TensorInfo outputTensorInfo({ 1, 1, 2, 2 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1142 | |
| 1143 | // Set quantization parameters if the requested type is a quantized type. |
| 1144 | if(armnn::IsQuantizedType<T>()) |
| 1145 | { |
| 1146 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1147 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1148 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1149 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1150 | } |
| 1151 | |
| 1152 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 1153 | QuantizedVector<T>(qScale, qOffset, { |
| 1154 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1155 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1156 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1157 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1158 | })); |
| 1159 | |
| 1160 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 1161 | QuantizedVector<T>(qScale, qOffset, { |
| 1162 | 2.0f, 3.5f, |
| 1163 | 2.0f, 3.5f |
| 1164 | })); |
| 1165 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1166 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1167 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1168 | } |
| 1169 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1170 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1171 | LayerTestResult<T, 4> IgnorePaddingAveragePooling2dSize3TestCommon( |
| 1172 | armnn::IWorkloadFactory& workloadFactory, |
| 1173 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1174 | float qScale = 1.0f, |
| 1175 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1176 | { |
| 1177 | armnn::Pooling2dDescriptor descriptor; |
| 1178 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 1179 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 1180 | descriptor.m_StrideX = descriptor.m_StrideY = 1; |
| 1181 | descriptor.m_PadLeft = 1; |
| 1182 | descriptor.m_PadRight = 1; |
| 1183 | descriptor.m_PadTop = 1; |
| 1184 | descriptor.m_PadBottom = 1; |
| 1185 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 1186 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1187 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
| 1188 | armnn::TensorInfo outputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1189 | |
| 1190 | // Set quantization parameters if the requested type is a quantized type. |
| 1191 | if(armnn::IsQuantizedType<T>()) |
| 1192 | { |
| 1193 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1194 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1195 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1196 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1197 | } |
| 1198 | |
| 1199 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 1200 | QuantizedVector<T>(qScale, qOffset, { |
| 1201 | 9.0f, 27.0f, 18.0f, 36.0f, |
| 1202 | 18.0f, 9.0f, 18.0f, 9.0f, |
| 1203 | 27.0f, 18.0f, 9.0f, 27.0f, |
| 1204 | 9.0f, 27.0f, 9.0f, 18.0f, |
| 1205 | })); |
| 1206 | |
| 1207 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 1208 | QuantizedVector<T>(qScale, qOffset, { |
| 1209 | 7.0f, 11.0f, 13.0f, 9.0f, |
| 1210 | 12.0f, 17.0f, 19.0f, 13.0f, |
| 1211 | 12.0f, 16.0f, 16.0f, 10.0f, |
| 1212 | 9.0f, 11.0f, 12.0f, 7.0f, |
| 1213 | })); |
| 1214 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1215 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1216 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1217 | } |
| 1218 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1219 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1220 | LayerTestResult<T, 4> IgnorePaddingSimpleL2Pooling2dTestCommon( |
| 1221 | armnn::IWorkloadFactory& workloadFactory, |
| 1222 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1223 | float qScale = 1.0f, |
| 1224 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1225 | { |
| 1226 | armnn::Pooling2dDescriptor descriptor; |
| 1227 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 1228 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| 1229 | descriptor.m_StrideX = descriptor.m_StrideY = 2; |
| 1230 | descriptor.m_PadLeft = 1; |
| 1231 | descriptor.m_PadRight = 1; |
| 1232 | descriptor.m_PadTop = 1; |
| 1233 | descriptor.m_PadBottom = 1; |
| 1234 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 1235 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1236 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
| 1237 | armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1238 | |
| 1239 | // Set quantization parameters if the requested type is a quantized type. |
| 1240 | if(armnn::IsQuantizedType<T>()) |
| 1241 | { |
| 1242 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1243 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1244 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1245 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1246 | } |
| 1247 | |
| 1248 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 1249 | QuantizedVector<T>(qScale, qOffset, { |
| 1250 | 2.0f, 4.0f, 8.0f, 16.0f, |
| 1251 | 4.0f, 2.0f, 2.0f, 4.0f, |
| 1252 | 8.0f, 2.0f, 4.0f, 2.0f, |
| 1253 | 16.0f, 2.0f, 2.0f, 8.0f, |
| 1254 | })); |
| 1255 | |
| 1256 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 1257 | QuantizedVector<T>(qScale, qOffset, { |
| 1258 | 1.0f, 4.4721f, 8.0f, |
| 1259 | 4.4721f, 2.6457f, 2.236f, |
| 1260 | 8.0f, 1.4142f, 4.0f, |
| 1261 | })); |
| 1262 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1263 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1264 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1265 | } |
| 1266 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1267 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1268 | LayerTestResult<T, 4> IgnorePaddingL2Pooling2dSize3TestCommon( |
| 1269 | armnn::IWorkloadFactory& workloadFactory, |
| 1270 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1271 | float qScale = 1.0f, |
| 1272 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1273 | { |
| 1274 | armnn::Pooling2dDescriptor descriptor; |
| 1275 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 1276 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 1277 | descriptor.m_StrideX = descriptor.m_StrideY = 1; |
| 1278 | descriptor.m_PadLeft = 1; |
| 1279 | descriptor.m_PadRight = 1; |
| 1280 | descriptor.m_PadTop = 1; |
| 1281 | descriptor.m_PadBottom = 1; |
| 1282 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 1283 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1284 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
| 1285 | armnn::TensorInfo outputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1286 | |
| 1287 | // Set quantization parameters if the requested type is a quantized type. |
| 1288 | if(armnn::IsQuantizedType<T>()) |
| 1289 | { |
| 1290 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1291 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1292 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1293 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1294 | } |
| 1295 | |
| 1296 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 1297 | QuantizedVector<T>(qScale, qOffset, { |
| 1298 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1299 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1300 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1301 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1302 | })); |
| 1303 | |
| 1304 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 1305 | QuantizedVector<T>(qScale, qOffset, { |
| 1306 | 1.0540f, 1.7638f, 2.5385f, 2.3570f, |
| 1307 | 1.2909f, 2.1602f, 3.1091f, 2.8867f, |
| 1308 | 1.2909f, 2.1602f, 3.1091f, 2.8867f, |
| 1309 | 1.0540f, 1.7638f, 2.5385f, 2.3570f, |
| 1310 | })); |
| 1311 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1312 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1313 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1314 | } |