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 | // |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 6 | #include "Pooling2dTestImpl.hpp" |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 8 | #include <armnn/LayerSupport.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 9 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 10 | #include <DataLayoutIndexed.hpp> |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 11 | #include <Permute.hpp> |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 12 | #include <ResolveType.hpp> |
| 13 | #include <TensorUtils.hpp> |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 14 | |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 15 | #include <backendsCommon/WorkloadInfo.hpp> |
| 16 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 17 | #include <backendsCommon/test/QuantizeHelper.hpp> |
| 18 | #include <backendsCommon/test/TensorCopyUtils.hpp> |
| 19 | #include <backendsCommon/test/WorkloadTestUtils.hpp> |
| 20 | |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 21 | #include <test/TensorHelpers.hpp> |
| 22 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 23 | #include <boost/numeric/conversion/cast.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 24 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 25 | namespace |
| 26 | { |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 27 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 28 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 29 | LayerTestResult<T, 4> SimplePooling2dTestImpl( |
| 30 | armnn::IWorkloadFactory& workloadFactory, |
| 31 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 32 | armnn::Pooling2dDescriptor descriptor, |
| 33 | float qScale, |
| 34 | int32_t qOffset, |
| 35 | const boost::multi_array<T, 4>& input, |
| 36 | const boost::multi_array<T, 4>& outputExpected) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 37 | { |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 38 | const armnn::DataLayout dataLayout = descriptor.m_DataLayout; |
Matteo Martincigh | 2135015 | 2018-11-28 16:22:22 +0000 | [diff] [blame] | 39 | const armnnUtils::DataLayoutIndexed dimensionIndices = dataLayout; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 40 | auto heightIndex = dimensionIndices.GetHeightIndex(); |
| 41 | auto widthIndex = dimensionIndices.GetWidthIndex(); |
| 42 | auto channelsIndex = dimensionIndices.GetChannelsIndex(); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 43 | |
James Conroy | 6948227 | 2018-10-19 10:41:35 +0100 | [diff] [blame] | 44 | unsigned int inputHeight = boost::numeric_cast<unsigned int>(input.shape()[heightIndex]); |
| 45 | unsigned int inputWidth = boost::numeric_cast<unsigned int>(input.shape()[widthIndex]); |
| 46 | unsigned int inputChannels = boost::numeric_cast<unsigned int>(input.shape()[channelsIndex]); |
| 47 | unsigned int inputBatchSize = boost::numeric_cast<unsigned int>(input.shape()[0]); |
| 48 | |
| 49 | unsigned int outputHeight = boost::numeric_cast<unsigned int>(outputExpected.shape()[heightIndex]); |
| 50 | unsigned int outputWidth = boost::numeric_cast<unsigned int>(outputExpected.shape()[widthIndex]); |
| 51 | unsigned int outputChannels = boost::numeric_cast<unsigned int>(outputExpected.shape()[channelsIndex]); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 52 | unsigned int outputBatchSize = boost::numeric_cast<unsigned int>(outputExpected.shape()[0]); |
| 53 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 54 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( |
| 55 | inputBatchSize, inputChannels, inputHeight, inputWidth, dataLayout, ArmnnType); |
| 56 | |
| 57 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( |
| 58 | outputBatchSize, outputChannels, outputHeight, outputWidth, dataLayout, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 59 | |
| 60 | // Set quantization parameters if the requested type is a quantized type. |
| 61 | if(armnn::IsQuantizedType<T>()) |
| 62 | { |
| 63 | inputTensorInfo.SetQuantizationScale(qScale); |
| 64 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 65 | outputTensorInfo.SetQuantizationScale(qScale); |
| 66 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 67 | } |
| 68 | |
| 69 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 70 | |
| 71 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 72 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 73 | |
| 74 | armnn::Pooling2dQueueDescriptor queueDescriptor; |
| 75 | queueDescriptor.m_Parameters = descriptor; |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 76 | queueDescriptor.m_Parameters.m_DataLayout = dataLayout; |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 77 | |
| 78 | armnn::WorkloadInfo workloadInfo; |
| 79 | AddInputToWorkload(queueDescriptor, workloadInfo, inputTensorInfo, inputHandle.get()); |
| 80 | AddOutputToWorkload(queueDescriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| 81 | |
| 82 | // 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] | 83 | armnn::BackendId backend = workloadFactory.GetBackendId(); |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 84 | const size_t reasonIfUnsupportedMaxLen = 255; |
| 85 | char reasonIfUnsupported[reasonIfUnsupportedMaxLen+1]; |
David Beck | 79141b9 | 2018-10-23 16:09:36 +0100 | [diff] [blame] | 86 | result.supported = armnn::IsPooling2dSupported(backend, inputTensorInfo, outputTensorInfo, |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 87 | queueDescriptor.m_Parameters, |
| 88 | reasonIfUnsupported, reasonIfUnsupportedMaxLen); |
| 89 | if (!result.supported) |
| 90 | { |
| 91 | return result; |
| 92 | } |
| 93 | |
| 94 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePooling2d(queueDescriptor, workloadInfo); |
| 95 | |
| 96 | inputHandle->Allocate(); |
| 97 | outputHandle->Allocate(); |
| 98 | |
| 99 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 100 | |
| 101 | workload->Execute(); |
| 102 | |
| 103 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 104 | |
| 105 | result.outputExpected = outputExpected; |
| 106 | |
| 107 | return result; |
| 108 | } |
| 109 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 110 | // |
| 111 | // Tests max pooling with the following parameters: |
| 112 | // |
| 113 | // Pooling size: 3x3 |
| 114 | // Stride: (2,4) |
| 115 | // input size: 8x13 |
| 116 | // channels: 2 |
| 117 | // batch size: 2 |
| 118 | // |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 119 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 120 | LayerTestResult<T, 4> SimpleMaxPooling2dSize3x3Stride2x4TestCommon( |
| 121 | armnn::IWorkloadFactory& workloadFactory, |
| 122 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 123 | bool forceNoPadding, |
| 124 | float qScale = 1.0f, |
| 125 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 126 | { |
| 127 | armnn::Pooling2dDescriptor descriptor; |
| 128 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 129 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 130 | descriptor.m_StrideX = 2; |
| 131 | descriptor.m_StrideY = 4; |
| 132 | // forceNoPadding is mainly used for compatibility with ARM Compute. |
| 133 | // As of 16/05/2017, it errors if padX or padY are equal to or greater than the pool size. |
| 134 | descriptor.m_PadLeft = descriptor.m_PadRight = forceNoPadding ? 0 : 3; |
| 135 | descriptor.m_PadTop = descriptor.m_PadBottom = 0; |
| 136 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 137 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 138 | |
| 139 | unsigned int inputWidth = 8; |
| 140 | unsigned int inputHeight = 13; |
| 141 | unsigned int outputWidth = |
| 142 | (inputWidth + descriptor.m_PadLeft + descriptor.m_PadRight + descriptor.m_StrideX - descriptor.m_PoolWidth) / |
| 143 | descriptor.m_StrideX; |
| 144 | unsigned int outputHeight = |
| 145 | (inputHeight + descriptor.m_PadTop + descriptor.m_PadBottom + descriptor.m_StrideY - descriptor.m_PoolHeight) / |
| 146 | descriptor.m_StrideY; |
| 147 | unsigned int channels = 2; |
| 148 | unsigned int batchSize = 2; |
| 149 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 150 | armnn::TensorInfo inputTensorInfo({ batchSize, channels, inputHeight, inputWidth }, ArmnnType); |
| 151 | armnn::TensorInfo outputTensorInfo({ batchSize, channels, outputHeight, outputWidth }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 152 | |
| 153 | // Set quantization parameters if the requested type is a quantized type. |
| 154 | if(armnn::IsQuantizedType<T>()) |
| 155 | { |
| 156 | inputTensorInfo.SetQuantizationScale(qScale); |
| 157 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 158 | outputTensorInfo.SetQuantizationScale(qScale); |
| 159 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 160 | } |
| 161 | |
| 162 | std::vector<float> singleChannelData({ |
| 163 | 0.0f, 4.0f, 8.0f, 1.0f, 6.0f, 4.0f, 5.0f, 8.0f, |
| 164 | 1.0f, 1.0f, 6.0f, 0.0f, 3.0f, 7.0f, 4.0f, 7.0f, |
| 165 | 8.0f, 5.0f, 0.0f, 0.0f, 8.0f, 3.0f, 4.0f, 3.0f, |
| 166 | 8.0f, 2.0f, 5.0f, 4.0f, 1.0f, 9.0f, 2.0f, 0.0f, |
| 167 | 5.0f, 4.0f, 5.0f, 0.0f, 0.0f, 0.0f, 7.0f, 2.0f, |
| 168 | 1.0f, 2.0f, 6.0f, 2.0f, 7.0f, 9.0f, 5.0f, 2.0f, |
| 169 | 9.0f, 7.0f, 3.0f, 1.0f, 3.0f, 4.0f, 8.0f, 3.0f, |
| 170 | 1.0f, 0.0f, 0.0f, 5.0f, 5.0f, 4.0f, 2.0f, 0.0f, |
| 171 | 6.0f, 4.0f, 3.0f, 6.0f, 9.0f, 5.0f, 5.0f, 6.0f, |
| 172 | 8.0f, 7.0f, 9.0f, 6.0f, 1.0f, 4.0f, 1.0f, 9.0f, |
| 173 | 7.0f, 1.0f, 9.0f, 2.0f, 9.0f, 9.0f, 8.0f, 1.0f, |
| 174 | 4.0f, 4.0f, 5.0f, 9.0f, 2.0f, 6.0f, 6.0f, 4.0f, |
| 175 | 3.0f, 5.0f, 4.0f, 0.0f, 1.0f, 5.0f, 9.0f, 7.0f, |
| 176 | }); |
| 177 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 178 | // Constructs input data. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 179 | std::vector<float> inputData; |
| 180 | auto negator = [](float f) { return -f; }; |
| 181 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 182 | // 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] | 183 | inputData.insert(inputData.end(), singleChannelData.begin(), singleChannelData.end()); |
| 184 | std::transform(singleChannelData.begin(), singleChannelData.end(), std::back_inserter(inputData), negator); |
| 185 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 186 | // Second image (same as first image). |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 187 | inputData.insert(inputData.end(), singleChannelData.begin(), singleChannelData.end()); |
| 188 | std::transform(singleChannelData.begin(), singleChannelData.end(), std::back_inserter(inputData), negator); |
| 189 | |
| 190 | auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, inputData)); |
| 191 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 192 | // These were calculated manually. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 193 | auto shape(GetTensorShapeAsArray<4>(outputTensorInfo)); |
| 194 | boost::multi_array<T, 4> outputExpected(shape); |
| 195 | if (forceNoPadding) |
| 196 | { |
| 197 | outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 198 | QuantizedVector<T>(qScale, qOffset, { |
| 199 | 8.0f, 8.0f, 8.0f, |
| 200 | 9.0f, 7.0f, 9.0f, |
| 201 | 9.0f, 9.0f, 9.0f, |
| 202 | |
| 203 | 0.0f, 0.0f, -3.0f, |
| 204 | -1.0f, 0.0f, 0.0f, |
| 205 | -1.0f, -1.0f, -1.0f, |
| 206 | |
| 207 | 8.0f, 8.0f, 8.0f, |
| 208 | 9.0f, 7.0f, 9.0f, |
| 209 | 9.0f, 9.0f, 9.0f, |
| 210 | |
| 211 | 0.0f, 0.0f, -3.0f, |
| 212 | -1.0f, 0.0f, 0.0f, |
| 213 | -1.0f, -1.0f, -1.0f |
| 214 | })); |
| 215 | } |
| 216 | else |
| 217 | { |
| 218 | outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 219 | QuantizedVector<T>(qScale, qOffset, { |
| 220 | 0.0f, 8.0f, 8.0f, 8.0f, 8.0f, 8.0f, |
| 221 | 0.0f, 9.0f, 7.0f, 9.0f, 9.0f, 3.0f, |
| 222 | 0.0f, 8.0f, 9.0f, 9.0f, 9.0f, 9.0f, |
| 223 | |
| 224 | 0.0f, 0.0f, 0.0f, 0.0f,-3.0f, 0.0f, |
| 225 | 0.0f,-1.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 226 | 0.0f,-1.0f,-1.0f,-1.0f,-1.0f, 0.0f, |
| 227 | |
| 228 | 0.0f, 8.0f, 8.0f, 8.0f, 8.0f, 8.0f, |
| 229 | 0.0f, 9.0f, 7.0f, 9.0f, 9.0f, 3.0f, |
| 230 | 0.0f, 8.0f, 9.0f, 9.0f, 9.0f, 9.0f, |
| 231 | |
| 232 | 0.0f, 0.0f, 0.0f, 0.0f,-3.0f, 0.0f, |
| 233 | 0.0f,-1.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 234 | 0.0f,-1.0f,-1.0f,-1.0f,-1.0f, 0.0f |
| 235 | })); |
| 236 | } |
| 237 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 238 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 239 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 240 | } |
| 241 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 242 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 243 | LayerTestResult<T, 4> SimpleMaxPooling2dTestCommon( |
| 244 | armnn::IWorkloadFactory& workloadFactory, |
| 245 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 246 | const armnn::DataLayout dataLayout = armnn::DataLayout::NCHW, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 247 | float qScale = 1.0f, |
| 248 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 249 | { |
| 250 | armnn::Pooling2dDescriptor descriptor; |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 251 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 252 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| 253 | descriptor.m_StrideX = descriptor.m_StrideY = 2; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 254 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
James Conroy | 6948227 | 2018-10-19 10:41:35 +0100 | [diff] [blame] | 255 | descriptor.m_DataLayout = dataLayout; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 256 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 257 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo(1, 2, 4, 4, dataLayout, ArmnnType); |
| 258 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo(1, 2, 2, 2, dataLayout, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 259 | |
| 260 | // Set quantization parameters if the requested type is a quantized type. |
| 261 | if(armnn::IsQuantizedType<T>()) |
| 262 | { |
| 263 | inputTensorInfo.SetQuantizationScale(qScale); |
| 264 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 265 | outputTensorInfo.SetQuantizationScale(qScale); |
| 266 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 267 | } |
| 268 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 269 | std::vector<T> inputData( |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 270 | QuantizedVector<T>(qScale, qOffset, { |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 271 | 1.0f, 2.0f, 5.0f, 6.0f, |
| 272 | 3.0f, 4.0f, 7.0f, 8.0f, |
| 273 | 9.0f, 10.0f, 13.0f, 14.0f, |
| 274 | 11.0f, 12.0f, 15.0f, 16.0f, |
| 275 | |
| 276 | 17.0f, 18.0f, 21.0f, 22.0f, |
| 277 | 19.0f, 20.0f, 23.0f, 24.0f, |
| 278 | 25.0f, 26.0f, 29.0f, 30.0f, |
| 279 | 27.0f, 28.0f, 31.0f, 32.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 280 | })); |
| 281 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 282 | std::vector<T> outputData( |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 283 | QuantizedVector<T>(qScale, qOffset, { |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 284 | 4.0f, 8.0f, |
| 285 | 12.0f, 16.0f, |
| 286 | |
| 287 | 20.0f, 24.0f, |
| 288 | 28.0f, 32.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 289 | })); |
| 290 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 291 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 292 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 293 | { |
| 294 | std::vector<T> tmp(inputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 295 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(T)); |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 296 | inputData = tmp; |
| 297 | |
| 298 | std::vector<T> tmp1(outputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 299 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(T)); |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 300 | outputData = tmp1; |
| 301 | } |
| 302 | |
| 303 | auto input = MakeTensor<T, 4>(inputTensorInfo, inputData); |
| 304 | |
| 305 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, outputData); |
| 306 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 307 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 308 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 309 | } |
| 310 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 311 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 312 | LayerTestResult<T, 4> SimpleAveragePooling2dTestCommon( |
| 313 | armnn::IWorkloadFactory& workloadFactory, |
| 314 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 315 | armnn::DataLayout dataLayout = armnn::DataLayout::NCHW, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 316 | float qScale = 1.0f, |
| 317 | int32_t qOffset = 0) |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 318 | { |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 319 | armnn::Pooling2dDescriptor descriptor; |
| 320 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 321 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| 322 | descriptor.m_StrideX = descriptor.m_StrideY = 2; |
| 323 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 324 | descriptor.m_DataLayout = dataLayout; |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 325 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 326 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo(1, 2, 4, 4, dataLayout, ArmnnType); |
| 327 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo(1, 2, 2, 2, dataLayout, ArmnnType); |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 328 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 329 | // Set quantization parameters if the requested type is a quantized type. |
| 330 | if(armnn::IsQuantizedType<T>()) |
| 331 | { |
| 332 | inputTensorInfo.SetQuantizationScale(qScale); |
| 333 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 334 | outputTensorInfo.SetQuantizationScale(qScale); |
| 335 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 336 | } |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 337 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 338 | std::vector<T> inputData( |
| 339 | QuantizedVector<T>(qScale, qOffset, { |
| 340 | 2.0f, 2.0f, 6.0f, 6.0f, |
| 341 | 4.0f, 4.0f, 8.0f, 8.0f, |
| 342 | 10.0f, 12.0f, 14.0f, 16.0f, |
| 343 | 10.0f, 12.0f, 16.0f, 14.0f, |
| 344 | |
| 345 | 18.0f, 20.0f, 24.0f, 22.0f, |
| 346 | 20.0f, 18.0f, 22.0f, 24.0f, |
| 347 | 26.0f, 28.0f, 0.0f, 0.0f, |
| 348 | 26.0f, 28.0f, 0.0f, 0.0f, |
| 349 | })); |
| 350 | |
| 351 | std::vector<T> outputData( |
| 352 | QuantizedVector<T>(qScale, qOffset, { |
| 353 | 3.0f, 7.0f, |
| 354 | 11.0f, 15.0f, |
| 355 | |
| 356 | 19.0f, 23.0f, |
| 357 | 27.0f, 0.0f, |
| 358 | })); |
| 359 | |
| 360 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 361 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 362 | { |
| 363 | std::vector<T> tmp(inputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 364 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(T)); |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 365 | inputData = tmp; |
| 366 | |
| 367 | std::vector<T> tmp1(outputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 368 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(T)); |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 369 | outputData = tmp1; |
| 370 | } |
| 371 | |
| 372 | auto input = MakeTensor<T, 4>(inputTensorInfo, inputData); |
| 373 | |
| 374 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, outputData); |
| 375 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 376 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 377 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [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> LargeTensorsAveragePooling2dTestCommon( |
| 382 | armnn::IWorkloadFactory& workloadFactory, |
| 383 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 384 | float qScale = 1.0f, |
| 385 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 386 | { |
| 387 | armnn::Pooling2dDescriptor descriptor; |
| 388 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 389 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 100; |
| 390 | descriptor.m_StrideX = descriptor.m_StrideY = 5; |
| 391 | descriptor.m_PadLeft = 50; |
| 392 | descriptor.m_PadRight = 50; |
| 393 | descriptor.m_PadTop = 50; |
| 394 | descriptor.m_PadBottom = 50; |
| 395 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 396 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 397 | armnn::TensorInfo inputTensorInfo({ 5, 3, 52, 60 }, ArmnnType); |
| 398 | armnn::TensorInfo outputTensorInfo({ 5, 3, 11, 13 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 399 | |
| 400 | // Set quantization parameters if the requested type is a quantized type. |
| 401 | if(armnn::IsQuantizedType<T>()) |
| 402 | { |
| 403 | inputTensorInfo.SetQuantizationScale(qScale); |
| 404 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 405 | outputTensorInfo.SetQuantizationScale(qScale); |
| 406 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 407 | } |
| 408 | |
| 409 | std::vector<T> inputVec; |
| 410 | |
| 411 | for (unsigned int i = 0 ; i < inputTensorInfo.GetShape().GetNumElements(); ++i) |
| 412 | { |
| 413 | inputVec.push_back(1); |
| 414 | } |
| 415 | |
| 416 | auto input = MakeTensor<T, 4>(inputTensorInfo, inputVec); |
| 417 | |
| 418 | std::vector<T> outputVec; |
| 419 | |
| 420 | for (unsigned int i = 0 ; i < outputTensorInfo.GetShape().GetNumElements(); ++i) |
| 421 | { |
| 422 | outputVec.push_back(1); |
| 423 | } |
| 424 | |
| 425 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, outputVec); |
| 426 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 427 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 428 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 429 | } |
| 430 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 431 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 432 | LayerTestResult<T, 4> SimpleL2Pooling2dTestCommon( |
| 433 | armnn::IWorkloadFactory& workloadFactory, |
| 434 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 435 | armnn::DataLayout dataLayout = armnn::DataLayout::NCHW, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 436 | float qScale = 1.0f, |
| 437 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 438 | { |
| 439 | armnn::Pooling2dDescriptor descriptor; |
| 440 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 441 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| 442 | descriptor.m_StrideX = descriptor.m_StrideY = 2; |
| 443 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 444 | descriptor.m_DataLayout = dataLayout; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 445 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 446 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo(1, 2, 4, 4, dataLayout, ArmnnType); |
| 447 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo(1, 2, 2, 2, dataLayout, ArmnnType); |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 448 | |
| 449 | std::vector<T> inputData( |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 450 | QuantizedVector<T>(qScale, qOffset, { |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 451 | 1.0f, 7.0f, 5.0f, 5.0f, |
| 452 | 1.0f, 7.0f, 5.0f, 5.0f, |
| 453 | 3.0f, 3.0f, 1.0f, 1.0f, |
| 454 | 3.0f, 3.0f, 1.0f, 1.0f, |
| 455 | |
| 456 | 1.0f, 7.0f, 0.0f, 0.0f, |
| 457 | 1.0f, 7.0f, 2.0f, 0.0f, |
| 458 | 0.0f, 2.0f, 1.0f, 1.0f, |
| 459 | 0.0f, 0.0f, 1.0f, 1.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 460 | })); |
| 461 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 462 | std::vector<T> outputData( |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 463 | QuantizedVector<T>(qScale, qOffset, { |
| 464 | 5.0f, 5.0f, |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 465 | 3.0f, 1.0f, |
| 466 | |
| 467 | 5.0f, 1.0f, |
| 468 | 1.0f, 1.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 469 | })); |
| 470 | |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 471 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 472 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 473 | { |
| 474 | std::vector<T> tmp(inputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 475 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(T)); |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 476 | inputData = tmp; |
| 477 | |
| 478 | std::vector<T> tmp1(outputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 479 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(T)); |
James Conroy | 45a9b77 | 2018-10-31 11:47:53 +0000 | [diff] [blame] | 480 | outputData = tmp1; |
| 481 | } |
| 482 | |
| 483 | auto input = MakeTensor<T, 4>(inputTensorInfo, inputData); |
| 484 | |
| 485 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, outputData); |
| 486 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 487 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 488 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 489 | } |
| 490 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 491 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 492 | LayerTestResult<T, 4> L2Pooling2dSize3Stride1TestCommon( |
| 493 | armnn::IWorkloadFactory& workloadFactory, |
| 494 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 495 | float qScale = 1.0f, |
| 496 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 497 | { |
| 498 | armnn::Pooling2dDescriptor descriptor; |
| 499 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 500 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 501 | descriptor.m_StrideX = descriptor.m_StrideY = 1; |
| 502 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 503 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 504 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 505 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 506 | QuantizedVector<T>(qScale, qOffset, { |
| 507 | 2.0f, 1.0f, 5.0f, 2.0f, |
| 508 | 1.0f, 2.0f, 2.0f, 1.0f, |
| 509 | 5.0f, 4.0f, 1.0f, 5.0f, |
| 510 | 2.0f, 1.0f, 5.0f, 2.0f, |
| 511 | })); |
| 512 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 513 | armnn::TensorInfo outputTensorInfo({ 1, 1, 2, 2 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 514 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 515 | QuantizedVector<T>(qScale, qOffset, { |
| 516 | 3.0f, 3.0f, |
| 517 | 3.0f, 3.0f, |
| 518 | })); |
| 519 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 520 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 521 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 522 | } |
| 523 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 524 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 525 | LayerTestResult<T, 4> L2Pooling2dSize3Stride3TestCommon( |
| 526 | armnn::IWorkloadFactory& workloadFactory, |
| 527 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 528 | float qScale = 1.0f, |
| 529 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 530 | { |
| 531 | armnn::Pooling2dDescriptor descriptor; |
| 532 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 533 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 534 | descriptor.m_StrideX = descriptor.m_StrideY = 3; |
| 535 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 536 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 537 | armnn::TensorInfo inputTensorInfo({ 1, 1, 9, 9 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 538 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 539 | QuantizedVector<T>(qScale, qOffset, { |
| 540 | 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, |
| 541 | 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, |
| 542 | 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, |
| 543 | 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, |
| 544 | 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, |
| 545 | 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, |
| 546 | 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, |
| 547 | 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, |
| 548 | 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, |
| 549 | })); |
| 550 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 551 | armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 552 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 553 | QuantizedVector<T>(qScale, qOffset, { |
| 554 | 3.0f, 3.0f, 3.0f, |
| 555 | 3.0f, 3.0f, 3.0f, |
| 556 | 3.0f, 3.0f, 3.0f, |
| 557 | })); |
| 558 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 559 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 560 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 561 | } |
| 562 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 563 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 564 | LayerTestResult<T, 4> L2Pooling2dSize3Stride4TestCommon( |
| 565 | armnn::IWorkloadFactory& workloadFactory, |
| 566 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 567 | float qScale = 1.0f, |
| 568 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 569 | { |
| 570 | armnn::Pooling2dDescriptor descriptor; |
| 571 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 572 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 573 | descriptor.m_StrideX = descriptor.m_StrideY = 4; |
| 574 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 575 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 576 | armnn::TensorInfo inputTensorInfo({ 1, 1, 7, 7 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 577 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 578 | QuantizedVector<T>(qScale, qOffset, { |
| 579 | 2.0f, 1.0f, 5.0f, 0.0f, 2.0f, 1.0f, 5.0f, |
| 580 | 1.0f, 2.0f, 2.0f, 0.0f, 1.0f, 2.0f, 2.0f, |
| 581 | 5.0f, 4.0f, 1.0f, 0.0f, 5.0f, 4.0f, 1.0f, |
| 582 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 583 | 2.0f, 1.0f, 5.0f, 0.0f, 2.0f, 1.0f, 5.0f, |
| 584 | 1.0f, 2.0f, 2.0f, 0.0f, 1.0f, 2.0f, 2.0f, |
| 585 | 5.0f, 4.0f, 1.0f, 0.0f, 5.0f, 4.0f, 1.0f, |
| 586 | })); |
| 587 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 588 | armnn::TensorInfo outputTensorInfo({ 1, 1, 2, 2 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 589 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 590 | QuantizedVector<T>(qScale, qOffset, { |
| 591 | 3.0f, 3.0f, |
| 592 | 3.0f, 3.0f, |
| 593 | })); |
| 594 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 595 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 596 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 597 | } |
| 598 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 599 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 600 | LayerTestResult<T, 4> L2Pooling2dSize7TestCommon( |
| 601 | armnn::IWorkloadFactory& workloadFactory, |
| 602 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 603 | float qScale = 1.0f, |
| 604 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 605 | { |
| 606 | armnn::Pooling2dDescriptor descriptor; |
| 607 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 608 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 7; |
| 609 | descriptor.m_StrideX = descriptor.m_StrideY = 7; |
| 610 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 611 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 612 | armnn::TensorInfo inputTensorInfo({ 1, 1, 7, 7 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 613 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 614 | QuantizedVector<T>(qScale, qOffset, { |
| 615 | 1.0f, 0.0f, 2.0f, 0.0f, 3.0f, 0.0f, 4.0f, |
| 616 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 617 | 0.0f, 5.0f, 0.0f, 6.0f, 0.0f, 7.0f, 0.0f, |
| 618 | 8.0f, 0.0f, 9.0f, 0.0f, 10.0f, 0.0f, 5.0f, |
| 619 | 0.0f, 5.0f, 0.0f, 2.0f, 0.0f, 1.0f, 1.0f, |
| 620 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 621 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 622 | })); |
| 623 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 624 | armnn::TensorInfo outputTensorInfo({ 1, 1, 1, 1 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 625 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 626 | QuantizedVector<T>(qScale, qOffset, { |
| 627 | 3.0f, |
| 628 | })); |
| 629 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 630 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 631 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 632 | } |
| 633 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 634 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 635 | LayerTestResult<T, 4> L2Pooling2dSize9TestCommon( |
| 636 | armnn::IWorkloadFactory& workloadFactory, |
| 637 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 638 | float qScale = 1.0f, |
| 639 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 640 | { |
| 641 | armnn::Pooling2dDescriptor descriptor; |
| 642 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 643 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 9; |
| 644 | descriptor.m_StrideX = descriptor.m_StrideY = 9; |
| 645 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 646 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 647 | armnn::TensorInfo inputTensorInfo({ 1, 1, 9, 9 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 648 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 649 | QuantizedVector<T>(qScale, qOffset, { |
| 650 | 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, |
| 651 | 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, |
| 652 | 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, |
| 653 | 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, |
| 654 | 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, |
| 655 | 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, |
| 656 | 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, 2.0f, 1.0f, 5.0f, |
| 657 | 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, 1.0f, 2.0f, 2.0f, |
| 658 | 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, 5.0f, 4.0f, 1.0f, |
| 659 | })); |
| 660 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 661 | armnn::TensorInfo outputTensorInfo({ 1, 1, 1, 1 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 662 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 663 | QuantizedVector<T>(qScale, qOffset, { |
| 664 | 3.0f, |
| 665 | })); |
| 666 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 667 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 668 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 669 | } |
| 670 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 671 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 672 | LayerTestResult<T, 4> AsymmetricNonSquarePooling2dTestCommon( |
| 673 | armnn::IWorkloadFactory& workloadFactory, |
| 674 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 675 | float qScale = 1.0f, |
| 676 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 677 | { |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 678 | armnn::TensorInfo inputTensorInfo({ 1, 1, 1, 3 }, ArmnnType); |
| 679 | armnn::TensorInfo outputTensorInfo({ 1, 1, 2, 2 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 680 | |
| 681 | armnn::Pooling2dDescriptor descriptor; |
| 682 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 683 | descriptor.m_PoolWidth = 2; |
| 684 | descriptor.m_PoolHeight = 3; |
| 685 | descriptor.m_StrideX = 2; |
| 686 | descriptor.m_StrideY = 1; |
| 687 | descriptor.m_PadLeft = 2; |
| 688 | descriptor.m_PadRight = 0; |
| 689 | descriptor.m_PadTop = 1; |
| 690 | descriptor.m_PadBottom = 2; |
| 691 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 692 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 693 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 694 | // Construct input data. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 695 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 696 | QuantizedVector<T>(qScale, qOffset, { |
| 697 | 1.0f, 3.0f, 4.0f, |
| 698 | })); |
| 699 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 700 | // These were calculated manually. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 701 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 702 | QuantizedVector<T>(qScale, qOffset, { |
| 703 | 0.0f, 3.0f, 0.0f, 3.0f, |
| 704 | })); |
| 705 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 706 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 707 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 708 | } |
| 709 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 710 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 711 | LayerTestResult<T, 4> ComparePooling2dTestCommon( |
| 712 | armnn::IWorkloadFactory& workloadFactory, |
| 713 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 714 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 715 | armnn::PoolingAlgorithm poolingType, |
| 716 | float qScale = 1.0f, |
| 717 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 718 | { |
| 719 | const unsigned int inputWidth = 16; |
| 720 | const unsigned int inputHeight = 32; |
| 721 | const unsigned int channelCount = 2; |
| 722 | const unsigned int batchSize = 5; |
| 723 | |
| 724 | const unsigned int poolSize = 3; |
| 725 | const unsigned int strideX = 2; |
| 726 | const unsigned int strideY = 4; |
| 727 | const unsigned int padX = 0; |
| 728 | const unsigned int padY = 0; |
| 729 | |
| 730 | const unsigned int outputWidth = (inputWidth + 2 * padX + strideX - poolSize) / strideX; |
| 731 | const unsigned int outputHeight = (inputHeight + 2 * padY + strideY - poolSize) / strideY; |
| 732 | |
| 733 | armnn::TensorInfo inputTensorInfo; |
| 734 | armnn::TensorInfo outputTensorInfo; |
| 735 | |
| 736 | unsigned int inputShape[] = { batchSize, channelCount, inputHeight, inputWidth }; |
| 737 | unsigned int outputShape[] = { batchSize, channelCount, outputHeight, outputWidth }; |
| 738 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 739 | inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType); |
| 740 | outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 741 | |
| 742 | // Set quantization parameters if the requested type is a quantized type. |
| 743 | if(armnn::IsQuantizedType<T>()) |
| 744 | { |
| 745 | inputTensorInfo.SetQuantizationScale(qScale); |
| 746 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 747 | outputTensorInfo.SetQuantizationScale(qScale); |
| 748 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 749 | } |
| 750 | |
| 751 | boost::multi_array<T, 4> input = MakeRandomTensor<T, 4>(inputTensorInfo, 81715); |
| 752 | |
| 753 | LayerTestResult<T, 4> comparisonResult(outputTensorInfo); |
| 754 | |
| 755 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 756 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 757 | |
| 758 | armnn::Pooling2dQueueDescriptor data; |
| 759 | armnn::WorkloadInfo info; |
| 760 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 761 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 762 | data.m_Parameters.m_PoolType = poolingType; |
| 763 | data.m_Parameters.m_PoolWidth = poolSize; |
| 764 | data.m_Parameters.m_PoolHeight = poolSize; |
| 765 | data.m_Parameters.m_StrideX = strideX; |
| 766 | data.m_Parameters.m_StrideY = strideY; |
| 767 | data.m_Parameters.m_PadLeft = padX; |
| 768 | data.m_Parameters.m_PadRight = padX; |
| 769 | data.m_Parameters.m_PadTop = padY; |
| 770 | data.m_Parameters.m_PadBottom = padY; |
| 771 | data.m_Parameters.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 772 | |
| 773 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refWorkloadFactory.CreateTensorHandle(outputTensorInfo); |
| 774 | std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refWorkloadFactory.CreateTensorHandle(inputTensorInfo); |
| 775 | |
| 776 | // 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] | 777 | armnn::BackendId backend = workloadFactory.GetBackendId(); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 778 | const size_t reasonIfUnsupportedMaxLen = 255; |
| 779 | char reasonIfUnsupported[reasonIfUnsupportedMaxLen+1]; |
David Beck | 79141b9 | 2018-10-23 16:09:36 +0100 | [diff] [blame] | 780 | comparisonResult.supported = armnn::IsPooling2dSupported(backend, inputTensorInfo, outputTensorInfo, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 781 | data.m_Parameters, |
| 782 | reasonIfUnsupported, reasonIfUnsupportedMaxLen); |
| 783 | if (!comparisonResult.supported) |
| 784 | { |
| 785 | return comparisonResult; |
| 786 | } |
| 787 | |
| 788 | armnn::Pooling2dQueueDescriptor refData = data; |
| 789 | armnn::WorkloadInfo refInfo = info; |
| 790 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get()); |
| 791 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 792 | |
| 793 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePooling2d(data, info); |
| 794 | std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreatePooling2d(refData, refInfo); |
| 795 | |
| 796 | outputHandleRef->Allocate(); |
| 797 | inputHandleRef->Allocate(); |
| 798 | inputHandle->Allocate(); |
| 799 | outputHandle->Allocate(); |
| 800 | |
| 801 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 802 | CopyDataToITensorHandle(inputHandleRef.get(), &input[0][0][0][0]); |
| 803 | |
| 804 | workload->Execute(); |
| 805 | workloadRef->Execute(); |
| 806 | |
| 807 | CopyDataFromITensorHandle(&comparisonResult.output[0][0][0][0], outputHandle.get()); |
| 808 | CopyDataFromITensorHandle(&comparisonResult.outputExpected[0][0][0][0], outputHandleRef.get()); |
| 809 | |
| 810 | return comparisonResult; |
| 811 | } |
| 812 | |
| 813 | // |
| 814 | // Tests max pooling with the following parameters: |
| 815 | // |
| 816 | // Pooling size: 2x2 |
| 817 | // Stride: (2,2) |
| 818 | // input size: 4x4 |
| 819 | // channels: 1 |
| 820 | // batch size: 1 |
| 821 | // |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 822 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 823 | LayerTestResult<T, 4> SimpleMaxPooling2dSize2x2Stride2x2TestCommon( |
| 824 | armnn::IWorkloadFactory& workloadFactory, |
| 825 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 826 | bool forceNoPadding, |
| 827 | float qScale = 1.0f, |
| 828 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 829 | { |
| 830 | armnn::Pooling2dDescriptor descriptor; |
| 831 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 832 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| 833 | descriptor.m_StrideX = 2; |
| 834 | descriptor.m_StrideY = 2; |
| 835 | descriptor.m_PadLeft = descriptor.m_PadRight = forceNoPadding ? 0 : 3; |
| 836 | descriptor.m_PadTop = descriptor.m_PadBottom = 0; |
| 837 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 838 | descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 839 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 840 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 841 | unsigned int inputWidth = 4; |
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 inputHeight = 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 outputWidth = |
| 846 | (inputWidth + descriptor.m_PadLeft + descriptor.m_PadRight + descriptor.m_StrideX - descriptor.m_PoolWidth) / |
| 847 | descriptor.m_StrideX; |
| 848 | unsigned int outputHeight = |
| 849 | (inputHeight + descriptor.m_PadTop + descriptor.m_PadBottom + descriptor.m_StrideY - descriptor.m_PoolHeight) / |
| 850 | descriptor.m_StrideY; |
| 851 | unsigned int channels = 1; |
| 852 | unsigned int batchSize = 1; |
| 853 | |
| 854 | std::vector<float> inputData = { |
| 855 | 510.0f, 222.0f, 780.0f, 654.0f, |
| 856 | 141.0f, 276.0f, 15.0f, 546.0f, |
| 857 | 303.0f, 618.0f, 582.0f, 339.0f, |
| 858 | 438.0f, 564.0f, 573.0f, 402.0f |
| 859 | }; |
| 860 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 861 | // 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] | 862 | std::vector<float> expectedOutputDataWithPadding = { |
| 863 | 0.0f, 510.0f, 780.0f, 654.0f, 0.0f, |
| 864 | 0.0f, 438.0f, 618.0f, 402.0f, 0.0f |
| 865 | }; |
| 866 | |
| 867 | std::vector<float> expectedOutputDataNoPadding = { |
| 868 | 510.0f, 780.0f, |
| 869 | 618.0f, 582.0f |
| 870 | }; |
| 871 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 872 | armnn::TensorInfo inputTensorInfo({ batchSize, channels, inputHeight, inputWidth }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 873 | |
| 874 | // Scale and offset should match input - we're just calculating maximum values. |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 875 | armnn::TensorInfo outputTensorInfo({ batchSize, channels, outputHeight, outputWidth }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 876 | |
| 877 | // Set quantization parameters if the requested type is a quantized type. |
| 878 | if(armnn::IsQuantizedType<T>()) |
| 879 | { |
| 880 | inputTensorInfo.SetQuantizationScale(qScale); |
| 881 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 882 | outputTensorInfo.SetQuantizationScale(qScale); |
| 883 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 884 | } |
| 885 | |
| 886 | auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, inputData)); |
| 887 | |
| 888 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 889 | forceNoPadding ? QuantizedVector<T>(qScale, qOffset, expectedOutputDataNoPadding) : |
| 890 | QuantizedVector<T>(qScale, qOffset, expectedOutputDataWithPadding)); |
| 891 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 892 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 893 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 894 | } |
| 895 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 896 | // |
| 897 | // Tests max pooling with the following parameters: |
| 898 | // |
| 899 | // Pooling size: 3x2 |
| 900 | // Stride: (2,2) |
| 901 | // input size: 3x2 |
| 902 | // channels: 1 |
| 903 | // batch size: 1 |
| 904 | // |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 905 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 906 | LayerTestResult<T, 4> IgnorePaddingAveragePooling2dSize3x2Stride2x2TestCommon( |
| 907 | armnn::IWorkloadFactory& workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 908 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 909 | bool forceNoPadding, |
| 910 | float qScale = 1.0f, |
| 911 | int32_t qOffset = 0) |
| 912 | { |
| 913 | armnn::Pooling2dDescriptor descriptor; |
| 914 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 915 | descriptor.m_PoolWidth = 3; |
| 916 | descriptor.m_PoolHeight = 2; |
| 917 | descriptor.m_StrideX = 2; |
| 918 | descriptor.m_StrideY = 2; |
| 919 | descriptor.m_PadLeft = (forceNoPadding) ? 0 : 1; |
| 920 | descriptor.m_PadRight = descriptor.m_PadLeft; |
| 921 | descriptor.m_PadTop = 0; |
| 922 | descriptor.m_PadBottom = 0; |
| 923 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 924 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 925 | |
| 926 | unsigned int inputWidth = 3; |
| 927 | unsigned int inputHeight = 2; |
| 928 | unsigned int outputWidth = |
| 929 | (inputWidth + descriptor.m_PadLeft + descriptor.m_PadRight + descriptor.m_StrideX - descriptor.m_PoolWidth) / |
| 930 | descriptor.m_StrideX; |
| 931 | unsigned int outputHeight = |
| 932 | (inputHeight + descriptor.m_PadTop + descriptor.m_PadBottom + descriptor.m_StrideY - descriptor.m_PoolHeight) / |
| 933 | descriptor.m_StrideY; |
| 934 | unsigned int channels = 1; |
| 935 | unsigned int batchSize = 1; |
| 936 | |
| 937 | std::vector<float> inputData = { |
| 938 | 3.0f, 6.0f, 9.0f, |
| 939 | 12.0f, 15.0f, 18.0f, |
| 940 | }; |
| 941 | |
| 942 | std::vector<float> expectedOutputDataWithPadding = { |
| 943 | 6.0f, 8.0f, |
| 944 | }; |
| 945 | |
| 946 | std::vector<float> expectedOutputDataNoPadding = { |
| 947 | 10.5f, |
| 948 | }; |
| 949 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 950 | armnn::TensorInfo inputTensorInfo({ batchSize, channels, inputHeight, inputWidth }, ArmnnType); |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 951 | |
| 952 | // Scale and offset should match input - we're just calculating average values. |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 953 | armnn::TensorInfo outputTensorInfo({ batchSize, channels, outputHeight, outputWidth }, ArmnnType); |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 954 | |
| 955 | // Set quantization parameters if the requested type is a quantized type. |
| 956 | if(armnn::IsQuantizedType<T>()) |
| 957 | { |
| 958 | inputTensorInfo.SetQuantizationScale(qScale); |
| 959 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 960 | outputTensorInfo.SetQuantizationScale(qScale); |
| 961 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 962 | } |
| 963 | |
| 964 | auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, inputData)); |
| 965 | |
| 966 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 967 | forceNoPadding ? QuantizedVector<T>(qScale, qOffset, expectedOutputDataNoPadding) : |
| 968 | QuantizedVector<T>(qScale, qOffset, expectedOutputDataWithPadding)); |
| 969 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 970 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 971 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 972 | } |
| 973 | |
| 974 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 975 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 976 | LayerTestResult<T, 4> IgnorePaddingSimpleMaxPooling2dTestCommon( |
| 977 | armnn::IWorkloadFactory& workloadFactory, |
| 978 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 979 | float qScale = 1.0f, |
| 980 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 981 | { |
| 982 | armnn::Pooling2dDescriptor descriptor; |
| 983 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 984 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| 985 | descriptor.m_StrideX = descriptor.m_StrideY = 2; |
| 986 | descriptor.m_PadLeft = 1; |
| 987 | descriptor.m_PadRight = 1; |
| 988 | descriptor.m_PadTop = 1; |
| 989 | descriptor.m_PadBottom = 1; |
| 990 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 991 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 992 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
| 993 | armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 994 | |
| 995 | // Set quantization parameters if the requested type is a quantized type. |
| 996 | if(armnn::IsQuantizedType<T>()) |
| 997 | { |
| 998 | inputTensorInfo.SetQuantizationScale(qScale); |
| 999 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1000 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1001 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1002 | } |
| 1003 | |
| 1004 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 1005 | QuantizedVector<T>(qScale, qOffset, { |
| 1006 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 1007 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 1008 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 1009 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 1010 | })); |
| 1011 | |
| 1012 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 1013 | QuantizedVector<T>(qScale, qOffset, { |
| 1014 | -1.0f, 3.0f, 4.0f, |
| 1015 | 1.0f, 3.0f, 4.0f, |
| 1016 | 1.0f, 2.0f, -4.0f, |
| 1017 | })); |
| 1018 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1019 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1020 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1021 | } |
| 1022 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1023 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1024 | LayerTestResult<T, 4> IgnorePaddingMaxPooling2dSize3TestCommon( |
| 1025 | armnn::IWorkloadFactory& workloadFactory, |
| 1026 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1027 | float qScale = 1.0f, |
| 1028 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1029 | { |
| 1030 | armnn::Pooling2dDescriptor descriptor; |
| 1031 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 1032 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 1033 | descriptor.m_StrideX = descriptor.m_StrideY = 1; |
| 1034 | descriptor.m_PadLeft = 1; |
| 1035 | descriptor.m_PadRight = 1; |
| 1036 | descriptor.m_PadTop = 1; |
| 1037 | descriptor.m_PadBottom = 1; |
| 1038 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 1039 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1040 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
| 1041 | armnn::TensorInfo outputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1042 | |
| 1043 | // Set quantization parameters if the requested type is a quantized type. |
| 1044 | if(armnn::IsQuantizedType<T>()) |
| 1045 | { |
| 1046 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1047 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1048 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1049 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1050 | } |
| 1051 | |
| 1052 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 1053 | QuantizedVector<T>(qScale, qOffset, { |
| 1054 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 1055 | -1.0f, -2.0f, 3.0f, 4.0f, |
| 1056 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 1057 | 1.0f, 2.0f, -3.0f, -4.0f, |
| 1058 | })); |
| 1059 | |
| 1060 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 1061 | QuantizedVector<T>(qScale, qOffset, { |
| 1062 | -1.0f, 3.0f, 4.0f, 4.0f, |
| 1063 | 2.0f, 3.0f, 4.0f, 4.0f, |
| 1064 | 2.0f, 3.0f, 4.0f, 4.0f, |
| 1065 | 2.0f, 2.0f, 2.0f, -3.0f, |
| 1066 | })); |
| 1067 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1068 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1069 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1070 | } |
| 1071 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1072 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1073 | LayerTestResult<T, 4> IgnorePaddingSimpleAveragePooling2dTestCommon( |
| 1074 | armnn::IWorkloadFactory& workloadFactory, |
| 1075 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1076 | float qScale = 1.0f, |
| 1077 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1078 | { |
| 1079 | armnn::Pooling2dDescriptor descriptor; |
| 1080 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 1081 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| 1082 | descriptor.m_StrideX = descriptor.m_StrideY = 2; |
| 1083 | descriptor.m_PadLeft = 1; |
| 1084 | descriptor.m_PadRight = 1; |
| 1085 | descriptor.m_PadTop = 1; |
| 1086 | descriptor.m_PadBottom = 1; |
| 1087 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 1088 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1089 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
| 1090 | armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1091 | |
| 1092 | // Set quantization parameters if the requested type is a quantized type. |
| 1093 | if(armnn::IsQuantizedType<T>()) |
| 1094 | { |
| 1095 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1096 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1097 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1098 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1099 | } |
| 1100 | |
| 1101 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 1102 | QuantizedVector<T>(qScale, qOffset, { |
| 1103 | 12.0f, 20.0f, 32.0f, 40.0f, |
| 1104 | 12.0f, 20.0f, 32.0f, 40.0f, |
| 1105 | 12.0f, 20.0f, 32.0f, 40.0f, |
| 1106 | 12.0f, 20.0f, 32.0f, 40.0f, |
| 1107 | })); |
| 1108 | |
| 1109 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 1110 | QuantizedVector<T>(qScale, qOffset, { |
| 1111 | 3.0f, 13.0f, 10.0f, |
| 1112 | 6.0f, 26.0f, 20.0f, |
| 1113 | 3.0f, 13.0f, 10.0f, |
| 1114 | })); |
| 1115 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1116 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1117 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1118 | } |
| 1119 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1120 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1121 | LayerTestResult<T, 4> IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon( |
| 1122 | armnn::IWorkloadFactory& workloadFactory, |
| 1123 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1124 | float qScale = 1.0f, |
| 1125 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1126 | { |
| 1127 | armnn::Pooling2dDescriptor descriptor; |
| 1128 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 1129 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 1130 | descriptor.m_StrideX = descriptor.m_StrideY = 2; |
| 1131 | descriptor.m_PadLeft = 0; |
| 1132 | descriptor.m_PadRight = 0; |
| 1133 | descriptor.m_PadTop = 0; |
| 1134 | descriptor.m_PadBottom = 0; |
| 1135 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 1136 | descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Ceiling; |
| 1137 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1138 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4}, ArmnnType); |
| 1139 | armnn::TensorInfo outputTensorInfo({ 1, 1, 2, 2 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1140 | |
| 1141 | // Set quantization parameters if the requested type is a quantized type. |
| 1142 | if(armnn::IsQuantizedType<T>()) |
| 1143 | { |
| 1144 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1145 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1146 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1147 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1148 | } |
| 1149 | |
| 1150 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 1151 | QuantizedVector<T>(qScale, qOffset, { |
| 1152 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1153 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1154 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1155 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1156 | })); |
| 1157 | |
| 1158 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 1159 | QuantizedVector<T>(qScale, qOffset, { |
| 1160 | 2.0f, 3.5f, |
| 1161 | 2.0f, 3.5f |
| 1162 | })); |
| 1163 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1164 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1165 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1166 | } |
| 1167 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1168 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1169 | LayerTestResult<T, 4> IgnorePaddingAveragePooling2dSize3TestCommon( |
| 1170 | armnn::IWorkloadFactory& workloadFactory, |
| 1171 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1172 | float qScale = 1.0f, |
| 1173 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1174 | { |
| 1175 | armnn::Pooling2dDescriptor descriptor; |
| 1176 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 1177 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 1178 | descriptor.m_StrideX = descriptor.m_StrideY = 1; |
| 1179 | descriptor.m_PadLeft = 1; |
| 1180 | descriptor.m_PadRight = 1; |
| 1181 | descriptor.m_PadTop = 1; |
| 1182 | descriptor.m_PadBottom = 1; |
| 1183 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 1184 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1185 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
| 1186 | armnn::TensorInfo outputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1187 | |
| 1188 | // Set quantization parameters if the requested type is a quantized type. |
| 1189 | if(armnn::IsQuantizedType<T>()) |
| 1190 | { |
| 1191 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1192 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1193 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1194 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1195 | } |
| 1196 | |
| 1197 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 1198 | QuantizedVector<T>(qScale, qOffset, { |
| 1199 | 9.0f, 27.0f, 18.0f, 36.0f, |
| 1200 | 18.0f, 9.0f, 18.0f, 9.0f, |
| 1201 | 27.0f, 18.0f, 9.0f, 27.0f, |
| 1202 | 9.0f, 27.0f, 9.0f, 18.0f, |
| 1203 | })); |
| 1204 | |
| 1205 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 1206 | QuantizedVector<T>(qScale, qOffset, { |
| 1207 | 7.0f, 11.0f, 13.0f, 9.0f, |
| 1208 | 12.0f, 17.0f, 19.0f, 13.0f, |
| 1209 | 12.0f, 16.0f, 16.0f, 10.0f, |
| 1210 | 9.0f, 11.0f, 12.0f, 7.0f, |
| 1211 | })); |
| 1212 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1213 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1214 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1215 | } |
| 1216 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1217 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1218 | LayerTestResult<T, 4> IgnorePaddingSimpleL2Pooling2dTestCommon( |
| 1219 | armnn::IWorkloadFactory& workloadFactory, |
| 1220 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1221 | float qScale = 1.0f, |
| 1222 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1223 | { |
| 1224 | armnn::Pooling2dDescriptor descriptor; |
| 1225 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 1226 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2; |
| 1227 | descriptor.m_StrideX = descriptor.m_StrideY = 2; |
| 1228 | descriptor.m_PadLeft = 1; |
| 1229 | descriptor.m_PadRight = 1; |
| 1230 | descriptor.m_PadTop = 1; |
| 1231 | descriptor.m_PadBottom = 1; |
| 1232 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 1233 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1234 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
| 1235 | armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1236 | |
| 1237 | // Set quantization parameters if the requested type is a quantized type. |
| 1238 | if(armnn::IsQuantizedType<T>()) |
| 1239 | { |
| 1240 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1241 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1242 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1243 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1244 | } |
| 1245 | |
| 1246 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 1247 | QuantizedVector<T>(qScale, qOffset, { |
| 1248 | 2.0f, 4.0f, 8.0f, 16.0f, |
| 1249 | 4.0f, 2.0f, 2.0f, 4.0f, |
| 1250 | 8.0f, 2.0f, 4.0f, 2.0f, |
| 1251 | 16.0f, 2.0f, 2.0f, 8.0f, |
| 1252 | })); |
| 1253 | |
| 1254 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 1255 | QuantizedVector<T>(qScale, qOffset, { |
| 1256 | 1.0f, 4.4721f, 8.0f, |
| 1257 | 4.4721f, 2.6457f, 2.236f, |
| 1258 | 8.0f, 1.4142f, 4.0f, |
| 1259 | })); |
| 1260 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1261 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1262 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1263 | } |
| 1264 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1265 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1266 | LayerTestResult<T, 4> IgnorePaddingL2Pooling2dSize3TestCommon( |
| 1267 | armnn::IWorkloadFactory& workloadFactory, |
| 1268 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1269 | float qScale = 1.0f, |
| 1270 | int32_t qOffset = 0) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1271 | { |
| 1272 | armnn::Pooling2dDescriptor descriptor; |
| 1273 | descriptor.m_PoolType = armnn::PoolingAlgorithm::L2; |
| 1274 | descriptor.m_PoolWidth = descriptor.m_PoolHeight = 3; |
| 1275 | descriptor.m_StrideX = descriptor.m_StrideY = 1; |
| 1276 | descriptor.m_PadLeft = 1; |
| 1277 | descriptor.m_PadRight = 1; |
| 1278 | descriptor.m_PadTop = 1; |
| 1279 | descriptor.m_PadBottom = 1; |
| 1280 | descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; |
| 1281 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1282 | armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
| 1283 | armnn::TensorInfo outputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1284 | |
| 1285 | // Set quantization parameters if the requested type is a quantized type. |
| 1286 | if(armnn::IsQuantizedType<T>()) |
| 1287 | { |
| 1288 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1289 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1290 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1291 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1292 | } |
| 1293 | |
| 1294 | auto input = MakeTensor<T, 4>(inputTensorInfo, |
| 1295 | QuantizedVector<T>(qScale, qOffset, { |
| 1296 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1297 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1298 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1299 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 1300 | })); |
| 1301 | |
| 1302 | auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, |
| 1303 | QuantizedVector<T>(qScale, qOffset, { |
| 1304 | 1.0540f, 1.7638f, 2.5385f, 2.3570f, |
| 1305 | 1.2909f, 2.1602f, 3.1091f, 2.8867f, |
| 1306 | 1.2909f, 2.1602f, 3.1091f, 2.8867f, |
| 1307 | 1.0540f, 1.7638f, 2.5385f, 2.3570f, |
| 1308 | })); |
| 1309 | |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 1310 | return SimplePooling2dTestImpl<ArmnnType>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1311 | workloadFactory, memoryManager, descriptor, qScale, qOffset, input, outputExpected); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1312 | } |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1313 | |
| 1314 | } // anonymous namespace |
| 1315 | |
| 1316 | LayerTestResult<float, 4> SimpleMaxPooling2dSize2x2Stride2x2Test( |
| 1317 | armnn::IWorkloadFactory& workloadFactory, |
| 1318 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1319 | bool forceNoPadding) |
| 1320 | { |
| 1321 | return SimpleMaxPooling2dSize2x2Stride2x2TestCommon<armnn::DataType::Float32>( |
| 1322 | workloadFactory, memoryManager, forceNoPadding); |
| 1323 | } |
| 1324 | |
| 1325 | LayerTestResult<uint8_t, 4> SimpleMaxPooling2dSize2x2Stride2x2Uint8Test( |
| 1326 | armnn::IWorkloadFactory& workloadFactory, |
| 1327 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1328 | bool forceNoPadding) |
| 1329 | { |
| 1330 | return SimpleMaxPooling2dSize2x2Stride2x2TestCommon<armnn::DataType::QuantisedAsymm8>( |
| 1331 | workloadFactory, memoryManager, forceNoPadding, 3.0f, -5); |
| 1332 | } |
| 1333 | |
| 1334 | LayerTestResult<int16_t, 4> SimpleMaxPooling2dSize2x2Stride2x2Int16Test( |
| 1335 | armnn::IWorkloadFactory& workloadFactory, |
| 1336 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1337 | bool forceNoPadding) |
| 1338 | { |
| 1339 | return SimpleMaxPooling2dSize2x2Stride2x2TestCommon<armnn::DataType::QuantisedSymm16>( |
| 1340 | workloadFactory, memoryManager, forceNoPadding); |
| 1341 | } |
| 1342 | |
| 1343 | LayerTestResult<float, 4> SimpleMaxPooling2dSize3x3Stride2x4Test( |
| 1344 | armnn::IWorkloadFactory& workloadFactory, |
| 1345 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1346 | bool forceNoPadding) |
| 1347 | { |
| 1348 | return SimpleMaxPooling2dSize3x3Stride2x4TestCommon<armnn::DataType::Float32>( |
| 1349 | workloadFactory, memoryManager, forceNoPadding); |
| 1350 | } |
| 1351 | |
| 1352 | LayerTestResult<uint8_t, 4> SimpleMaxPooling2dSize3x3Stride2x4Uint8Test( |
| 1353 | armnn::IWorkloadFactory& workloadFactory, |
| 1354 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1355 | bool forceNoPadding) |
| 1356 | { |
| 1357 | return SimpleMaxPooling2dSize3x3Stride2x4TestCommon<armnn::DataType::QuantisedAsymm8>( |
| 1358 | workloadFactory, memoryManager, forceNoPadding, 0.1f, 128); |
| 1359 | } |
| 1360 | |
| 1361 | LayerTestResult<int16_t, 4> SimpleMaxPooling2dSize3x3Stride2x4Int16Test( |
| 1362 | armnn::IWorkloadFactory& workloadFactory, |
| 1363 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1364 | bool forceNoPadding) |
| 1365 | { |
| 1366 | return SimpleMaxPooling2dSize3x3Stride2x4TestCommon<armnn::DataType::QuantisedSymm16>( |
| 1367 | workloadFactory, memoryManager, forceNoPadding); |
| 1368 | } |
| 1369 | |
| 1370 | LayerTestResult<float, 4> SimpleMaxPooling2dTest( |
| 1371 | armnn::IWorkloadFactory& workloadFactory, |
| 1372 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1373 | const armnn::DataLayout dataLayout) |
| 1374 | { |
| 1375 | return SimpleMaxPooling2dTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, dataLayout); |
| 1376 | } |
| 1377 | |
| 1378 | LayerTestResult<uint8_t, 4> SimpleMaxPooling2dUint8Test( |
| 1379 | armnn::IWorkloadFactory& workloadFactory, |
| 1380 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1381 | const armnn::DataLayout dataLayout) |
| 1382 | { |
| 1383 | return SimpleMaxPooling2dTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, dataLayout); |
| 1384 | } |
| 1385 | |
| 1386 | LayerTestResult<int16_t, 4> SimpleMaxPooling2dInt16Test( |
| 1387 | armnn::IWorkloadFactory& workloadFactory, |
| 1388 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1389 | const armnn::DataLayout dataLayout) |
| 1390 | { |
| 1391 | return SimpleMaxPooling2dTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, dataLayout); |
| 1392 | } |
| 1393 | LayerTestResult<float, 4> IgnorePaddingSimpleMaxPooling2dTest( |
| 1394 | armnn::IWorkloadFactory& workloadFactory, |
| 1395 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1396 | { |
| 1397 | return IgnorePaddingSimpleMaxPooling2dTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
| 1398 | } |
| 1399 | |
| 1400 | LayerTestResult<uint8_t, 4> IgnorePaddingSimpleMaxPooling2dUint8Test( |
| 1401 | armnn::IWorkloadFactory& workloadFactory, |
| 1402 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1403 | { |
| 1404 | return IgnorePaddingSimpleMaxPooling2dTestCommon<armnn::DataType::QuantisedAsymm8>( |
| 1405 | workloadFactory, memoryManager, 1.0f, -5); |
| 1406 | } |
| 1407 | |
| 1408 | LayerTestResult<int16_t, 4> IgnorePaddingSimpleMaxPooling2dInt16Test( |
| 1409 | armnn::IWorkloadFactory& workloadFactory, |
| 1410 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1411 | { |
| 1412 | return IgnorePaddingSimpleMaxPooling2dTestCommon<armnn::DataType::QuantisedSymm16>( |
| 1413 | workloadFactory, memoryManager); |
| 1414 | } |
| 1415 | |
| 1416 | LayerTestResult<float, 4> IgnorePaddingMaxPooling2dSize3Test( |
| 1417 | armnn::IWorkloadFactory& workloadFactory, |
| 1418 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1419 | { |
| 1420 | return IgnorePaddingMaxPooling2dSize3TestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
| 1421 | } |
| 1422 | |
| 1423 | LayerTestResult<uint8_t, 4> IgnorePaddingMaxPooling2dSize3Uint8Test( |
| 1424 | armnn::IWorkloadFactory& workloadFactory, |
| 1425 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1426 | { |
| 1427 | return IgnorePaddingMaxPooling2dSize3TestCommon<armnn::DataType::QuantisedAsymm8>( |
| 1428 | workloadFactory, memoryManager, 1.0f, -5); |
| 1429 | } |
| 1430 | |
| 1431 | LayerTestResult<int16_t, 4> IgnorePaddingMaxPooling2dSize3Int16Test( |
| 1432 | armnn::IWorkloadFactory& workloadFactory, |
| 1433 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1434 | { |
| 1435 | return IgnorePaddingMaxPooling2dSize3TestCommon<armnn::DataType::QuantisedSymm16>( |
| 1436 | workloadFactory, memoryManager); |
| 1437 | } |
| 1438 | |
| 1439 | LayerTestResult<float, 4> SimpleAveragePooling2dTest( |
| 1440 | armnn::IWorkloadFactory& workloadFactory, |
| 1441 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1442 | const armnn::DataLayout dataLayout) |
| 1443 | { |
| 1444 | return SimpleAveragePooling2dTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, dataLayout); |
| 1445 | } |
| 1446 | |
| 1447 | LayerTestResult<uint8_t, 4> SimpleAveragePooling2dUint8Test( |
| 1448 | armnn::IWorkloadFactory& workloadFactory, |
| 1449 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1450 | const armnn::DataLayout dataLayout) |
| 1451 | { |
| 1452 | return SimpleAveragePooling2dTestCommon<armnn::DataType::QuantisedAsymm8>( |
| 1453 | workloadFactory, memoryManager, dataLayout, 0.5, -1); |
| 1454 | } |
| 1455 | |
| 1456 | LayerTestResult<int16_t, 4> SimpleAveragePooling2dInt16Test( |
| 1457 | armnn::IWorkloadFactory& workloadFactory, |
| 1458 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1459 | const armnn::DataLayout dataLayout) |
| 1460 | { |
| 1461 | return SimpleAveragePooling2dTestCommon<armnn::DataType::QuantisedSymm16>( |
| 1462 | workloadFactory, memoryManager, dataLayout); |
| 1463 | } |
| 1464 | |
| 1465 | LayerTestResult<float, 4> IgnorePaddingAveragePooling2dSize3x2Stride2x2Test( |
| 1466 | armnn::IWorkloadFactory& workloadFactory, |
| 1467 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1468 | bool forceNoPadding) |
| 1469 | { |
| 1470 | return IgnorePaddingAveragePooling2dSize3x2Stride2x2TestCommon<armnn::DataType::Float32>( |
| 1471 | workloadFactory, memoryManager, forceNoPadding); |
| 1472 | } |
| 1473 | |
| 1474 | LayerTestResult<float, 4> LargeTensorsAveragePooling2dTest( |
| 1475 | armnn::IWorkloadFactory& workloadFactory, |
| 1476 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1477 | { |
| 1478 | return LargeTensorsAveragePooling2dTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
| 1479 | } |
| 1480 | |
| 1481 | LayerTestResult<uint8_t, 4> LargeTensorsAveragePooling2dUint8Test( |
| 1482 | armnn::IWorkloadFactory& workloadFactory, |
| 1483 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1484 | { |
| 1485 | return LargeTensorsAveragePooling2dTestCommon<armnn::DataType::QuantisedAsymm8>( |
| 1486 | workloadFactory, memoryManager, 0.5, -1); |
| 1487 | } |
| 1488 | |
| 1489 | LayerTestResult<int16_t, 4> LargeTensorsAveragePooling2dInt16Test( |
| 1490 | armnn::IWorkloadFactory& workloadFactory, |
| 1491 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1492 | { |
| 1493 | return LargeTensorsAveragePooling2dTestCommon<armnn::DataType::QuantisedSymm16>( |
| 1494 | workloadFactory, memoryManager); |
| 1495 | } |
| 1496 | LayerTestResult<float, 4> IgnorePaddingSimpleAveragePooling2dTest( |
| 1497 | armnn::IWorkloadFactory& workloadFactory, |
| 1498 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1499 | { |
| 1500 | return IgnorePaddingSimpleAveragePooling2dTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
| 1501 | } |
| 1502 | |
| 1503 | LayerTestResult<uint8_t, 4> IgnorePaddingSimpleAveragePooling2dUint8Test( |
| 1504 | armnn::IWorkloadFactory& workloadFactory, |
| 1505 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1506 | { |
| 1507 | return IgnorePaddingSimpleAveragePooling2dTestCommon<armnn::DataType::QuantisedAsymm8>( |
| 1508 | workloadFactory, memoryManager); |
| 1509 | } |
| 1510 | |
| 1511 | LayerTestResult<int16_t, 4> IgnorePaddingSimpleAveragePooling2dInt16Test( |
| 1512 | armnn::IWorkloadFactory& workloadFactory, |
| 1513 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1514 | { |
| 1515 | return IgnorePaddingSimpleAveragePooling2dTestCommon<armnn::DataType::QuantisedSymm16>( |
| 1516 | workloadFactory, memoryManager); |
| 1517 | } |
| 1518 | |
| 1519 | LayerTestResult<float, 4> IgnorePaddingSimpleAveragePooling2dNoPaddingTest( |
| 1520 | armnn::IWorkloadFactory& workloadFactory, |
| 1521 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1522 | { |
| 1523 | return IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon<armnn::DataType::Float32>( |
| 1524 | workloadFactory, memoryManager); |
| 1525 | } |
| 1526 | |
| 1527 | LayerTestResult<uint8_t, 4> IgnorePaddingSimpleAveragePooling2dNoPaddingUint8Test( |
| 1528 | armnn::IWorkloadFactory& workloadFactory, |
| 1529 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1530 | { |
| 1531 | return IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon<armnn::DataType::QuantisedAsymm8>( |
| 1532 | workloadFactory, memoryManager); |
| 1533 | } |
| 1534 | |
| 1535 | LayerTestResult<int16_t, 4> IgnorePaddingSimpleAveragePooling2dNoPaddingInt16Test( |
| 1536 | armnn::IWorkloadFactory& workloadFactory, |
| 1537 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1538 | { |
| 1539 | return IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon<armnn::DataType::QuantisedSymm16>( |
| 1540 | workloadFactory, memoryManager); |
| 1541 | } |
| 1542 | |
| 1543 | LayerTestResult<float, 4> IgnorePaddingAveragePooling2dSize3Test( |
| 1544 | armnn::IWorkloadFactory& workloadFactory, |
| 1545 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1546 | { |
| 1547 | return IgnorePaddingAveragePooling2dSize3TestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
| 1548 | } |
| 1549 | |
| 1550 | LayerTestResult<uint8_t, 4> IgnorePaddingAveragePooling2dSize3Uint8Test( |
| 1551 | armnn::IWorkloadFactory& workloadFactory, |
| 1552 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1553 | { |
| 1554 | return IgnorePaddingAveragePooling2dSize3TestCommon<armnn::DataType::QuantisedAsymm8>( |
| 1555 | workloadFactory, memoryManager); |
| 1556 | } |
| 1557 | |
| 1558 | LayerTestResult<int16_t, 4> IgnorePaddingAveragePooling2dSize3Int16Test( |
| 1559 | armnn::IWorkloadFactory& workloadFactory, |
| 1560 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1561 | { |
| 1562 | return IgnorePaddingAveragePooling2dSize3TestCommon<armnn::DataType::QuantisedSymm16>( |
| 1563 | workloadFactory, memoryManager); |
| 1564 | } |
| 1565 | |
| 1566 | LayerTestResult<float, 4> SimpleL2Pooling2dTest( |
| 1567 | armnn::IWorkloadFactory& workloadFactory, |
| 1568 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1569 | const armnn::DataLayout dataLayout) |
| 1570 | { |
| 1571 | return SimpleL2Pooling2dTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, dataLayout); |
| 1572 | } |
| 1573 | |
| 1574 | LayerTestResult<uint8_t, 4> SimpleL2Pooling2dUint8Test( |
| 1575 | armnn::IWorkloadFactory& workloadFactory, |
| 1576 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1577 | const armnn::DataLayout dataLayout) |
| 1578 | { |
| 1579 | return SimpleL2Pooling2dTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, dataLayout); |
| 1580 | } |
| 1581 | |
| 1582 | LayerTestResult<int16_t, 4> SimpleL2Pooling2dInt16Test( |
| 1583 | armnn::IWorkloadFactory& workloadFactory, |
| 1584 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1585 | const armnn::DataLayout dataLayout) |
| 1586 | { |
| 1587 | return SimpleL2Pooling2dTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, dataLayout); |
| 1588 | } |
| 1589 | |
| 1590 | LayerTestResult<float, 4> L2Pooling2dSize3Stride1Test( |
| 1591 | armnn::IWorkloadFactory& workloadFactory, |
| 1592 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1593 | { |
| 1594 | return L2Pooling2dSize3Stride1TestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
| 1595 | } |
| 1596 | |
| 1597 | LayerTestResult<uint8_t, 4> L2Pooling2dSize3Stride1Uint8Test( |
| 1598 | armnn::IWorkloadFactory& workloadFactory, |
| 1599 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1600 | { |
| 1601 | return L2Pooling2dSize3Stride1TestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager); |
| 1602 | } |
| 1603 | |
| 1604 | LayerTestResult<int16_t, 4> L2Pooling2dSize3Stride1Int16Test( |
| 1605 | armnn::IWorkloadFactory& workloadFactory, |
| 1606 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1607 | { |
| 1608 | return L2Pooling2dSize3Stride1TestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager); |
| 1609 | } |
| 1610 | |
| 1611 | LayerTestResult<float, 4> L2Pooling2dSize3Stride3Test( |
| 1612 | armnn::IWorkloadFactory& workloadFactory, |
| 1613 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1614 | { |
| 1615 | return L2Pooling2dSize3Stride3TestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
| 1616 | } |
| 1617 | |
| 1618 | LayerTestResult<uint8_t, 4> L2Pooling2dSize3Stride3Uint8Test( |
| 1619 | armnn::IWorkloadFactory& workloadFactory, |
| 1620 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1621 | { |
| 1622 | return L2Pooling2dSize3Stride3TestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager); |
| 1623 | } |
| 1624 | |
| 1625 | LayerTestResult<int16_t, 4> L2Pooling2dSize3Stride3Int16Test( |
| 1626 | armnn::IWorkloadFactory& workloadFactory, |
| 1627 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1628 | { |
| 1629 | return L2Pooling2dSize3Stride3TestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager); |
| 1630 | } |
| 1631 | LayerTestResult<float, 4> L2Pooling2dSize3Stride4Test( |
| 1632 | armnn::IWorkloadFactory& workloadFactory, |
| 1633 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1634 | { |
| 1635 | return L2Pooling2dSize3Stride4TestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
| 1636 | } |
| 1637 | |
| 1638 | LayerTestResult<uint8_t, 4> L2Pooling2dSize3Stride4Uint8Test( |
| 1639 | armnn::IWorkloadFactory& workloadFactory, |
| 1640 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1641 | { |
| 1642 | return L2Pooling2dSize3Stride4TestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager); |
| 1643 | } |
| 1644 | |
| 1645 | LayerTestResult<int16_t, 4> L2Pooling2dSize3Stride4Int16Test( |
| 1646 | armnn::IWorkloadFactory& workloadFactory, |
| 1647 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1648 | { |
| 1649 | return L2Pooling2dSize3Stride4TestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager); |
| 1650 | } |
| 1651 | |
| 1652 | LayerTestResult<float, 4> L2Pooling2dSize7Test( |
| 1653 | armnn::IWorkloadFactory& workloadFactory, |
| 1654 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1655 | { |
| 1656 | return L2Pooling2dSize7TestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
| 1657 | } |
| 1658 | |
| 1659 | LayerTestResult<uint8_t, 4> L2Pooling2dSize7Uint8Test( |
| 1660 | armnn::IWorkloadFactory& workloadFactory, |
| 1661 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1662 | { |
| 1663 | return L2Pooling2dSize7TestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager); |
| 1664 | } |
| 1665 | |
| 1666 | LayerTestResult<int16_t, 4> L2Pooling2dSize7Int16Test( |
| 1667 | armnn::IWorkloadFactory& workloadFactory, |
| 1668 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1669 | { |
| 1670 | return L2Pooling2dSize7TestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager); |
| 1671 | } |
| 1672 | |
| 1673 | LayerTestResult<float, 4> L2Pooling2dSize9Test( |
| 1674 | armnn::IWorkloadFactory& workloadFactory, |
| 1675 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1676 | { |
| 1677 | return L2Pooling2dSize9TestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
| 1678 | } |
| 1679 | |
| 1680 | LayerTestResult<uint8_t, 4> L2Pooling2dSize9Uint8Test( |
| 1681 | armnn::IWorkloadFactory& workloadFactory, |
| 1682 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1683 | { |
| 1684 | return L2Pooling2dSize9TestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager); |
| 1685 | } |
| 1686 | |
| 1687 | LayerTestResult<int16_t, 4> L2Pooling2dSize9Int16Test( |
| 1688 | armnn::IWorkloadFactory& workloadFactory, |
| 1689 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1690 | { |
| 1691 | return L2Pooling2dSize9TestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager); |
| 1692 | } |
| 1693 | LayerTestResult<float, 4> IgnorePaddingSimpleL2Pooling2dTest( |
| 1694 | armnn::IWorkloadFactory& workloadFactory, |
| 1695 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1696 | { |
| 1697 | return IgnorePaddingSimpleL2Pooling2dTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
| 1698 | } |
| 1699 | |
| 1700 | LayerTestResult<uint8_t, 4> IgnorePaddingSimpleL2Pooling2dUint8Test( |
| 1701 | armnn::IWorkloadFactory& workloadFactory, |
| 1702 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1703 | { |
| 1704 | return IgnorePaddingSimpleL2Pooling2dTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager); |
| 1705 | } |
| 1706 | |
| 1707 | LayerTestResult<int16_t, 4> IgnorePaddingSimpleL2Pooling2dInt16Test( |
| 1708 | armnn::IWorkloadFactory& workloadFactory, |
| 1709 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1710 | { |
| 1711 | return IgnorePaddingSimpleL2Pooling2dTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager); |
| 1712 | } |
| 1713 | |
| 1714 | LayerTestResult<float, 4> IgnorePaddingL2Pooling2dSize3Test( |
| 1715 | armnn::IWorkloadFactory& workloadFactory, |
| 1716 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1717 | { |
| 1718 | return IgnorePaddingL2Pooling2dSize3TestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
| 1719 | } |
| 1720 | |
| 1721 | LayerTestResult<uint8_t, 4> IgnorePaddingL2Pooling2dSize3Uint8Test( |
| 1722 | armnn::IWorkloadFactory& workloadFactory, |
| 1723 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1724 | { |
| 1725 | return IgnorePaddingL2Pooling2dSize3TestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager); |
| 1726 | } |
| 1727 | |
| 1728 | LayerTestResult<int16_t, 4> IgnorePaddingL2Pooling2dSize3Int16Test( |
| 1729 | armnn::IWorkloadFactory& workloadFactory, |
| 1730 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1731 | { |
| 1732 | return IgnorePaddingL2Pooling2dSize3TestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager); |
| 1733 | } |
| 1734 | |
| 1735 | LayerTestResult<float, 4> AsymmetricNonSquarePooling2dTest( |
| 1736 | armnn::IWorkloadFactory& workloadFactory, |
| 1737 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1738 | { |
| 1739 | return AsymmetricNonSquarePooling2dTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); |
| 1740 | } |
| 1741 | |
| 1742 | LayerTestResult<uint8_t, 4> AsymmetricNonSquarePooling2dUint8Test( |
| 1743 | armnn::IWorkloadFactory& workloadFactory, |
| 1744 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1745 | { |
| 1746 | return AsymmetricNonSquarePooling2dTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager); |
| 1747 | } |
| 1748 | |
| 1749 | LayerTestResult<int16_t, 4> AsymmetricNonSquarePooling2dInt16Test( |
| 1750 | armnn::IWorkloadFactory& workloadFactory, |
| 1751 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1752 | { |
| 1753 | return AsymmetricNonSquarePooling2dTestCommon<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager); |
| 1754 | } |
| 1755 | |
| 1756 | LayerTestResult<float, 4> ComparePooling2dTest( |
| 1757 | armnn::IWorkloadFactory& workloadFactory, |
| 1758 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1759 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 1760 | armnn::PoolingAlgorithm poolingType) |
| 1761 | { |
| 1762 | return ComparePooling2dTestCommon<armnn::DataType::Float32>( |
| 1763 | workloadFactory, memoryManager, refWorkloadFactory, poolingType); |
| 1764 | } |
| 1765 | |
| 1766 | LayerTestResult<uint8_t, 4> ComparePooling2dUint8Test( |
| 1767 | armnn::IWorkloadFactory& workloadFactory, |
| 1768 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1769 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 1770 | armnn::PoolingAlgorithm poolingType) |
| 1771 | { |
| 1772 | return ComparePooling2dTestCommon<armnn::DataType::QuantisedAsymm8>( |
| 1773 | workloadFactory, memoryManager, refWorkloadFactory, poolingType, 0.1f, 128); |
| 1774 | } |
| 1775 | |
| 1776 | LayerTestResult<int16_t, 4> ComparePooling2dInt16Test( |
| 1777 | armnn::IWorkloadFactory& workloadFactory, |
| 1778 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1779 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 1780 | armnn::PoolingAlgorithm poolingType) |
| 1781 | { |
| 1782 | return ComparePooling2dTestCommon<armnn::DataType::QuantisedSymm16>( |
| 1783 | workloadFactory, memoryManager, refWorkloadFactory, poolingType); |
| 1784 | } |