Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1 | // |
Mike Kelly | ec67a0f | 2022-11-25 13:55:24 +0000 | [diff] [blame] | 2 | // Copyright © 2017,2022 Arm Ltd and Contributors. All rights reserved. |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #include "Conv2dTestImpl.hpp" |
| 7 | |
Colm Donelan | c42a987 | 2022-02-02 16:35:09 +0000 | [diff] [blame] | 8 | #include <armnnUtils/QuantizeHelper.hpp> |
Matteo Martincigh | e011d20 | 2019-11-28 11:35:47 +0000 | [diff] [blame] | 9 | #include <armnnUtils/TensorUtils.hpp> |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 10 | |
Jan Eilers | 8eb2560 | 2020-03-09 12:13:48 +0000 | [diff] [blame] | 11 | #include <armnn/utility/IgnoreUnused.hpp> |
Matthew Sloyan | 171214c | 2020-09-09 09:07:37 +0100 | [diff] [blame] | 12 | #include <armnn/utility/NumericCast.hpp> |
Matteo Martincigh | e011d20 | 2019-11-28 11:35:47 +0000 | [diff] [blame] | 13 | #include <armnnUtils/DataLayoutIndexed.hpp> |
| 14 | #include <armnnUtils/Permute.hpp> |
| 15 | |
Colm Donelan | 0c47974 | 2021-12-10 12:43:54 +0000 | [diff] [blame] | 16 | #include <armnn/backends/TensorHandle.hpp> |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 17 | |
Sadik Armagan | a097d2a | 2021-11-24 15:47:28 +0000 | [diff] [blame] | 18 | #include <armnnTestUtils/DataLayoutUtils.hpp> |
| 19 | #include <armnnTestUtils/TensorCopyUtils.hpp> |
Colm Donelan | 0c47974 | 2021-12-10 12:43:54 +0000 | [diff] [blame] | 20 | #include <armnnTestUtils/WorkloadTestUtils.hpp> |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 21 | |
Colm Donelan | c42a987 | 2022-02-02 16:35:09 +0000 | [diff] [blame] | 22 | #include <armnnTestUtils/TensorHelpers.hpp> |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 23 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 24 | #include <string> |
| 25 | |
| 26 | // |
| 27 | // Static data |
| 28 | // |
| 29 | |
| 30 | // 2-channel bias used by a number of Conv2d tests. |
| 31 | static std::vector<float> Bias2({0, 2}); |
| 32 | |
| 33 | static std::vector<float> Bias4({1, 2, 3, 4}); |
| 34 | |
| 35 | static std::vector<float> Bias8({1, 2, 3, 4, 1, 2, 3, 4}); |
| 36 | |
| 37 | // 3-channel 16x8 image used as common input data for a number of Conv2d tests. |
| 38 | static std::vector<float> ConvInput3x8x16({ |
| 39 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 40 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 41 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 42 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 43 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 44 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 45 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 46 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 47 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 48 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 49 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 50 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 51 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 52 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 53 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 54 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 55 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 56 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 57 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 58 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 59 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 60 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 61 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 62 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 |
| 63 | }); |
| 64 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 65 | using namespace armnnUtils; |
| 66 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 67 | // |
| 68 | // Helper templates |
| 69 | // |
| 70 | |
| 71 | // Helper template that returns either Bias2 or an empty vector depending on whether bias is enabled. |
| 72 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 73 | std::vector<T> GetBias2(bool biasEnabled, float qScale) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 74 | { |
| 75 | if(biasEnabled) |
| 76 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 77 | return QuantizedVector<T>(Bias2, qScale, 0); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 78 | } |
| 79 | else |
| 80 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 81 | return std::vector<T>(); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 82 | } |
| 83 | } |
| 84 | |
| 85 | // Helper template that returns either Bias4 or an empty vector depending on whether bias is enabled. |
| 86 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 87 | std::vector<T> GetBias4(bool biasEnabled, float qScale) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 88 | { |
| 89 | if(biasEnabled) |
| 90 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 91 | return QuantizedVector<T>(Bias4, qScale, 0); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 92 | } |
| 93 | else |
| 94 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 95 | return std::vector<T>(); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 96 | } |
| 97 | } |
| 98 | |
| 99 | // Helper template that returns either Bias8 or an empty vector depending on whether bias is enabled. |
| 100 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 101 | std::vector<T> GetBias8(bool biasEnabled, float qScale) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 102 | { |
| 103 | if(biasEnabled) |
| 104 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 105 | return QuantizedVector<T>(Bias8, qScale, 0); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 106 | } |
| 107 | else |
| 108 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 109 | return std::vector<T>(); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 110 | } |
| 111 | } |
| 112 | |
| 113 | // Helper template that returns either Bias4 or an empty vector depending on whether bias is enabled. |
| 114 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 115 | std::vector<T> GetBias(bool biasEnabled, float qScale, armnn::TensorInfo outputInfo, armnn::DataLayout layout) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 116 | { |
| 117 | const armnnUtils::DataLayoutIndexed dataLayoutIndexed(layout); |
| 118 | const unsigned int channelsIndex = dataLayoutIndexed.GetChannelsIndex(); |
| 119 | const unsigned int outputChannels = outputInfo.GetShape()[channelsIndex]; |
| 120 | |
| 121 | switch (outputChannels) |
| 122 | { |
| 123 | case 2: |
| 124 | default: |
| 125 | { |
| 126 | return GetBias2<ArmnnType>(biasEnabled, qScale); |
| 127 | } |
| 128 | case 4: |
| 129 | { |
| 130 | return GetBias4<ArmnnType>(biasEnabled, qScale); |
| 131 | } |
| 132 | case 8: |
| 133 | { |
| 134 | return GetBias8<ArmnnType>(biasEnabled, qScale); |
| 135 | } |
| 136 | } |
| 137 | } |
| 138 | |
| 139 | // |
| 140 | // Implementation templates |
| 141 | // |
| 142 | |
| 143 | // Mapping from input type to bias type for fully connected layers. |
| 144 | // float => float, uint8_t => int32_t |
| 145 | template<typename T> |
| 146 | struct FullyConnectedBiasTypeForInputType; |
| 147 | |
| 148 | template<> |
| 149 | struct FullyConnectedBiasTypeForInputType<float> |
| 150 | { |
| 151 | using Type = float; |
| 152 | }; |
| 153 | |
| 154 | template<> |
| 155 | struct FullyConnectedBiasTypeForInputType<uint8_t> |
| 156 | { |
| 157 | using Type = int32_t; |
| 158 | }; |
| 159 | |
| 160 | // Modifies a std::vector in-place using a specified bias. |
| 161 | template<typename T, typename B> |
| 162 | void ApplyBias(std::vector<T>& v, float vScale, int32_t vOffset, |
| 163 | const std::vector<B>& bias, float bScale, int32_t bOffset, uint32_t w, uint32_t h) |
| 164 | { |
Narumol Prangnawarat | ac2770a | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 165 | ARMNN_ASSERT_MSG((armnn::IsQuantizedType<T>() && vScale != 0.0f) || (!armnn::IsQuantizedType<T>()), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 166 | "Invalid type and parameter combination."); |
Narumol Prangnawarat | ac2770a | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 167 | ARMNN_ASSERT_MSG((armnn::IsQuantizedType<B>() && bScale != 0.0f) || (!armnn::IsQuantizedType<B>()), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 168 | "Invalid type and parameter combination."); |
| 169 | |
| 170 | // Note we need to dequantize and re-quantize the image value and the bias. |
| 171 | for (uint32_t i = 0; i < bias.size(); ++i) |
| 172 | { |
| 173 | float dBias = SelectiveDequantize(bias[i], bScale, bOffset); |
| 174 | for (uint32_t y = 0; y < h; ++y) |
| 175 | { |
| 176 | for (uint32_t x = 0; x < w; ++x) |
| 177 | { |
| 178 | uint32_t offset = (i * h + y) * w + x; |
Narumol Prangnawarat | ac2770a | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 179 | ARMNN_ASSERT(offset < v.size()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 180 | T& outRef = v[offset]; |
| 181 | float dOutput = SelectiveDequantize(outRef, vScale, vOffset); |
| 182 | outRef = SelectiveQuantize<T>(dOutput + dBias, vScale, vOffset); |
| 183 | } |
| 184 | } |
| 185 | } |
| 186 | } |
| 187 | |
| 188 | // |
| 189 | // Convolution2d implementations |
| 190 | // |
| 191 | |
| 192 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 193 | typename T = armnn::ResolveType<ArmnnType>, typename B = armnn::ResolveType<ArmnnBType>> |
| 194 | LayerTestResult<T, 4> SimpleConvolution2dTestImpl( |
| 195 | armnn::IWorkloadFactory& workloadFactory, |
| 196 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 197 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 198 | const std::vector<T>& originalInput, |
| 199 | const std::vector<T>& originalKernel, |
| 200 | const std::vector<B>& bias, |
| 201 | const std::vector<T>& originalOutputExpected, |
| 202 | const armnn::TensorShape& originalInputShape, |
| 203 | const armnn::TensorShape& originalKernelShape, |
| 204 | const armnn::TensorShape& originalOutputExpectedShape, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 205 | float qScale, |
| 206 | int32_t qOffset, |
| 207 | const armnn::DataLayout layout = armnn::DataLayout::NCHW, |
| 208 | uint32_t padLeft = 0, |
| 209 | uint32_t padTop = 0, |
| 210 | uint32_t padRight = 0, |
| 211 | uint32_t padBottom = 0, |
| 212 | uint32_t strideX = 1, |
| 213 | uint32_t strideY = 1, |
| 214 | uint32_t dilationX = 1, |
| 215 | uint32_t dilationY = 1) |
| 216 | { |
Jan Eilers | 8eb2560 | 2020-03-09 12:13:48 +0000 | [diff] [blame] | 217 | armnn::IgnoreUnused(memoryManager); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 218 | unsigned int inputHeight = armnn::numeric_cast<unsigned int>(originalInputShape[2]); |
| 219 | unsigned int inputWidth = armnn::numeric_cast<unsigned int>(originalInputShape[3]); |
| 220 | unsigned int inputChannels = armnn::numeric_cast<unsigned int>(originalInputShape[1]); |
| 221 | unsigned int inputNum = armnn::numeric_cast<unsigned int>(originalInputShape[0]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 222 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 223 | unsigned int outputHeight = armnn::numeric_cast<unsigned int>(originalOutputExpectedShape[2]); |
| 224 | unsigned int outputWidth = armnn::numeric_cast<unsigned int>(originalOutputExpectedShape[3]); |
| 225 | unsigned int outputChannels = armnn::numeric_cast<unsigned int>(originalOutputExpectedShape[1]); |
| 226 | unsigned int outputNum = armnn::numeric_cast<unsigned int>(originalOutputExpectedShape[0]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 227 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 228 | unsigned int kernelHeight = armnn::numeric_cast<unsigned int>(originalKernelShape[2]); |
| 229 | unsigned int kernelWidth = armnn::numeric_cast<unsigned int>(originalKernelShape[3]); |
| 230 | unsigned int kernelChannels = armnn::numeric_cast<unsigned int>(originalKernelShape[1]); |
| 231 | unsigned int kernelDepthMul = armnn::numeric_cast<unsigned int>(originalKernelShape[0]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 232 | |
| 233 | bool biasEnabled = bias.size() > 0; |
| 234 | |
| 235 | // This function currently assumes 1 batch of input/output (and duplicates this into 2 batches). |
Narumol Prangnawarat | ac2770a | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 236 | ARMNN_ASSERT(inputNum == 1); |
| 237 | ARMNN_ASSERT(outputNum == 1); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 238 | |
| 239 | // If a bias is used, its size must equal the number of output channels. |
Narumol Prangnawarat | ac2770a | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 240 | ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 241 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 242 | // Note these tensors will use two (identical) batches. |
| 243 | armnn::TensorInfo inputTensorInfo = |
| 244 | armnnUtils::GetTensorInfo(2*inputNum, inputChannels, inputHeight, inputWidth, layout, ArmnnType); |
| 245 | armnn::TensorInfo outputTensorInfo = |
| 246 | armnnUtils::GetTensorInfo(2*outputNum, outputChannels, outputHeight, outputWidth, layout, ArmnnType); |
| 247 | armnn::TensorInfo kernelDesc = |
| 248 | armnnUtils::GetTensorInfo(kernelDepthMul, kernelChannels, kernelHeight, kernelWidth, layout, ArmnnType); |
| 249 | armnn::TensorInfo biasDesc({static_cast<unsigned int>(bias.size())}, ArmnnBType); |
| 250 | |
| 251 | // Set quantization parameters if the requested type is a quantized type. |
| 252 | if(armnn::IsQuantizedType<T>()) |
| 253 | { |
| 254 | inputTensorInfo.SetQuantizationScale(qScale); |
| 255 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 256 | outputTensorInfo.SetQuantizationScale(qScale); |
| 257 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 258 | kernelDesc.SetQuantizationScale(qScale); |
| 259 | kernelDesc.SetQuantizationOffset(qOffset); |
| 260 | biasDesc.SetQuantizationScale(qScale*qScale); |
| 261 | biasDesc.SetQuantizationOffset(0); |
| 262 | } |
| 263 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 264 | // Construct input data - two batches of the same input image. |
| 265 | std::vector<T> inputImage; |
| 266 | inputImage.assign(originalInput.data(), originalInput.data() + 1*inputChannels*inputHeight*inputWidth); |
| 267 | std::vector<T> inputData; |
| 268 | inputData.insert(inputData.end(), inputImage.begin(), inputImage.end()); |
| 269 | inputData.insert(inputData.end(), inputImage.begin(), inputImage.end()); |
| 270 | |
| 271 | // at this point if we require it permute the input data |
| 272 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
| 273 | if (layout == armnn::DataLayout::NHWC) |
| 274 | { |
| 275 | std::vector<T> tmp(inputData.size()); |
| 276 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(T)); |
| 277 | inputData = tmp; |
| 278 | } |
| 279 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 280 | std::vector<T> outputImage; |
| 281 | outputImage.assign(originalOutputExpected.data(), |
| 282 | originalOutputExpected.data() + outputChannels*outputHeight*outputWidth); |
| 283 | |
| 284 | // Apply bias to output image if it is enabled. |
| 285 | if(biasEnabled) |
| 286 | { |
| 287 | std::vector<T> biasV; |
| 288 | biasV.assign(bias.data(), bias.data() + outputChannels); |
| 289 | ApplyBias(outputImage, outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset(), |
| 290 | biasV, biasDesc.GetQuantizationScale(), biasDesc.GetQuantizationOffset(), |
| 291 | outputWidth, outputHeight); |
| 292 | } |
| 293 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 294 | // Data will be copied from outputHandle |
| 295 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
| 296 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 297 | // Construct expected output data - two identical images. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 298 | std::vector<T> expectedOutput; |
| 299 | expectedOutput.insert(expectedOutput.end(), outputImage.begin(), outputImage.end()); |
| 300 | expectedOutput.insert(expectedOutput.end(), outputImage.begin(), outputImage.end()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 301 | |
| 302 | // at this point if we require it permute the expected output |
| 303 | if (layout == armnn::DataLayout::NHWC) |
| 304 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 305 | std::vector<T> tmp(expectedOutput.size()); |
| 306 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, expectedOutput.data(), tmp.data(), sizeof(T)); |
| 307 | expectedOutput = tmp; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 308 | } |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 309 | |
| 310 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 311 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 312 | std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 313 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 314 | armnn::Convolution2dQueueDescriptor data; |
| 315 | armnn::WorkloadInfo info; |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 316 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 317 | // Permute the kernel if necessary |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 318 | std::vector<T> kernel = originalKernel; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 319 | if (layout == armnn::DataLayout::NHWC) |
| 320 | { |
| 321 | armnnUtils::Permute(kernelDesc.GetShape(), NCHWToNHWC, originalKernel.data(), kernel.data(), sizeof(T)); |
| 322 | } |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 323 | |
| 324 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 325 | AddInputToWorkload(data, info, kernelDesc, weightsHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 326 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 327 | |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 328 | std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr; |
| 329 | if (biasEnabled) |
| 330 | { |
| 331 | biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc); |
| 332 | AddInputToWorkload(data, info, biasDesc, biasHandle.get()); |
| 333 | } |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 334 | data.m_Parameters.m_StrideX = strideX; |
| 335 | data.m_Parameters.m_StrideY = strideY; |
| 336 | data.m_Parameters.m_PadLeft = padLeft; |
| 337 | data.m_Parameters.m_PadRight = padRight; |
| 338 | data.m_Parameters.m_PadTop = padTop; |
| 339 | data.m_Parameters.m_PadBottom = padBottom; |
| 340 | data.m_Parameters.m_BiasEnabled = biasEnabled; |
| 341 | data.m_Parameters.m_DataLayout = layout; |
| 342 | data.m_Parameters.m_DilationX = dilationX; |
| 343 | data.m_Parameters.m_DilationY = dilationY; |
| 344 | |
Teresa Charlin | 611c7fb | 2022-01-07 09:47:29 +0000 | [diff] [blame] | 345 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateWorkload(armnn::LayerType::Convolution2d, |
| 346 | data, |
| 347 | info); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 348 | inputHandle->Allocate(); |
| 349 | outputHandle->Allocate(); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 350 | weightsHandle->Allocate(); |
| 351 | |
| 352 | if (biasEnabled) |
| 353 | { |
| 354 | biasHandle->Allocate(); |
| 355 | CopyDataToITensorHandle(biasHandle.get(), bias.data()); |
| 356 | } |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 357 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 358 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 359 | CopyDataToITensorHandle(weightsHandle.get(), kernel.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 360 | |
| 361 | ExecuteWorkload(*workload, memoryManager); |
| 362 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 363 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 364 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 365 | return LayerTestResult<T, 4>(actualOutput, |
| 366 | expectedOutput, |
| 367 | outputHandle->GetShape(), |
| 368 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 369 | } |
| 370 | |
| 371 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 372 | typename T = armnn::ResolveType<ArmnnType>, typename B = armnn::ResolveType<ArmnnBType>, |
| 373 | armnn::DataType OutType = ArmnnType, typename O = armnn::ResolveType<OutType>> |
| 374 | LayerTestResult<O, 4> SimpleConvolution2dNhwcTestImpl( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 375 | armnn::IWorkloadFactory& workloadFactory, |
| 376 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 377 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 378 | const std::vector<T>& input, |
| 379 | const std::vector<T>& kernel, |
| 380 | const std::vector<B>& bias, |
| 381 | const std::vector<O>& outputExpected, |
| 382 | const armnn::TensorShape& inputShape, |
| 383 | const armnn::TensorShape& kernelShape, |
| 384 | const armnn::TensorShape& outputExpectedShape, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 385 | const armnn::DataLayout dataLayout, |
| 386 | float qScale, |
| 387 | int32_t qOffset, |
| 388 | uint32_t padLeft = 1, |
| 389 | uint32_t padTop = 1, |
| 390 | uint32_t padRight = 1, |
| 391 | uint32_t padBottom = 1, |
| 392 | uint32_t strideX = 1, |
| 393 | uint32_t strideY = 1) |
| 394 | { |
Jan Eilers | 8eb2560 | 2020-03-09 12:13:48 +0000 | [diff] [blame] | 395 | armnn::IgnoreUnused(qScale, qOffset); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 396 | unsigned int inputNum = armnn::numeric_cast<unsigned int>(inputShape[0]); |
| 397 | unsigned int inputChannels = armnn::numeric_cast<unsigned int>(inputShape[3]); |
| 398 | unsigned int inputHeight = armnn::numeric_cast<unsigned int>(inputShape[1]); |
| 399 | unsigned int inputWidth = armnn::numeric_cast<unsigned int>(inputShape[2]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 400 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 401 | unsigned int kernelChanMul = armnn::numeric_cast<unsigned int>(kernelShape[0]); |
| 402 | unsigned int kernelChannels = armnn::numeric_cast<unsigned int>(kernelShape[3]); |
| 403 | unsigned int kernelHeight = armnn::numeric_cast<unsigned int>(kernelShape[1]); |
| 404 | unsigned int kernelWidth = armnn::numeric_cast<unsigned int>(kernelShape[2]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 405 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 406 | unsigned int outputNum = armnn::numeric_cast<unsigned int>(outputExpectedShape[0]); |
| 407 | unsigned int outputChannels = armnn::numeric_cast<unsigned int>(outputExpectedShape[3]); |
| 408 | unsigned int outputHeight = armnn::numeric_cast<unsigned int>(outputExpectedShape[1]); |
| 409 | unsigned int outputWidth = armnn::numeric_cast<unsigned int>(outputExpectedShape[2]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 410 | |
| 411 | bool biasEnabled = bias.size() > 0; |
| 412 | |
| 413 | // Creates the tensors. |
| 414 | armnn::TensorInfo inputTensorInfo({inputNum, inputHeight, inputWidth, inputChannels}, ArmnnType); |
| 415 | armnn::TensorInfo outputTensorInfo({outputNum, outputHeight, outputWidth, outputChannels}, |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 416 | OutType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 417 | armnn::TensorInfo kernelDesc({kernelChanMul, kernelHeight, kernelWidth, kernelChannels}, ArmnnType); |
| 418 | armnn::TensorInfo biasDesc({static_cast<unsigned int>(bias.size())}, ArmnnBType); |
| 419 | |
| 420 | // Construct the input data. |
| 421 | std::vector<T> inputData; |
| 422 | inputData.assign(input.data(), input.data() + inputHeight*inputWidth*inputChannels); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 423 | |
| 424 | // Construct the output data, with bias applied, as appropriate. |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 425 | std::vector<O> outputData; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 426 | outputData.assign(outputExpected.data(), outputExpected.data() + outputHeight*outputWidth*outputChannels); |
| 427 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 428 | std::vector<O> actualOutput(outputTensorInfo.GetNumElements()); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 429 | |
| 430 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 431 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 432 | std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc); |
| 433 | std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr; |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 434 | |
Mike Kelly | ec67a0f | 2022-11-25 13:55:24 +0000 | [diff] [blame] | 435 | // armnn::ScopedTensorHandle weightsTensor(kernelDesc); |
| 436 | // AllocateAndCopyDataToITensorHandle(&weightsTensor, kernel.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 437 | |
Mike Kelly | ec67a0f | 2022-11-25 13:55:24 +0000 | [diff] [blame] | 438 | // armnn::ScopedTensorHandle biasTensor(biasDesc); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 439 | |
| 440 | armnn::Convolution2dQueueDescriptor data; |
| 441 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 442 | data.m_Parameters.m_StrideX = strideX; |
| 443 | data.m_Parameters.m_StrideY = strideY; |
| 444 | data.m_Parameters.m_PadLeft = padLeft; |
| 445 | data.m_Parameters.m_PadRight = padRight; |
| 446 | data.m_Parameters.m_PadTop = padTop; |
| 447 | data.m_Parameters.m_PadBottom = padBottom; |
| 448 | data.m_Parameters.m_BiasEnabled = biasEnabled; |
| 449 | data.m_Parameters.m_DataLayout = dataLayout; |
| 450 | |
| 451 | armnn::WorkloadInfo info; |
| 452 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 453 | AddInputToWorkload(data, info, kernelDesc, weightsHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 454 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 455 | |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 456 | if (biasEnabled) |
| 457 | { |
| 458 | biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc); |
| 459 | AddInputToWorkload(data, info, biasDesc, biasHandle.get()); |
| 460 | } |
| 461 | |
Teresa Charlin | 611c7fb | 2022-01-07 09:47:29 +0000 | [diff] [blame] | 462 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateWorkload(armnn::LayerType::Convolution2d, |
| 463 | data, |
| 464 | info); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 465 | inputHandle->Allocate(); |
| 466 | outputHandle->Allocate(); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 467 | weightsHandle->Allocate(); |
| 468 | |
| 469 | if (biasEnabled) |
| 470 | { |
| 471 | biasHandle->Allocate(); |
| 472 | CopyDataToITensorHandle(biasHandle.get(), bias.data()); |
| 473 | } |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 474 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 475 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 476 | CopyDataToITensorHandle(weightsHandle.get(), kernel.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 477 | |
| 478 | ExecuteWorkload(*workload, memoryManager); |
| 479 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 480 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 481 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 482 | return LayerTestResult<O, 4>(actualOutput, |
| 483 | outputData, |
| 484 | outputHandle->GetShape(), |
| 485 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 486 | } |
| 487 | |
| 488 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> |
| 489 | LayerTestResult<T,4> Convolution1dTestImpl( |
| 490 | armnn::IWorkloadFactory& workloadFactory, |
| 491 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 492 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 493 | float qScale, |
| 494 | int32_t qOffset, |
| 495 | bool biasEnabled) |
| 496 | { |
| 497 | using B = armnn::ResolveType<ArmnnBType>; |
| 498 | // Until we have a specialist 1D convolution layer, we can fake one using |
| 499 | // 2D convolution with the final dimension set to 1. |
| 500 | // I don't anticipate this being particularly slow, given that convolution is implemented |
| 501 | // as a matrix multiplication, at which point dimension doesn't matter. |
| 502 | |
| 503 | unsigned int batchSize = 1; |
| 504 | unsigned int inputChannels = 2; |
| 505 | unsigned int outputChannels = 3; |
| 506 | unsigned int inputSize = 5; // The 1D size (could view as 'width' or 'height'). |
| 507 | unsigned int kernelSize = 3; |
| 508 | unsigned int padSize = 2; |
| 509 | unsigned int stride = 1; |
| 510 | unsigned int outputSize = 7; // (inputSize + 2 * padSize - kernelSize + 1) / stride. |
| 511 | |
| 512 | armnn::TensorInfo inputInfo({batchSize, inputChannels, inputSize, 1}, ArmnnType); |
| 513 | armnn::TensorInfo outputInfo({batchSize, outputChannels, outputSize, 1}, ArmnnType); |
| 514 | armnn::TensorInfo kernelInfo({outputChannels, inputChannels, kernelSize, 1}, ArmnnType); |
| 515 | armnn::TensorInfo biasInfo({outputChannels}, ArmnnBType); |
| 516 | |
| 517 | // Set quantization parameters if the requested type is a quantized type. |
| 518 | if(armnn::IsQuantizedType<T>()) |
| 519 | { |
| 520 | inputInfo.SetQuantizationScale(qScale); |
| 521 | inputInfo.SetQuantizationOffset(qOffset); |
| 522 | outputInfo.SetQuantizationScale(qScale); |
| 523 | outputInfo.SetQuantizationOffset(qOffset); |
| 524 | kernelInfo.SetQuantizationScale(qScale); |
| 525 | kernelInfo.SetQuantizationOffset(qOffset); |
| 526 | biasInfo.SetQuantizationScale(inputInfo.GetQuantizationScale()*kernelInfo.GetQuantizationScale()); |
| 527 | biasInfo.SetQuantizationOffset(0); |
| 528 | } |
| 529 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 530 | std::vector<T> inputData = QuantizedVector<T>( |
| 531 | { |
| 532 | 5.0f, -2.0f, 2.5f, 0.0f, 1.0f, |
| 533 | -3.0f, 3.2f, 5.0f, 2.0f, 3.0f, |
| 534 | }, |
| 535 | inputInfo.GetQuantizationScale(), |
| 536 | inputInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 537 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 538 | std::vector<T> kernelData = QuantizedVector<T>( |
| 539 | { |
| 540 | 1.0f, 0.0f, 0.0f, |
| 541 | 0.0f, 2.0f, -1.5f, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 542 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 543 | 0.0f, 0.0f, 0.0f, |
| 544 | 0.2f, 0.2f, 0.2f, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 545 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 546 | 0.5f, 0.0f, 0.5f, |
| 547 | 0.0f, -1.0f, 0.0f |
| 548 | }, |
| 549 | kernelInfo.GetQuantizationScale(), |
| 550 | kernelInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 551 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 552 | std::vector<B> biasData = |
| 553 | QuantizedVector<B>({ 1.0f, 0.0f, 0.0f }, biasInfo.GetQuantizationScale(), biasInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 554 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 555 | std::vector<T> outputData = QuantizedVector<T>( |
| 556 | { |
| 557 | 4.5f, -10.8f, 5.0f + 6.4f - 7.5f, -2.0f + 10.0f -3.0f, 2.5f + 4.0f - 4.5f, 6.0f, 1.0f, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 558 | -0.6f, -0.6f + 0.64f, -0.6f + 0.64f + 1.0f, 0.64f + 1.0f + 0.4f, 1.0f + 0.4f + 0.6f, 0.4f + 0.6f, 0.6f, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 559 | 2.5f, -1.0f + 3.0f, 1.25f - 3.2f + 2.5f, -1.0f - 5.0f, 1.25f + 0.5f - 2.0f, -3.0f, 0.5f |
| 560 | }, |
| 561 | outputInfo.GetQuantizationScale(), |
| 562 | outputInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 563 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 564 | std::vector<T> actualOutput(outputInfo.GetNumElements()); |
| 565 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 566 | // Optionally apply bias to output image. |
| 567 | if(biasEnabled) |
| 568 | { |
| 569 | ApplyBias(outputData, outputInfo.GetQuantizationScale(), outputInfo.GetQuantizationOffset(), |
| 570 | biasData, biasInfo.GetQuantizationScale(), biasInfo.GetQuantizationOffset(), |
| 571 | 1, outputSize); |
| 572 | } |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 573 | |
| 574 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputInfo); |
| 575 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputInfo); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 576 | std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelInfo); |
| 577 | std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr; |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 578 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 579 | armnn::Convolution2dQueueDescriptor data; |
| 580 | armnn::WorkloadInfo info; |
Mike Kelly | ec67a0f | 2022-11-25 13:55:24 +0000 | [diff] [blame] | 581 | // armnn::ScopedTensorHandle weightsTensor(kernelInfo); |
| 582 | // armnn::ScopedTensorHandle biasTensor(biasInfo); |
| 583 | // |
| 584 | // AllocateAndCopyDataToITensorHandle(&weightsTensor, kernelData.data()); |
| 585 | // AllocateAndCopyDataToITensorHandle(&biasTensor, biasData.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 586 | |
| 587 | AddInputToWorkload(data, info, inputInfo, inputHandle.get()); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 588 | AddInputToWorkload(data, info, kernelInfo, weightsHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 589 | AddOutputToWorkload(data, info, outputInfo, outputHandle.get()); |
| 590 | |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 591 | data.m_Parameters.m_StrideX = 1; |
| 592 | data.m_Parameters.m_StrideY = stride; |
| 593 | data.m_Parameters.m_PadLeft = 0; |
| 594 | data.m_Parameters.m_PadRight = 0; |
| 595 | data.m_Parameters.m_PadTop = padSize; |
| 596 | data.m_Parameters.m_PadBottom = padSize; |
| 597 | data.m_Parameters.m_BiasEnabled = biasEnabled; |
| 598 | |
| 599 | if (biasEnabled) |
| 600 | { |
| 601 | biasHandle = tensorHandleFactory.CreateTensorHandle(biasInfo); |
| 602 | AddInputToWorkload(data, info, biasInfo, biasHandle.get()); |
| 603 | } |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 604 | |
Teresa Charlin | 611c7fb | 2022-01-07 09:47:29 +0000 | [diff] [blame] | 605 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateWorkload(armnn::LayerType::Convolution2d, |
| 606 | data, |
| 607 | info); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 608 | inputHandle->Allocate(); |
| 609 | outputHandle->Allocate(); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 610 | weightsHandle->Allocate(); |
| 611 | |
| 612 | if (biasEnabled) |
| 613 | { |
| 614 | biasHandle->Allocate(); |
| 615 | CopyDataToITensorHandle(biasHandle.get(), biasData.data()); |
| 616 | } |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 617 | |
| 618 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 619 | CopyDataToITensorHandle(weightsHandle.get(), kernelData.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 620 | |
| 621 | ExecuteWorkload(*workload, memoryManager); |
| 622 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 623 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
| 624 | |
| 625 | return LayerTestResult<T, 4>(actualOutput, |
| 626 | outputData, |
| 627 | outputHandle->GetShape(), |
| 628 | outputInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 629 | } |
| 630 | |
| 631 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 632 | LayerTestResult<T, 4> SimpleConvolution2d3x3NhwcTestCommon( |
| 633 | armnn::IWorkloadFactory& workloadFactory, |
| 634 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 635 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 636 | float qScale, |
| 637 | int32_t qOffset, |
| 638 | bool biasEnabled, |
| 639 | armnn::DataLayout dataLayout) |
| 640 | { |
Jan Eilers | 8eb2560 | 2020-03-09 12:13:48 +0000 | [diff] [blame] | 641 | armnn::IgnoreUnused(biasEnabled); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 642 | // Use common single-batch 5x5 image. |
| 643 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 644 | armnn::TensorInfo inputDesc({ 1, 3, 4, 1 }, ArmnnType); |
| 645 | std::vector<T> input = |
| 646 | { |
| 647 | 1, 5, 2, 3, |
| 648 | 8, 7, 3, 6, |
| 649 | 3, 3, 9, 1 |
| 650 | }; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 651 | |
| 652 | // Use a 2-element batch of 3-channel 3x3 kernels. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 653 | armnn::TensorInfo kernelDesc({ 1, 3, 3, 1 }, ArmnnType); |
| 654 | std::vector<T> kernel = |
| 655 | { |
| 656 | 4, 5, 6, |
| 657 | 0, 0, 0, |
| 658 | 3, 2, 1 |
| 659 | }; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 660 | |
| 661 | // Expected output is 1 batch of a 5x5 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 662 | armnn::TensorInfo outputDesc({ 1, 3, 4, 1 }, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 663 | const std::vector<float> outputData = |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 664 | { |
| 665 | 23, 41, 33, 21, |
| 666 | 44, 65, 76, 52, |
| 667 | 82, 85, 79, 42 |
| 668 | }; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 669 | |
| 670 | return SimpleConvolution2dNhwcTestImpl<ArmnnType, ArmnnType>( |
| 671 | workloadFactory, |
| 672 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 673 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 674 | input, |
| 675 | kernel, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 676 | std::vector<T>(), |
| 677 | outputData, |
| 678 | inputDesc.GetShape(), |
| 679 | kernelDesc.GetShape(), |
| 680 | outputDesc.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 681 | dataLayout, |
| 682 | qScale, |
| 683 | qOffset); |
| 684 | } |
| 685 | |
| 686 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 687 | LayerTestResult<T, 4> SimpleConvolution2d3x3Stride2x2TestCommon( |
| 688 | armnn::IWorkloadFactory& workloadFactory, |
| 689 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 690 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 691 | float qScale, |
| 692 | int32_t qOffset, |
| 693 | bool biasEnabled, |
| 694 | const armnn::DataLayout& dataLayout) |
| 695 | { |
Jan Eilers | 8eb2560 | 2020-03-09 12:13:48 +0000 | [diff] [blame] | 696 | armnn::IgnoreUnused(biasEnabled); |
Derek Lamberti | c374ff0 | 2019-12-10 21:57:35 +0000 | [diff] [blame] | 697 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 698 | // Input is a single-batch, 1 channel, 5x5 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 699 | armnn::TensorInfo inputDesc({ 1, 5, 5, 1 }, ArmnnType); |
| 700 | std::vector<T> input = |
| 701 | { |
| 702 | 1, 5, 2, 3, 5, |
| 703 | 8, 7, 3, 6, 3, |
| 704 | 3, 3, 9, 1, 9, |
| 705 | 4, 1, 8, 1, 3, |
| 706 | 6, 8, 1, 9, 2 |
| 707 | }; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 708 | |
| 709 | // Use a 3x3 kernel. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 710 | armnn::TensorInfo kernelDesc({ 1, 3, 3, 1 }, ArmnnType); |
| 711 | std::vector<T> kernel = |
| 712 | { |
| 713 | 4, 5, 6, |
| 714 | 0, 0, 0, |
| 715 | 3, 2, 1 |
| 716 | }; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 717 | |
| 718 | // Expected output is a single-batch, 1 channel, 3x3 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 719 | armnn::TensorInfo outputDesc({ 1, 3, 3, 1 }, ArmnnType); |
| 720 | std::vector<T> outputData = |
| 721 | { |
| 722 | 23, 33, 24, |
| 723 | 91, 99, 48, |
| 724 | 26, 50, 19 |
| 725 | }; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 726 | |
| 727 | uint32_t padLeft = 1; |
| 728 | uint32_t padTop = 1; |
| 729 | uint32_t padRight = 1; |
| 730 | uint32_t padBottom = 1; |
| 731 | uint32_t strideX = 2; |
| 732 | uint32_t strideY = 2; |
| 733 | |
| 734 | return SimpleConvolution2dNhwcTestImpl<ArmnnType, ArmnnType>( |
| 735 | workloadFactory, |
| 736 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 737 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 738 | input, |
| 739 | kernel, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 740 | std::vector<T>(), |
| 741 | outputData, |
| 742 | inputDesc.GetShape(), |
| 743 | kernelDesc.GetShape(), |
| 744 | outputDesc.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 745 | dataLayout, |
| 746 | qScale, |
| 747 | qOffset, |
| 748 | padLeft, |
| 749 | padTop, |
| 750 | padRight, |
| 751 | padBottom, |
| 752 | strideX, |
| 753 | strideY); |
| 754 | } |
| 755 | |
| 756 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> |
| 757 | LayerTestResult<T, 4> SimpleConvolution2d3x5TestCommon( |
| 758 | armnn::IWorkloadFactory& workloadFactory, |
| 759 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 760 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 761 | float qScale, |
| 762 | int32_t qOffset, |
| 763 | bool biasEnabled, |
| 764 | const armnn::DataLayout layout) |
| 765 | { |
| 766 | // Use common single-batch 3-channel 16x8 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 767 | armnn::TensorInfo inputDesc({ 1, 3, 8, 16 }, ArmnnType); |
| 768 | std::vector<T> input = QuantizedVector<T>(ConvInput3x8x16, qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 769 | |
| 770 | // Use a 2-element batch with 3-channel 3x5 kernels. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 771 | armnn::TensorInfo kernelDesc({ 2, 3, 5, 3 }, ArmnnType); |
| 772 | std::vector<T> kernel = QuantizedVector<T>({ |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 773 | 1, 1, 1, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 774 | 1, -1, 1, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 775 | 1, 1, 1, |
| 776 | 1, 1, 1, |
| 777 | 1, 1, 1, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 778 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 779 | 0, 0, 0, |
| 780 | 0, 0, 0, |
| 781 | 0, 0, 0, |
| 782 | 0, 0, 0, |
| 783 | 0, 0, 0, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 784 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 785 | 2, 2, 2, |
| 786 | 2, 2, 2, |
| 787 | 2, 2, 2, |
| 788 | 2, 2, 2, |
| 789 | 2, 2, 2, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 790 | |
| 791 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 792 | 0, 0, 0, |
| 793 | 0, 0, 0, |
| 794 | 0, 0, 0, |
| 795 | 0, 0, 0, |
| 796 | 0, 0, 0, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 797 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 798 | 1, 1, 1, |
| 799 | 1, 1, 1, |
| 800 | 1, 1, 1, |
| 801 | 1, 1, 1, |
| 802 | 1, 1, 1, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 803 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 804 | 0, 0, 0, |
| 805 | 0, 0, 0, |
| 806 | 0, 0, 0, |
| 807 | 0, 0, 0, |
| 808 | 0, 0, 0 |
| 809 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 810 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 811 | |
| 812 | // Expected output is 2 batch elements of a 1-channel 14x4 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 813 | armnn::TensorInfo outputDesc({ 1, 2, 4, 14 }, ArmnnType); |
| 814 | std::vector<T> expectedOutput = QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 815 | -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, |
| 816 | -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, |
| 817 | -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, |
| 818 | -23.5f, -23.5f, -23.5f, |
| 819 | -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, |
| 820 | -23.5f, -23.5f, -23.5f, |
| 821 | |
| 822 | 5, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 823 | 5, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 824 | 5, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 825 | 5, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 826 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 827 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 828 | |
| 829 | return SimpleConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 830 | workloadFactory, |
| 831 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 832 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 833 | input, |
| 834 | kernel, |
| 835 | GetBias2<ArmnnBType>(biasEnabled, qScale * qScale), |
| 836 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 837 | inputDesc.GetShape(), |
| 838 | kernelDesc.GetShape(), |
| 839 | outputDesc.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 840 | qScale, |
| 841 | qOffset, |
| 842 | layout); |
| 843 | } |
| 844 | |
| 845 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 846 | typename T = armnn::ResolveType<ArmnnType>> |
| 847 | LayerTestResult<T, 4> SimpleConvolution2d3x3TestCommon( |
| 848 | armnn::IWorkloadFactory& workloadFactory, |
| 849 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 850 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 851 | float qScale, |
| 852 | int32_t qOffset, |
| 853 | bool biasEnabled, |
| 854 | const armnn::DataLayout layout) |
| 855 | { |
| 856 | // Use a 3x3 kernel, which exercises ArmCompute's direct convolution path. |
| 857 | |
| 858 | // Use common single-batch 3-channel 16x8 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 859 | armnn::TensorInfo inputDesc({ 1, 3, 8, 16 }, ArmnnType); |
| 860 | std::vector<unsigned int> inputShape = { 1, 3, 8, 16 }; |
| 861 | std::vector<T> input = QuantizedVector<T>(ConvInput3x8x16, qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 862 | |
| 863 | // Use a 2-element batch of 3-channel 3x3 kernels. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 864 | armnn::TensorInfo kernelDesc({ 2, 3, 3, 3 }, ArmnnType); |
| 865 | std::vector<T> kernel = QuantizedVector<T>({ |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 866 | 1, 1, 1, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 867 | 1, -1, 1, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 868 | 1, 1, 1, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 869 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 870 | 0, 0, 0, |
| 871 | 0, 0, 0, |
| 872 | 0, 0, 0, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 873 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 874 | 2, 2, 2, |
| 875 | 2, 2, 2, |
| 876 | 2, 2, 2, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 877 | |
| 878 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 879 | 0, 0, 0, |
| 880 | 0, 0, 0, |
| 881 | 0, 0, 0, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 882 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 883 | 1, 1, 1, |
| 884 | 1, 1, 1, |
| 885 | 1, 1, 1, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 886 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 887 | 0, 0, 0, |
| 888 | 0, 0, 0, |
| 889 | 0, 0, 0 |
| 890 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 891 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 892 | |
| 893 | // Expected output is 1 batch of a 2-channel 14x6 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 894 | armnn::TensorInfo outputDesc({ 1, 2, 6, 14 }, ArmnnType); |
| 895 | std::vector<T> expectedOutput = QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 896 | -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, |
| 897 | -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, |
| 898 | -14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f, |
| 899 | -14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f, |
| 900 | -14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f, |
| 901 | -14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f, |
| 902 | |
| 903 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 904 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 905 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 906 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 907 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 908 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 909 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 910 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 911 | |
| 912 | return SimpleConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 913 | workloadFactory, |
| 914 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 915 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 916 | input, |
| 917 | kernel, |
| 918 | GetBias2<ArmnnBType>(biasEnabled, qScale * qScale), |
| 919 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 920 | inputDesc.GetShape(), |
| 921 | kernelDesc.GetShape(), |
| 922 | outputDesc.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 923 | qScale, |
| 924 | qOffset, |
| 925 | layout); |
| 926 | } |
| 927 | |
| 928 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 929 | typename T = armnn::ResolveType<ArmnnType>> |
| 930 | LayerTestResult<T, 4> Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon( |
| 931 | armnn::IWorkloadFactory& workloadFactory, |
| 932 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 933 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 934 | const armnn::DataLayout layout, |
| 935 | float qScale, |
| 936 | int32_t qOffset) |
| 937 | { |
| 938 | // Use a single-batch 1-channel 3x3 image as input. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 939 | armnn::TensorInfo inputDesc({ 1, 1, 3, 3 }, ArmnnType); |
| 940 | std::vector<T> input = |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 941 | QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 942 | 11,21,31, |
| 943 | 12,22,32, |
| 944 | 13,23,33 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 945 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 946 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 947 | |
| 948 | // Use 1 batch of a 1-channel 2x2 kernel. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 949 | armnn::TensorInfo kernelDesc({ 1, 1, 2, 2 }, ArmnnType); |
| 950 | std::vector<T> kernel = |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 951 | QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 952 | -11,-21, |
| 953 | -12,-22, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 954 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 955 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 956 | |
| 957 | // Expected output is 1 batch of a 1-channel 6x8 image. |
| 958 | // Manually calculated like this: |
| 959 | //[-11*0 -21*0 -12*0 -22*0 ; -11*0 -21*0 -12*0 -22*0 ; -11*0 -21*0 -12*0 -22*0 ; -11*0 -21*0 -12*0 -22*0 ..] |
| 960 | //[-11*0 -21*0 -12*0 -22*11 ; -11*0 -21*0 -12*11 -22*21 ; -11*0 -21*0 -12*21 -22*31 ; -11*0 -21*0 -12*31 -22*0 ..] |
| 961 | //[-11*0 -21*11 -12*0 -22*12 ; -11*11 -21*21 -12*12 -22*22 ; -11*21 -21*31 -12*22 -22*32 ; -11*31 -21*0 -12*32 -22*0 ..] |
| 962 | //[-11*0 -21*12 -12*0 -22*13 ; -11*12 -21*22 -12*13 -22*23 ; -11*22 -21*32 -12*23 -22*33 ; -11*32 -21*0 -12*33 -22*0 ..] |
| 963 | //[-11*0 -21*13 -12*0 -22*0 ; -11*13 -21*23 -12*0 -22*0 ; -11*23 -21*33 -12*0 -22*0 ; -11*33 -21*0 -12*0 -22*0 ..] |
| 964 | //[-11*0 -21*0 -12*0 -22*0 ; -11*0 -21*0 -12*0 -22*0 ; -11*0 -21*0 -12*0 -22*0 ; -11*0 -21*0 -12*0 -22*0 ..] |
| 965 | //[..... ..... ..... ..... ; ..... ..... ..... ..... ; ..... ..... ..... ..... ; ..... ..... ..... ..... ..] |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 966 | armnn::TensorInfo outputDesc({ 1, 1, 8, 6 }, ArmnnType); |
| 967 | std::vector<T> expectedOutput = |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 968 | QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 969 | 0, 0, 0, 0, 0, 0, |
| 970 | -242, -594, -934, -372, 0, 0, |
| 971 | -495, -1190, -1850, -725, 0, 0, |
| 972 | -538, -1256, -1916, -748, 0, 0, |
| 973 | -273, -626, -946, -363, 0, 0, |
| 974 | 0, 0, 0, 0, 0, 0, |
| 975 | 0, 0, 0, 0, 0, 0, |
| 976 | 0, 0, 0, 0, 0, 0 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 977 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 978 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 979 | |
| 980 | return SimpleConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 981 | workloadFactory, |
| 982 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 983 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 984 | input, |
| 985 | kernel, |
| 986 | GetBias2<ArmnnBType>(false, qScale * qScale), |
| 987 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 988 | inputDesc.GetShape(), |
| 989 | kernelDesc.GetShape(), |
| 990 | outputDesc.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 991 | qScale, |
| 992 | qOffset, |
| 993 | layout, |
| 994 | 1, // Padding left. |
| 995 | 2, // Padding top. |
| 996 | 3, // Padding right. |
| 997 | 4); // Padding bottom. |
| 998 | } |
| 999 | |
| 1000 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 1001 | typename T = armnn::ResolveType<ArmnnType>> |
| 1002 | LayerTestResult<T, 4> SimpleConvolution2dAsymmetricPaddingTestCommon( |
| 1003 | armnn::IWorkloadFactory& workloadFactory, |
| 1004 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1005 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1006 | const armnn::DataLayout layout, |
| 1007 | float qScale, |
| 1008 | int32_t qOffset) |
| 1009 | { |
| 1010 | // Use a single-batch 1-channel 5x5 image as input. |
| 1011 | armnn::TensorInfo inputDesc({ 1, 1, 5, 5 }, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1012 | std::vector<T> input = |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1013 | QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1014 | 11,21,31,41,51, |
| 1015 | 12,22,32,42,52, |
| 1016 | 13,23,33,43,53, |
| 1017 | 14,24,34,44,54, |
| 1018 | 15,25,35,45,55, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1019 | }, qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1020 | |
| 1021 | // Use 1 batch of a 1-channel 4x4 kernel. |
| 1022 | armnn::TensorInfo kernelDesc({ 1, 1, 4, 4 }, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1023 | std::vector<T> kernel = |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1024 | QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1025 | -11,-21,-31,-41, |
| 1026 | -12,-22,-32,-42, |
| 1027 | -13,-23,-33,-43, |
| 1028 | -14,-24,-34,-44, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1029 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1030 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1031 | |
| 1032 | // Expected output is 1 batch of a 1-channel 5x5 image. |
| 1033 | armnn::TensorInfo outputDesc({ 1, 1, 5, 5 }, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1034 | std::vector<T> expectedOutput = |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1035 | QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1036 | -7140, -10580, -13940, -9300, -5230, |
| 1037 | -9590, -14120, -18520, -12290, -6860, |
| 1038 | -9980, -14560, -18960, -12560, -7000, |
| 1039 | -7518, -10904, -14144, -9318, -5152, |
| 1040 | -5032, -7256, -9376, -6142, -3368, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1041 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1042 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1043 | |
| 1044 | return SimpleConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 1045 | workloadFactory, |
| 1046 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1047 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1048 | input, |
| 1049 | kernel, |
| 1050 | GetBias2<ArmnnBType>(false, qScale * qScale), |
| 1051 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1052 | inputDesc.GetShape(), |
| 1053 | kernelDesc.GetShape(), |
| 1054 | outputDesc.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1055 | qScale, |
| 1056 | qOffset, |
| 1057 | layout, |
| 1058 | 1, // Padding left. |
| 1059 | 1, // Padding top. |
| 1060 | 2, // Padding right. |
| 1061 | 2); // Padding bottom. |
| 1062 | } |
| 1063 | |
| 1064 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> |
| 1065 | LayerTestResult<T, 4> Convolution2d3x3DilationTestCommon( |
| 1066 | armnn::IWorkloadFactory& workloadFactory, |
| 1067 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1068 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1069 | const std::vector<float>& inputNoQuantizedValues, |
| 1070 | armnn::TensorInfo& inputTensorInfo, |
| 1071 | const std::vector<float>& kernelNoQuantizedValues, |
| 1072 | armnn::TensorInfo& kernelTensorInfo, |
| 1073 | const std::vector<float>& outputExpectedNoQuantizedValues, |
| 1074 | armnn::TensorInfo& outputTensorInfo, |
| 1075 | uint32_t dilationX, |
| 1076 | uint32_t dilationY, |
| 1077 | armnn::DataLayout layout = armnn::DataLayout::NCHW, |
| 1078 | uint32_t padLeft = 0, |
| 1079 | uint32_t padTop = 0, |
| 1080 | uint32_t padRight = 0, |
| 1081 | uint32_t padBottom = 0, |
| 1082 | uint32_t strideX = 1, |
| 1083 | uint32_t strideY = 1, |
| 1084 | bool biasEnabled = false |
| 1085 | ) |
| 1086 | { |
| 1087 | float qScale; |
| 1088 | int32_t qOffset; |
| 1089 | switch (ArmnnType) |
| 1090 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 1091 | case armnn::DataType::QAsymmU8: |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 1092 | case armnn::DataType::QAsymmS8: |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1093 | { |
| 1094 | qScale = 0.1f; |
| 1095 | qOffset = 128; |
| 1096 | break; |
| 1097 | } |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 1098 | case armnn::DataType::QSymmS16: |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1099 | { |
| 1100 | qScale = 0.1f; |
| 1101 | qOffset = 0; |
| 1102 | break; |
| 1103 | } |
| 1104 | case armnn::DataType::Float32: |
| 1105 | default: |
| 1106 | { |
| 1107 | qScale = 0.f; |
| 1108 | qOffset = 0; |
| 1109 | break; |
| 1110 | } |
| 1111 | } |
| 1112 | |
| 1113 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1114 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1115 | kernelTensorInfo.SetQuantizationScale(qScale); |
| 1116 | kernelTensorInfo.SetQuantizationOffset(qOffset); |
| 1117 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1118 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1119 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1120 | auto input = QuantizedVector<T>(inputNoQuantizedValues, |
| 1121 | inputTensorInfo.GetQuantizationScale(), |
| 1122 | inputTensorInfo.GetQuantizationOffset()); |
| 1123 | auto kernel = QuantizedVector<T>(kernelNoQuantizedValues, |
| 1124 | kernelTensorInfo.GetQuantizationScale(), |
| 1125 | kernelTensorInfo.GetQuantizationOffset()); |
| 1126 | auto expectedOutput = QuantizedVector<T>(outputExpectedNoQuantizedValues, |
| 1127 | outputTensorInfo.GetQuantizationScale(), |
| 1128 | outputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1129 | |
| 1130 | return SimpleConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 1131 | workloadFactory, |
| 1132 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1133 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1134 | input, |
| 1135 | kernel, |
| 1136 | GetBias2<ArmnnBType>(biasEnabled, qScale * qScale), |
| 1137 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1138 | inputTensorInfo.GetShape(), |
| 1139 | kernelTensorInfo.GetShape(), |
| 1140 | outputTensorInfo.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1141 | qScale, |
| 1142 | qOffset, |
| 1143 | layout, |
| 1144 | padLeft, |
| 1145 | padTop, |
| 1146 | padRight, |
| 1147 | padBottom, |
| 1148 | strideX, |
| 1149 | strideY, |
| 1150 | dilationX, |
| 1151 | dilationY); |
| 1152 | } |
| 1153 | |
| 1154 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T> |
| 1155 | LayerTestResult<T, 4> Convolution2d3x3Dilation3x3Test( |
| 1156 | armnn::IWorkloadFactory& workloadFactory, |
| 1157 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1158 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1159 | bool biasEnabled, |
| 1160 | const armnn::DataLayout layout) |
| 1161 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1162 | armnn::TensorInfo inputTensorInfo({ 1, 1, 10, 10 }, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1163 | std::vector<float> inputNoQuantizedValues = |
| 1164 | { |
| 1165 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1166 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1167 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1168 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1169 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1170 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1171 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1172 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1173 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1174 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| 1175 | }; |
| 1176 | |
| 1177 | armnn::TensorInfo kernelTensorInfo({ 1, 1, 3, 3}, ArmnnType); |
| 1178 | std::vector<float> kernelNoQuantizedValues = |
| 1179 | { |
| 1180 | 1, 2, 3, |
| 1181 | 4, 5, 6, |
| 1182 | 7, 8, 9 |
| 1183 | }; |
| 1184 | |
| 1185 | // Since the dilation rate is 3 this will dilate the kernel to be like 7x7, |
| 1186 | // therefore the output will be 4x4: (I−K+2P)/S +1 => (10-7 +0)/1 +1 |
| 1187 | armnn::TensorInfo outputTensorInfo({ 1, 1, 4, 4}, ArmnnType); |
| 1188 | std::vector<float> outputExpectedNoQuantizedValues = |
| 1189 | { |
| 1190 | 6., 5., 5., 5., |
| 1191 | 6., 5., 5., 5., |
| 1192 | 6., 5., 5., 5., |
| 1193 | 3., 2., 2., 2. |
| 1194 | }; |
| 1195 | |
| 1196 | return Convolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( |
| 1197 | workloadFactory, |
| 1198 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1199 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1200 | inputNoQuantizedValues, |
| 1201 | inputTensorInfo, |
| 1202 | kernelNoQuantizedValues, |
| 1203 | kernelTensorInfo, |
| 1204 | outputExpectedNoQuantizedValues, |
| 1205 | outputTensorInfo, |
| 1206 | 3, |
| 1207 | 3, |
| 1208 | layout, |
| 1209 | biasEnabled); |
| 1210 | } |
| 1211 | |
| 1212 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T> |
| 1213 | LayerTestResult<T, 4> Convolution2d2x3x3Dilation3x3Test( |
| 1214 | armnn::IWorkloadFactory& workloadFactory, |
| 1215 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1216 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1217 | bool biasEnabled, |
| 1218 | const armnn::DataLayout layout) |
| 1219 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1220 | armnn::TensorInfo inputTensorInfo({ 1, 2, 10, 10 }, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1221 | std::vector<float> inputNoQuantizedValues = |
| 1222 | { |
| 1223 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1224 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1225 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1226 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1227 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1228 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1229 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1230 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1231 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1232 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1233 | |
| 1234 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1235 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1236 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1237 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1238 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1239 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1240 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1241 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1242 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1243 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| 1244 | }; |
| 1245 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1246 | armnn::TensorInfo kernelTensorInfo({ 1, 2, 3, 3 }, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1247 | std::vector<float> kernelNoQuantizedValues = |
| 1248 | { |
| 1249 | 1, 2, 3, |
| 1250 | 4, 5, 6, |
| 1251 | 7, 8, 9, |
| 1252 | |
| 1253 | 1, 2, 3, |
| 1254 | 4, 5, 6, |
| 1255 | 7, 8, 9 |
| 1256 | }; |
| 1257 | |
| 1258 | // Since the dilation rate is 3 this will dilate the kernel to be like 7x7, |
| 1259 | // therefore the output will be 4x4: (I−K+2P)/S +1 => (10-7 +0)/1 +1 |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1260 | armnn::TensorInfo outputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1261 | std::vector<float> outputExpectedNoQuantizedValues = |
| 1262 | { |
| 1263 | 12., 10., 10., 10., |
| 1264 | 12., 10., 10., 10., |
| 1265 | 12., 10., 10., 10., |
| 1266 | 6., 4., 4., 4. |
| 1267 | }; |
| 1268 | |
| 1269 | return Convolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( |
| 1270 | workloadFactory, |
| 1271 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1272 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1273 | inputNoQuantizedValues, |
| 1274 | inputTensorInfo, |
| 1275 | kernelNoQuantizedValues, |
| 1276 | kernelTensorInfo, |
| 1277 | outputExpectedNoQuantizedValues, |
| 1278 | outputTensorInfo, |
| 1279 | 3, |
| 1280 | 3, |
| 1281 | layout, |
| 1282 | biasEnabled); |
| 1283 | } |
| 1284 | |
| 1285 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T> |
| 1286 | LayerTestResult<T, 4> Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test( |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1287 | armnn::IWorkloadFactory& workloadFactory, |
| 1288 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1289 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1290 | bool biasEnabled, |
| 1291 | const armnn::DataLayout layout) |
| 1292 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1293 | armnn::TensorInfo inputTensorInfo({ 1, 1, 10, 10 }, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1294 | std::vector<float> inputNoQuantizedValues = |
| 1295 | { |
| 1296 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1297 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1298 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1299 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1300 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1301 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1302 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1303 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1304 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1305 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 |
| 1306 | }; |
| 1307 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1308 | armnn::TensorInfo kernelTensorInfo({ 1, 1, 2, 2 }, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1309 | std::vector<float> kernelNoQuantizedValues = |
| 1310 | { |
| 1311 | 1, 2, |
| 1312 | 3, 4 |
| 1313 | }; |
| 1314 | |
| 1315 | // Since the dilation rate is 2 this will dilate the kernel to be like 3x3: d(K-1)+1 --> 2 x (2-1) + 1 = 3, |
| 1316 | // therefore the output will be 4x4: (I − K + 2P)/S +1 => trunc ( (10 - 3 + 2x2 ) / 3 + 1 ) |
| 1317 | // where, dilation size = d = 2; kernel size = K = 2; input size = I = 10; padding size = P = 2; stride = S = 3 |
| 1318 | armnn::TensorInfo outputTensorInfo({ 1, 1, 4, 4}, ArmnnType); |
| 1319 | std::vector<float> outputExpectedNoQuantizedValues = |
| 1320 | { |
| 1321 | 4, 7, 7, 3, |
| 1322 | 6, 10, 10, 4, |
| 1323 | 6, 10, 10, 4, |
| 1324 | 2, 3, 3, 1 |
| 1325 | }; |
| 1326 | uint32_t padLeft = 1; |
| 1327 | uint32_t padTop = 1; |
| 1328 | uint32_t padRight = 1; |
| 1329 | uint32_t padBottom = 1; |
| 1330 | |
| 1331 | return Convolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( |
| 1332 | workloadFactory, |
| 1333 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1334 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1335 | inputNoQuantizedValues, |
| 1336 | inputTensorInfo, |
| 1337 | kernelNoQuantizedValues, |
| 1338 | kernelTensorInfo, |
| 1339 | outputExpectedNoQuantizedValues, |
| 1340 | outputTensorInfo, |
| 1341 | 2, |
| 1342 | 2, |
| 1343 | layout, |
| 1344 | padLeft, |
| 1345 | padTop, |
| 1346 | padRight, |
| 1347 | padBottom, |
| 1348 | 3, |
| 1349 | 3, |
| 1350 | biasEnabled |
| 1351 | ); |
| 1352 | } |
| 1353 | |
| 1354 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 1355 | LayerTestResult<T,4> CompareConvolution2dTestImpl( |
| 1356 | armnn::IWorkloadFactory& workloadFactory, |
| 1357 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1358 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 1359 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1360 | const armnn::ITensorHandleFactory& refTensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1361 | { |
| 1362 | unsigned int inputHeight = 8; |
| 1363 | unsigned int inputWidth = 16; |
| 1364 | unsigned int inputChannels = 3; |
| 1365 | unsigned int inputNum = 5; |
| 1366 | |
| 1367 | unsigned int kernelHeight = 3; |
| 1368 | unsigned int kernelWidth = 3; |
| 1369 | |
| 1370 | unsigned int strideX = 2; |
| 1371 | unsigned int strideY = 3; |
| 1372 | unsigned int padX = 1; |
| 1373 | unsigned int padY = 1; |
| 1374 | |
| 1375 | unsigned int outputNum = inputNum; |
| 1376 | unsigned int outputChannels = 2; |
| 1377 | unsigned int outputHeight = (inputHeight + 2 * padY - kernelHeight + strideY) / strideY; |
| 1378 | unsigned int outputWidth = (inputWidth + 2 * padX - kernelWidth + strideX) / strideX; |
| 1379 | |
| 1380 | armnn::TensorInfo inputTensorInfo; |
| 1381 | armnn::TensorInfo outputTensorInfo; |
| 1382 | armnn::TensorInfo kernelDesc; |
| 1383 | armnn::TensorInfo biasDesc; |
| 1384 | |
| 1385 | unsigned int inputShape[] = {inputNum, inputChannels, inputHeight, inputWidth}; |
| 1386 | unsigned int outputShape[] = {outputNum, outputChannels, outputHeight, outputWidth}; |
| 1387 | unsigned int kernelShape[] = {outputChannels, inputChannels, kernelHeight, kernelWidth}; |
| 1388 | unsigned int biasShape[] = {outputChannels}; |
| 1389 | |
| 1390 | inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType); |
| 1391 | outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType); |
| 1392 | kernelDesc = armnn::TensorInfo(4, kernelShape, ArmnnType); |
| 1393 | biasDesc = armnn::TensorInfo(1, biasShape, ArmnnType); |
| 1394 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1395 | auto input = MakeRandomTensor<T>(inputTensorInfo, 124908); |
| 1396 | auto kernel = MakeRandomTensor<T>(kernelDesc, 891234); |
| 1397 | auto bias = MakeRandomTensor<T>(biasDesc, 1028); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1398 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1399 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
| 1400 | std::vector<T> expectedOutput(outputTensorInfo.GetNumElements()); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1401 | |
| 1402 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 1403 | std::unique_ptr<armnn::ITensorHandle> biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc); |
| 1404 | std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1405 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 1406 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1407 | armnn::Convolution2dQueueDescriptor data; |
| 1408 | armnn::WorkloadInfo info; |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 1409 | |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 1410 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 1411 | AddInputToWorkload(data, info, kernelDesc, weightsHandle.get()); |
| 1412 | AddInputToWorkload(data, info, biasDesc, biasHandle.get()); |
| 1413 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1414 | |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 1415 | AllocateAndCopyDataToITensorHandle(weightsHandle.get(), kernel.data()); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 1416 | AllocateAndCopyDataToITensorHandle(biasHandle.get(), bias.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1417 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1418 | data.m_Parameters.m_StrideX = strideX; |
| 1419 | data.m_Parameters.m_StrideY = strideY; |
| 1420 | data.m_Parameters.m_PadLeft = padX; |
| 1421 | data.m_Parameters.m_PadRight = padX; |
| 1422 | data.m_Parameters.m_PadTop = padY; |
| 1423 | data.m_Parameters.m_PadBottom = padY; |
| 1424 | data.m_Parameters.m_BiasEnabled = true; |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1425 | |
| 1426 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refTensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 1427 | std::unique_ptr<armnn::ITensorHandle> weightsHandleRef = refTensorHandleFactory.CreateTensorHandle(kernelDesc); |
| 1428 | std::unique_ptr<armnn::ITensorHandle> biasHandleRef = refTensorHandleFactory.CreateTensorHandle(biasDesc); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1429 | std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refTensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 1430 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1431 | armnn::Convolution2dQueueDescriptor refData = data; |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1432 | armnn::WorkloadInfo refInfo = info; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1433 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get()); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 1434 | SetWorkloadInput(refData, refInfo, 1, kernelDesc, weightsHandleRef.get()); |
| 1435 | SetWorkloadInput(refData, refInfo, 2, biasDesc, biasHandleRef.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1436 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 1437 | |
Teresa Charlin | 611c7fb | 2022-01-07 09:47:29 +0000 | [diff] [blame] | 1438 | std::unique_ptr<armnn::IWorkload> workload |
| 1439 | = workloadFactory.CreateWorkload(armnn::LayerType::Convolution2d, data, info); |
| 1440 | std::unique_ptr<armnn::IWorkload> workloadRef |
| 1441 | = refWorkloadFactory.CreateWorkload(armnn::LayerType::Convolution2d, refData, refInfo); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1442 | |
| 1443 | outputHandleRef->Allocate(); |
| 1444 | inputHandleRef->Allocate(); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 1445 | weightsHandleRef->Allocate(); |
| 1446 | biasHandleRef->Allocate(); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1447 | |
| 1448 | inputHandle->Allocate(); |
| 1449 | outputHandle->Allocate(); |
| 1450 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1451 | CopyDataToITensorHandle(inputHandle.get(), input.data()); |
| 1452 | CopyDataToITensorHandle(inputHandleRef.get(), input.data()); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 1453 | CopyDataToITensorHandle(weightsHandleRef.get(), kernel.data()); |
| 1454 | CopyDataToITensorHandle(biasHandleRef.get(), bias.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1455 | |
| 1456 | ExecuteWorkload(*workload, memoryManager); |
| 1457 | |
| 1458 | workloadRef->PostAllocationConfigure(); |
| 1459 | workloadRef->Execute(); |
| 1460 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1461 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
| 1462 | CopyDataFromITensorHandle(expectedOutput.data(), outputHandleRef.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1463 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1464 | return LayerTestResult<T, 4>(actualOutput, |
| 1465 | expectedOutput, |
| 1466 | outputHandle->GetShape(), |
| 1467 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1468 | } |
| 1469 | |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1470 | LayerTestResult<float, 4> Convolution2d3x3Stride2x2BFloat16Test( |
| 1471 | armnn::IWorkloadFactory& workloadFactory, |
| 1472 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1473 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1474 | bool biasEnabled, |
| 1475 | const armnn::DataLayout& dataLayout) |
| 1476 | { |
| 1477 | // BFloat16 input and weight, Float32 output |
| 1478 | armnn::IgnoreUnused(biasEnabled); |
| 1479 | |
| 1480 | // Input is a single-batch, 1 channel, 5x5 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1481 | armnn::TensorInfo inputDesc({ 1, 5, 5, 1 }, armnn::DataType::BFloat16); |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1482 | |
| 1483 | std::vector<armnn::BFloat16> inputValues = armnnUtils::QuantizedVector<armnn::BFloat16>( |
| 1484 | { |
| 1485 | 10.0367984f, // 10.0625 |
| 1486 | 2.0380895f, // 2.03125 |
| 1487 | 15.0420157f, // 15.0625 |
| 1488 | 22.0675631f, // 22.125 |
| 1489 | 8.0938920f, // 8.125 |
| 1490 | 5.0476106f, // 5.0625 |
| 1491 | 80.1035490f, // 80 |
| 1492 | 100.1260370f, // 100 |
| 1493 | 55.0461647f, // 55 |
| 1494 | 120.0883828f, // 120 |
| 1495 | 9.1159540f, // 9.125 |
| 1496 | 90.0498519f, // 90 |
| 1497 | 200.0104630f, // 200 |
| 1498 | 30.0154114f, // 30 |
| 1499 | 75.00137681f, // 75 |
| 1500 | 30.0344238f, // 30 |
| 1501 | 25.0356445f, // 25 |
| 1502 | 130.0495605f, // 130 |
| 1503 | 60.0683594f, // 60 |
| 1504 | 35.0991211f, // 35 |
| 1505 | 8.0461426f, // 8.0625 |
| 1506 | 12.0996094f, // 12.125 |
| 1507 | 98.1269530f, // 98 |
| 1508 | 125.0393066f, // 125 |
| 1509 | 5.103516f // 5.0937 |
| 1510 | }, |
| 1511 | 1.0f, 0); |
| 1512 | |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1513 | // Use a 3x3 kernel. |
| 1514 | armnn::TensorInfo kernelDesc({1, 3, 3, 1}, armnn::DataType::BFloat16); |
| 1515 | |
| 1516 | std::vector<armnn::BFloat16> kernelValues = armnnUtils::QuantizedVector<armnn::BFloat16>( |
| 1517 | { |
| 1518 | -0.126184f, // -0.125977 |
| 1519 | -0.150468f, // -0.150391 |
| 1520 | -0.101412f, // -0.101562 |
| 1521 | -0.0586369f,// -0.0585938 |
| 1522 | -0.0865864f,// -0.0864258 |
| 1523 | -0.0435089f,// -0.043457 |
| 1524 | 0.0347555f, // 0.034668 |
| 1525 | 0.0323111f, // 0.0322266 |
| 1526 | 0.0385381f // 0.0385742 |
| 1527 | }, |
| 1528 | 1.0f, 0); |
| 1529 | |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1530 | // Expected output is a single-batch, 1 channel, 3x3 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1531 | armnn::TensorInfo outputDesc({ 1, 3, 3, 1 }, armnn::DataType::Float32); |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1532 | |
| 1533 | // Expected output (with results if calculated as FP32 in the comments) |
| 1534 | const std::vector<float> outputData = |
| 1535 | { |
| 1536 | 2.296875f, // 2.29240716 |
| 1537 | 5.75f, // 5.75851926 |
| 1538 | 3.78125f, // 3.79855026 |
| 1539 | -11.625f, // -11.65498118 |
| 1540 | -47.25f, // -47.27316893 |
| 1541 | -30.0f, // -30.04771684 |
| 1542 | -8.25f, // -8.28126168 |
| 1543 | -43.5f, // -43.46531337 |
| 1544 | -20.625f // -20.63477281 |
| 1545 | }; |
| 1546 | |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1547 | uint32_t padLeft = 1; |
| 1548 | uint32_t padTop = 1; |
| 1549 | uint32_t padRight = 1; |
| 1550 | uint32_t padBottom = 1; |
| 1551 | uint32_t strideX = 2; |
| 1552 | uint32_t strideY = 2; |
| 1553 | |
| 1554 | return SimpleConvolution2dNhwcTestImpl |
| 1555 | <armnn::DataType::BFloat16, armnn::DataType::Float32, armnn::BFloat16, float, armnn::DataType::Float32, float>( |
| 1556 | workloadFactory, |
| 1557 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1558 | tensorHandleFactory, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1559 | inputValues, |
| 1560 | kernelValues, |
| 1561 | std::vector<float>(), |
| 1562 | outputData, |
| 1563 | inputDesc.GetShape(), |
| 1564 | kernelDesc.GetShape(), |
| 1565 | outputDesc.GetShape(), |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1566 | dataLayout, |
| 1567 | 1.0f, |
| 1568 | 0, |
| 1569 | padLeft, |
| 1570 | padTop, |
| 1571 | padRight, |
| 1572 | padBottom, |
| 1573 | strideX, |
| 1574 | strideY); |
| 1575 | } |
| 1576 | |
| 1577 | LayerTestResult<float, 4> Convolution2d3x3Stride2x2BFloat16SmallValueTest( |
| 1578 | armnn::IWorkloadFactory& workloadFactory, |
| 1579 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1580 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1581 | bool biasEnabled, |
| 1582 | const armnn::DataLayout& dataLayout) |
| 1583 | { |
| 1584 | // BFloat16 input and weight, Float32 output |
| 1585 | armnn::IgnoreUnused(biasEnabled); |
| 1586 | |
| 1587 | // Input is a single-batch, 1 channel, 5x5 image. |
| 1588 | armnn::TensorInfo inputDesc({1, 5, 5, 1}, armnn::DataType::BFloat16); |
| 1589 | |
| 1590 | std::vector<armnn::BFloat16> inputValues = armnnUtils::QuantizedVector<armnn::BFloat16>( |
| 1591 | { |
| 1592 | 0.0367984f, // 0.0368652 |
| 1593 | 0.0380895f, // 0.0380859 |
| 1594 | 0.0420157f, // 0.0419922 |
| 1595 | 0.0675631f, // 0.0673828 |
| 1596 | 0.0938920f, // 0.09375 |
| 1597 | 0.0476106f, // 0.0476074 |
| 1598 | 0.1035490f, // 0.103516 |
| 1599 | 0.1260370f, // 0.125977 |
| 1600 | 0.0461647f, // 0.0461426 |
| 1601 | 0.0883828f, // 0.0883789 |
| 1602 | 0.1159540f, // 0.115723 |
| 1603 | 0.0498519f, // 0.0498047 |
| 1604 | 0.0104630f, // 0.010437 |
| 1605 | 0.0154114f, // 0.0154419 |
| 1606 | 0.00137681f, // 0.00137329 |
| 1607 | 0.0344238f, // 0.0344616 |
| 1608 | 0.0356445f, // 0.0355693 |
| 1609 | 0.0495605f, // 0.0495018 |
| 1610 | 0.0683594f, // 0.0683308 |
| 1611 | 0.0991211f, // 0.0988837 |
| 1612 | 0.0461426f, // 0.0461838 |
| 1613 | 0.0996094f, // 0.0997546 |
| 1614 | 0.1269530f, // 0.127099 |
| 1615 | 0.0393066f, // 0.0392791 |
| 1616 | 0.103516f // 0.103641 |
| 1617 | }, |
| 1618 | 1.0f, 0); |
| 1619 | |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1620 | // Use a 3x3 kernel. |
| 1621 | armnn::TensorInfo kernelDesc({1, 3, 3, 1}, armnn::DataType::BFloat16); |
| 1622 | |
| 1623 | std::vector<armnn::BFloat16> kernelValues = armnnUtils::QuantizedVector<armnn::BFloat16>( |
| 1624 | { |
| 1625 | -0.126184f, // -0.125977 |
| 1626 | -0.150468f, // -0.150391 |
| 1627 | -0.101412f, // -0.101562 |
| 1628 | -0.0586369f,// -0.0585938 |
| 1629 | -0.0865864f,// -0.0864258 |
| 1630 | -0.0435089f,// -0.043457 |
| 1631 | 0.0347555f, // 0.034668 |
| 1632 | 0.0323111f, // 0.0322266 |
| 1633 | 0.0385381f // 0.0385742 |
| 1634 | }, |
| 1635 | 1.0f, 0); |
| 1636 | |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1637 | // Expected output is a single-batch, 1 channel, 3x3 image. |
| 1638 | armnn::TensorInfo outputDesc({1, 3, 3, 1}, armnn::DataType::Float32); |
| 1639 | |
| 1640 | // Expected output (with results if calculated as FP32 in the comments) |
| 1641 | const std::vector<float> outputData = |
| 1642 | { |
| 1643 | 0.000686645508f, // 0.000685 |
| 1644 | 0.000640869141f, // 0.000639 |
| 1645 | -0.00759887695f, // -0.007631 |
| 1646 | -0.02734375f, // -0.027388 |
| 1647 | -0.0356445312f, // -0.035737 |
| 1648 | -0.0145874023f, // -0.014568 |
| 1649 | -0.0170898438f, // -0.017124 |
| 1650 | -0.0373535156f, // -0.037431 |
| 1651 | -0.0346679688f // -0.034808 |
| 1652 | }; |
| 1653 | |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1654 | uint32_t padLeft = 1; |
| 1655 | uint32_t padTop = 1; |
| 1656 | uint32_t padRight = 1; |
| 1657 | uint32_t padBottom = 1; |
| 1658 | uint32_t strideX = 2; |
| 1659 | uint32_t strideY = 2; |
| 1660 | |
| 1661 | return SimpleConvolution2dNhwcTestImpl |
| 1662 | <armnn::DataType::BFloat16, armnn::DataType::Float32, armnn::BFloat16, float, armnn::DataType::Float32, float>( |
| 1663 | workloadFactory, |
| 1664 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1665 | tensorHandleFactory, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1666 | inputValues, |
| 1667 | kernelValues, |
| 1668 | std::vector<float>(), |
| 1669 | outputData, |
| 1670 | inputDesc.GetShape(), |
| 1671 | kernelDesc.GetShape(), |
| 1672 | outputDesc.GetShape(), |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1673 | dataLayout, |
| 1674 | 1.0f, |
| 1675 | 0, |
| 1676 | padLeft, |
| 1677 | padTop, |
| 1678 | padRight, |
| 1679 | padBottom, |
| 1680 | strideX, |
| 1681 | strideY); |
| 1682 | } |
| 1683 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1684 | // |
| 1685 | // DepthwiseConvolution2d implementations |
| 1686 | // |
| 1687 | |
| 1688 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 1689 | typename T = armnn::ResolveType<ArmnnType>, typename B = armnn::ResolveType<ArmnnBType>> |
| 1690 | LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl( |
| 1691 | armnn::IWorkloadFactory& workloadFactory, |
| 1692 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1693 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1694 | const std::vector<T>& input, |
| 1695 | const std::vector<T>& kernel, |
| 1696 | const std::vector<B>& bias, |
| 1697 | const std::vector<T>& outputExpected, |
| 1698 | const armnn::TensorShape& inputShape, |
| 1699 | const armnn::TensorShape& kernelShape, |
| 1700 | const armnn::TensorShape& outputExpectedShape, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1701 | float qScale, |
| 1702 | int32_t qOffset, |
| 1703 | const armnn::DataLayout layout, |
| 1704 | uint32_t padLeft = 0, |
| 1705 | uint32_t padTop = 0, |
| 1706 | uint32_t padRight = 0, |
| 1707 | uint32_t padBottom = 0, |
| 1708 | uint32_t strideX = 1, |
| 1709 | uint32_t strideY = 1) |
| 1710 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1711 | unsigned int inputNum = armnn::numeric_cast<unsigned int>(inputShape[0]); |
| 1712 | unsigned int inputChannels = armnn::numeric_cast<unsigned int>(inputShape[1]); |
| 1713 | unsigned int inputHeight = armnn::numeric_cast<unsigned int>(inputShape[2]); |
| 1714 | unsigned int inputWidth = armnn::numeric_cast<unsigned int>(inputShape[3]); |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 1715 | unsigned int kernelHeight = armnn::numeric_cast<unsigned int>(kernelShape[1]); |
| 1716 | unsigned int kernelWidth = armnn::numeric_cast<unsigned int>(kernelShape[2]); |
| 1717 | unsigned int kernelChannels = armnn::numeric_cast<unsigned int>(kernelShape[3]); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1718 | unsigned int outputNum = armnn::numeric_cast<unsigned int>(outputExpectedShape[0]); |
| 1719 | unsigned int outputChannels = armnn::numeric_cast<unsigned int>(outputExpectedShape[1]); |
| 1720 | unsigned int outputHeight = armnn::numeric_cast<unsigned int>(outputExpectedShape[2]); |
| 1721 | unsigned int outputWidth = armnn::numeric_cast<unsigned int>(outputExpectedShape[3]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1722 | |
| 1723 | // If a bias is used, its size must equal the number of output channels. |
| 1724 | bool biasEnabled = bias.size() > 0; |
Narumol Prangnawarat | ac2770a | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1725 | ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1726 | |
| 1727 | // Creates the tensors. |
| 1728 | armnn::TensorInfo inputTensorInfo = |
| 1729 | armnnUtils::GetTensorInfo(inputNum, inputChannels, inputHeight, inputWidth, layout, ArmnnType); |
| 1730 | armnn::TensorInfo outputTensorInfo = |
| 1731 | armnnUtils::GetTensorInfo(outputNum, outputChannels, outputHeight, outputWidth, layout, ArmnnType); |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 1732 | armnn::TensorInfo kernelDesc({1, kernelHeight, kernelWidth, kernelChannels}, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1733 | armnn::TensorInfo biasDesc({static_cast<unsigned int>(bias.size())}, ArmnnBType); |
| 1734 | |
| 1735 | // Set quantization parameters if the requested type is a quantized type. |
| 1736 | if (armnn::IsQuantizedType<T>()) |
| 1737 | { |
| 1738 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1739 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1740 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1741 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1742 | kernelDesc.SetQuantizationScale(qScale); |
| 1743 | kernelDesc.SetQuantizationOffset(qOffset); |
| 1744 | biasDesc.SetQuantizationScale(qScale*qScale); |
| 1745 | biasDesc.SetQuantizationOffset(0); |
| 1746 | } |
| 1747 | |
| 1748 | // Construct the input data. |
| 1749 | std::vector<T> inputData; |
| 1750 | inputData.assign(input.data(), input.data() + inputChannels*inputHeight*inputWidth); |
| 1751 | |
| 1752 | // At this point if we require it permute the input data |
| 1753 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
| 1754 | if (layout == armnn::DataLayout::NHWC) |
| 1755 | { |
| 1756 | std::vector<T> tmp(inputData.size()); |
| 1757 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(T)); |
| 1758 | inputData = tmp; |
| 1759 | } |
| 1760 | |
Cathal Corbett | 4b19d22 | 2022-05-11 20:12:17 +0100 | [diff] [blame] | 1761 | std::vector<T> kernelData; |
| 1762 | kernelData.assign(kernel.data(), kernel.data() + kernelHeight * kernelWidth * outputChannels); |
| 1763 | if (workloadFactory.GetBackendId() == armnn::BackendId("GpuAcc") || |
| 1764 | workloadFactory.GetBackendId() == armnn::BackendId("CpuAcc")) |
| 1765 | { |
| 1766 | if (layout == armnn::DataLayout::NCHW) |
| 1767 | { |
| 1768 | std::vector<T> tmp(kernelData.size()); |
| 1769 | kernelDesc.SetShape(armnnUtils::Permuted(kernelDesc.GetShape(), {0, 2, 3, 1})); |
| 1770 | armnnUtils::Permute(kernelDesc.GetShape(), {0, 2, 3, 1}, kernelData.data(), tmp.data(), sizeof(T)); |
| 1771 | kernelData = tmp; |
| 1772 | } |
| 1773 | } |
| 1774 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1775 | // Construct the output data, with bias applied, as appropriate. |
| 1776 | std::vector<T> outputData; |
| 1777 | outputData.assign(outputExpected.data(), outputExpected.data() + outputChannels*outputHeight*outputWidth); |
| 1778 | if (biasEnabled) |
| 1779 | { |
| 1780 | std::vector<T> biasV; |
| 1781 | biasV.assign(bias.data(), bias.data() + outputChannels); |
| 1782 | ApplyBias(outputData, outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset(), |
| 1783 | biasV, biasDesc.GetQuantizationScale(), biasDesc.GetQuantizationOffset(), |
| 1784 | outputWidth, outputHeight); |
| 1785 | } |
| 1786 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1787 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1788 | |
| 1789 | // At this point if we require it permute the expected output |
| 1790 | if (layout == armnn::DataLayout::NHWC) |
| 1791 | { |
| 1792 | std::vector<T> tmp(outputData.size()); |
| 1793 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp.data(), sizeof(T)); |
| 1794 | outputData = tmp; |
| 1795 | } |
| 1796 | |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1797 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 1798 | std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc); |
| 1799 | std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr; |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1800 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 1801 | |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 1802 | armnn::DepthwiseConvolution2dQueueDescriptor data; |
| 1803 | armnn::WorkloadInfo info; |
| 1804 | |
Cathal Corbett | 4b19d22 | 2022-05-11 20:12:17 +0100 | [diff] [blame] | 1805 | AllocateAndCopyDataToITensorHandle(weightsHandle.get(), kernelData.data()); // required for ConstantTensor |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 1806 | |
| 1807 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 1808 | AddInputToWorkload(data, info, kernelDesc, weightsHandle.get()); |
| 1809 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1810 | |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 1811 | armnn::ScopedTensorHandle biasTensor(biasDesc); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1812 | if (biasEnabled) |
| 1813 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1814 | AllocateAndCopyDataToITensorHandle(&biasTensor, bias.data()); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 1815 | |
| 1816 | biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc); |
| 1817 | AllocateAndCopyDataToITensorHandle(biasHandle.get(), bias.data()); |
| 1818 | AddInputToWorkload(data, info, biasDesc, biasHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1819 | } |
| 1820 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1821 | data.m_Parameters.m_StrideX = strideX; |
| 1822 | data.m_Parameters.m_StrideY = strideY; |
| 1823 | data.m_Parameters.m_PadLeft = padLeft; |
| 1824 | data.m_Parameters.m_PadRight = padRight; |
| 1825 | data.m_Parameters.m_PadTop = padTop; |
| 1826 | data.m_Parameters.m_PadBottom = padBottom; |
| 1827 | data.m_Parameters.m_BiasEnabled = biasEnabled; |
| 1828 | data.m_Parameters.m_DataLayout = layout; |
| 1829 | |
Teresa Charlin | 611c7fb | 2022-01-07 09:47:29 +0000 | [diff] [blame] | 1830 | std::unique_ptr<armnn::IWorkload> workload |
| 1831 | = workloadFactory.CreateWorkload(armnn::LayerType::DepthwiseConvolution2d, data, info); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 1832 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1833 | inputHandle->Allocate(); |
| 1834 | outputHandle->Allocate(); |
| 1835 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1836 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1837 | |
| 1838 | ExecuteWorkload(*workload, memoryManager); |
| 1839 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1840 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1841 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1842 | return LayerTestResult<T, 4>(actualOutput, |
| 1843 | outputData, |
| 1844 | outputHandle->GetShape(), |
| 1845 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1846 | } |
| 1847 | |
| 1848 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> |
| 1849 | LayerTestResult<T, 4> DepthwiseConvolution2dDepthMul1TestImpl( |
| 1850 | armnn::IWorkloadFactory& workloadFactory, |
| 1851 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1852 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1853 | float qScale, |
| 1854 | int32_t qOffset, |
| 1855 | bool biasEnabled, |
| 1856 | const armnn::DataLayout layout) |
| 1857 | { |
| 1858 | using B = armnn::ResolveType<ArmnnBType>; |
| 1859 | |
| 1860 | unsigned int inputHeight = 3; |
| 1861 | unsigned int inputWidth = 3; |
| 1862 | unsigned int inputChannels = 2; |
| 1863 | unsigned int inputNum = 1; |
| 1864 | |
| 1865 | unsigned int kernelHeight = 3; |
| 1866 | unsigned int kernelWidth = 3; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1867 | |
| 1868 | unsigned int outputHeight = 1; |
| 1869 | unsigned int outputWidth = 1; |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 1870 | unsigned int outputChannels = inputChannels; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1871 | unsigned int outputNum = inputNum; |
| 1872 | |
| 1873 | armnn::TensorInfo inputTensorInfo = |
| 1874 | armnnUtils::GetTensorInfo(inputNum, inputChannels, inputHeight, inputWidth, layout, ArmnnType); |
| 1875 | armnn::TensorInfo outputTensorInfo = |
| 1876 | armnnUtils::GetTensorInfo(outputNum, outputChannels, outputHeight, outputWidth, layout, ArmnnType); |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 1877 | armnn::TensorInfo kernelDesc({1, kernelHeight, kernelWidth, outputChannels}, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1878 | ArmnnType); |
| 1879 | armnn::TensorInfo biasDesc({ outputChannels }, ArmnnBType); |
| 1880 | |
| 1881 | // Set quantization parameters if the requested type is a quantized type. |
| 1882 | if(armnn::IsQuantizedType<T>()) |
| 1883 | { |
| 1884 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1885 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1886 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1887 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1888 | kernelDesc.SetQuantizationScale(qScale); |
| 1889 | kernelDesc.SetQuantizationOffset(qOffset); |
| 1890 | biasDesc.SetQuantizationScale(qScale*qScale); |
| 1891 | biasDesc.SetQuantizationOffset(0); |
| 1892 | } |
| 1893 | std::vector<T> inputData = std::vector<T>( |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1894 | QuantizedVector<T>({ |
| 1895 | 1.f, 2.f, 1.f, |
| 1896 | 2.f, 1.f, 2.f, |
| 1897 | 1.f, 2.f, 1.f, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1898 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1899 | 1.f, 2.f, 1.f, |
| 1900 | 2.f, 1.f, 2.f, |
| 1901 | 1.f, 2.f, 1.f, |
| 1902 | }, |
| 1903 | inputTensorInfo.GetQuantizationScale(), |
| 1904 | inputTensorInfo.GetQuantizationOffset())); |
| 1905 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1906 | // at this point if we require it permute the input data |
| 1907 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
| 1908 | if (layout == armnn::DataLayout::NHWC) |
| 1909 | { |
| 1910 | std::vector<T> tmp(inputData.size()); |
| 1911 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(T)); |
| 1912 | inputData = tmp; |
| 1913 | } |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1914 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1915 | std::vector<B> biasV(QuantizedVector<B>({ 0, 2 }, |
| 1916 | biasDesc.GetQuantizationScale(), |
| 1917 | biasDesc.GetQuantizationOffset())); |
| 1918 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1919 | std::vector<T> kernelData = std::vector<T>( |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1920 | QuantizedVector<T>({ |
| 1921 | 1.f, 0.f, 1.f, |
| 1922 | 0.f, 0.f, 0.f, |
| 1923 | -1.f, 0.f, -1.f, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1924 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1925 | 1.f, 0.f, 1.f, |
| 1926 | 0.f, 0.f, 0.f, |
| 1927 | -1.f, 0.f, -1.f, |
| 1928 | }, |
| 1929 | kernelDesc.GetQuantizationScale(), |
| 1930 | kernelDesc.GetQuantizationOffset())); |
| 1931 | |
Cathal Corbett | 4b19d22 | 2022-05-11 20:12:17 +0100 | [diff] [blame] | 1932 | if (workloadFactory.GetBackendId() == armnn::BackendId("GpuAcc") || |
| 1933 | workloadFactory.GetBackendId() == armnn::BackendId("CpuAcc")) |
| 1934 | { |
| 1935 | if (layout == armnn::DataLayout::NCHW) |
| 1936 | { |
| 1937 | std::vector<T> tmp(kernelData.size()); |
| 1938 | kernelDesc.SetShape(armnnUtils::Permuted(kernelDesc.GetShape(), {0, 2, 3, 1})); |
| 1939 | armnnUtils::Permute(kernelDesc.GetShape(), {0, 2, 3, 1}, kernelData.data(), tmp.data(), sizeof(T)); |
| 1940 | kernelData = tmp; |
| 1941 | } |
| 1942 | } |
| 1943 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1944 | // Manually calculated. |
| 1945 | std::vector<T> outputImage( |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1946 | QuantizedVector<T>({ 0.f, 0.f }, |
| 1947 | outputTensorInfo.GetQuantizationScale(), |
| 1948 | outputTensorInfo.GetQuantizationOffset()) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1949 | ); |
| 1950 | |
| 1951 | // Optionally apply bias to output image. |
| 1952 | if(biasEnabled) |
| 1953 | { |
| 1954 | ApplyBias(outputImage, outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset(), |
| 1955 | biasV, biasDesc.GetQuantizationScale(), biasDesc.GetQuantizationOffset(), |
| 1956 | outputWidth, outputHeight); |
| 1957 | } |
| 1958 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1959 | if (layout == armnn::DataLayout::NHWC) |
| 1960 | { |
| 1961 | std::vector<T> tmp(outputImage.size()); |
| 1962 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputImage.data(), tmp.data(), sizeof(T)); |
| 1963 | outputImage = tmp; |
| 1964 | } |
| 1965 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 1966 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1967 | |
| 1968 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 1969 | std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc); |
| 1970 | std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr; |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1971 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 1972 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1973 | armnn::DepthwiseConvolution2dQueueDescriptor data; |
| 1974 | armnn::WorkloadInfo info; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1975 | |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 1976 | AllocateAndCopyDataToITensorHandle(weightsHandle.get(), kernelData.data()); // required for ConstantTensor |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1977 | |
| 1978 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 1979 | AddInputToWorkload(data, info, kernelDesc, weightsHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1980 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1981 | |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 1982 | armnn::ScopedTensorHandle biasTensor(biasDesc); |
| 1983 | if (biasEnabled) |
| 1984 | { |
| 1985 | AllocateAndCopyDataToITensorHandle(&biasTensor, biasV.data()); |
| 1986 | |
| 1987 | biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc); |
| 1988 | AllocateAndCopyDataToITensorHandle(biasHandle.get(), biasV.data()); |
| 1989 | AddInputToWorkload(data, info, biasDesc, biasHandle.get()); |
| 1990 | } |
| 1991 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1992 | data.m_Parameters.m_StrideX = 1; |
| 1993 | data.m_Parameters.m_StrideY = 1; |
| 1994 | data.m_Parameters.m_PadLeft = 0; |
| 1995 | data.m_Parameters.m_PadRight = 0; |
| 1996 | data.m_Parameters.m_PadTop = 0; |
| 1997 | data.m_Parameters.m_PadBottom = 0; |
| 1998 | data.m_Parameters.m_BiasEnabled = biasEnabled; |
| 1999 | data.m_Parameters.m_DataLayout = layout; |
| 2000 | |
Teresa Charlin | 611c7fb | 2022-01-07 09:47:29 +0000 | [diff] [blame] | 2001 | std::unique_ptr<armnn::IWorkload> workload |
| 2002 | = workloadFactory.CreateWorkload(armnn::LayerType::DepthwiseConvolution2d, data, info); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 2003 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2004 | inputHandle->Allocate(); |
| 2005 | outputHandle->Allocate(); |
| 2006 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2007 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2008 | |
| 2009 | ExecuteWorkload(*workload, memoryManager); |
| 2010 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2011 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2012 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2013 | return LayerTestResult<T, 4>(actualOutput, |
| 2014 | outputImage, |
| 2015 | outputHandle->GetShape(), |
| 2016 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2017 | } |
| 2018 | |
| 2019 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> |
| 2020 | LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl( |
| 2021 | armnn::IWorkloadFactory& workloadFactory, |
| 2022 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2023 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2024 | float qScale, |
| 2025 | int32_t qOffset, |
| 2026 | bool biasEnabled, |
| 2027 | const armnn::DataLayout layout) |
| 2028 | { |
| 2029 | using B = armnn::ResolveType<ArmnnBType>; |
| 2030 | |
| 2031 | unsigned int depthMultiplier = 2; |
| 2032 | |
| 2033 | unsigned int inputHeight = 8; |
| 2034 | unsigned int inputWidth = 16; |
| 2035 | unsigned int inputChannels = 2; |
| 2036 | unsigned int inputBatchSize = 1; |
| 2037 | |
| 2038 | unsigned int kernelHeight = 5; |
| 2039 | unsigned int kernelWidth = 3; |
| 2040 | |
| 2041 | unsigned int outputHeight = inputHeight - kernelHeight + 1 + 2; |
| 2042 | unsigned int outputWidth = (inputWidth - kernelWidth + 1)/2; |
| 2043 | unsigned int outputChannels = inputChannels * depthMultiplier; |
| 2044 | unsigned int outputBatchSize = inputBatchSize; |
| 2045 | |
| 2046 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( |
| 2047 | inputBatchSize, inputChannels, inputHeight, inputWidth, layout, ArmnnType); |
| 2048 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( |
| 2049 | outputBatchSize, outputChannels, outputHeight, outputWidth, layout, ArmnnType); |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2050 | armnn::TensorInfo kernelDesc({1, kernelHeight, kernelWidth, outputChannels}, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2051 | ArmnnType); |
| 2052 | armnn::TensorInfo biasDesc({outputChannels}, ArmnnBType); |
| 2053 | |
| 2054 | // Set quantization parameters if the requested type is a quantized type. |
| 2055 | if(armnn::IsQuantizedType<T>()) |
| 2056 | { |
| 2057 | inputTensorInfo.SetQuantizationScale(qScale); |
| 2058 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 2059 | outputTensorInfo.SetQuantizationScale(qScale); |
| 2060 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 2061 | kernelDesc.SetQuantizationScale(qScale); |
| 2062 | kernelDesc.SetQuantizationOffset(qOffset); |
| 2063 | biasDesc.SetQuantizationScale(qScale*qScale); |
| 2064 | biasDesc.SetQuantizationOffset(0); |
| 2065 | } |
| 2066 | |
| 2067 | // NOTE: originalInputData is in NCHW format |
| 2068 | std::vector<T> originalInputData = std::vector<T>( |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2069 | QuantizedVector<T>({ |
| 2070 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 2071 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2072 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 2073 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 2074 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 2075 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 2076 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 2077 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 2078 | 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2079 | 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2080 | 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2081 | 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2082 | 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2083 | 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2084 | 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2085 | 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f |
| 2086 | }, |
| 2087 | inputTensorInfo.GetQuantizationScale(), |
| 2088 | inputTensorInfo.GetQuantizationOffset())); |
| 2089 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2090 | std::vector<T> inputData = originalInputData; |
| 2091 | // at this point if we require it permute the input data |
| 2092 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
| 2093 | if (layout == armnn::DataLayout::NHWC) |
| 2094 | { |
| 2095 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, |
| 2096 | originalInputData.data(), inputData.data(), sizeof(T)); |
| 2097 | } |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2098 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2099 | std::vector<B> biasV = QuantizedVector<B>({ 0, 2, 1, -1 }, |
| 2100 | biasDesc.GetQuantizationScale(), |
| 2101 | biasDesc.GetQuantizationOffset()); |
| 2102 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2103 | std::vector<T> kernelData = std::vector<T>( |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2104 | QuantizedVector<T>({ |
| 2105 | 1, 1, 1, |
| 2106 | 1, -1, 1, |
| 2107 | 1, 1, 1, |
| 2108 | 1, 1, 1, |
| 2109 | 1, 1, 1, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2110 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2111 | 2, 2, 2, |
| 2112 | 2, 2, 2, |
| 2113 | 2, 2, 2, |
| 2114 | 2, 2, 2, |
| 2115 | 2, 2, 2, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2116 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2117 | 0, 0, 0, |
| 2118 | 0, -1, 0, |
| 2119 | 0, 0, 0, |
| 2120 | 0, 0, 0, |
| 2121 | 0, 0, 0, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2122 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2123 | 0, 0, 0, |
| 2124 | 0, 0, 0, |
| 2125 | 0, 1, 0, |
| 2126 | 0, 0, 0, |
| 2127 | 0, 0, 0 |
| 2128 | }, |
| 2129 | kernelDesc.GetQuantizationScale(), |
| 2130 | kernelDesc.GetQuantizationOffset())); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2131 | |
Cathal Corbett | 4b19d22 | 2022-05-11 20:12:17 +0100 | [diff] [blame] | 2132 | if (workloadFactory.GetBackendId() == armnn::BackendId("GpuAcc") || |
| 2133 | workloadFactory.GetBackendId() == armnn::BackendId("CpuAcc")) |
| 2134 | { |
| 2135 | if (layout == armnn::DataLayout::NCHW) |
| 2136 | { |
| 2137 | std::vector<T> tmp(kernelData.size()); |
| 2138 | kernelDesc.SetShape(armnnUtils::Permuted(kernelDesc.GetShape(), {0, 2, 3, 1})); |
| 2139 | armnnUtils::Permute(kernelDesc.GetShape(), {0, 2, 3, 1}, kernelData.data(), tmp.data(), sizeof(T)); |
| 2140 | kernelData = tmp; |
| 2141 | } |
| 2142 | } |
| 2143 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2144 | // Manually calculated. |
| 2145 | std::vector<T> originalOutputImage = std::vector<T>( |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2146 | QuantizedVector<T>({ |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2147 | 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, |
| 2148 | 5, 5, 5, 5, 5, 5, 5, 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, |
| 2149 | 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, 5, 5, 5, 5, 5, 5, 5, |
| 2150 | 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, |
| 2151 | 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 6, 6, 6, 6, 6, 6, 6, |
| 2152 | 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, |
| 2153 | 1, 3, 0, 0, 0, 0, 0, 2, 4, 0, 0, 0, 0, 0, |
| 2154 | 2, 4, 0, 0, 0, 0, 0, 2, 4, 0, 0, 0, 0, 0, |
| 2155 | 2, 4, 0, 0, 0, 0, 0, 2, 4, 0, 0, 0, 0, 0, |
| 2156 | 2, 4, 0, 0, 0, 0, 0, 3, 5, 0, 0, 0, 0, 0, |
| 2157 | 3, 5, 0, 0, 0, 0, 0, 3, 5, 0, 0, 0, 0, 0, |
| 2158 | 3, 5, 0, 0, 0, 0, 0, 3, 5, 0, 0, 0, 0, 0 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2159 | }, |
| 2160 | outputTensorInfo.GetQuantizationScale(), |
| 2161 | outputTensorInfo.GetQuantizationOffset())); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2162 | |
| 2163 | // Optionally apply bias to output image. |
| 2164 | if(biasEnabled) |
| 2165 | { |
| 2166 | ApplyBias(originalOutputImage, |
| 2167 | outputTensorInfo.GetQuantizationScale(), |
| 2168 | outputTensorInfo.GetQuantizationOffset(), |
| 2169 | biasV, |
| 2170 | biasDesc.GetQuantizationScale(), |
| 2171 | biasDesc.GetQuantizationOffset(), |
| 2172 | outputWidth, |
| 2173 | outputHeight); |
| 2174 | } |
| 2175 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2176 | std::vector<T> outputImage = originalOutputImage; |
| 2177 | if (layout == armnn::DataLayout::NHWC) |
| 2178 | { |
| 2179 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, |
| 2180 | originalOutputImage.data(), outputImage.data(), sizeof(T)); |
| 2181 | } |
| 2182 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2183 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2184 | |
| 2185 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 2186 | std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc); |
| 2187 | std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr; |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2188 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 2189 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2190 | armnn::DepthwiseConvolution2dQueueDescriptor data; |
| 2191 | armnn::WorkloadInfo info; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2192 | |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 2193 | AllocateAndCopyDataToITensorHandle(weightsHandle.get(), kernelData.data()); // required for ConstantTensor |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2194 | |
| 2195 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 2196 | AddInputToWorkload(data, info, kernelDesc, weightsHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2197 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 2198 | |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 2199 | armnn::ScopedTensorHandle biasTensor(biasDesc); |
| 2200 | if (biasEnabled) |
| 2201 | { |
| 2202 | AllocateAndCopyDataToITensorHandle(&biasTensor, biasV.data()); |
| 2203 | |
| 2204 | biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc); |
| 2205 | AllocateAndCopyDataToITensorHandle(biasHandle.get(), biasV.data()); |
| 2206 | AddInputToWorkload(data, info, biasDesc, biasHandle.get()); |
| 2207 | } |
| 2208 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2209 | data.m_Parameters.m_StrideX = 2; |
| 2210 | data.m_Parameters.m_StrideY = 1; |
| 2211 | data.m_Parameters.m_PadLeft = 0; |
| 2212 | data.m_Parameters.m_PadRight = 0; |
| 2213 | data.m_Parameters.m_PadTop = 1; |
| 2214 | data.m_Parameters.m_PadBottom = 1; |
| 2215 | data.m_Parameters.m_BiasEnabled = biasEnabled; |
| 2216 | data.m_Parameters.m_DataLayout = layout; |
| 2217 | |
Teresa Charlin | 611c7fb | 2022-01-07 09:47:29 +0000 | [diff] [blame] | 2218 | std::unique_ptr<armnn::IWorkload> workload |
| 2219 | = workloadFactory.CreateWorkload(armnn::LayerType::DepthwiseConvolution2d, data, info); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 2220 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2221 | inputHandle->Allocate(); |
| 2222 | outputHandle->Allocate(); |
| 2223 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2224 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2225 | |
| 2226 | ExecuteWorkload(*workload, memoryManager); |
| 2227 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2228 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2229 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2230 | return LayerTestResult<T, 4>(actualOutput, |
| 2231 | outputImage, |
| 2232 | outputHandle->GetShape(), |
| 2233 | outputTensorInfo.GetShape()); |
| 2234 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2235 | } |
| 2236 | |
| 2237 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 2238 | typename T = armnn::ResolveType<ArmnnType>, typename B = armnn::ResolveType<ArmnnBType>> |
| 2239 | LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl( |
| 2240 | armnn::IWorkloadFactory& workloadFactory, |
| 2241 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2242 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2243 | const std::vector<T>& originalInput, |
| 2244 | const std::vector<T>& originalKernel, |
| 2245 | const std::vector<B>& bias, |
| 2246 | const std::vector<T>& originalOutputExpected, |
| 2247 | const armnn::TensorShape& originalInputShape, |
| 2248 | const armnn::TensorShape& originalKernelShape, |
| 2249 | const armnn::TensorShape& originalOutputExpectedShape, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2250 | float qScale, |
| 2251 | int32_t qOffset, |
| 2252 | const armnn::DataLayout layout = armnn::DataLayout::NCHW, |
| 2253 | uint32_t padLeft = 0, |
| 2254 | uint32_t padTop = 0, |
| 2255 | uint32_t padRight = 0, |
| 2256 | uint32_t padBottom = 0, |
| 2257 | uint32_t strideX = 1, |
| 2258 | uint32_t strideY = 1, |
| 2259 | uint32_t dilationX = 1, |
| 2260 | uint32_t dilationY = 1) |
| 2261 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2262 | unsigned int inputHeight = armnn::numeric_cast<unsigned int>(originalInputShape[2]); |
| 2263 | unsigned int inputWidth = armnn::numeric_cast<unsigned int>(originalInputShape[3]); |
| 2264 | unsigned int inputChannels = armnn::numeric_cast<unsigned int>(originalInputShape[1]); |
| 2265 | unsigned int inputNum = armnn::numeric_cast<unsigned int>(originalInputShape[0]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2266 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2267 | unsigned int outputHeight = armnn::numeric_cast<unsigned int>(originalOutputExpectedShape[2]); |
| 2268 | unsigned int outputWidth = armnn::numeric_cast<unsigned int>(originalOutputExpectedShape[3]); |
| 2269 | unsigned int outputChannels = armnn::numeric_cast<unsigned int>(originalOutputExpectedShape[1]); |
| 2270 | unsigned int outputNum = armnn::numeric_cast<unsigned int>(originalOutputExpectedShape[0]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2271 | |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2272 | unsigned int kernelHeight = armnn::numeric_cast<unsigned int>(originalKernelShape[1]); |
| 2273 | unsigned int kernelWidth = armnn::numeric_cast<unsigned int>(originalKernelShape[2]); |
| 2274 | unsigned int kernelChannels = armnn::numeric_cast<unsigned int>(originalKernelShape[3]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2275 | |
| 2276 | bool biasEnabled = bias.size() > 0; |
| 2277 | |
| 2278 | // This function currently assumes 1 batch of input/output (and duplicates this into 2 batches). |
Narumol Prangnawarat | ac2770a | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 2279 | ARMNN_ASSERT(inputNum == 1); |
| 2280 | ARMNN_ASSERT(outputNum == 1); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2281 | |
| 2282 | // If a bias is used, its size must equal the number of output channels. |
Narumol Prangnawarat | ac2770a | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 2283 | ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2284 | |
| 2285 | |
| 2286 | // Note these tensors will use two (identical) batches. |
| 2287 | armnn::TensorInfo inputTensorInfo = |
| 2288 | armnnUtils::GetTensorInfo(2*inputNum, inputChannels, inputHeight, inputWidth, layout, ArmnnType); |
| 2289 | armnn::TensorInfo outputTensorInfo = |
| 2290 | armnnUtils::GetTensorInfo(2*outputNum, outputChannels, outputHeight, outputWidth, layout, ArmnnType); |
| 2291 | |
| 2292 | // Kernel must be NCHW layout always, independently of the layout of the input and output for depthwise convolution. |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2293 | armnn::TensorInfo kernelDesc({1, kernelHeight, kernelWidth, kernelChannels}, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2294 | |
| 2295 | armnn::TensorInfo biasDesc({static_cast<unsigned int>(bias.size())}, ArmnnBType); |
| 2296 | |
| 2297 | // Set quantization parameters if the requested type is a quantized type. |
| 2298 | if(armnn::IsQuantizedType<T>()) |
| 2299 | { |
| 2300 | inputTensorInfo.SetQuantizationScale(qScale); |
| 2301 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 2302 | outputTensorInfo.SetQuantizationScale(qScale); |
| 2303 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 2304 | kernelDesc.SetQuantizationScale(qScale); |
| 2305 | kernelDesc.SetQuantizationOffset(qOffset); |
| 2306 | biasDesc.SetQuantizationScale(qScale*qScale); |
| 2307 | biasDesc.SetQuantizationOffset(0); |
| 2308 | } |
| 2309 | |
Cathal Corbett | 4b19d22 | 2022-05-11 20:12:17 +0100 | [diff] [blame] | 2310 | std::vector<T> kernelData; |
| 2311 | kernelData.assign(originalKernel.data(), originalKernel.data() + kernelHeight*kernelWidth*outputChannels); |
| 2312 | if (workloadFactory.GetBackendId() == armnn::BackendId("GpuAcc") || |
| 2313 | workloadFactory.GetBackendId() == armnn::BackendId("CpuAcc")) |
| 2314 | { |
| 2315 | if (layout == armnn::DataLayout::NCHW) |
| 2316 | { |
| 2317 | std::vector<T> tmp(kernelData.size()); |
| 2318 | kernelDesc.SetShape(armnnUtils::Permuted(kernelDesc.GetShape(), {0, 2, 3, 1})); |
| 2319 | armnnUtils::Permute(kernelDesc.GetShape(), {0, 2, 3, 1}, kernelData.data(), tmp.data(), sizeof(T)); |
| 2320 | kernelData = tmp; |
| 2321 | } |
| 2322 | } |
| 2323 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2324 | // Construct input data |
| 2325 | std::vector<T> input; |
| 2326 | input.assign(originalInput.data(), originalInput.data() + 1*inputChannels*inputHeight*inputWidth); |
| 2327 | std::vector<T> inputData; |
| 2328 | inputData.insert(inputData.end(), input.begin(), input.end()); |
| 2329 | inputData.insert(inputData.end(), input.begin(), input.end()); |
| 2330 | |
| 2331 | // at this point if we require it permute the input data |
| 2332 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
| 2333 | if (layout == armnn::DataLayout::NHWC) |
| 2334 | { |
| 2335 | std::vector<T> tmp(inputData.size()); |
| 2336 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(T)); |
| 2337 | inputData = tmp; |
| 2338 | } |
| 2339 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2340 | std::vector<T> output; |
| 2341 | output.assign(originalOutputExpected.data(), |
| 2342 | originalOutputExpected.data() + outputChannels*outputHeight*outputWidth); |
| 2343 | |
| 2344 | // Apply bias to output data if it is enabled. |
| 2345 | if(biasEnabled) |
| 2346 | { |
| 2347 | std::vector<T> biasV; |
| 2348 | biasV.assign(bias.data(), bias.data() + outputChannels); |
| 2349 | ApplyBias(output, outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset(), |
| 2350 | biasV, biasDesc.GetQuantizationScale(), biasDesc.GetQuantizationOffset(), |
| 2351 | outputWidth, outputHeight); |
| 2352 | } |
| 2353 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2354 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
| 2355 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2356 | // Construct expected output data |
| 2357 | std::vector<T> outputData; |
| 2358 | outputData.insert(outputData.end(), output.begin(), output.end()); |
| 2359 | outputData.insert(outputData.end(), output.begin(), output.end()); |
| 2360 | |
| 2361 | // at this point if we require it permute the expected output |
| 2362 | if (layout == armnn::DataLayout::NHWC) |
| 2363 | { |
| 2364 | std::vector<T> tmp(outputData.size()); |
| 2365 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp.data(), sizeof(T)); |
| 2366 | outputData = tmp; |
| 2367 | } |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2368 | |
| 2369 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 2370 | std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc); |
| 2371 | std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr; |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2372 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 2373 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2374 | armnn::DepthwiseConvolution2dQueueDescriptor data; |
| 2375 | armnn::WorkloadInfo info; |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 2376 | |
Cathal Corbett | 4b19d22 | 2022-05-11 20:12:17 +0100 | [diff] [blame] | 2377 | AllocateAndCopyDataToITensorHandle(weightsHandle.get(), kernelData.data()); // required for ConstantTensor |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2378 | |
| 2379 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 2380 | AddInputToWorkload(data, info, kernelDesc, weightsHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2381 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 2382 | |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 2383 | armnn::ScopedTensorHandle biasTensor(biasDesc); |
| 2384 | if (biasEnabled) |
| 2385 | { |
| 2386 | AllocateAndCopyDataToITensorHandle(&biasTensor, bias.data()); |
| 2387 | |
| 2388 | biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc); |
| 2389 | AllocateAndCopyDataToITensorHandle(biasHandle.get(), bias.data()); |
| 2390 | AddInputToWorkload(data, info, biasDesc, biasHandle.get()); |
| 2391 | } |
| 2392 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2393 | data.m_Parameters.m_StrideX = strideX; |
| 2394 | data.m_Parameters.m_StrideY = strideY; |
| 2395 | data.m_Parameters.m_PadLeft = padLeft; |
| 2396 | data.m_Parameters.m_PadRight = padRight; |
| 2397 | data.m_Parameters.m_PadTop = padTop; |
| 2398 | data.m_Parameters.m_PadBottom = padBottom; |
| 2399 | data.m_Parameters.m_BiasEnabled = biasEnabled; |
| 2400 | data.m_Parameters.m_DataLayout = layout; |
| 2401 | data.m_Parameters.m_DilationX = dilationX; |
| 2402 | data.m_Parameters.m_DilationY = dilationY; |
| 2403 | |
Teresa Charlin | 611c7fb | 2022-01-07 09:47:29 +0000 | [diff] [blame] | 2404 | std::unique_ptr<armnn::IWorkload> workload |
| 2405 | = workloadFactory.CreateWorkload(armnn::LayerType::DepthwiseConvolution2d, data, info); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 2406 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2407 | inputHandle->Allocate(); |
| 2408 | outputHandle->Allocate(); |
| 2409 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2410 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2411 | |
| 2412 | ExecuteWorkload(*workload, memoryManager); |
| 2413 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2414 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2415 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2416 | return LayerTestResult<T, 4>(actualOutput, |
| 2417 | outputData, |
| 2418 | outputHandle->GetShape(), |
| 2419 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2420 | } |
| 2421 | |
| 2422 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 2423 | typename T = armnn::ResolveType<ArmnnType>> |
| 2424 | LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestCommon( |
| 2425 | armnn::IWorkloadFactory& workloadFactory, |
| 2426 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2427 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2428 | float qScale, |
| 2429 | int32_t qOffset, |
| 2430 | bool biasEnabled, |
| 2431 | const armnn::DataLayout layout) |
| 2432 | { |
| 2433 | // Use a single-batch 2-channel 5x5 image as input. |
| 2434 | armnn::TensorInfo inputTensorInfo({ 1, 2, 5, 5 }, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2435 | auto input = QuantizedVector<T>( |
| 2436 | { |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2437 | 0, 1, 2, 3, 4, |
| 2438 | 5, 6, 7, 8, 9, |
| 2439 | 10, 11, 12, 13, 14, |
| 2440 | 15, 16, 17, 18, 19, |
| 2441 | 20, 21, 22, 23, 24, |
| 2442 | |
| 2443 | 25, 26, 27, 28, 29, |
| 2444 | 30, 31, 32, 33, 34, |
| 2445 | 35, 36, 37, 38, 39, |
| 2446 | 40, 41, 42, 43, 44, |
| 2447 | 45, 46, 47, 48, 49 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2448 | }, |
| 2449 | inputTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2450 | inputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2451 | |
| 2452 | // Use a depth multiplier of 1 on a 2-channel 4x4 kernel. |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2453 | // Weights layout for depthwise: [1,H,W,I*M] |
| 2454 | armnn::TensorInfo kernelTensorInfo({ 1, 4, 4, 2 }, ArmnnType); |
| 2455 | auto kernel = QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2456 | 32, 31, 30, 29, |
| 2457 | 28, 27, 26, 25, |
| 2458 | 24, 23, 22, 21, |
| 2459 | 20, 19, 18, 17, |
| 2460 | |
| 2461 | 16, 15, 14, 13, |
| 2462 | 12, 11, 10, 9, |
| 2463 | 8, 7, 6, 5, |
| 2464 | 4, 3, 2, 1 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2465 | }, |
| 2466 | kernelTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2467 | kernelTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2468 | |
| 2469 | // Expected output is 1 batch of a 2-channel 5x5 image. |
| 2470 | // Calculated using the python tensorflow library with strideX=1, strideY=1. |
| 2471 | armnn::TensorInfo outputTensorInfo({ 1, 2, 5, 5 }, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2472 | auto expectedOutput = QuantizedVector<T>( |
| 2473 | { |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2474 | 396, 664, 820, 756, 602, 1016, 1608, 1880, 1652, 1268, 1976, 2968, 3240, 2732, |
| 2475 | 2028, 2628, 3808, 4060, 3312, 2390, 2596, 3700, 3900, 3130, 2226, 2817, 4186, |
| 2476 | 4330, 3609, 2651, 5414, 7864, 8120, 6626, 4780, 6314, 9144, 9400, 7646, 5500, |
| 2477 | 6759, 9610, 9850, 7875, 5579, 5935, 8348, 8540, 6757, 4742 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2478 | }, |
| 2479 | outputTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2480 | outputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2481 | |
| 2482 | return DepthwiseConvolution2dAsymmetricTestImpl<ArmnnType, ArmnnBType>( |
| 2483 | workloadFactory, |
| 2484 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2485 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2486 | input, |
| 2487 | kernel, |
| 2488 | GetBias2<ArmnnBType>(biasEnabled, qScale * qScale), |
| 2489 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2490 | inputTensorInfo.GetShape(), |
| 2491 | kernelTensorInfo.GetShape(), |
| 2492 | outputTensorInfo.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2493 | qScale, |
| 2494 | qOffset, |
| 2495 | layout, |
| 2496 | 1, // Padding left. |
| 2497 | 1, // Padding top. |
| 2498 | 2, // Padding right. |
| 2499 | 2, // Padding bottom. |
| 2500 | 1, // strideX |
| 2501 | 1); // strideY |
| 2502 | } |
| 2503 | |
| 2504 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 2505 | typename T = armnn::ResolveType<ArmnnType>> |
| 2506 | LayerTestResult<T, 4> DepthwiseConvolution2dNhwcTestCommon( |
| 2507 | armnn::IWorkloadFactory& workloadFactory, |
| 2508 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2509 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2510 | float qScale, |
| 2511 | int32_t qOffset, |
| 2512 | bool biasEnabled) |
| 2513 | { |
| 2514 | auto layout = armnn::DataLayout::NHWC; |
| 2515 | |
| 2516 | armnn::TensorInfo inputTensorInfo({ 1, 2, 5, 5}, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2517 | auto input = QuantizedVector<T>( |
| 2518 | { |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2519 | 0, 1, 2, 3, 4, |
| 2520 | 5, 6, 7, 8, 9, |
| 2521 | 10, 11, 12, 13, 14, |
| 2522 | 15, 16, 17, 18, 19, |
| 2523 | 20, 21, 22, 23, 24, |
| 2524 | |
| 2525 | 25, 26, 27, 28, 29, |
| 2526 | 30, 31, 32, 33, 34, |
| 2527 | 35, 36, 37, 38, 39, |
| 2528 | 40, 41, 42, 43, 44, |
| 2529 | 45, 46, 47, 48, 49 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2530 | }, |
| 2531 | inputTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2532 | inputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2533 | |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2534 | armnn::TensorInfo kernelTensorInfo({ 1, 4, 4, 2 }, ArmnnType); |
| 2535 | auto kernel = QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2536 | 32, 31, 30, 29, |
| 2537 | 28, 27, 26, 25, |
| 2538 | 24, 23, 22, 21, |
| 2539 | 20, 19, 18, 17, |
| 2540 | |
| 2541 | 16, 15, 14, 13, |
| 2542 | 12, 11, 10, 9, |
| 2543 | 8, 7, 6, 5, |
| 2544 | 4, 3, 2, 1 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2545 | }, |
| 2546 | kernelTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2547 | kernelTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2548 | |
| 2549 | armnn::TensorInfo outputTensorInfo({ 1, 2, 5, 5}, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2550 | auto expectedOutput = QuantizedVector<T>( |
| 2551 | { |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2552 | 396,664,820,756,602, |
| 2553 | 1016,1608,1880,1652,1268, |
| 2554 | 1976,2968,3240,2732,2028, |
| 2555 | 2628,3808,4060,3312,2390, |
| 2556 | 2596,3700,3900,3130,2226, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2557 | |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2558 | 2817,4186,4330,3609,2651, |
| 2559 | 5414,7864,8120,6626,4780, |
| 2560 | 6314,9144,9400,7646,5500, |
| 2561 | 6759,9610,9850,7875,5579, |
| 2562 | 5935,8348,8540,6757,4742 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2563 | }, |
| 2564 | outputTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2565 | outputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2566 | |
| 2567 | return DepthwiseConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 2568 | workloadFactory, |
| 2569 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2570 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2571 | input, |
| 2572 | kernel, |
| 2573 | GetBias2<ArmnnBType>(biasEnabled, qScale * qScale), |
| 2574 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2575 | inputTensorInfo.GetShape(), |
| 2576 | kernelTensorInfo.GetShape(), |
| 2577 | outputTensorInfo.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2578 | qScale, |
| 2579 | qOffset, |
| 2580 | layout, |
| 2581 | 1, // Padding left. |
| 2582 | 1, // Padding top. |
| 2583 | 2, // Padding right. |
| 2584 | 2, // Padding bottom. |
| 2585 | 1, // strideX |
| 2586 | 1); // strideY |
| 2587 | } |
| 2588 | |
| 2589 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 2590 | typename T = armnn::ResolveType<ArmnnType>> |
| 2591 | LayerTestResult<T, 4> SimpleDepthwiseConvolution2d3x3Dilation3x3NhwcTestCommon( |
| 2592 | armnn::IWorkloadFactory& workloadFactory, |
| 2593 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2594 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2595 | float qScale, |
| 2596 | int32_t qOffset, |
| 2597 | bool biasEnabled) |
| 2598 | { |
| 2599 | auto layout = armnn::DataLayout::NHWC; |
| 2600 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2601 | armnn::TensorInfo inputTensorInfo({ 1, 1, 9, 9 }, ArmnnType); |
| 2602 | auto input = QuantizedVector<T>( |
| 2603 | { |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2604 | 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2605 | 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2606 | 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2607 | 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2608 | 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2609 | 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2610 | 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2611 | 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2612 | 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| 2613 | }, |
| 2614 | inputTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2615 | inputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2616 | |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2617 | armnn::TensorInfo kernelTensorInfo({ 1, 3, 3, 1}, ArmnnType); |
| 2618 | auto kernel = QuantizedVector<T>({ |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2619 | 1, 2, 3, |
| 2620 | 4, 5, 6, |
| 2621 | 7, 8, 9 |
| 2622 | }, |
| 2623 | kernelTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2624 | kernelTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2625 | |
| 2626 | uint32_t padLeft = 0; |
| 2627 | uint32_t padTop = 0; |
| 2628 | uint32_t padRight = 0; |
| 2629 | uint32_t padBottom = 0; |
| 2630 | uint32_t strideX = 1; |
| 2631 | uint32_t strideY = 1; |
| 2632 | uint32_t dilationX = 3; |
| 2633 | uint32_t dilationY = 3; |
| 2634 | |
| 2635 | // Since the dilation rate is 3 this will reduce the size of the output from 9x9 to 3x3 of all 5s. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2636 | armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, ArmnnType); |
| 2637 | auto expectedOutput = QuantizedVector<T>( |
| 2638 | { |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2639 | 5, 5, 5, |
| 2640 | 5, 5, 5, |
| 2641 | 5, 5, 5 |
| 2642 | }, |
| 2643 | outputTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2644 | outputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2645 | |
| 2646 | return DepthwiseConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 2647 | workloadFactory, |
| 2648 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2649 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2650 | input, |
| 2651 | kernel, |
| 2652 | GetBias2<ArmnnBType>(biasEnabled, qScale * qScale), |
| 2653 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2654 | inputTensorInfo.GetShape(), |
| 2655 | kernelTensorInfo.GetShape(), |
| 2656 | outputTensorInfo.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2657 | qScale, |
| 2658 | qOffset, |
| 2659 | layout, |
| 2660 | padLeft, |
| 2661 | padTop, |
| 2662 | padRight, |
| 2663 | padBottom, |
| 2664 | strideX, |
| 2665 | strideY, |
| 2666 | dilationX, |
| 2667 | dilationY); |
| 2668 | } |
| 2669 | |
| 2670 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> |
| 2671 | LayerTestResult<T, 4> DepthwiseConvolution2d3x3DilationTestCommon( |
| 2672 | armnn::IWorkloadFactory& workloadFactory, |
| 2673 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2674 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2675 | const std::vector<float>& inputNoQuantizedValues, |
| 2676 | armnn::TensorInfo& inputTensorInfo, |
| 2677 | const std::vector<float>& kernelNoQuantizedValues, |
| 2678 | armnn::TensorInfo& kernelTensorInfo, |
| 2679 | const std::vector<float>& outputExpectedNoQuantizedValues, |
| 2680 | armnn::TensorInfo& outputTensorInfo, |
| 2681 | uint32_t dilationX, |
| 2682 | uint32_t dilationY, |
| 2683 | armnn::DataLayout layout = armnn::DataLayout::NCHW, |
| 2684 | bool biasEnabled = false) |
| 2685 | { |
| 2686 | float qScale; |
| 2687 | int32_t qOffset; |
| 2688 | switch (ArmnnType) |
| 2689 | { |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 2690 | case armnn::DataType::QAsymmS8: |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 2691 | case armnn::DataType::QAsymmU8: |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2692 | { |
| 2693 | qScale = 0.1f; |
| 2694 | qOffset = 128; |
| 2695 | break; |
| 2696 | } |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 2697 | case armnn::DataType::QSymmS16: |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2698 | { |
| 2699 | qScale = 0.1f; |
| 2700 | qOffset = 0; |
| 2701 | break; |
| 2702 | } |
| 2703 | case armnn::DataType::Float32: |
| 2704 | default: |
| 2705 | { |
| 2706 | qScale = 0.f; |
| 2707 | qOffset = 0; |
| 2708 | break; |
| 2709 | } |
| 2710 | } |
| 2711 | |
| 2712 | inputTensorInfo.SetQuantizationScale(qScale); |
| 2713 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 2714 | kernelTensorInfo.SetQuantizationScale(qScale); |
| 2715 | kernelTensorInfo.SetQuantizationOffset(qOffset); |
| 2716 | outputTensorInfo.SetQuantizationScale(qScale); |
| 2717 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 2718 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2719 | auto input = QuantizedVector<T>(inputNoQuantizedValues, |
| 2720 | inputTensorInfo.GetQuantizationScale(), |
| 2721 | inputTensorInfo.GetQuantizationOffset()); |
| 2722 | auto kernel = QuantizedVector<T>(kernelNoQuantizedValues, |
| 2723 | kernelTensorInfo.GetQuantizationScale(), |
| 2724 | kernelTensorInfo.GetQuantizationOffset()); |
| 2725 | auto expectedOutput = QuantizedVector<T>(outputExpectedNoQuantizedValues, |
| 2726 | outputTensorInfo.GetQuantizationScale(), |
| 2727 | outputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2728 | |
| 2729 | uint32_t padLeft = 0; |
| 2730 | uint32_t padTop = 0; |
| 2731 | uint32_t padRight = 0; |
| 2732 | uint32_t padBottom = 0; |
| 2733 | uint32_t strideX = 1; |
| 2734 | uint32_t strideY = 1; |
| 2735 | |
| 2736 | return DepthwiseConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 2737 | workloadFactory, |
| 2738 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2739 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2740 | input, |
| 2741 | kernel, |
| 2742 | GetBias<ArmnnBType>(biasEnabled, qScale * qScale, outputTensorInfo, layout), |
| 2743 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 2744 | inputTensorInfo.GetShape(), |
| 2745 | kernelTensorInfo.GetShape(), |
| 2746 | outputTensorInfo.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2747 | qScale, |
| 2748 | qOffset, |
| 2749 | layout, |
| 2750 | padLeft, |
| 2751 | padTop, |
| 2752 | padRight, |
| 2753 | padBottom, |
| 2754 | strideX, |
| 2755 | strideY, |
| 2756 | dilationX, |
| 2757 | dilationY); |
| 2758 | } |
| 2759 | |
| 2760 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T> |
| 2761 | LayerTestResult<T, 4> DepthwiseConvolution2d3x3Dilation3x3Test( |
| 2762 | armnn::IWorkloadFactory& workloadFactory, |
| 2763 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2764 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2765 | bool biasEnabled, |
| 2766 | const armnn::DataLayout layout) |
| 2767 | { |
| 2768 | armnn::TensorInfo inputTensorInfo({1, 1, 10, 10}, ArmnnType); |
| 2769 | std::vector<float> inputNoQuantizedValues = |
| 2770 | { |
| 2771 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2772 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2773 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2774 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2775 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2776 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2777 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2778 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2779 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2780 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| 2781 | }; |
| 2782 | |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2783 | armnn::TensorInfo kernelTensorInfo({ 1, 3, 3, 1}, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2784 | std::vector<float> kernelNoQuantizedValues = |
| 2785 | { |
| 2786 | 1, 2, 3, |
| 2787 | 4, 5, 6, |
| 2788 | 7, 8, 9 |
| 2789 | }; |
| 2790 | |
| 2791 | // Since the dilation rate is 3 this will dilate the kernel to be like 7x7, |
| 2792 | // therefore the output will be 4x4: (I−K+2P)/S +1 => (10-7 +0)/1 +1 |
| 2793 | armnn::TensorInfo outputTensorInfo({ 1, 1, 4, 4}, ArmnnType); |
| 2794 | std::vector<float> outputExpectedNoQuantizedValues = |
| 2795 | { |
| 2796 | 6., 5., 5., 5., |
| 2797 | 6., 5., 5., 5., |
| 2798 | 6., 5., 5., 5., |
| 2799 | 3., 2., 2., 2. |
| 2800 | }; |
| 2801 | |
| 2802 | return DepthwiseConvolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( |
| 2803 | workloadFactory, |
| 2804 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2805 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2806 | inputNoQuantizedValues, |
| 2807 | inputTensorInfo, |
| 2808 | kernelNoQuantizedValues, |
| 2809 | kernelTensorInfo, |
| 2810 | outputExpectedNoQuantizedValues, |
| 2811 | outputTensorInfo, |
| 2812 | 3, |
| 2813 | 3, |
| 2814 | layout, |
| 2815 | biasEnabled); |
| 2816 | } |
| 2817 | |
| 2818 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T> |
| 2819 | LayerTestResult<T, 4> DepthwiseConvolution2d2x3x3Dilation3x3Test( |
| 2820 | armnn::IWorkloadFactory& workloadFactory, |
| 2821 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2822 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2823 | bool biasEnabled, |
| 2824 | const armnn::DataLayout layout) |
| 2825 | { |
| 2826 | armnn::TensorInfo inputTensorInfo({1, 2, 10, 10}, ArmnnType); |
| 2827 | std::vector<float> inputNoQuantizedValues = |
| 2828 | { |
| 2829 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2830 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2831 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2832 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2833 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2834 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2835 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2836 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2837 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2838 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2839 | |
| 2840 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2841 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2842 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2843 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2844 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2845 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2846 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2847 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2848 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2849 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| 2850 | }; |
| 2851 | |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2852 | armnn::TensorInfo kernelTensorInfo({ 1, 3, 3, 2}, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2853 | std::vector<float> kernelNoQuantizedValues = |
| 2854 | { |
| 2855 | 1, 2, 3, |
| 2856 | 4, 5, 6, |
| 2857 | 7, 8, 9, |
| 2858 | |
| 2859 | 1, 2, 3, |
| 2860 | 4, 5, 6, |
| 2861 | 7, 8, 9 |
| 2862 | }; |
| 2863 | |
| 2864 | // Since the dilation rate is 3 this will dilate the kernel to be like 7x7, |
| 2865 | // therefore the output will be 2x4x4: (I−K+2P)/S +1 => (10-7 +0)/1 +1 |
| 2866 | armnn::TensorInfo outputTensorInfo({ 1, 2, 4, 4}, ArmnnType); |
| 2867 | std::vector<float> outputExpectedNoQuantizedValues = |
| 2868 | { |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2869 | 2, 9, 9, 9, 2, 9, 9, 9, 2, 9, 9, 9, 5, 3, 3, 3, 3, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2870 | |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2871 | 1, 1, 1, 3, 1, 1, 1, 3, 1, 1, 1, 6, 4, 4, 4 |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2872 | }; |
| 2873 | |
| 2874 | return DepthwiseConvolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( |
| 2875 | workloadFactory, |
| 2876 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2877 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2878 | inputNoQuantizedValues, |
| 2879 | inputTensorInfo, |
| 2880 | kernelNoQuantizedValues, |
| 2881 | kernelTensorInfo, |
| 2882 | outputExpectedNoQuantizedValues, |
| 2883 | outputTensorInfo, |
| 2884 | 3, |
| 2885 | 3, |
| 2886 | layout, |
| 2887 | biasEnabled); |
| 2888 | } |
| 2889 | |
| 2890 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T> |
| 2891 | LayerTestResult<T, 4> DepthwiseConvolution2dMult4Test( |
| 2892 | armnn::IWorkloadFactory& workloadFactory, |
| 2893 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2894 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2895 | bool biasEnabled, |
| 2896 | const armnn::DataLayout layout) |
| 2897 | { |
| 2898 | armnn::TensorInfo inputTensorInfo({1, 2, 3, 3}, ArmnnType); |
| 2899 | std::vector<float> inputNoQuantizedValues = |
| 2900 | { |
| 2901 | 10.0, 10.0, 10.0, |
| 2902 | 10.0, 10.0, 10.0, |
| 2903 | 10.0, 10.0, 10.0, |
| 2904 | |
| 2905 | 21.0, 22.0, 23.0, |
| 2906 | 24.0, 25.0, 26.0, |
| 2907 | 27.0, 28.0, 29.0 |
| 2908 | }; |
| 2909 | |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2910 | armnn::TensorInfo kernelTensorInfo({ 1, 2, 2, 8}, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2911 | |
| 2912 | std::vector<float> kernelNoQuantizedValues = |
| 2913 | { |
| 2914 | 0.25f, 0.25f, |
| 2915 | 0.25f, 0.25f, |
| 2916 | |
| 2917 | 0.25f, 0.25f, |
| 2918 | 0.25f, 0.25f, |
| 2919 | |
| 2920 | 0.0f , 0.0f, |
| 2921 | 0.0f , 0.1f, |
| 2922 | |
| 2923 | 0.0f , 0.0f, |
| 2924 | 0.0f , 0.1f, |
| 2925 | |
| 2926 | 0.2f , 0.0f, |
| 2927 | 0.0f , 0.0f, |
| 2928 | |
| 2929 | 0.2f , 0.0f, |
| 2930 | 0.0f , 0.0f, |
| 2931 | |
| 2932 | 0.0f , 0.3f, |
| 2933 | 0.0f , 0.0f, |
| 2934 | |
| 2935 | 0.0f , 0.3f, |
| 2936 | 0.0f , 0.0f |
| 2937 | }; |
| 2938 | |
| 2939 | armnn::TensorInfo outputTensorInfo({ 1, 8, 2, 2}, ArmnnType); |
| 2940 | std::vector<float> outputExpectedNoQuantizedValues = |
| 2941 | { |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2942 | 4.5f, 4.5f, 4.5f, 4.5f, 5.5f, 5.5f, 5.5f, 5.5f, |
| 2943 | 2.5f, 2.5f, 2.5f, 2.5f, 3.5f, 3.5f, 3.5f, 3.5f, |
| 2944 | 10.05f, 10.5f, 11.4f, 11.85f, 12.75f, 13.3f, 14.4f, 14.95f, |
| 2945 | 5.25f, 5.5f, 6.0f, 6.25f, 7.45f, 7.8f, 8.5f, 8.85f |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2946 | }; |
| 2947 | |
| 2948 | |
| 2949 | return DepthwiseConvolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( |
| 2950 | workloadFactory, |
| 2951 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2952 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2953 | inputNoQuantizedValues, |
| 2954 | inputTensorInfo, |
| 2955 | kernelNoQuantizedValues, |
| 2956 | kernelTensorInfo, |
| 2957 | outputExpectedNoQuantizedValues, |
| 2958 | outputTensorInfo, |
| 2959 | 1, |
| 2960 | 1, |
| 2961 | layout, |
| 2962 | biasEnabled); |
| 2963 | } |
| 2964 | |
| 2965 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T> |
| 2966 | LayerTestResult<T, 4> DepthwiseConvolution2dMult2Test( |
| 2967 | armnn::IWorkloadFactory& workloadFactory, |
| 2968 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2969 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2970 | bool biasEnabled, |
| 2971 | const armnn::DataLayout layout) |
| 2972 | { |
| 2973 | armnn::TensorInfo inputTensorInfo({1, 2, 3, 3}, ArmnnType); |
| 2974 | std::vector<float> inputNoQuantizedValues = |
| 2975 | { |
| 2976 | 10.0, 10.0, 10.0, |
| 2977 | 10.0, 10.0, 10.0, |
| 2978 | 10.0, 10.0, 10.0, |
| 2979 | |
| 2980 | 21.0, 22.0, 23.0, |
| 2981 | 24.0, 25.0, 26.0, |
| 2982 | 27.0, 28.0, 29.0 |
| 2983 | }; |
| 2984 | |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 2985 | armnn::TensorInfo kernelTensorInfo({ 1, 2, 2, 4}, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2986 | |
| 2987 | std::vector<float> kernelNoQuantizedValues = |
| 2988 | { |
| 2989 | 0.25f, 0.25f, |
| 2990 | 0.25f, 0.25f, |
| 2991 | |
| 2992 | 0.2f , 0.0f, |
| 2993 | 0.0f , 0.0f, |
| 2994 | |
| 2995 | 0.0f , 0.0f, |
| 2996 | 0.0f , 0.1f, |
| 2997 | |
| 2998 | 0.0f , 0.3f, |
| 2999 | 0.0f , 0.0f |
| 3000 | |
| 3001 | }; |
| 3002 | |
| 3003 | armnn::TensorInfo outputTensorInfo({ 1, 4, 2, 2}, ArmnnType); |
| 3004 | std::vector<float> outputExpectedNoQuantizedValues = |
| 3005 | { |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 3006 | 4.5f, 4.5f, 4.5f, 4.5f, |
| 3007 | 5.5f, 5.5f, 5.5f, 5.5f, |
| 3008 | 5.25f, 5.5f, 6.0f, 6.25f, |
| 3009 | 7.65f, 8.0f, 8.7f, 9.05f |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3010 | }; |
| 3011 | |
| 3012 | |
| 3013 | return DepthwiseConvolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( |
| 3014 | workloadFactory, |
| 3015 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3016 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3017 | inputNoQuantizedValues, |
| 3018 | inputTensorInfo, |
| 3019 | kernelNoQuantizedValues, |
| 3020 | kernelTensorInfo, |
| 3021 | outputExpectedNoQuantizedValues, |
| 3022 | outputTensorInfo, |
| 3023 | 1, |
| 3024 | 1, |
| 3025 | layout, |
| 3026 | biasEnabled); |
| 3027 | } |
| 3028 | |
| 3029 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 3030 | LayerTestResult<T, 4> CompareDepthwiseConvolution2dTestImpl( |
| 3031 | armnn::IWorkloadFactory& workloadFactory, |
| 3032 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3033 | armnn::IWorkloadFactory& refWorkloadFactory, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3034 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 3035 | const armnn::ITensorHandleFactory& refTensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3036 | const armnnUtils::DataLayoutIndexed& layout) |
| 3037 | { |
| 3038 | unsigned int inputHeight = 8; |
| 3039 | unsigned int inputWidth = 16; |
| 3040 | unsigned int inputChannels = 3; |
| 3041 | unsigned int inputNum = 5; |
| 3042 | |
| 3043 | unsigned int kernelHeight = 3; |
| 3044 | unsigned int kernelWidth = 3; |
| 3045 | unsigned int channelMultiplier = 1; |
| 3046 | |
| 3047 | unsigned int strideX = 2; |
| 3048 | unsigned int strideY = 3; |
| 3049 | unsigned int padX = 1; |
| 3050 | unsigned int padY = 1; |
| 3051 | |
| 3052 | unsigned int outputNum = inputNum; |
| 3053 | unsigned int outputChannels = inputChannels * channelMultiplier; |
| 3054 | unsigned int outputHeight = (inputHeight + 2 * padY - kernelHeight + strideY) / strideY; |
| 3055 | unsigned int outputWidth = (inputWidth + 2 * padX - kernelWidth + strideX) / strideX; |
| 3056 | |
| 3057 | armnn::TensorInfo inputTensorInfo; |
| 3058 | armnn::TensorInfo outputTensorInfo; |
| 3059 | armnn::TensorInfo kernelDesc; |
| 3060 | armnn::TensorInfo biasDesc; |
| 3061 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3062 | std::vector<unsigned int> inputShape; |
| 3063 | std::vector<unsigned int> outputShape; |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 3064 | std::vector<unsigned int> kernelShape{ 1, kernelHeight, kernelWidth, outputChannels }; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3065 | std::vector<unsigned int> biasShape{ outputChannels }; |
| 3066 | switch (layout.GetDataLayout()) |
| 3067 | { |
| 3068 | case armnn::DataLayout::NCHW: |
| 3069 | inputShape = { inputNum, inputChannels, inputHeight, inputWidth }; |
| 3070 | outputShape = { outputNum, outputChannels, outputHeight, outputWidth }; |
| 3071 | break; |
| 3072 | case armnn::DataLayout ::NHWC: |
| 3073 | inputShape = { inputNum, inputHeight, inputWidth, inputChannels }; |
| 3074 | outputShape = { outputNum, outputHeight, outputWidth, outputChannels }; |
| 3075 | break; |
| 3076 | default: |
| 3077 | throw armnn::InvalidArgumentException("unknown data layout [" |
| 3078 | + std::to_string(static_cast<int>(layout.GetDataLayout())) + "]"); |
| 3079 | } |
| 3080 | |
| 3081 | float inputsQScale = armnn::IsQuantizedType<T>() ? 1.0f : 0; |
| 3082 | float outputQScale = armnn::IsQuantizedType<T>() ? 2.0f : 0; |
| 3083 | int32_t qOffset = 0; |
| 3084 | |
| 3085 | inputTensorInfo = armnn::TensorInfo(4, inputShape.data(), ArmnnType, inputsQScale, qOffset); |
| 3086 | outputTensorInfo = armnn::TensorInfo(4, outputShape.data(), ArmnnType, outputQScale, qOffset); |
| 3087 | kernelDesc = armnn::TensorInfo(4, kernelShape.data(), ArmnnType, inputsQScale, qOffset); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 3088 | biasDesc = armnn::TensorInfo(1, biasShape.data(), armnn::GetBiasDataType(ArmnnType), inputsQScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3089 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 3090 | auto input = MakeRandomTensor<T>(inputTensorInfo, 124908, 0.0f, 255.0f); |
| 3091 | auto kernel = MakeRandomTensor<T>(kernelDesc, 891234, 0.0f, 255.0f); |
| 3092 | auto bias = MakeRandomTensor<typename FullyConnectedBiasTypeForInputType<T>::Type>(biasDesc, 1028, 0.0f, 255.0f); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3093 | |
Cathal Corbett | 4b19d22 | 2022-05-11 20:12:17 +0100 | [diff] [blame] | 3094 | armnn::TensorInfo aclKernelDescriptor = kernelDesc; |
| 3095 | std::vector<T> aclKernelData; |
| 3096 | aclKernelData.assign(kernel.data(), kernel.data() + kernelHeight * kernelWidth * outputChannels); |
| 3097 | if (workloadFactory.GetBackendId() == armnn::BackendId("GpuAcc") || |
| 3098 | workloadFactory.GetBackendId() == armnn::BackendId("CpuAcc")) |
| 3099 | { |
| 3100 | if (layout == armnn::DataLayout::NCHW) |
| 3101 | { |
| 3102 | std::vector<T> tmp(kernel.size()); |
| 3103 | aclKernelDescriptor.SetShape(armnnUtils::Permuted(kernelDesc.GetShape(), {0, 2, 3, 1})); |
| 3104 | armnnUtils::Permute(kernelDesc.GetShape(), {0, 2, 3, 1}, kernel.data(), tmp.data(), sizeof(T)); |
| 3105 | aclKernelData = tmp; |
| 3106 | } |
| 3107 | } |
| 3108 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 3109 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
| 3110 | std::vector<T> expectedOutput(outputTensorInfo.GetNumElements()); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3111 | |
| 3112 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
Cathal Corbett | 4b19d22 | 2022-05-11 20:12:17 +0100 | [diff] [blame] | 3113 | std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(aclKernelDescriptor); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 3114 | std::unique_ptr<armnn::ITensorHandle> biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3115 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 3116 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3117 | armnn::DepthwiseConvolution2dQueueDescriptor data; |
| 3118 | armnn::WorkloadInfo info; |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 3119 | |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 3120 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
Cathal Corbett | 4b19d22 | 2022-05-11 20:12:17 +0100 | [diff] [blame] | 3121 | AddInputToWorkload(data, info, aclKernelDescriptor, weightsHandle.get()); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 3122 | AddInputToWorkload(data, info, biasDesc, biasHandle.get()); |
| 3123 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 3124 | |
Cathal Corbett | 4b19d22 | 2022-05-11 20:12:17 +0100 | [diff] [blame] | 3125 | AllocateAndCopyDataToITensorHandle(weightsHandle.get(), aclKernelData.data()); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 3126 | AllocateAndCopyDataToITensorHandle(biasHandle.get(), bias.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3127 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3128 | data.m_Parameters.m_StrideX = strideX; |
| 3129 | data.m_Parameters.m_StrideY = strideY; |
| 3130 | data.m_Parameters.m_PadLeft = padX; |
| 3131 | data.m_Parameters.m_PadRight = padX; |
| 3132 | data.m_Parameters.m_PadTop = padY; |
| 3133 | data.m_Parameters.m_PadBottom = padY; |
| 3134 | data.m_Parameters.m_BiasEnabled = true; |
| 3135 | data.m_Parameters.m_DataLayout = layout.GetDataLayout(); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3136 | |
| 3137 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refTensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 3138 | std::unique_ptr<armnn::ITensorHandle> weightsHandleRef = refTensorHandleFactory.CreateTensorHandle(kernelDesc); |
| 3139 | std::unique_ptr<armnn::ITensorHandle> biasHandleRef = refTensorHandleFactory.CreateTensorHandle(biasDesc); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3140 | std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refTensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 3141 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3142 | armnn::DepthwiseConvolution2dQueueDescriptor refData = data; |
| 3143 | armnn::WorkloadInfo refInfo = info; |
| 3144 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get()); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 3145 | SetWorkloadInput(refData, refInfo, 1, kernelDesc, weightsHandleRef.get()); |
| 3146 | SetWorkloadInput(refData, refInfo, 2, biasDesc, biasHandleRef.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3147 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 3148 | |
Teresa Charlin | 611c7fb | 2022-01-07 09:47:29 +0000 | [diff] [blame] | 3149 | std::unique_ptr<armnn::IWorkload> workload |
| 3150 | = workloadFactory.CreateWorkload(armnn::LayerType::DepthwiseConvolution2d, data, info); |
| 3151 | std::unique_ptr<armnn::IWorkload> workloadRef |
| 3152 | = refWorkloadFactory.CreateWorkload(armnn::LayerType::DepthwiseConvolution2d, refData, refInfo); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3153 | |
| 3154 | outputHandleRef->Allocate(); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 3155 | weightsHandleRef->Allocate(); |
| 3156 | biasHandleRef->Allocate(); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3157 | inputHandleRef->Allocate(); |
| 3158 | |
| 3159 | inputHandle->Allocate(); |
| 3160 | outputHandle->Allocate(); |
| 3161 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 3162 | CopyDataToITensorHandle(inputHandle.get(), input.data()); |
| 3163 | CopyDataToITensorHandle(inputHandleRef.get(), input.data()); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 3164 | CopyDataToITensorHandle(weightsHandleRef.get(), kernel.data()); |
| 3165 | CopyDataToITensorHandle(biasHandleRef.get(), bias.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3166 | |
| 3167 | ExecuteWorkload(*workload, memoryManager); |
| 3168 | |
| 3169 | workloadRef->PostAllocationConfigure(); |
| 3170 | workloadRef->Execute(); |
| 3171 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 3172 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
| 3173 | CopyDataFromITensorHandle(expectedOutput.data(), outputHandleRef.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3174 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 3175 | return LayerTestResult<T, 4>(actualOutput, |
| 3176 | expectedOutput, |
| 3177 | outputHandle->GetShape(), |
| 3178 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3179 | } |
| 3180 | |
| 3181 | // |
| 3182 | // Explicit template specializations |
| 3183 | // |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3184 | template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> |
| 3185 | Convolution2d3x3Dilation3x3Test<armnn::DataType::BFloat16, armnn::DataType::BFloat16>( |
| 3186 | armnn::IWorkloadFactory&, |
| 3187 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3188 | const armnn::ITensorHandleFactory&, |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3189 | bool, |
| 3190 | armnn::DataLayout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3191 | |
| 3192 | template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> |
| 3193 | Convolution2d3x3Dilation3x3Test<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3194 | armnn::IWorkloadFactory&, |
| 3195 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3196 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3197 | bool, |
| 3198 | armnn::DataLayout); |
| 3199 | |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3200 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 4> |
| 3201 | Convolution2d3x3Dilation3x3Test<armnn::DataType::QAsymmS8, armnn::DataType::Signed32>( |
| 3202 | armnn::IWorkloadFactory&, |
| 3203 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3204 | const armnn::ITensorHandleFactory&, |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3205 | bool, |
| 3206 | armnn::DataLayout); |
| 3207 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3208 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 4> |
| 3209 | Convolution2d3x3Dilation3x3Test<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3210 | armnn::IWorkloadFactory&, |
| 3211 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3212 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3213 | bool, |
| 3214 | armnn::DataLayout); |
| 3215 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3216 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 4> |
| 3217 | Convolution2d3x3Dilation3x3Test<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3218 | armnn::IWorkloadFactory&, |
| 3219 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3220 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3221 | bool, |
| 3222 | armnn::DataLayout); |
| 3223 | |
| 3224 | template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> |
| 3225 | Convolution2d2x3x3Dilation3x3Test<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3226 | armnn::IWorkloadFactory&, |
| 3227 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3228 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3229 | bool, |
| 3230 | armnn::DataLayout); |
| 3231 | |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3232 | template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> |
| 3233 | Convolution2d2x3x3Dilation3x3Test<armnn::DataType::BFloat16, armnn::DataType::BFloat16>( |
| 3234 | armnn::IWorkloadFactory&, |
| 3235 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3236 | const armnn::ITensorHandleFactory&, |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3237 | bool, |
| 3238 | armnn::DataLayout); |
| 3239 | |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3240 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 4> |
| 3241 | Convolution2d2x3x3Dilation3x3Test<armnn::DataType::QAsymmS8, armnn::DataType::Signed32>( |
| 3242 | armnn::IWorkloadFactory&, |
| 3243 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3244 | const armnn::ITensorHandleFactory&, |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3245 | bool, |
| 3246 | armnn::DataLayout); |
| 3247 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3248 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 4> |
| 3249 | Convolution2d2x3x3Dilation3x3Test<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3250 | armnn::IWorkloadFactory&, |
| 3251 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3252 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3253 | bool, |
| 3254 | armnn::DataLayout); |
| 3255 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3256 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 4> |
| 3257 | Convolution2d2x3x3Dilation3x3Test<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3258 | armnn::IWorkloadFactory&, |
| 3259 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3260 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3261 | bool, |
| 3262 | armnn::DataLayout); |
| 3263 | |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3264 | template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> |
| 3265 | Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test<armnn::DataType::BFloat16, armnn::DataType::BFloat16>( |
| 3266 | armnn::IWorkloadFactory &workloadFactory, |
| 3267 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3268 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3269 | bool biasEnabled, |
| 3270 | const armnn::DataLayout layout); |
| 3271 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3272 | template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> |
| 3273 | Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3274 | armnn::IWorkloadFactory &workloadFactory, |
| 3275 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3276 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3277 | bool biasEnabled, |
| 3278 | const armnn::DataLayout layout); |
| 3279 | |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3280 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 4> |
| 3281 | Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test<armnn::DataType::QAsymmS8, armnn::DataType::Signed32>( |
| 3282 | armnn::IWorkloadFactory &workloadFactory, |
| 3283 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3284 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3285 | bool biasEnabled, |
| 3286 | const armnn::DataLayout layout); |
| 3287 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3288 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 4> |
| 3289 | Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3290 | armnn::IWorkloadFactory &workloadFactory, |
| 3291 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3292 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3293 | bool biasEnabled, |
| 3294 | const armnn::DataLayout layout); |
| 3295 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3296 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 4> |
| 3297 | Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3298 | armnn::IWorkloadFactory &workloadFactory, |
| 3299 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3300 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3301 | bool biasEnabled, |
| 3302 | const armnn::DataLayout layout); |
| 3303 | |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3304 | template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> |
| 3305 | DepthwiseConvolution2d3x3Dilation3x3Test<armnn::DataType::BFloat16, armnn::DataType::BFloat16>( |
| 3306 | armnn::IWorkloadFactory&, |
| 3307 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3308 | const armnn::ITensorHandleFactory&, |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3309 | bool, |
| 3310 | armnn::DataLayout); |
| 3311 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3312 | template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> |
| 3313 | DepthwiseConvolution2d3x3Dilation3x3Test<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3314 | armnn::IWorkloadFactory&, |
| 3315 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3316 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3317 | bool, |
| 3318 | armnn::DataLayout); |
| 3319 | |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3320 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 4> |
| 3321 | DepthwiseConvolution2d3x3Dilation3x3Test<armnn::DataType::QAsymmS8, armnn::DataType::Signed32>( |
| 3322 | armnn::IWorkloadFactory&, |
| 3323 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3324 | const armnn::ITensorHandleFactory&, |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3325 | bool, |
| 3326 | armnn::DataLayout); |
| 3327 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3328 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 4> |
| 3329 | DepthwiseConvolution2d3x3Dilation3x3Test<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3330 | armnn::IWorkloadFactory&, |
| 3331 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3332 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3333 | bool, |
| 3334 | armnn::DataLayout); |
| 3335 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3336 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 4> |
| 3337 | DepthwiseConvolution2d3x3Dilation3x3Test<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3338 | armnn::IWorkloadFactory&, |
| 3339 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3340 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3341 | bool, |
| 3342 | armnn::DataLayout); |
| 3343 | |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3344 | template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> |
| 3345 | DepthwiseConvolution2d2x3x3Dilation3x3Test<armnn::DataType::BFloat16, armnn::DataType::BFloat16>( |
| 3346 | armnn::IWorkloadFactory&, |
| 3347 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3348 | const armnn::ITensorHandleFactory&, |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3349 | bool, |
| 3350 | armnn::DataLayout); |
| 3351 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3352 | template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> |
| 3353 | DepthwiseConvolution2d2x3x3Dilation3x3Test<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3354 | armnn::IWorkloadFactory&, |
| 3355 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3356 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3357 | bool, |
| 3358 | armnn::DataLayout); |
| 3359 | |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3360 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 4> |
| 3361 | DepthwiseConvolution2d2x3x3Dilation3x3Test<armnn::DataType::QAsymmS8, armnn::DataType::Signed32>( |
| 3362 | armnn::IWorkloadFactory&, |
| 3363 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3364 | const armnn::ITensorHandleFactory&, |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3365 | bool, |
| 3366 | armnn::DataLayout); |
| 3367 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3368 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 4> |
| 3369 | DepthwiseConvolution2d2x3x3Dilation3x3Test<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3370 | armnn::IWorkloadFactory&, |
| 3371 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3372 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3373 | bool, |
| 3374 | armnn::DataLayout); |
| 3375 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3376 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 4> |
| 3377 | DepthwiseConvolution2d2x3x3Dilation3x3Test<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3378 | armnn::IWorkloadFactory&, |
| 3379 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3380 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3381 | bool, |
| 3382 | armnn::DataLayout); |
| 3383 | |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3384 | template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> |
| 3385 | DepthwiseConvolution2dMult4Test<armnn::DataType::BFloat16, armnn::DataType::BFloat16>( |
| 3386 | armnn::IWorkloadFactory &workloadFactory, |
| 3387 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3388 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3389 | bool biasEnabled, |
| 3390 | const armnn::DataLayout layout); |
| 3391 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3392 | template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> |
| 3393 | DepthwiseConvolution2dMult4Test<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3394 | armnn::IWorkloadFactory &workloadFactory, |
| 3395 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3396 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3397 | bool biasEnabled, |
| 3398 | const armnn::DataLayout layout); |
| 3399 | |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3400 | template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> |
| 3401 | DepthwiseConvolution2dMult2Test<armnn::DataType::BFloat16, armnn::DataType::BFloat16>( |
| 3402 | armnn::IWorkloadFactory &workloadFactory, |
| 3403 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3404 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3405 | bool biasEnabled, |
| 3406 | const armnn::DataLayout layout); |
| 3407 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3408 | template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> |
| 3409 | DepthwiseConvolution2dMult2Test<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3410 | armnn::IWorkloadFactory &workloadFactory, |
| 3411 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3412 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3413 | bool biasEnabled, |
| 3414 | const armnn::DataLayout layout); |
| 3415 | |
| 3416 | // |
| 3417 | // Implementation functions |
| 3418 | // |
| 3419 | |
| 3420 | LayerTestResult<float, 4> SimpleConvolution2d3x5Test( |
| 3421 | armnn::IWorkloadFactory& workloadFactory, |
| 3422 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3423 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3424 | bool biasEnabled, |
| 3425 | const armnn::DataLayout layout) |
| 3426 | { |
| 3427 | return SimpleConvolution2d3x5TestCommon<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3428 | workloadFactory, memoryManager, tensorHandleFactory, 0.f, 0, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3429 | } |
| 3430 | |
| 3431 | LayerTestResult<uint8_t, 4> SimpleConvolution2d3x5Uint8Test( |
| 3432 | armnn::IWorkloadFactory& workloadFactory, |
| 3433 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3434 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3435 | bool biasEnabled, |
| 3436 | const armnn::DataLayout layout) |
| 3437 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3438 | return SimpleConvolution2d3x5TestCommon<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3439 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3440 | } |
| 3441 | |
| 3442 | LayerTestResult<float, 4> SimpleConvolution2d3x3Test( |
| 3443 | armnn::IWorkloadFactory& workloadFactory, |
| 3444 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3445 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3446 | bool biasEnabled, |
| 3447 | const armnn::DataLayout layout) |
| 3448 | { |
| 3449 | return SimpleConvolution2d3x3TestCommon<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3450 | workloadFactory, memoryManager, tensorHandleFactory, 0.f, 0, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3451 | } |
| 3452 | |
| 3453 | LayerTestResult<float, 4> SimpleConvolution2d3x3NhwcTest( |
| 3454 | armnn::IWorkloadFactory& workloadFactory, |
| 3455 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3456 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3457 | bool biasEnabled) |
| 3458 | { |
| 3459 | return SimpleConvolution2d3x3NhwcTestCommon<armnn::DataType::Float32>( |
| 3460 | workloadFactory, |
| 3461 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3462 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3463 | 0.f, |
| 3464 | 0, |
| 3465 | biasEnabled, |
| 3466 | armnn::DataLayout::NHWC); |
| 3467 | } |
| 3468 | |
| 3469 | LayerTestResult<float, 4> SimpleConvolution2d3x3Stride2x2Test( |
| 3470 | armnn::IWorkloadFactory& workloadFactory, |
| 3471 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3472 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3473 | bool biasEnabled, |
| 3474 | const armnn::DataLayout layout) |
| 3475 | { |
| 3476 | return SimpleConvolution2d3x3Stride2x2TestCommon<armnn::DataType::Float32>( |
| 3477 | workloadFactory, |
| 3478 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3479 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3480 | 0.f, |
| 3481 | 0, |
| 3482 | biasEnabled, |
| 3483 | layout); |
| 3484 | } |
| 3485 | |
| 3486 | LayerTestResult<uint8_t, 4> SimpleConvolution2d3x3Uint8Test( |
| 3487 | armnn::IWorkloadFactory& workloadFactory, |
| 3488 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3489 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3490 | bool biasEnabled, |
| 3491 | const armnn::DataLayout layout) |
| 3492 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3493 | return SimpleConvolution2d3x3TestCommon<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3494 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3495 | } |
| 3496 | |
| 3497 | LayerTestResult<int16_t, 4> SimpleConvolution2d3x5QSymm16Test( |
| 3498 | armnn::IWorkloadFactory& workloadFactory, |
| 3499 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3500 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3501 | bool biasEnabled, |
| 3502 | const armnn::DataLayout layout) |
| 3503 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3504 | return SimpleConvolution2d3x5TestCommon<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3505 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3506 | } |
| 3507 | |
| 3508 | LayerTestResult<int16_t, 4> SimpleConvolution2d3x3QSymm16Test( |
| 3509 | armnn::IWorkloadFactory& workloadFactory, |
| 3510 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3511 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3512 | bool biasEnabled, |
| 3513 | const armnn::DataLayout layout) |
| 3514 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3515 | return SimpleConvolution2d3x3TestCommon<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3516 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3517 | } |
| 3518 | |
| 3519 | LayerTestResult<float, 4> Convolution2dAsymmetricPaddingTest( |
| 3520 | armnn::IWorkloadFactory& workloadFactory, |
| 3521 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3522 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3523 | armnn::DataLayout layout) |
| 3524 | { |
| 3525 | return SimpleConvolution2dAsymmetricPaddingTestCommon<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3526 | workloadFactory, memoryManager, tensorHandleFactory, layout, 0.0f, 0); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3527 | } |
| 3528 | |
| 3529 | LayerTestResult<float, 4> Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTest( |
| 3530 | armnn::IWorkloadFactory& workloadFactory, |
| 3531 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3532 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3533 | armnn::DataLayout layout) |
| 3534 | { |
| 3535 | return Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon |
| 3536 | <armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3537 | workloadFactory, memoryManager, tensorHandleFactory, layout, 0.0f, 0); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3538 | } |
| 3539 | |
| 3540 | LayerTestResult<float, 4> Convolution1dTest( |
| 3541 | armnn::IWorkloadFactory& workloadFactory, |
| 3542 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3543 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3544 | bool biasEnabled) |
| 3545 | { |
| 3546 | return Convolution1dTestImpl<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3547 | workloadFactory, memoryManager, tensorHandleFactory, 0.0f, 0, biasEnabled); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3548 | } |
| 3549 | |
| 3550 | LayerTestResult<uint8_t, 4> Convolution1dUint8Test( |
| 3551 | armnn::IWorkloadFactory& workloadFactory, |
| 3552 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3553 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3554 | bool biasEnabled) |
| 3555 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3556 | return Convolution1dTestImpl<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3557 | workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 128, biasEnabled); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3558 | } |
| 3559 | |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3560 | LayerTestResult<uint8_t, 4> Convolution2dPerAxisQuantTest( |
| 3561 | armnn::IWorkloadFactory& workloadFactory, |
| 3562 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3563 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3564 | const armnn::DataLayout layout) |
| 3565 | { |
| 3566 | using namespace armnn; |
| 3567 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3568 | const DataType inputType = DataType::QAsymmU8; |
Derek Lamberti | d466a54 | 2020-01-22 15:37:29 +0000 | [diff] [blame] | 3569 | const DataType kernelType = DataType::QSymmS8; |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3570 | const DataType biasType = DataType::Signed32; |
| 3571 | |
| 3572 | TensorInfo inputInfo ({ 1, 3, 1, 2 }, inputType, 0.5f, 128); |
| 3573 | TensorInfo outputInfo({ 1, 3, 1, 3 }, inputType, 1.0f, 128); |
| 3574 | |
| 3575 | const std::vector<float> quantScales{ 0.5f, 0.75f, 1.0f }; |
| 3576 | constexpr unsigned int quantDimension = 0; |
| 3577 | |
| 3578 | TensorInfo kernelInfo({ 3, 1, 1, 2 }, kernelType, quantScales, quantDimension); |
| 3579 | |
| 3580 | const std::vector<float> biasQuantScales{ 0.25f, 0.375f, 0.5f }; |
| 3581 | TensorInfo biasInfo({ 3 }, biasType, biasQuantScales, quantDimension); |
| 3582 | |
| 3583 | std::vector<uint8_t> inputData = |
| 3584 | { |
| 3585 | 138, 108, 138, 108, 138, 108 |
| 3586 | }; |
| 3587 | |
| 3588 | std::vector<int8_t> kernelData = |
| 3589 | { |
| 3590 | 1, 2, 1, 2, 1, 2 |
| 3591 | }; |
| 3592 | |
| 3593 | std::vector<int32_t> biasData = |
| 3594 | { |
| 3595 | 4, 4, 4 |
| 3596 | }; |
| 3597 | |
| 3598 | std::vector<uint8_t> expectedOutputData = |
| 3599 | { |
| 3600 | 121, 118, 115, 121, 118, 115, 121, 118, 115 |
| 3601 | }; |
| 3602 | |
| 3603 | if (layout == DataLayout::NCHW) |
| 3604 | { |
| 3605 | PermuteTensorNhwcToNchw(inputInfo, inputData); |
| 3606 | PermuteTensorNhwcToNchw(kernelInfo, kernelData); |
| 3607 | PermuteTensorNhwcToNchw(outputInfo, expectedOutputData); |
| 3608 | } |
| 3609 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 3610 | std::vector<uint8_t> actualOutput(outputInfo.GetNumElements()); |
| 3611 | |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3612 | Convolution2dDescriptor descriptor; |
| 3613 | descriptor.m_StrideX = 1; |
| 3614 | descriptor.m_StrideY = 1; |
| 3615 | descriptor.m_PadLeft = 0; |
| 3616 | descriptor.m_PadRight = 0; |
| 3617 | descriptor.m_PadTop = 0; |
| 3618 | descriptor.m_PadBottom = 0; |
| 3619 | descriptor.m_BiasEnabled = true; |
| 3620 | descriptor.m_DataLayout = layout; |
| 3621 | |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3622 | std::unique_ptr<ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputInfo); |
| 3623 | std::unique_ptr<ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputInfo); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 3624 | std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelInfo); |
| 3625 | std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr; |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3626 | |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3627 | WorkloadInfo workloadInfo; |
Mike Kelly | ec67a0f | 2022-11-25 13:55:24 +0000 | [diff] [blame] | 3628 | // ScopedTensorHandle weightTensor(kernelInfo); |
| 3629 | // ScopedTensorHandle biasTensor(biasInfo); |
| 3630 | // |
| 3631 | // AllocateAndCopyDataToITensorHandle(&weightTensor, kernelData.data()); |
| 3632 | // AllocateAndCopyDataToITensorHandle(&biasTensor, biasData.data()); |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3633 | |
| 3634 | Convolution2dQueueDescriptor queueDescriptor; |
| 3635 | queueDescriptor.m_Parameters = descriptor; |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3636 | |
| 3637 | AddInputToWorkload(queueDescriptor, workloadInfo, inputInfo, inputHandle.get()); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 3638 | AddInputToWorkload(queueDescriptor, workloadInfo, kernelInfo, weightsHandle.get()); |
| 3639 | |
| 3640 | if (descriptor.m_BiasEnabled) |
| 3641 | { |
| 3642 | biasHandle = tensorHandleFactory.CreateTensorHandle(biasInfo); |
| 3643 | AddInputToWorkload(queueDescriptor, workloadInfo, biasInfo, biasHandle.get()); |
| 3644 | } |
| 3645 | |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3646 | AddOutputToWorkload(queueDescriptor, workloadInfo, outputInfo, outputHandle.get()); |
| 3647 | |
Teresa Charlin | 611c7fb | 2022-01-07 09:47:29 +0000 | [diff] [blame] | 3648 | std::unique_ptr<IWorkload> workload= workloadFactory.CreateWorkload(armnn::LayerType::Convolution2d, |
| 3649 | queueDescriptor, |
| 3650 | workloadInfo); |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3651 | inputHandle->Allocate(); |
| 3652 | outputHandle->Allocate(); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 3653 | weightsHandle->Allocate(); |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3654 | |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 3655 | if (descriptor.m_BiasEnabled) |
| 3656 | { |
| 3657 | biasHandle->Allocate(); |
| 3658 | CopyDataToITensorHandle(biasHandle.get(), biasData.data()); |
| 3659 | } |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3660 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 3661 | CopyDataToITensorHandle(weightsHandle.get(), kernelData.data()); |
| 3662 | |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3663 | |
| 3664 | ExecuteWorkload(*workload, memoryManager); |
| 3665 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 3666 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3667 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 3668 | return LayerTestResult<uint8_t, 4>(actualOutput, |
| 3669 | expectedOutputData, |
| 3670 | outputHandle->GetShape(), |
| 3671 | outputInfo.GetShape()); |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3672 | } |
| 3673 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3674 | LayerTestResult<float,4> CompareConvolution2dTest( |
| 3675 | armnn::IWorkloadFactory& workloadFactory, |
| 3676 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3677 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 3678 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 3679 | const armnn::ITensorHandleFactory& refTensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3680 | { |
| 3681 | return CompareConvolution2dTestImpl<armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3682 | workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3683 | } |
| 3684 | |
| 3685 | LayerTestResult<float, 4> DepthwiseConvolution2dTest( |
| 3686 | armnn::IWorkloadFactory& workloadFactory, |
| 3687 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3688 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3689 | bool biasEnabled, |
| 3690 | const armnn::DataLayout layout) |
| 3691 | { |
| 3692 | return DepthwiseConvolution2dTestImpl<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3693 | workloadFactory, memoryManager, tensorHandleFactory, 0.0f, 0, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3694 | } |
| 3695 | |
| 3696 | LayerTestResult<float, 4> DepthwiseConvolution2dDepthNhwcTest( |
| 3697 | armnn::IWorkloadFactory& workloadFactory, |
| 3698 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3699 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3700 | bool biasEnabled) |
| 3701 | { |
| 3702 | return DepthwiseConvolution2dNhwcTestCommon<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3703 | workloadFactory, memoryManager, tensorHandleFactory, 0.0f, 0, biasEnabled); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3704 | } |
| 3705 | |
| 3706 | LayerTestResult<float, 4> DepthwiseConvolution2dDepthMul1Test( |
| 3707 | armnn::IWorkloadFactory& workloadFactory, |
| 3708 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3709 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3710 | bool biasEnabled, |
| 3711 | const armnn::DataLayout layout) |
| 3712 | { |
| 3713 | return DepthwiseConvolution2dDepthMul1TestImpl<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3714 | workloadFactory, memoryManager, tensorHandleFactory, 0.0f, 0, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3715 | } |
| 3716 | |
| 3717 | LayerTestResult<float, 4> DepthwiseConvolution2dDepthMul64Test( |
| 3718 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3719 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3720 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3721 | { |
| 3722 | armnn::TensorInfo inputTensorInfo({ 1, 1, 2, 2 }, armnn::DataType::Float32); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 3723 | std::vector<float> input = { 1.f, 2.f, 3.f, 4.f }; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3724 | |
| 3725 | std::vector<float> kernelData; |
| 3726 | std::vector<float> singleDepthKernel{ 1.f, -1.f, -1.f, 1.f }; |
| 3727 | for (unsigned int i = 0; i < 64; ++i) |
| 3728 | { |
| 3729 | kernelData.insert(kernelData.end(), singleDepthKernel.begin(), singleDepthKernel.end()); |
| 3730 | } |
| 3731 | armnn::TensorInfo kernelTensorInfo({ 64, 1, 2, 2 }, armnn::DataType::Float32); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3732 | |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 3733 | // permute from [O,1,H,W] --> [1,H,W,O] |
| 3734 | armnn::PermutationVector permutationVector {3,0,1,2}; |
| 3735 | kernelTensorInfo = armnnUtils::Permuted(kernelTensorInfo, permutationVector); |
| 3736 | std::vector<float> kernelPermuted(kernelTensorInfo.GetNumElements()); |
| 3737 | armnnUtils::Permute(kernelTensorInfo.GetShape(), permutationVector, |
| 3738 | kernelData.data(), kernelPermuted.data(), |
| 3739 | GetDataTypeSize(kernelTensorInfo.GetDataType())); |
| 3740 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3741 | std::vector<float> expectedOutputData(64, 0.f); |
| 3742 | armnn::TensorInfo outputTensorInfo({ 1, 64, 1, 1 }, armnn::DataType::Float32); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3743 | |
| 3744 | return DepthwiseConvolution2dTestImpl<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3745 | workloadFactory, |
| 3746 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3747 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3748 | input, |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 3749 | kernelPermuted, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 3750 | std::vector<float>(), |
| 3751 | expectedOutputData, |
| 3752 | inputTensorInfo.GetShape(), |
| 3753 | kernelTensorInfo.GetShape(), |
| 3754 | outputTensorInfo.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3755 | 0.f, |
| 3756 | 0, |
| 3757 | armnn::DataLayout::NCHW); |
| 3758 | } |
| 3759 | |
| 3760 | LayerTestResult<float, 4> DepthwiseConvolution2dAsymmetricTest( |
| 3761 | armnn::IWorkloadFactory& workloadFactory, |
| 3762 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3763 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3764 | bool biasEnabled, |
| 3765 | const armnn::DataLayout layout) |
| 3766 | { |
| 3767 | return DepthwiseConvolution2dAsymmetricTestCommon<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3768 | workloadFactory, memoryManager, tensorHandleFactory, 0.0f, 0, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3769 | } |
| 3770 | |
| 3771 | LayerTestResult<uint8_t, 4> DepthwiseConvolution2dUint8Test( |
| 3772 | armnn::IWorkloadFactory& workloadFactory, |
| 3773 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3774 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3775 | bool biasEnabled, |
| 3776 | const armnn::DataLayout layout) |
| 3777 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3778 | return DepthwiseConvolution2dTestImpl<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3779 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3780 | } |
| 3781 | |
| 3782 | LayerTestResult<uint8_t, 4> DepthwiseConvolution2dDepthMul1Uint8Test( |
| 3783 | armnn::IWorkloadFactory& workloadFactory, |
| 3784 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3785 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3786 | bool biasEnabled, |
| 3787 | const armnn::DataLayout layout) |
| 3788 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3789 | return DepthwiseConvolution2dDepthMul1TestImpl<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3790 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3791 | } |
| 3792 | |
| 3793 | LayerTestResult<float, 4> SimpleDepthwiseConvolution2d3x3Dilation3x3NhwcTest( |
| 3794 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3795 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3796 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3797 | { |
| 3798 | return SimpleDepthwiseConvolution2d3x3Dilation3x3NhwcTestCommon<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3799 | workloadFactory, |
| 3800 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3801 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3802 | 0.f, |
| 3803 | 0, |
| 3804 | false); |
| 3805 | } |
| 3806 | |
| 3807 | LayerTestResult<int16_t, 4> DepthwiseConvolution2dInt16Test( |
| 3808 | armnn::IWorkloadFactory& workloadFactory, |
| 3809 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3810 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3811 | bool biasEnabled, |
| 3812 | const armnn::DataLayout layout) |
| 3813 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3814 | return DepthwiseConvolution2dTestImpl<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3815 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3816 | } |
| 3817 | |
| 3818 | LayerTestResult<int16_t, 4> DepthwiseConvolution2dDepthMul1Int16Test( |
| 3819 | armnn::IWorkloadFactory& workloadFactory, |
| 3820 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3821 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3822 | bool biasEnabled, |
| 3823 | const armnn::DataLayout layout) |
| 3824 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3825 | return DepthwiseConvolution2dDepthMul1TestImpl<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3826 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3827 | } |
| 3828 | |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3829 | LayerTestResult<uint8_t, 4> DepthwiseConvolution2dPerAxisQuantTest( |
| 3830 | armnn::IWorkloadFactory& workloadFactory, |
| 3831 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3832 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3833 | const armnn::DataLayout layout) |
| 3834 | { |
| 3835 | using namespace armnn; |
| 3836 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3837 | const DataType inputType = DataType::QAsymmU8; |
Derek Lamberti | d466a54 | 2020-01-22 15:37:29 +0000 | [diff] [blame] | 3838 | const DataType kernelType = DataType::QSymmS8; |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3839 | const DataType biasType = DataType::Signed32; |
| 3840 | |
| 3841 | TensorInfo inputInfo ({ 1, 3, 3, 2 }, inputType, 0.5f, 128); // N H W C |
| 3842 | TensorInfo outputInfo({ 1, 2, 2, 4 }, inputType, 1.0f, 128); // N H W C |
| 3843 | |
| 3844 | const std::vector<float> quantScales{ 1.0f, 0.5f, 1.0f, 0.5f }; |
Jan Eilers | 53ef795 | 2021-06-02 12:01:25 +0100 | [diff] [blame] | 3845 | const unsigned int quantDimension = 3; |
| 3846 | TensorInfo kernelInfo({ 1, 2, 2, 4 }, kernelType, quantScales, quantDimension); // [1, H, W, I*M] |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3847 | |
| 3848 | const std::vector<float> biasQuantScales{ 0.5f, 0.25f, 0.5f, 0.25f }; |
| 3849 | constexpr unsigned int biasQuantDimension = 0; |
| 3850 | TensorInfo biasInfo({ 4 }, biasType, biasQuantScales, biasQuantDimension); |
| 3851 | |
| 3852 | std::vector<uint8_t> inputData = |
| 3853 | { |
| 3854 | 129, 130, |
| 3855 | 129, 130, |
| 3856 | 129, 130, |
| 3857 | 129, 130, |
| 3858 | 129, 130, |
| 3859 | 129, 130, |
| 3860 | 129, 130, |
| 3861 | 129, 130, |
| 3862 | 129, 130 |
| 3863 | }; |
| 3864 | |
| 3865 | std::vector<int8_t> kernelData = |
| 3866 | { |
| 3867 | 1, 1, 1, 1, |
| 3868 | 1, 1, 1, 1, |
| 3869 | 1, 1, 1, 1, |
| 3870 | 1, 1, 1, 1 |
| 3871 | }; |
| 3872 | |
Cathal Corbett | 4b19d22 | 2022-05-11 20:12:17 +0100 | [diff] [blame] | 3873 | if (workloadFactory.GetBackendId() == armnn::BackendId("GpuAcc") || |
| 3874 | workloadFactory.GetBackendId() == armnn::BackendId("CpuAcc")) |
| 3875 | { |
| 3876 | if (layout == armnn::DataLayout::NCHW) |
| 3877 | { |
| 3878 | std::vector<int8_t> tmp(kernelData.size()); |
| 3879 | kernelInfo.SetShape(armnnUtils::Permuted(kernelInfo.GetShape(), {0, 2, 3, 1})); |
| 3880 | armnnUtils::Permute(kernelInfo.GetShape(), {0, 2, 3, 1}, kernelData.data(), tmp.data(), sizeof(int8_t)); |
| 3881 | kernelData = tmp; |
| 3882 | } |
| 3883 | } |
| 3884 | |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3885 | std::vector<int32_t> biasData = |
| 3886 | { |
| 3887 | 4, 4, 4, 4 |
| 3888 | }; |
| 3889 | |
| 3890 | std::vector<uint8_t> expectedOutputData = |
| 3891 | { |
| 3892 | 132, 130, 134, 131, |
| 3893 | 132, 130, 134, 131, |
| 3894 | 132, 130, 134, 131, |
| 3895 | 132, 130, 134, 131 |
| 3896 | }; |
| 3897 | |
| 3898 | if (layout == DataLayout::NCHW) |
| 3899 | { |
| 3900 | PermuteTensorNhwcToNchw(inputInfo, inputData); |
| 3901 | PermuteTensorNhwcToNchw(outputInfo, expectedOutputData); |
| 3902 | } |
| 3903 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 3904 | std::vector<uint8_t> actualOutput(outputInfo.GetNumElements()); |
| 3905 | |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3906 | DepthwiseConvolution2dDescriptor descriptor; |
| 3907 | descriptor.m_StrideX = 1; |
| 3908 | descriptor.m_StrideY = 1; |
| 3909 | descriptor.m_PadLeft = 0; |
| 3910 | descriptor.m_PadRight = 0; |
| 3911 | descriptor.m_PadTop = 0; |
| 3912 | descriptor.m_PadBottom = 0; |
| 3913 | descriptor.m_DilationX = 1; |
| 3914 | descriptor.m_DilationY = 1; |
| 3915 | descriptor.m_BiasEnabled = true; |
| 3916 | descriptor.m_DataLayout = layout; |
| 3917 | |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3918 | std::unique_ptr<ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputInfo); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 3919 | std::unique_ptr<ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelInfo); |
| 3920 | std::unique_ptr<ITensorHandle> biasHandle = tensorHandleFactory.CreateTensorHandle(biasInfo); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3921 | std::unique_ptr<ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputInfo); |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3922 | |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 3923 | DepthwiseConvolution2dQueueDescriptor queueDescriptor; |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3924 | WorkloadInfo workloadInfo; |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3925 | |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 3926 | AddInputToWorkload(queueDescriptor, workloadInfo, inputInfo, inputHandle.get()); |
| 3927 | AddInputToWorkload(queueDescriptor, workloadInfo, kernelInfo, weightsHandle.get()); |
| 3928 | AddOutputToWorkload(queueDescriptor, workloadInfo, outputInfo, outputHandle.get()); |
| 3929 | AddInputToWorkload(queueDescriptor, workloadInfo, biasInfo, biasHandle.get()); |
| 3930 | |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 3931 | AllocateAndCopyDataToITensorHandle(weightsHandle.get(), kernelData.data()); |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 3932 | AllocateAndCopyDataToITensorHandle(biasHandle.get(), biasData.data()); |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3933 | |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3934 | queueDescriptor.m_Parameters = descriptor; |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3935 | |
Teresa Charlin | 611c7fb | 2022-01-07 09:47:29 +0000 | [diff] [blame] | 3936 | std::unique_ptr<IWorkload> workload = workloadFactory.CreateWorkload(armnn::LayerType::DepthwiseConvolution2d, |
| 3937 | queueDescriptor, |
| 3938 | workloadInfo); |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3939 | inputHandle->Allocate(); |
| 3940 | outputHandle->Allocate(); |
| 3941 | |
| 3942 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
| 3943 | |
| 3944 | ExecuteWorkload(*workload, memoryManager); |
| 3945 | |
| 3946 | LayerTestResult<uint8_t, 4> ret(outputInfo); |
| 3947 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 3948 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3949 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame] | 3950 | return LayerTestResult<uint8_t, 4>(actualOutput, |
| 3951 | expectedOutputData, |
| 3952 | outputHandle->GetShape(), |
| 3953 | outputInfo.GetShape()); |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3954 | } |
| 3955 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3956 | LayerTestResult<float, 4> CompareDepthwiseConvolution2dFloatTest( |
| 3957 | armnn::IWorkloadFactory& workloadFactory, |
| 3958 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3959 | armnn::IWorkloadFactory& refWorkloadFactory, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3960 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 3961 | const armnn::ITensorHandleFactory& refTensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3962 | const armnn::DataLayout layout) |
| 3963 | { |
| 3964 | return CompareDepthwiseConvolution2dTestImpl<armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3965 | workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3966 | } |
| 3967 | |
| 3968 | LayerTestResult<uint8_t, 4> CompareDepthwiseConvolution2dUint8Test( |
| 3969 | armnn::IWorkloadFactory& workloadFactory, |
| 3970 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3971 | armnn::IWorkloadFactory& refWorkloadFactory, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3972 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 3973 | const armnn::ITensorHandleFactory& refTensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3974 | const armnn::DataLayout layout) |
| 3975 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3976 | return CompareDepthwiseConvolution2dTestImpl<armnn::DataType::QAsymmU8>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3977 | workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3978 | } |