Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1 | // |
Teresa Charlin | fbf0e5b | 2020-08-17 01:01:06 +0100 | [diff] [blame] | 2 | // Copyright © 2017 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 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 8 | #include <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 | |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 16 | #include <backendsCommon/TensorHandle.hpp> |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 17 | |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 18 | #include <backendsCommon/test/DataLayoutUtils.hpp> |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 19 | #include <backendsCommon/test/TensorCopyUtils.hpp> |
| 20 | #include <backendsCommon/test/WorkloadTestUtils.hpp> |
| 21 | |
| 22 | #include <test/TensorHelpers.hpp> |
| 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); |
| 312 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 313 | armnn::Convolution2dQueueDescriptor data; |
| 314 | armnn::WorkloadInfo info; |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 315 | armnn::ScopedTensorHandle weightsTensor(kernelDesc); |
| 316 | armnn::ScopedTensorHandle biasTensor(biasDesc); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 317 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 318 | // Permute the kernel if necessary |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 319 | std::vector<T> kernel = originalKernel; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 320 | if (layout == armnn::DataLayout::NHWC) |
| 321 | { |
| 322 | armnnUtils::Permute(kernelDesc.GetShape(), NCHWToNHWC, originalKernel.data(), kernel.data(), sizeof(T)); |
| 323 | } |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 324 | AllocateAndCopyDataToITensorHandle(&weightsTensor, kernel.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 325 | |
| 326 | if(biasEnabled) |
| 327 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 328 | AllocateAndCopyDataToITensorHandle(&biasTensor, bias.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 329 | } |
| 330 | |
| 331 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 332 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 333 | |
| 334 | data.m_Weight = &weightsTensor; |
| 335 | data.m_Bias = &biasTensor; // Still set this whether or not bias is enabled - can be a source of bugs. |
| 336 | data.m_Parameters.m_StrideX = strideX; |
| 337 | data.m_Parameters.m_StrideY = strideY; |
| 338 | data.m_Parameters.m_PadLeft = padLeft; |
| 339 | data.m_Parameters.m_PadRight = padRight; |
| 340 | data.m_Parameters.m_PadTop = padTop; |
| 341 | data.m_Parameters.m_PadBottom = padBottom; |
| 342 | data.m_Parameters.m_BiasEnabled = biasEnabled; |
| 343 | data.m_Parameters.m_DataLayout = layout; |
| 344 | data.m_Parameters.m_DilationX = dilationX; |
| 345 | data.m_Parameters.m_DilationY = dilationY; |
| 346 | |
| 347 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConvolution2d(data, info); |
| 348 | inputHandle->Allocate(); |
| 349 | outputHandle->Allocate(); |
| 350 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 351 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 352 | |
| 353 | ExecuteWorkload(*workload, memoryManager); |
| 354 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 355 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 356 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 357 | return LayerTestResult<T, 4>(actualOutput, |
| 358 | expectedOutput, |
| 359 | outputHandle->GetShape(), |
| 360 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 361 | } |
| 362 | |
| 363 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 364 | typename T = armnn::ResolveType<ArmnnType>, typename B = armnn::ResolveType<ArmnnBType>, |
| 365 | armnn::DataType OutType = ArmnnType, typename O = armnn::ResolveType<OutType>> |
| 366 | LayerTestResult<O, 4> SimpleConvolution2dNhwcTestImpl( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 367 | armnn::IWorkloadFactory& workloadFactory, |
| 368 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 369 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 370 | const std::vector<T>& input, |
| 371 | const std::vector<T>& kernel, |
| 372 | const std::vector<B>& bias, |
| 373 | const std::vector<O>& outputExpected, |
| 374 | const armnn::TensorShape& inputShape, |
| 375 | const armnn::TensorShape& kernelShape, |
| 376 | const armnn::TensorShape& outputExpectedShape, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 377 | const armnn::DataLayout dataLayout, |
| 378 | float qScale, |
| 379 | int32_t qOffset, |
| 380 | uint32_t padLeft = 1, |
| 381 | uint32_t padTop = 1, |
| 382 | uint32_t padRight = 1, |
| 383 | uint32_t padBottom = 1, |
| 384 | uint32_t strideX = 1, |
| 385 | uint32_t strideY = 1) |
| 386 | { |
Jan Eilers | 8eb2560 | 2020-03-09 12:13:48 +0000 | [diff] [blame] | 387 | armnn::IgnoreUnused(qScale, qOffset); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 388 | unsigned int inputNum = armnn::numeric_cast<unsigned int>(inputShape[0]); |
| 389 | unsigned int inputChannels = armnn::numeric_cast<unsigned int>(inputShape[3]); |
| 390 | unsigned int inputHeight = armnn::numeric_cast<unsigned int>(inputShape[1]); |
| 391 | unsigned int inputWidth = armnn::numeric_cast<unsigned int>(inputShape[2]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 392 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 393 | unsigned int kernelChanMul = armnn::numeric_cast<unsigned int>(kernelShape[0]); |
| 394 | unsigned int kernelChannels = armnn::numeric_cast<unsigned int>(kernelShape[3]); |
| 395 | unsigned int kernelHeight = armnn::numeric_cast<unsigned int>(kernelShape[1]); |
| 396 | unsigned int kernelWidth = armnn::numeric_cast<unsigned int>(kernelShape[2]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 397 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 398 | unsigned int outputNum = armnn::numeric_cast<unsigned int>(outputExpectedShape[0]); |
| 399 | unsigned int outputChannels = armnn::numeric_cast<unsigned int>(outputExpectedShape[3]); |
| 400 | unsigned int outputHeight = armnn::numeric_cast<unsigned int>(outputExpectedShape[1]); |
| 401 | unsigned int outputWidth = armnn::numeric_cast<unsigned int>(outputExpectedShape[2]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 402 | |
| 403 | bool biasEnabled = bias.size() > 0; |
| 404 | |
| 405 | // Creates the tensors. |
| 406 | armnn::TensorInfo inputTensorInfo({inputNum, inputHeight, inputWidth, inputChannels}, ArmnnType); |
| 407 | armnn::TensorInfo outputTensorInfo({outputNum, outputHeight, outputWidth, outputChannels}, |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 408 | OutType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 409 | armnn::TensorInfo kernelDesc({kernelChanMul, kernelHeight, kernelWidth, kernelChannels}, ArmnnType); |
| 410 | armnn::TensorInfo biasDesc({static_cast<unsigned int>(bias.size())}, ArmnnBType); |
| 411 | |
| 412 | // Construct the input data. |
| 413 | std::vector<T> inputData; |
| 414 | inputData.assign(input.data(), input.data() + inputHeight*inputWidth*inputChannels); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 415 | |
| 416 | // Construct the output data, with bias applied, as appropriate. |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 417 | std::vector<O> outputData; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 418 | outputData.assign(outputExpected.data(), outputExpected.data() + outputHeight*outputWidth*outputChannels); |
| 419 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 420 | std::vector<O> actualOutput(outputTensorInfo.GetNumElements()); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 421 | |
| 422 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 423 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 424 | |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 425 | armnn::ScopedTensorHandle weightsTensor(kernelDesc); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 426 | AllocateAndCopyDataToITensorHandle(&weightsTensor, kernel.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 427 | |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 428 | armnn::ScopedTensorHandle biasTensor(biasDesc); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 429 | |
| 430 | armnn::Convolution2dQueueDescriptor data; |
| 431 | |
| 432 | data.m_Weight = &weightsTensor; |
| 433 | data.m_Bias = &biasTensor; // Still set this whether or not bias is enabled - can be a source of bugs. |
| 434 | data.m_Parameters.m_StrideX = strideX; |
| 435 | data.m_Parameters.m_StrideY = strideY; |
| 436 | data.m_Parameters.m_PadLeft = padLeft; |
| 437 | data.m_Parameters.m_PadRight = padRight; |
| 438 | data.m_Parameters.m_PadTop = padTop; |
| 439 | data.m_Parameters.m_PadBottom = padBottom; |
| 440 | data.m_Parameters.m_BiasEnabled = biasEnabled; |
| 441 | data.m_Parameters.m_DataLayout = dataLayout; |
| 442 | |
| 443 | armnn::WorkloadInfo info; |
| 444 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 445 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 446 | |
| 447 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConvolution2d(data, info); |
| 448 | inputHandle->Allocate(); |
| 449 | outputHandle->Allocate(); |
| 450 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 451 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 452 | |
| 453 | ExecuteWorkload(*workload, memoryManager); |
| 454 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 455 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 456 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 457 | return LayerTestResult<O, 4>(actualOutput, |
| 458 | outputData, |
| 459 | outputHandle->GetShape(), |
| 460 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 461 | } |
| 462 | |
| 463 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> |
| 464 | LayerTestResult<T,4> Convolution1dTestImpl( |
| 465 | armnn::IWorkloadFactory& workloadFactory, |
| 466 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 467 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 468 | float qScale, |
| 469 | int32_t qOffset, |
| 470 | bool biasEnabled) |
| 471 | { |
| 472 | using B = armnn::ResolveType<ArmnnBType>; |
| 473 | // Until we have a specialist 1D convolution layer, we can fake one using |
| 474 | // 2D convolution with the final dimension set to 1. |
| 475 | // I don't anticipate this being particularly slow, given that convolution is implemented |
| 476 | // as a matrix multiplication, at which point dimension doesn't matter. |
| 477 | |
| 478 | unsigned int batchSize = 1; |
| 479 | unsigned int inputChannels = 2; |
| 480 | unsigned int outputChannels = 3; |
| 481 | unsigned int inputSize = 5; // The 1D size (could view as 'width' or 'height'). |
| 482 | unsigned int kernelSize = 3; |
| 483 | unsigned int padSize = 2; |
| 484 | unsigned int stride = 1; |
| 485 | unsigned int outputSize = 7; // (inputSize + 2 * padSize - kernelSize + 1) / stride. |
| 486 | |
| 487 | armnn::TensorInfo inputInfo({batchSize, inputChannels, inputSize, 1}, ArmnnType); |
| 488 | armnn::TensorInfo outputInfo({batchSize, outputChannels, outputSize, 1}, ArmnnType); |
| 489 | armnn::TensorInfo kernelInfo({outputChannels, inputChannels, kernelSize, 1}, ArmnnType); |
| 490 | armnn::TensorInfo biasInfo({outputChannels}, ArmnnBType); |
| 491 | |
| 492 | // Set quantization parameters if the requested type is a quantized type. |
| 493 | if(armnn::IsQuantizedType<T>()) |
| 494 | { |
| 495 | inputInfo.SetQuantizationScale(qScale); |
| 496 | inputInfo.SetQuantizationOffset(qOffset); |
| 497 | outputInfo.SetQuantizationScale(qScale); |
| 498 | outputInfo.SetQuantizationOffset(qOffset); |
| 499 | kernelInfo.SetQuantizationScale(qScale); |
| 500 | kernelInfo.SetQuantizationOffset(qOffset); |
| 501 | biasInfo.SetQuantizationScale(inputInfo.GetQuantizationScale()*kernelInfo.GetQuantizationScale()); |
| 502 | biasInfo.SetQuantizationOffset(0); |
| 503 | } |
| 504 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 505 | std::vector<T> inputData = QuantizedVector<T>( |
| 506 | { |
| 507 | 5.0f, -2.0f, 2.5f, 0.0f, 1.0f, |
| 508 | -3.0f, 3.2f, 5.0f, 2.0f, 3.0f, |
| 509 | }, |
| 510 | inputInfo.GetQuantizationScale(), |
| 511 | inputInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 512 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 513 | std::vector<T> kernelData = QuantizedVector<T>( |
| 514 | { |
| 515 | 1.0f, 0.0f, 0.0f, |
| 516 | 0.0f, 2.0f, -1.5f, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 517 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 518 | 0.0f, 0.0f, 0.0f, |
| 519 | 0.2f, 0.2f, 0.2f, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 520 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 521 | 0.5f, 0.0f, 0.5f, |
| 522 | 0.0f, -1.0f, 0.0f |
| 523 | }, |
| 524 | kernelInfo.GetQuantizationScale(), |
| 525 | kernelInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 526 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 527 | std::vector<B> biasData = |
| 528 | 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] | 529 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 530 | std::vector<T> outputData = QuantizedVector<T>( |
| 531 | { |
| 532 | 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] | 533 | -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] | 534 | 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 |
| 535 | }, |
| 536 | outputInfo.GetQuantizationScale(), |
| 537 | outputInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 538 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 539 | std::vector<T> actualOutput(outputInfo.GetNumElements()); |
| 540 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 541 | // Optionally apply bias to output image. |
| 542 | if(biasEnabled) |
| 543 | { |
| 544 | ApplyBias(outputData, outputInfo.GetQuantizationScale(), outputInfo.GetQuantizationOffset(), |
| 545 | biasData, biasInfo.GetQuantizationScale(), biasInfo.GetQuantizationOffset(), |
| 546 | 1, outputSize); |
| 547 | } |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 548 | |
| 549 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputInfo); |
| 550 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputInfo); |
| 551 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 552 | armnn::Convolution2dQueueDescriptor data; |
| 553 | armnn::WorkloadInfo info; |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 554 | armnn::ScopedTensorHandle weightsTensor(kernelInfo); |
| 555 | armnn::ScopedTensorHandle biasTensor(biasInfo); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 556 | |
| 557 | AllocateAndCopyDataToITensorHandle(&weightsTensor, kernelData.data()); |
| 558 | AllocateAndCopyDataToITensorHandle(&biasTensor, biasData.data()); |
| 559 | |
| 560 | AddInputToWorkload(data, info, inputInfo, inputHandle.get()); |
| 561 | AddOutputToWorkload(data, info, outputInfo, outputHandle.get()); |
| 562 | |
| 563 | data.m_Weight = &weightsTensor; |
| 564 | data.m_Bias = &biasTensor; |
| 565 | data.m_Parameters.m_StrideX = 1; |
| 566 | data.m_Parameters.m_StrideY = stride; |
| 567 | data.m_Parameters.m_PadLeft = 0; |
| 568 | data.m_Parameters.m_PadRight = 0; |
| 569 | data.m_Parameters.m_PadTop = padSize; |
| 570 | data.m_Parameters.m_PadBottom = padSize; |
| 571 | data.m_Parameters.m_BiasEnabled = biasEnabled; |
| 572 | |
| 573 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConvolution2d(data, info); |
| 574 | inputHandle->Allocate(); |
| 575 | outputHandle->Allocate(); |
| 576 | |
| 577 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
| 578 | |
| 579 | ExecuteWorkload(*workload, memoryManager); |
| 580 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 581 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
| 582 | |
| 583 | return LayerTestResult<T, 4>(actualOutput, |
| 584 | outputData, |
| 585 | outputHandle->GetShape(), |
| 586 | outputInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 587 | } |
| 588 | |
| 589 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 590 | LayerTestResult<T, 4> SimpleConvolution2d3x3NhwcTestCommon( |
| 591 | armnn::IWorkloadFactory& workloadFactory, |
| 592 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 593 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 594 | float qScale, |
| 595 | int32_t qOffset, |
| 596 | bool biasEnabled, |
| 597 | armnn::DataLayout dataLayout) |
| 598 | { |
Jan Eilers | 8eb2560 | 2020-03-09 12:13:48 +0000 | [diff] [blame] | 599 | armnn::IgnoreUnused(biasEnabled); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 600 | // Use common single-batch 5x5 image. |
| 601 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 602 | armnn::TensorInfo inputDesc({ 1, 3, 4, 1 }, ArmnnType); |
| 603 | std::vector<T> input = |
| 604 | { |
| 605 | 1, 5, 2, 3, |
| 606 | 8, 7, 3, 6, |
| 607 | 3, 3, 9, 1 |
| 608 | }; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 609 | |
| 610 | // Use a 2-element batch of 3-channel 3x3 kernels. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 611 | armnn::TensorInfo kernelDesc({ 1, 3, 3, 1 }, ArmnnType); |
| 612 | std::vector<T> kernel = |
| 613 | { |
| 614 | 4, 5, 6, |
| 615 | 0, 0, 0, |
| 616 | 3, 2, 1 |
| 617 | }; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 618 | |
| 619 | // Expected output is 1 batch of a 5x5 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 620 | armnn::TensorInfo outputDesc({ 1, 3, 4, 1 }, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 621 | const std::vector<float> outputData = |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 622 | { |
| 623 | 23, 41, 33, 21, |
| 624 | 44, 65, 76, 52, |
| 625 | 82, 85, 79, 42 |
| 626 | }; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 627 | |
| 628 | return SimpleConvolution2dNhwcTestImpl<ArmnnType, ArmnnType>( |
| 629 | workloadFactory, |
| 630 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 631 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 632 | input, |
| 633 | kernel, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 634 | std::vector<T>(), |
| 635 | outputData, |
| 636 | inputDesc.GetShape(), |
| 637 | kernelDesc.GetShape(), |
| 638 | outputDesc.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 639 | dataLayout, |
| 640 | qScale, |
| 641 | qOffset); |
| 642 | } |
| 643 | |
| 644 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 645 | LayerTestResult<T, 4> SimpleConvolution2d3x3Stride2x2TestCommon( |
| 646 | armnn::IWorkloadFactory& workloadFactory, |
| 647 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 648 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 649 | float qScale, |
| 650 | int32_t qOffset, |
| 651 | bool biasEnabled, |
| 652 | const armnn::DataLayout& dataLayout) |
| 653 | { |
Jan Eilers | 8eb2560 | 2020-03-09 12:13:48 +0000 | [diff] [blame] | 654 | armnn::IgnoreUnused(biasEnabled); |
Derek Lamberti | c374ff0 | 2019-12-10 21:57:35 +0000 | [diff] [blame] | 655 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 656 | // Input is a single-batch, 1 channel, 5x5 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 657 | armnn::TensorInfo inputDesc({ 1, 5, 5, 1 }, ArmnnType); |
| 658 | std::vector<T> input = |
| 659 | { |
| 660 | 1, 5, 2, 3, 5, |
| 661 | 8, 7, 3, 6, 3, |
| 662 | 3, 3, 9, 1, 9, |
| 663 | 4, 1, 8, 1, 3, |
| 664 | 6, 8, 1, 9, 2 |
| 665 | }; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 666 | |
| 667 | // Use a 3x3 kernel. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 668 | armnn::TensorInfo kernelDesc({ 1, 3, 3, 1 }, ArmnnType); |
| 669 | std::vector<T> kernel = |
| 670 | { |
| 671 | 4, 5, 6, |
| 672 | 0, 0, 0, |
| 673 | 3, 2, 1 |
| 674 | }; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 675 | |
| 676 | // Expected output is a single-batch, 1 channel, 3x3 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 677 | armnn::TensorInfo outputDesc({ 1, 3, 3, 1 }, ArmnnType); |
| 678 | std::vector<T> outputData = |
| 679 | { |
| 680 | 23, 33, 24, |
| 681 | 91, 99, 48, |
| 682 | 26, 50, 19 |
| 683 | }; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 684 | |
| 685 | uint32_t padLeft = 1; |
| 686 | uint32_t padTop = 1; |
| 687 | uint32_t padRight = 1; |
| 688 | uint32_t padBottom = 1; |
| 689 | uint32_t strideX = 2; |
| 690 | uint32_t strideY = 2; |
| 691 | |
| 692 | return SimpleConvolution2dNhwcTestImpl<ArmnnType, ArmnnType>( |
| 693 | workloadFactory, |
| 694 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 695 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 696 | input, |
| 697 | kernel, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 698 | std::vector<T>(), |
| 699 | outputData, |
| 700 | inputDesc.GetShape(), |
| 701 | kernelDesc.GetShape(), |
| 702 | outputDesc.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 703 | dataLayout, |
| 704 | qScale, |
| 705 | qOffset, |
| 706 | padLeft, |
| 707 | padTop, |
| 708 | padRight, |
| 709 | padBottom, |
| 710 | strideX, |
| 711 | strideY); |
| 712 | } |
| 713 | |
| 714 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> |
| 715 | LayerTestResult<T, 4> SimpleConvolution2d3x5TestCommon( |
| 716 | armnn::IWorkloadFactory& workloadFactory, |
| 717 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 718 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 719 | float qScale, |
| 720 | int32_t qOffset, |
| 721 | bool biasEnabled, |
| 722 | const armnn::DataLayout layout) |
| 723 | { |
| 724 | // Use common single-batch 3-channel 16x8 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 725 | armnn::TensorInfo inputDesc({ 1, 3, 8, 16 }, ArmnnType); |
| 726 | std::vector<T> input = QuantizedVector<T>(ConvInput3x8x16, qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 727 | |
| 728 | // Use a 2-element batch with 3-channel 3x5 kernels. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 729 | armnn::TensorInfo kernelDesc({ 2, 3, 5, 3 }, ArmnnType); |
| 730 | std::vector<T> kernel = QuantizedVector<T>({ |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 731 | 1, 1, 1, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 732 | 1, -1, 1, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 733 | 1, 1, 1, |
| 734 | 1, 1, 1, |
| 735 | 1, 1, 1, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 736 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 737 | 0, 0, 0, |
| 738 | 0, 0, 0, |
| 739 | 0, 0, 0, |
| 740 | 0, 0, 0, |
| 741 | 0, 0, 0, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 742 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 743 | 2, 2, 2, |
| 744 | 2, 2, 2, |
| 745 | 2, 2, 2, |
| 746 | 2, 2, 2, |
| 747 | 2, 2, 2, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 748 | |
| 749 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 750 | 0, 0, 0, |
| 751 | 0, 0, 0, |
| 752 | 0, 0, 0, |
| 753 | 0, 0, 0, |
| 754 | 0, 0, 0, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 755 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 756 | 1, 1, 1, |
| 757 | 1, 1, 1, |
| 758 | 1, 1, 1, |
| 759 | 1, 1, 1, |
| 760 | 1, 1, 1, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 761 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 762 | 0, 0, 0, |
| 763 | 0, 0, 0, |
| 764 | 0, 0, 0, |
| 765 | 0, 0, 0, |
| 766 | 0, 0, 0 |
| 767 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 768 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 769 | |
| 770 | // Expected output is 2 batch elements of a 1-channel 14x4 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 771 | armnn::TensorInfo outputDesc({ 1, 2, 4, 14 }, ArmnnType); |
| 772 | std::vector<T> expectedOutput = QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 773 | -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, |
| 774 | -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, |
| 775 | -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, |
| 776 | -23.5f, -23.5f, -23.5f, |
| 777 | -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, |
| 778 | -23.5f, -23.5f, -23.5f, |
| 779 | |
| 780 | 5, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 781 | 5, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 782 | 5, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 783 | 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] | 784 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 785 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 786 | |
| 787 | return SimpleConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 788 | workloadFactory, |
| 789 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 790 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 791 | input, |
| 792 | kernel, |
| 793 | GetBias2<ArmnnBType>(biasEnabled, qScale * qScale), |
| 794 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 795 | inputDesc.GetShape(), |
| 796 | kernelDesc.GetShape(), |
| 797 | outputDesc.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 798 | qScale, |
| 799 | qOffset, |
| 800 | layout); |
| 801 | } |
| 802 | |
| 803 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 804 | typename T = armnn::ResolveType<ArmnnType>> |
| 805 | LayerTestResult<T, 4> SimpleConvolution2d3x3TestCommon( |
| 806 | armnn::IWorkloadFactory& workloadFactory, |
| 807 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 808 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 809 | float qScale, |
| 810 | int32_t qOffset, |
| 811 | bool biasEnabled, |
| 812 | const armnn::DataLayout layout) |
| 813 | { |
| 814 | // Use a 3x3 kernel, which exercises ArmCompute's direct convolution path. |
| 815 | |
| 816 | // Use common single-batch 3-channel 16x8 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 817 | armnn::TensorInfo inputDesc({ 1, 3, 8, 16 }, ArmnnType); |
| 818 | std::vector<unsigned int> inputShape = { 1, 3, 8, 16 }; |
| 819 | std::vector<T> input = QuantizedVector<T>(ConvInput3x8x16, qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 820 | |
| 821 | // Use a 2-element batch of 3-channel 3x3 kernels. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 822 | armnn::TensorInfo kernelDesc({ 2, 3, 3, 3 }, ArmnnType); |
| 823 | std::vector<T> kernel = QuantizedVector<T>({ |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 824 | 1, 1, 1, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 825 | 1, -1, 1, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 826 | 1, 1, 1, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 827 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 828 | 0, 0, 0, |
| 829 | 0, 0, 0, |
| 830 | 0, 0, 0, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 831 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 832 | 2, 2, 2, |
| 833 | 2, 2, 2, |
| 834 | 2, 2, 2, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 835 | |
| 836 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 837 | 0, 0, 0, |
| 838 | 0, 0, 0, |
| 839 | 0, 0, 0, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 840 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 841 | 1, 1, 1, |
| 842 | 1, 1, 1, |
| 843 | 1, 1, 1, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 844 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 845 | 0, 0, 0, |
| 846 | 0, 0, 0, |
| 847 | 0, 0, 0 |
| 848 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 849 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 850 | |
| 851 | // Expected output is 1 batch of a 2-channel 14x6 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 852 | armnn::TensorInfo outputDesc({ 1, 2, 6, 14 }, ArmnnType); |
| 853 | std::vector<T> expectedOutput = QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 854 | -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, |
| 855 | -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, |
| 856 | -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, |
| 857 | -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, |
| 858 | -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, |
| 859 | -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, |
| 860 | |
| 861 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 862 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 863 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 864 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 865 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 866 | 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] | 867 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 868 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 869 | |
| 870 | return SimpleConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 871 | workloadFactory, |
| 872 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 873 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 874 | input, |
| 875 | kernel, |
| 876 | GetBias2<ArmnnBType>(biasEnabled, qScale * qScale), |
| 877 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 878 | inputDesc.GetShape(), |
| 879 | kernelDesc.GetShape(), |
| 880 | outputDesc.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 881 | qScale, |
| 882 | qOffset, |
| 883 | layout); |
| 884 | } |
| 885 | |
| 886 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 887 | typename T = armnn::ResolveType<ArmnnType>> |
| 888 | LayerTestResult<T, 4> Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon( |
| 889 | armnn::IWorkloadFactory& workloadFactory, |
| 890 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 891 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 892 | const armnn::DataLayout layout, |
| 893 | float qScale, |
| 894 | int32_t qOffset) |
| 895 | { |
| 896 | // Use a single-batch 1-channel 3x3 image as input. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 897 | armnn::TensorInfo inputDesc({ 1, 1, 3, 3 }, ArmnnType); |
| 898 | std::vector<T> input = |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 899 | QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 900 | 11,21,31, |
| 901 | 12,22,32, |
| 902 | 13,23,33 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 903 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 904 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 905 | |
| 906 | // Use 1 batch of a 1-channel 2x2 kernel. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 907 | armnn::TensorInfo kernelDesc({ 1, 1, 2, 2 }, ArmnnType); |
| 908 | std::vector<T> kernel = |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 909 | QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 910 | -11,-21, |
| 911 | -12,-22, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 912 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 913 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 914 | |
| 915 | // Expected output is 1 batch of a 1-channel 6x8 image. |
| 916 | // Manually calculated like this: |
| 917 | //[-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 ..] |
| 918 | //[-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 ..] |
| 919 | //[-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 ..] |
| 920 | //[-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 ..] |
| 921 | //[-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 ..] |
| 922 | //[-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 ..] |
| 923 | //[..... ..... ..... ..... ; ..... ..... ..... ..... ; ..... ..... ..... ..... ; ..... ..... ..... ..... ..] |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 924 | armnn::TensorInfo outputDesc({ 1, 1, 8, 6 }, ArmnnType); |
| 925 | std::vector<T> expectedOutput = |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 926 | QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 927 | 0, 0, 0, 0, 0, 0, |
| 928 | -242, -594, -934, -372, 0, 0, |
| 929 | -495, -1190, -1850, -725, 0, 0, |
| 930 | -538, -1256, -1916, -748, 0, 0, |
| 931 | -273, -626, -946, -363, 0, 0, |
| 932 | 0, 0, 0, 0, 0, 0, |
| 933 | 0, 0, 0, 0, 0, 0, |
| 934 | 0, 0, 0, 0, 0, 0 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 935 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 936 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 937 | |
| 938 | return SimpleConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 939 | workloadFactory, |
| 940 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 941 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 942 | input, |
| 943 | kernel, |
| 944 | GetBias2<ArmnnBType>(false, qScale * qScale), |
| 945 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 946 | inputDesc.GetShape(), |
| 947 | kernelDesc.GetShape(), |
| 948 | outputDesc.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 949 | qScale, |
| 950 | qOffset, |
| 951 | layout, |
| 952 | 1, // Padding left. |
| 953 | 2, // Padding top. |
| 954 | 3, // Padding right. |
| 955 | 4); // Padding bottom. |
| 956 | } |
| 957 | |
| 958 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 959 | typename T = armnn::ResolveType<ArmnnType>> |
| 960 | LayerTestResult<T, 4> SimpleConvolution2dAsymmetricPaddingTestCommon( |
| 961 | armnn::IWorkloadFactory& workloadFactory, |
| 962 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 963 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 964 | const armnn::DataLayout layout, |
| 965 | float qScale, |
| 966 | int32_t qOffset) |
| 967 | { |
| 968 | // Use a single-batch 1-channel 5x5 image as input. |
| 969 | armnn::TensorInfo inputDesc({ 1, 1, 5, 5 }, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 970 | std::vector<T> input = |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 971 | QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 972 | 11,21,31,41,51, |
| 973 | 12,22,32,42,52, |
| 974 | 13,23,33,43,53, |
| 975 | 14,24,34,44,54, |
| 976 | 15,25,35,45,55, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 977 | }, qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 978 | |
| 979 | // Use 1 batch of a 1-channel 4x4 kernel. |
| 980 | armnn::TensorInfo kernelDesc({ 1, 1, 4, 4 }, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 981 | std::vector<T> kernel = |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 982 | QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 983 | -11,-21,-31,-41, |
| 984 | -12,-22,-32,-42, |
| 985 | -13,-23,-33,-43, |
| 986 | -14,-24,-34,-44, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 987 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 988 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 989 | |
| 990 | // Expected output is 1 batch of a 1-channel 5x5 image. |
| 991 | armnn::TensorInfo outputDesc({ 1, 1, 5, 5 }, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 992 | std::vector<T> expectedOutput = |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 993 | QuantizedVector<T>({ |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 994 | -7140, -10580, -13940, -9300, -5230, |
| 995 | -9590, -14120, -18520, -12290, -6860, |
| 996 | -9980, -14560, -18960, -12560, -7000, |
| 997 | -7518, -10904, -14144, -9318, -5152, |
| 998 | -5032, -7256, -9376, -6142, -3368, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 999 | }, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1000 | qScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1001 | |
| 1002 | return SimpleConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 1003 | workloadFactory, |
| 1004 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1005 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1006 | input, |
| 1007 | kernel, |
| 1008 | GetBias2<ArmnnBType>(false, qScale * qScale), |
| 1009 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1010 | inputDesc.GetShape(), |
| 1011 | kernelDesc.GetShape(), |
| 1012 | outputDesc.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1013 | qScale, |
| 1014 | qOffset, |
| 1015 | layout, |
| 1016 | 1, // Padding left. |
| 1017 | 1, // Padding top. |
| 1018 | 2, // Padding right. |
| 1019 | 2); // Padding bottom. |
| 1020 | } |
| 1021 | |
| 1022 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> |
| 1023 | LayerTestResult<T, 4> Convolution2d3x3DilationTestCommon( |
| 1024 | armnn::IWorkloadFactory& workloadFactory, |
| 1025 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1026 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1027 | const std::vector<float>& inputNoQuantizedValues, |
| 1028 | armnn::TensorInfo& inputTensorInfo, |
| 1029 | const std::vector<float>& kernelNoQuantizedValues, |
| 1030 | armnn::TensorInfo& kernelTensorInfo, |
| 1031 | const std::vector<float>& outputExpectedNoQuantizedValues, |
| 1032 | armnn::TensorInfo& outputTensorInfo, |
| 1033 | uint32_t dilationX, |
| 1034 | uint32_t dilationY, |
| 1035 | armnn::DataLayout layout = armnn::DataLayout::NCHW, |
| 1036 | uint32_t padLeft = 0, |
| 1037 | uint32_t padTop = 0, |
| 1038 | uint32_t padRight = 0, |
| 1039 | uint32_t padBottom = 0, |
| 1040 | uint32_t strideX = 1, |
| 1041 | uint32_t strideY = 1, |
| 1042 | bool biasEnabled = false |
| 1043 | ) |
| 1044 | { |
| 1045 | float qScale; |
| 1046 | int32_t qOffset; |
| 1047 | switch (ArmnnType) |
| 1048 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 1049 | case armnn::DataType::QAsymmU8: |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 1050 | case armnn::DataType::QAsymmS8: |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1051 | { |
| 1052 | qScale = 0.1f; |
| 1053 | qOffset = 128; |
| 1054 | break; |
| 1055 | } |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 1056 | case armnn::DataType::QSymmS16: |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1057 | { |
| 1058 | qScale = 0.1f; |
| 1059 | qOffset = 0; |
| 1060 | break; |
| 1061 | } |
| 1062 | case armnn::DataType::Float32: |
| 1063 | default: |
| 1064 | { |
| 1065 | qScale = 0.f; |
| 1066 | qOffset = 0; |
| 1067 | break; |
| 1068 | } |
| 1069 | } |
| 1070 | |
| 1071 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1072 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1073 | kernelTensorInfo.SetQuantizationScale(qScale); |
| 1074 | kernelTensorInfo.SetQuantizationOffset(qOffset); |
| 1075 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1076 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1077 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1078 | auto input = QuantizedVector<T>(inputNoQuantizedValues, |
| 1079 | inputTensorInfo.GetQuantizationScale(), |
| 1080 | inputTensorInfo.GetQuantizationOffset()); |
| 1081 | auto kernel = QuantizedVector<T>(kernelNoQuantizedValues, |
| 1082 | kernelTensorInfo.GetQuantizationScale(), |
| 1083 | kernelTensorInfo.GetQuantizationOffset()); |
| 1084 | auto expectedOutput = QuantizedVector<T>(outputExpectedNoQuantizedValues, |
| 1085 | outputTensorInfo.GetQuantizationScale(), |
| 1086 | outputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1087 | |
| 1088 | return SimpleConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 1089 | workloadFactory, |
| 1090 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1091 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1092 | input, |
| 1093 | kernel, |
| 1094 | GetBias2<ArmnnBType>(biasEnabled, qScale * qScale), |
| 1095 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1096 | inputTensorInfo.GetShape(), |
| 1097 | kernelTensorInfo.GetShape(), |
| 1098 | outputTensorInfo.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1099 | qScale, |
| 1100 | qOffset, |
| 1101 | layout, |
| 1102 | padLeft, |
| 1103 | padTop, |
| 1104 | padRight, |
| 1105 | padBottom, |
| 1106 | strideX, |
| 1107 | strideY, |
| 1108 | dilationX, |
| 1109 | dilationY); |
| 1110 | } |
| 1111 | |
| 1112 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T> |
| 1113 | LayerTestResult<T, 4> Convolution2d3x3Dilation3x3Test( |
| 1114 | armnn::IWorkloadFactory& workloadFactory, |
| 1115 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1116 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1117 | bool biasEnabled, |
| 1118 | const armnn::DataLayout layout) |
| 1119 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1120 | armnn::TensorInfo inputTensorInfo({ 1, 1, 10, 10 }, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1121 | std::vector<float> inputNoQuantizedValues = |
| 1122 | { |
| 1123 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1124 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1125 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1126 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1127 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1128 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1129 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1130 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1131 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1132 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| 1133 | }; |
| 1134 | |
| 1135 | armnn::TensorInfo kernelTensorInfo({ 1, 1, 3, 3}, ArmnnType); |
| 1136 | std::vector<float> kernelNoQuantizedValues = |
| 1137 | { |
| 1138 | 1, 2, 3, |
| 1139 | 4, 5, 6, |
| 1140 | 7, 8, 9 |
| 1141 | }; |
| 1142 | |
| 1143 | // Since the dilation rate is 3 this will dilate the kernel to be like 7x7, |
| 1144 | // therefore the output will be 4x4: (I−K+2P)/S +1 => (10-7 +0)/1 +1 |
| 1145 | armnn::TensorInfo outputTensorInfo({ 1, 1, 4, 4}, ArmnnType); |
| 1146 | std::vector<float> outputExpectedNoQuantizedValues = |
| 1147 | { |
| 1148 | 6., 5., 5., 5., |
| 1149 | 6., 5., 5., 5., |
| 1150 | 6., 5., 5., 5., |
| 1151 | 3., 2., 2., 2. |
| 1152 | }; |
| 1153 | |
| 1154 | return Convolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( |
| 1155 | workloadFactory, |
| 1156 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1157 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1158 | inputNoQuantizedValues, |
| 1159 | inputTensorInfo, |
| 1160 | kernelNoQuantizedValues, |
| 1161 | kernelTensorInfo, |
| 1162 | outputExpectedNoQuantizedValues, |
| 1163 | outputTensorInfo, |
| 1164 | 3, |
| 1165 | 3, |
| 1166 | layout, |
| 1167 | biasEnabled); |
| 1168 | } |
| 1169 | |
| 1170 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T> |
| 1171 | LayerTestResult<T, 4> Convolution2d2x3x3Dilation3x3Test( |
| 1172 | armnn::IWorkloadFactory& workloadFactory, |
| 1173 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1174 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1175 | bool biasEnabled, |
| 1176 | const armnn::DataLayout layout) |
| 1177 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1178 | armnn::TensorInfo inputTensorInfo({ 1, 2, 10, 10 }, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1179 | std::vector<float> inputNoQuantizedValues = |
| 1180 | { |
| 1181 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1182 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1183 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1184 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1185 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1186 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1187 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1188 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1189 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1190 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1191 | |
| 1192 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1193 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1194 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1195 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1196 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1197 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 1198 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1199 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1200 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 1201 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| 1202 | }; |
| 1203 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1204 | armnn::TensorInfo kernelTensorInfo({ 1, 2, 3, 3 }, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1205 | std::vector<float> kernelNoQuantizedValues = |
| 1206 | { |
| 1207 | 1, 2, 3, |
| 1208 | 4, 5, 6, |
| 1209 | 7, 8, 9, |
| 1210 | |
| 1211 | 1, 2, 3, |
| 1212 | 4, 5, 6, |
| 1213 | 7, 8, 9 |
| 1214 | }; |
| 1215 | |
| 1216 | // Since the dilation rate is 3 this will dilate the kernel to be like 7x7, |
| 1217 | // 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^] | 1218 | armnn::TensorInfo outputTensorInfo({ 1, 1, 4, 4 }, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1219 | std::vector<float> outputExpectedNoQuantizedValues = |
| 1220 | { |
| 1221 | 12., 10., 10., 10., |
| 1222 | 12., 10., 10., 10., |
| 1223 | 12., 10., 10., 10., |
| 1224 | 6., 4., 4., 4. |
| 1225 | }; |
| 1226 | |
| 1227 | return Convolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( |
| 1228 | workloadFactory, |
| 1229 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1230 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1231 | inputNoQuantizedValues, |
| 1232 | inputTensorInfo, |
| 1233 | kernelNoQuantizedValues, |
| 1234 | kernelTensorInfo, |
| 1235 | outputExpectedNoQuantizedValues, |
| 1236 | outputTensorInfo, |
| 1237 | 3, |
| 1238 | 3, |
| 1239 | layout, |
| 1240 | biasEnabled); |
| 1241 | } |
| 1242 | |
| 1243 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T> |
| 1244 | LayerTestResult<T, 4> Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test( |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1245 | armnn::IWorkloadFactory& workloadFactory, |
| 1246 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1247 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1248 | bool biasEnabled, |
| 1249 | const armnn::DataLayout layout) |
| 1250 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1251 | armnn::TensorInfo inputTensorInfo({ 1, 1, 10, 10 }, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1252 | std::vector<float> inputNoQuantizedValues = |
| 1253 | { |
| 1254 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1255 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1256 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1257 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1258 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1259 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1260 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1261 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1262 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
| 1263 | 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 |
| 1264 | }; |
| 1265 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1266 | armnn::TensorInfo kernelTensorInfo({ 1, 1, 2, 2 }, ArmnnType); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1267 | std::vector<float> kernelNoQuantizedValues = |
| 1268 | { |
| 1269 | 1, 2, |
| 1270 | 3, 4 |
| 1271 | }; |
| 1272 | |
| 1273 | // 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, |
| 1274 | // therefore the output will be 4x4: (I − K + 2P)/S +1 => trunc ( (10 - 3 + 2x2 ) / 3 + 1 ) |
| 1275 | // where, dilation size = d = 2; kernel size = K = 2; input size = I = 10; padding size = P = 2; stride = S = 3 |
| 1276 | armnn::TensorInfo outputTensorInfo({ 1, 1, 4, 4}, ArmnnType); |
| 1277 | std::vector<float> outputExpectedNoQuantizedValues = |
| 1278 | { |
| 1279 | 4, 7, 7, 3, |
| 1280 | 6, 10, 10, 4, |
| 1281 | 6, 10, 10, 4, |
| 1282 | 2, 3, 3, 1 |
| 1283 | }; |
| 1284 | uint32_t padLeft = 1; |
| 1285 | uint32_t padTop = 1; |
| 1286 | uint32_t padRight = 1; |
| 1287 | uint32_t padBottom = 1; |
| 1288 | |
| 1289 | return Convolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( |
| 1290 | workloadFactory, |
| 1291 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1292 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1293 | inputNoQuantizedValues, |
| 1294 | inputTensorInfo, |
| 1295 | kernelNoQuantizedValues, |
| 1296 | kernelTensorInfo, |
| 1297 | outputExpectedNoQuantizedValues, |
| 1298 | outputTensorInfo, |
| 1299 | 2, |
| 1300 | 2, |
| 1301 | layout, |
| 1302 | padLeft, |
| 1303 | padTop, |
| 1304 | padRight, |
| 1305 | padBottom, |
| 1306 | 3, |
| 1307 | 3, |
| 1308 | biasEnabled |
| 1309 | ); |
| 1310 | } |
| 1311 | |
| 1312 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 1313 | LayerTestResult<T,4> CompareConvolution2dTestImpl( |
| 1314 | armnn::IWorkloadFactory& workloadFactory, |
| 1315 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1316 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 1317 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 1318 | const armnn::ITensorHandleFactory& refTensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1319 | { |
| 1320 | unsigned int inputHeight = 8; |
| 1321 | unsigned int inputWidth = 16; |
| 1322 | unsigned int inputChannels = 3; |
| 1323 | unsigned int inputNum = 5; |
| 1324 | |
| 1325 | unsigned int kernelHeight = 3; |
| 1326 | unsigned int kernelWidth = 3; |
| 1327 | |
| 1328 | unsigned int strideX = 2; |
| 1329 | unsigned int strideY = 3; |
| 1330 | unsigned int padX = 1; |
| 1331 | unsigned int padY = 1; |
| 1332 | |
| 1333 | unsigned int outputNum = inputNum; |
| 1334 | unsigned int outputChannels = 2; |
| 1335 | unsigned int outputHeight = (inputHeight + 2 * padY - kernelHeight + strideY) / strideY; |
| 1336 | unsigned int outputWidth = (inputWidth + 2 * padX - kernelWidth + strideX) / strideX; |
| 1337 | |
| 1338 | armnn::TensorInfo inputTensorInfo; |
| 1339 | armnn::TensorInfo outputTensorInfo; |
| 1340 | armnn::TensorInfo kernelDesc; |
| 1341 | armnn::TensorInfo biasDesc; |
| 1342 | |
| 1343 | unsigned int inputShape[] = {inputNum, inputChannels, inputHeight, inputWidth}; |
| 1344 | unsigned int outputShape[] = {outputNum, outputChannels, outputHeight, outputWidth}; |
| 1345 | unsigned int kernelShape[] = {outputChannels, inputChannels, kernelHeight, kernelWidth}; |
| 1346 | unsigned int biasShape[] = {outputChannels}; |
| 1347 | |
| 1348 | inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType); |
| 1349 | outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType); |
| 1350 | kernelDesc = armnn::TensorInfo(4, kernelShape, ArmnnType); |
| 1351 | biasDesc = armnn::TensorInfo(1, biasShape, ArmnnType); |
| 1352 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1353 | auto input = MakeRandomTensor<T>(inputTensorInfo, 124908); |
| 1354 | auto kernel = MakeRandomTensor<T>(kernelDesc, 891234); |
| 1355 | auto bias = MakeRandomTensor<T>(biasDesc, 1028); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1356 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1357 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
| 1358 | std::vector<T> expectedOutput(outputTensorInfo.GetNumElements()); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1359 | |
| 1360 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 1361 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 1362 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1363 | armnn::Convolution2dQueueDescriptor data; |
| 1364 | armnn::WorkloadInfo info; |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 1365 | armnn::ScopedTensorHandle weightsTensor(kernelDesc); |
| 1366 | armnn::ScopedTensorHandle biasTensor(biasDesc); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1367 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1368 | AllocateAndCopyDataToITensorHandle(&weightsTensor, kernel.data()); |
| 1369 | AllocateAndCopyDataToITensorHandle(&biasTensor, bias.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1370 | |
| 1371 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 1372 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1373 | data.m_Weight = &weightsTensor; |
| 1374 | data.m_Bias = &biasTensor; |
| 1375 | data.m_Parameters.m_StrideX = strideX; |
| 1376 | data.m_Parameters.m_StrideY = strideY; |
| 1377 | data.m_Parameters.m_PadLeft = padX; |
| 1378 | data.m_Parameters.m_PadRight = padX; |
| 1379 | data.m_Parameters.m_PadTop = padY; |
| 1380 | data.m_Parameters.m_PadBottom = padY; |
| 1381 | data.m_Parameters.m_BiasEnabled = true; |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1382 | |
| 1383 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refTensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 1384 | std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refTensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 1385 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1386 | armnn::Convolution2dQueueDescriptor refData = data; |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1387 | armnn::WorkloadInfo refInfo = info; |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1388 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get()); |
| 1389 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 1390 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1391 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConvolution2d(data, info); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1392 | std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateConvolution2d(refData, refInfo); |
| 1393 | |
| 1394 | outputHandleRef->Allocate(); |
| 1395 | inputHandleRef->Allocate(); |
| 1396 | |
| 1397 | inputHandle->Allocate(); |
| 1398 | outputHandle->Allocate(); |
| 1399 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1400 | CopyDataToITensorHandle(inputHandle.get(), input.data()); |
| 1401 | CopyDataToITensorHandle(inputHandleRef.get(), input.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1402 | |
| 1403 | ExecuteWorkload(*workload, memoryManager); |
| 1404 | |
| 1405 | workloadRef->PostAllocationConfigure(); |
| 1406 | workloadRef->Execute(); |
| 1407 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1408 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
| 1409 | CopyDataFromITensorHandle(expectedOutput.data(), outputHandleRef.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1410 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1411 | return LayerTestResult<T, 4>(actualOutput, |
| 1412 | expectedOutput, |
| 1413 | outputHandle->GetShape(), |
| 1414 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1415 | } |
| 1416 | |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1417 | LayerTestResult<float, 4> Convolution2d3x3Stride2x2BFloat16Test( |
| 1418 | armnn::IWorkloadFactory& workloadFactory, |
| 1419 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1420 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1421 | bool biasEnabled, |
| 1422 | const armnn::DataLayout& dataLayout) |
| 1423 | { |
| 1424 | // BFloat16 input and weight, Float32 output |
| 1425 | armnn::IgnoreUnused(biasEnabled); |
| 1426 | |
| 1427 | // Input is a single-batch, 1 channel, 5x5 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1428 | armnn::TensorInfo inputDesc({ 1, 5, 5, 1 }, armnn::DataType::BFloat16); |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1429 | |
| 1430 | std::vector<armnn::BFloat16> inputValues = armnnUtils::QuantizedVector<armnn::BFloat16>( |
| 1431 | { |
| 1432 | 10.0367984f, // 10.0625 |
| 1433 | 2.0380895f, // 2.03125 |
| 1434 | 15.0420157f, // 15.0625 |
| 1435 | 22.0675631f, // 22.125 |
| 1436 | 8.0938920f, // 8.125 |
| 1437 | 5.0476106f, // 5.0625 |
| 1438 | 80.1035490f, // 80 |
| 1439 | 100.1260370f, // 100 |
| 1440 | 55.0461647f, // 55 |
| 1441 | 120.0883828f, // 120 |
| 1442 | 9.1159540f, // 9.125 |
| 1443 | 90.0498519f, // 90 |
| 1444 | 200.0104630f, // 200 |
| 1445 | 30.0154114f, // 30 |
| 1446 | 75.00137681f, // 75 |
| 1447 | 30.0344238f, // 30 |
| 1448 | 25.0356445f, // 25 |
| 1449 | 130.0495605f, // 130 |
| 1450 | 60.0683594f, // 60 |
| 1451 | 35.0991211f, // 35 |
| 1452 | 8.0461426f, // 8.0625 |
| 1453 | 12.0996094f, // 12.125 |
| 1454 | 98.1269530f, // 98 |
| 1455 | 125.0393066f, // 125 |
| 1456 | 5.103516f // 5.0937 |
| 1457 | }, |
| 1458 | 1.0f, 0); |
| 1459 | |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1460 | // Use a 3x3 kernel. |
| 1461 | armnn::TensorInfo kernelDesc({1, 3, 3, 1}, armnn::DataType::BFloat16); |
| 1462 | |
| 1463 | std::vector<armnn::BFloat16> kernelValues = armnnUtils::QuantizedVector<armnn::BFloat16>( |
| 1464 | { |
| 1465 | -0.126184f, // -0.125977 |
| 1466 | -0.150468f, // -0.150391 |
| 1467 | -0.101412f, // -0.101562 |
| 1468 | -0.0586369f,// -0.0585938 |
| 1469 | -0.0865864f,// -0.0864258 |
| 1470 | -0.0435089f,// -0.043457 |
| 1471 | 0.0347555f, // 0.034668 |
| 1472 | 0.0323111f, // 0.0322266 |
| 1473 | 0.0385381f // 0.0385742 |
| 1474 | }, |
| 1475 | 1.0f, 0); |
| 1476 | |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1477 | // Expected output is a single-batch, 1 channel, 3x3 image. |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1478 | armnn::TensorInfo outputDesc({ 1, 3, 3, 1 }, armnn::DataType::Float32); |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1479 | |
| 1480 | // Expected output (with results if calculated as FP32 in the comments) |
| 1481 | const std::vector<float> outputData = |
| 1482 | { |
| 1483 | 2.296875f, // 2.29240716 |
| 1484 | 5.75f, // 5.75851926 |
| 1485 | 3.78125f, // 3.79855026 |
| 1486 | -11.625f, // -11.65498118 |
| 1487 | -47.25f, // -47.27316893 |
| 1488 | -30.0f, // -30.04771684 |
| 1489 | -8.25f, // -8.28126168 |
| 1490 | -43.5f, // -43.46531337 |
| 1491 | -20.625f // -20.63477281 |
| 1492 | }; |
| 1493 | |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1494 | uint32_t padLeft = 1; |
| 1495 | uint32_t padTop = 1; |
| 1496 | uint32_t padRight = 1; |
| 1497 | uint32_t padBottom = 1; |
| 1498 | uint32_t strideX = 2; |
| 1499 | uint32_t strideY = 2; |
| 1500 | |
| 1501 | return SimpleConvolution2dNhwcTestImpl |
| 1502 | <armnn::DataType::BFloat16, armnn::DataType::Float32, armnn::BFloat16, float, armnn::DataType::Float32, float>( |
| 1503 | workloadFactory, |
| 1504 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1505 | tensorHandleFactory, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1506 | inputValues, |
| 1507 | kernelValues, |
| 1508 | std::vector<float>(), |
| 1509 | outputData, |
| 1510 | inputDesc.GetShape(), |
| 1511 | kernelDesc.GetShape(), |
| 1512 | outputDesc.GetShape(), |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1513 | dataLayout, |
| 1514 | 1.0f, |
| 1515 | 0, |
| 1516 | padLeft, |
| 1517 | padTop, |
| 1518 | padRight, |
| 1519 | padBottom, |
| 1520 | strideX, |
| 1521 | strideY); |
| 1522 | } |
| 1523 | |
| 1524 | LayerTestResult<float, 4> Convolution2d3x3Stride2x2BFloat16SmallValueTest( |
| 1525 | armnn::IWorkloadFactory& workloadFactory, |
| 1526 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1527 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1528 | bool biasEnabled, |
| 1529 | const armnn::DataLayout& dataLayout) |
| 1530 | { |
| 1531 | // BFloat16 input and weight, Float32 output |
| 1532 | armnn::IgnoreUnused(biasEnabled); |
| 1533 | |
| 1534 | // Input is a single-batch, 1 channel, 5x5 image. |
| 1535 | armnn::TensorInfo inputDesc({1, 5, 5, 1}, armnn::DataType::BFloat16); |
| 1536 | |
| 1537 | std::vector<armnn::BFloat16> inputValues = armnnUtils::QuantizedVector<armnn::BFloat16>( |
| 1538 | { |
| 1539 | 0.0367984f, // 0.0368652 |
| 1540 | 0.0380895f, // 0.0380859 |
| 1541 | 0.0420157f, // 0.0419922 |
| 1542 | 0.0675631f, // 0.0673828 |
| 1543 | 0.0938920f, // 0.09375 |
| 1544 | 0.0476106f, // 0.0476074 |
| 1545 | 0.1035490f, // 0.103516 |
| 1546 | 0.1260370f, // 0.125977 |
| 1547 | 0.0461647f, // 0.0461426 |
| 1548 | 0.0883828f, // 0.0883789 |
| 1549 | 0.1159540f, // 0.115723 |
| 1550 | 0.0498519f, // 0.0498047 |
| 1551 | 0.0104630f, // 0.010437 |
| 1552 | 0.0154114f, // 0.0154419 |
| 1553 | 0.00137681f, // 0.00137329 |
| 1554 | 0.0344238f, // 0.0344616 |
| 1555 | 0.0356445f, // 0.0355693 |
| 1556 | 0.0495605f, // 0.0495018 |
| 1557 | 0.0683594f, // 0.0683308 |
| 1558 | 0.0991211f, // 0.0988837 |
| 1559 | 0.0461426f, // 0.0461838 |
| 1560 | 0.0996094f, // 0.0997546 |
| 1561 | 0.1269530f, // 0.127099 |
| 1562 | 0.0393066f, // 0.0392791 |
| 1563 | 0.103516f // 0.103641 |
| 1564 | }, |
| 1565 | 1.0f, 0); |
| 1566 | |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1567 | // Use a 3x3 kernel. |
| 1568 | armnn::TensorInfo kernelDesc({1, 3, 3, 1}, armnn::DataType::BFloat16); |
| 1569 | |
| 1570 | std::vector<armnn::BFloat16> kernelValues = armnnUtils::QuantizedVector<armnn::BFloat16>( |
| 1571 | { |
| 1572 | -0.126184f, // -0.125977 |
| 1573 | -0.150468f, // -0.150391 |
| 1574 | -0.101412f, // -0.101562 |
| 1575 | -0.0586369f,// -0.0585938 |
| 1576 | -0.0865864f,// -0.0864258 |
| 1577 | -0.0435089f,// -0.043457 |
| 1578 | 0.0347555f, // 0.034668 |
| 1579 | 0.0323111f, // 0.0322266 |
| 1580 | 0.0385381f // 0.0385742 |
| 1581 | }, |
| 1582 | 1.0f, 0); |
| 1583 | |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1584 | // Expected output is a single-batch, 1 channel, 3x3 image. |
| 1585 | armnn::TensorInfo outputDesc({1, 3, 3, 1}, armnn::DataType::Float32); |
| 1586 | |
| 1587 | // Expected output (with results if calculated as FP32 in the comments) |
| 1588 | const std::vector<float> outputData = |
| 1589 | { |
| 1590 | 0.000686645508f, // 0.000685 |
| 1591 | 0.000640869141f, // 0.000639 |
| 1592 | -0.00759887695f, // -0.007631 |
| 1593 | -0.02734375f, // -0.027388 |
| 1594 | -0.0356445312f, // -0.035737 |
| 1595 | -0.0145874023f, // -0.014568 |
| 1596 | -0.0170898438f, // -0.017124 |
| 1597 | -0.0373535156f, // -0.037431 |
| 1598 | -0.0346679688f // -0.034808 |
| 1599 | }; |
| 1600 | |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1601 | uint32_t padLeft = 1; |
| 1602 | uint32_t padTop = 1; |
| 1603 | uint32_t padRight = 1; |
| 1604 | uint32_t padBottom = 1; |
| 1605 | uint32_t strideX = 2; |
| 1606 | uint32_t strideY = 2; |
| 1607 | |
| 1608 | return SimpleConvolution2dNhwcTestImpl |
| 1609 | <armnn::DataType::BFloat16, armnn::DataType::Float32, armnn::BFloat16, float, armnn::DataType::Float32, float>( |
| 1610 | workloadFactory, |
| 1611 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1612 | tensorHandleFactory, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1613 | inputValues, |
| 1614 | kernelValues, |
| 1615 | std::vector<float>(), |
| 1616 | outputData, |
| 1617 | inputDesc.GetShape(), |
| 1618 | kernelDesc.GetShape(), |
| 1619 | outputDesc.GetShape(), |
Narumol Prangnawarat | e8cddeb | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1620 | dataLayout, |
| 1621 | 1.0f, |
| 1622 | 0, |
| 1623 | padLeft, |
| 1624 | padTop, |
| 1625 | padRight, |
| 1626 | padBottom, |
| 1627 | strideX, |
| 1628 | strideY); |
| 1629 | } |
| 1630 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1631 | // |
| 1632 | // DepthwiseConvolution2d implementations |
| 1633 | // |
| 1634 | |
| 1635 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 1636 | typename T = armnn::ResolveType<ArmnnType>, typename B = armnn::ResolveType<ArmnnBType>> |
| 1637 | LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl( |
| 1638 | armnn::IWorkloadFactory& workloadFactory, |
| 1639 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1640 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1641 | const std::vector<T>& input, |
| 1642 | const std::vector<T>& kernel, |
| 1643 | const std::vector<B>& bias, |
| 1644 | const std::vector<T>& outputExpected, |
| 1645 | const armnn::TensorShape& inputShape, |
| 1646 | const armnn::TensorShape& kernelShape, |
| 1647 | const armnn::TensorShape& outputExpectedShape, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1648 | float qScale, |
| 1649 | int32_t qOffset, |
| 1650 | const armnn::DataLayout layout, |
| 1651 | uint32_t padLeft = 0, |
| 1652 | uint32_t padTop = 0, |
| 1653 | uint32_t padRight = 0, |
| 1654 | uint32_t padBottom = 0, |
| 1655 | uint32_t strideX = 1, |
| 1656 | uint32_t strideY = 1) |
| 1657 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1658 | unsigned int inputNum = armnn::numeric_cast<unsigned int>(inputShape[0]); |
| 1659 | unsigned int inputChannels = armnn::numeric_cast<unsigned int>(inputShape[1]); |
| 1660 | unsigned int inputHeight = armnn::numeric_cast<unsigned int>(inputShape[2]); |
| 1661 | unsigned int inputWidth = armnn::numeric_cast<unsigned int>(inputShape[3]); |
| 1662 | unsigned int kernelChanMul = armnn::numeric_cast<unsigned int>(kernelShape[0]); |
| 1663 | unsigned int kernelChannels = armnn::numeric_cast<unsigned int>(kernelShape[1]); |
| 1664 | unsigned int kernelHeight = armnn::numeric_cast<unsigned int>(kernelShape[2]); |
| 1665 | unsigned int kernelWidth = armnn::numeric_cast<unsigned int>(kernelShape[3]); |
| 1666 | unsigned int outputNum = armnn::numeric_cast<unsigned int>(outputExpectedShape[0]); |
| 1667 | unsigned int outputChannels = armnn::numeric_cast<unsigned int>(outputExpectedShape[1]); |
| 1668 | unsigned int outputHeight = armnn::numeric_cast<unsigned int>(outputExpectedShape[2]); |
| 1669 | unsigned int outputWidth = armnn::numeric_cast<unsigned int>(outputExpectedShape[3]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1670 | |
| 1671 | // If a bias is used, its size must equal the number of output channels. |
| 1672 | bool biasEnabled = bias.size() > 0; |
Narumol Prangnawarat | ac2770a | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 1673 | ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1674 | |
| 1675 | // Creates the tensors. |
| 1676 | armnn::TensorInfo inputTensorInfo = |
| 1677 | armnnUtils::GetTensorInfo(inputNum, inputChannels, inputHeight, inputWidth, layout, ArmnnType); |
| 1678 | armnn::TensorInfo outputTensorInfo = |
| 1679 | armnnUtils::GetTensorInfo(outputNum, outputChannels, outputHeight, outputWidth, layout, ArmnnType); |
| 1680 | armnn::TensorInfo kernelDesc({kernelChanMul, kernelChannels, kernelHeight, kernelWidth}, ArmnnType); |
| 1681 | armnn::TensorInfo biasDesc({static_cast<unsigned int>(bias.size())}, ArmnnBType); |
| 1682 | |
| 1683 | // Set quantization parameters if the requested type is a quantized type. |
| 1684 | if (armnn::IsQuantizedType<T>()) |
| 1685 | { |
| 1686 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1687 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1688 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1689 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1690 | kernelDesc.SetQuantizationScale(qScale); |
| 1691 | kernelDesc.SetQuantizationOffset(qOffset); |
| 1692 | biasDesc.SetQuantizationScale(qScale*qScale); |
| 1693 | biasDesc.SetQuantizationOffset(0); |
| 1694 | } |
| 1695 | |
| 1696 | // Construct the input data. |
| 1697 | std::vector<T> inputData; |
| 1698 | inputData.assign(input.data(), input.data() + inputChannels*inputHeight*inputWidth); |
| 1699 | |
| 1700 | // At this point if we require it permute the input data |
| 1701 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
| 1702 | if (layout == armnn::DataLayout::NHWC) |
| 1703 | { |
| 1704 | std::vector<T> tmp(inputData.size()); |
| 1705 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(T)); |
| 1706 | inputData = tmp; |
| 1707 | } |
| 1708 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1709 | // Construct the output data, with bias applied, as appropriate. |
| 1710 | std::vector<T> outputData; |
| 1711 | outputData.assign(outputExpected.data(), outputExpected.data() + outputChannels*outputHeight*outputWidth); |
| 1712 | if (biasEnabled) |
| 1713 | { |
| 1714 | std::vector<T> biasV; |
| 1715 | biasV.assign(bias.data(), bias.data() + outputChannels); |
| 1716 | ApplyBias(outputData, outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset(), |
| 1717 | biasV, biasDesc.GetQuantizationScale(), biasDesc.GetQuantizationOffset(), |
| 1718 | outputWidth, outputHeight); |
| 1719 | } |
| 1720 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1721 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1722 | |
| 1723 | // At this point if we require it permute the expected output |
| 1724 | if (layout == armnn::DataLayout::NHWC) |
| 1725 | { |
| 1726 | std::vector<T> tmp(outputData.size()); |
| 1727 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp.data(), sizeof(T)); |
| 1728 | outputData = tmp; |
| 1729 | } |
| 1730 | |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1731 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 1732 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 1733 | |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 1734 | armnn::ScopedTensorHandle weightsTensor(kernelDesc); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1735 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1736 | AllocateAndCopyDataToITensorHandle(&weightsTensor, kernel.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1737 | |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 1738 | armnn::ScopedTensorHandle biasTensor(biasDesc); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1739 | if (biasEnabled) |
| 1740 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1741 | AllocateAndCopyDataToITensorHandle(&biasTensor, bias.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1742 | } |
| 1743 | |
| 1744 | armnn::DepthwiseConvolution2dQueueDescriptor data; |
| 1745 | data.m_Weight = &weightsTensor; |
| 1746 | data.m_Bias = &biasTensor; // Still set this whether or not bias is enabled - it can be a source of bugs. |
| 1747 | data.m_Parameters.m_StrideX = strideX; |
| 1748 | data.m_Parameters.m_StrideY = strideY; |
| 1749 | data.m_Parameters.m_PadLeft = padLeft; |
| 1750 | data.m_Parameters.m_PadRight = padRight; |
| 1751 | data.m_Parameters.m_PadTop = padTop; |
| 1752 | data.m_Parameters.m_PadBottom = padBottom; |
| 1753 | data.m_Parameters.m_BiasEnabled = biasEnabled; |
| 1754 | data.m_Parameters.m_DataLayout = layout; |
| 1755 | |
| 1756 | armnn::WorkloadInfo info; |
| 1757 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 1758 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1759 | |
| 1760 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateDepthwiseConvolution2d(data, info); |
| 1761 | inputHandle->Allocate(); |
| 1762 | outputHandle->Allocate(); |
| 1763 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1764 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1765 | |
| 1766 | ExecuteWorkload(*workload, memoryManager); |
| 1767 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1768 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1769 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1770 | return LayerTestResult<T, 4>(actualOutput, |
| 1771 | outputData, |
| 1772 | outputHandle->GetShape(), |
| 1773 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1774 | } |
| 1775 | |
| 1776 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> |
| 1777 | LayerTestResult<T, 4> DepthwiseConvolution2dDepthMul1TestImpl( |
| 1778 | armnn::IWorkloadFactory& workloadFactory, |
| 1779 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1780 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1781 | float qScale, |
| 1782 | int32_t qOffset, |
| 1783 | bool biasEnabled, |
| 1784 | const armnn::DataLayout layout) |
| 1785 | { |
| 1786 | using B = armnn::ResolveType<ArmnnBType>; |
| 1787 | |
| 1788 | unsigned int inputHeight = 3; |
| 1789 | unsigned int inputWidth = 3; |
| 1790 | unsigned int inputChannels = 2; |
| 1791 | unsigned int inputNum = 1; |
| 1792 | |
| 1793 | unsigned int kernelHeight = 3; |
| 1794 | unsigned int kernelWidth = 3; |
| 1795 | unsigned int kernelChannels = inputChannels; |
| 1796 | unsigned int kernelDepthMultiplier = 1; |
| 1797 | |
| 1798 | unsigned int outputHeight = 1; |
| 1799 | unsigned int outputWidth = 1; |
| 1800 | unsigned int outputChannels = kernelChannels; |
| 1801 | unsigned int outputNum = inputNum; |
| 1802 | |
| 1803 | armnn::TensorInfo inputTensorInfo = |
| 1804 | armnnUtils::GetTensorInfo(inputNum, inputChannels, inputHeight, inputWidth, layout, ArmnnType); |
| 1805 | armnn::TensorInfo outputTensorInfo = |
| 1806 | armnnUtils::GetTensorInfo(outputNum, outputChannels, outputHeight, outputWidth, layout, ArmnnType); |
| 1807 | armnn::TensorInfo kernelDesc({kernelDepthMultiplier, kernelChannels, kernelHeight, kernelWidth}, |
| 1808 | ArmnnType); |
| 1809 | armnn::TensorInfo biasDesc({ outputChannels }, ArmnnBType); |
| 1810 | |
| 1811 | // Set quantization parameters if the requested type is a quantized type. |
| 1812 | if(armnn::IsQuantizedType<T>()) |
| 1813 | { |
| 1814 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1815 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1816 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1817 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1818 | kernelDesc.SetQuantizationScale(qScale); |
| 1819 | kernelDesc.SetQuantizationOffset(qOffset); |
| 1820 | biasDesc.SetQuantizationScale(qScale*qScale); |
| 1821 | biasDesc.SetQuantizationOffset(0); |
| 1822 | } |
| 1823 | std::vector<T> inputData = std::vector<T>( |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1824 | QuantizedVector<T>({ |
| 1825 | 1.f, 2.f, 1.f, |
| 1826 | 2.f, 1.f, 2.f, |
| 1827 | 1.f, 2.f, 1.f, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1828 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1829 | 1.f, 2.f, 1.f, |
| 1830 | 2.f, 1.f, 2.f, |
| 1831 | 1.f, 2.f, 1.f, |
| 1832 | }, |
| 1833 | inputTensorInfo.GetQuantizationScale(), |
| 1834 | inputTensorInfo.GetQuantizationOffset())); |
| 1835 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1836 | // at this point if we require it permute the input data |
| 1837 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
| 1838 | if (layout == armnn::DataLayout::NHWC) |
| 1839 | { |
| 1840 | std::vector<T> tmp(inputData.size()); |
| 1841 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(T)); |
| 1842 | inputData = tmp; |
| 1843 | } |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1844 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1845 | std::vector<B> biasV(QuantizedVector<B>({ 0, 2 }, |
| 1846 | biasDesc.GetQuantizationScale(), |
| 1847 | biasDesc.GetQuantizationOffset())); |
| 1848 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1849 | std::vector<T> kernelData = std::vector<T>( |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1850 | QuantizedVector<T>({ |
| 1851 | 1.f, 0.f, 1.f, |
| 1852 | 0.f, 0.f, 0.f, |
| 1853 | -1.f, 0.f, -1.f, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1854 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1855 | 1.f, 0.f, 1.f, |
| 1856 | 0.f, 0.f, 0.f, |
| 1857 | -1.f, 0.f, -1.f, |
| 1858 | }, |
| 1859 | kernelDesc.GetQuantizationScale(), |
| 1860 | kernelDesc.GetQuantizationOffset())); |
| 1861 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1862 | // Manually calculated. |
| 1863 | std::vector<T> outputImage( |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1864 | QuantizedVector<T>({ 0.f, 0.f }, |
| 1865 | outputTensorInfo.GetQuantizationScale(), |
| 1866 | outputTensorInfo.GetQuantizationOffset()) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1867 | ); |
| 1868 | |
| 1869 | // Optionally apply bias to output image. |
| 1870 | if(biasEnabled) |
| 1871 | { |
| 1872 | ApplyBias(outputImage, outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset(), |
| 1873 | biasV, biasDesc.GetQuantizationScale(), biasDesc.GetQuantizationOffset(), |
| 1874 | outputWidth, outputHeight); |
| 1875 | } |
| 1876 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1877 | if (layout == armnn::DataLayout::NHWC) |
| 1878 | { |
| 1879 | std::vector<T> tmp(outputImage.size()); |
| 1880 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputImage.data(), tmp.data(), sizeof(T)); |
| 1881 | outputImage = tmp; |
| 1882 | } |
| 1883 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1884 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1885 | |
| 1886 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 1887 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 1888 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1889 | armnn::DepthwiseConvolution2dQueueDescriptor data; |
| 1890 | armnn::WorkloadInfo info; |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 1891 | armnn::ScopedTensorHandle weightsTensor(kernelDesc); |
| 1892 | armnn::ScopedTensorHandle biasTensor(biasDesc); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1893 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1894 | AllocateAndCopyDataToITensorHandle(&weightsTensor, kernelData.data()); |
| 1895 | AllocateAndCopyDataToITensorHandle(&biasTensor, biasV.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1896 | |
| 1897 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 1898 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1899 | |
| 1900 | data.m_Weight = &weightsTensor; |
| 1901 | data.m_Bias = &biasTensor; // Still set this whether or not bias is enabled. |
| 1902 | data.m_Parameters.m_StrideX = 1; |
| 1903 | data.m_Parameters.m_StrideY = 1; |
| 1904 | data.m_Parameters.m_PadLeft = 0; |
| 1905 | data.m_Parameters.m_PadRight = 0; |
| 1906 | data.m_Parameters.m_PadTop = 0; |
| 1907 | data.m_Parameters.m_PadBottom = 0; |
| 1908 | data.m_Parameters.m_BiasEnabled = biasEnabled; |
| 1909 | data.m_Parameters.m_DataLayout = layout; |
| 1910 | |
| 1911 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateDepthwiseConvolution2d(data, info); |
| 1912 | inputHandle->Allocate(); |
| 1913 | outputHandle->Allocate(); |
| 1914 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1915 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1916 | |
| 1917 | ExecuteWorkload(*workload, memoryManager); |
| 1918 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1919 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1920 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 1921 | return LayerTestResult<T, 4>(actualOutput, |
| 1922 | outputImage, |
| 1923 | outputHandle->GetShape(), |
| 1924 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1925 | } |
| 1926 | |
| 1927 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> |
| 1928 | LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl( |
| 1929 | armnn::IWorkloadFactory& workloadFactory, |
| 1930 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 1931 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1932 | float qScale, |
| 1933 | int32_t qOffset, |
| 1934 | bool biasEnabled, |
| 1935 | const armnn::DataLayout layout) |
| 1936 | { |
| 1937 | using B = armnn::ResolveType<ArmnnBType>; |
| 1938 | |
| 1939 | unsigned int depthMultiplier = 2; |
| 1940 | |
| 1941 | unsigned int inputHeight = 8; |
| 1942 | unsigned int inputWidth = 16; |
| 1943 | unsigned int inputChannels = 2; |
| 1944 | unsigned int inputBatchSize = 1; |
| 1945 | |
| 1946 | unsigned int kernelHeight = 5; |
| 1947 | unsigned int kernelWidth = 3; |
| 1948 | |
| 1949 | unsigned int outputHeight = inputHeight - kernelHeight + 1 + 2; |
| 1950 | unsigned int outputWidth = (inputWidth - kernelWidth + 1)/2; |
| 1951 | unsigned int outputChannels = inputChannels * depthMultiplier; |
| 1952 | unsigned int outputBatchSize = inputBatchSize; |
| 1953 | |
| 1954 | armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( |
| 1955 | inputBatchSize, inputChannels, inputHeight, inputWidth, layout, ArmnnType); |
| 1956 | armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( |
| 1957 | outputBatchSize, outputChannels, outputHeight, outputWidth, layout, ArmnnType); |
| 1958 | armnn::TensorInfo kernelDesc({depthMultiplier, inputChannels, kernelHeight, kernelWidth}, |
| 1959 | ArmnnType); |
| 1960 | armnn::TensorInfo biasDesc({outputChannels}, ArmnnBType); |
| 1961 | |
| 1962 | // Set quantization parameters if the requested type is a quantized type. |
| 1963 | if(armnn::IsQuantizedType<T>()) |
| 1964 | { |
| 1965 | inputTensorInfo.SetQuantizationScale(qScale); |
| 1966 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 1967 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1968 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1969 | kernelDesc.SetQuantizationScale(qScale); |
| 1970 | kernelDesc.SetQuantizationOffset(qOffset); |
| 1971 | biasDesc.SetQuantizationScale(qScale*qScale); |
| 1972 | biasDesc.SetQuantizationOffset(0); |
| 1973 | } |
| 1974 | |
| 1975 | // NOTE: originalInputData is in NCHW format |
| 1976 | std::vector<T> originalInputData = std::vector<T>( |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 1977 | QuantizedVector<T>({ |
| 1978 | 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, |
| 1979 | 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, |
| 1980 | 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, |
| 1981 | 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, |
| 1982 | 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, |
| 1983 | 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, |
| 1984 | 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, |
| 1985 | 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, |
| 1986 | 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, |
| 1987 | 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, |
| 1988 | 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, |
| 1989 | 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, |
| 1990 | 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, |
| 1991 | 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, |
| 1992 | 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, |
| 1993 | 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 |
| 1994 | }, |
| 1995 | inputTensorInfo.GetQuantizationScale(), |
| 1996 | inputTensorInfo.GetQuantizationOffset())); |
| 1997 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 1998 | std::vector<T> inputData = originalInputData; |
| 1999 | // at this point if we require it permute the input data |
| 2000 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
| 2001 | if (layout == armnn::DataLayout::NHWC) |
| 2002 | { |
| 2003 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, |
| 2004 | originalInputData.data(), inputData.data(), sizeof(T)); |
| 2005 | } |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2006 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2007 | std::vector<B> biasV = QuantizedVector<B>({ 0, 2, 1, -1 }, |
| 2008 | biasDesc.GetQuantizationScale(), |
| 2009 | biasDesc.GetQuantizationOffset()); |
| 2010 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2011 | std::vector<T> kernelData = std::vector<T>( |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2012 | QuantizedVector<T>({ |
| 2013 | 1, 1, 1, |
| 2014 | 1, -1, 1, |
| 2015 | 1, 1, 1, |
| 2016 | 1, 1, 1, |
| 2017 | 1, 1, 1, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2018 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2019 | 2, 2, 2, |
| 2020 | 2, 2, 2, |
| 2021 | 2, 2, 2, |
| 2022 | 2, 2, 2, |
| 2023 | 2, 2, 2, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2024 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2025 | 0, 0, 0, |
| 2026 | 0, -1, 0, |
| 2027 | 0, 0, 0, |
| 2028 | 0, 0, 0, |
| 2029 | 0, 0, 0, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2030 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2031 | 0, 0, 0, |
| 2032 | 0, 0, 0, |
| 2033 | 0, 1, 0, |
| 2034 | 0, 0, 0, |
| 2035 | 0, 0, 0 |
| 2036 | }, |
| 2037 | kernelDesc.GetQuantizationScale(), |
| 2038 | kernelDesc.GetQuantizationOffset())); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2039 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2040 | // Manually calculated. |
| 2041 | std::vector<T> originalOutputImage = std::vector<T>( |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2042 | QuantizedVector<T>({ |
| 2043 | 3.5f, 3.5f, 3.5f, 3.5f, 3.5f, 3.5f, 3.5f, |
| 2044 | 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, |
| 2045 | 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, |
| 2046 | 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, |
| 2047 | 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, |
| 2048 | 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2049 | |
| 2050 | -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2051 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2052 | -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, |
| 2053 | -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, |
| 2054 | -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, |
| 2055 | -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, |
| 2056 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2057 | 8.0f, 8.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2058 | 10.0f, 10.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2059 | 10.0f, 10.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2060 | 10.0f, 10.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2061 | 10.0f, 10.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2062 | 8.0f, 8.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2063 | |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2064 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2065 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2066 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2067 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2068 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 2069 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f |
| 2070 | }, |
| 2071 | outputTensorInfo.GetQuantizationScale(), |
| 2072 | outputTensorInfo.GetQuantizationOffset())); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2073 | |
| 2074 | // Optionally apply bias to output image. |
| 2075 | if(biasEnabled) |
| 2076 | { |
| 2077 | ApplyBias(originalOutputImage, |
| 2078 | outputTensorInfo.GetQuantizationScale(), |
| 2079 | outputTensorInfo.GetQuantizationOffset(), |
| 2080 | biasV, |
| 2081 | biasDesc.GetQuantizationScale(), |
| 2082 | biasDesc.GetQuantizationOffset(), |
| 2083 | outputWidth, |
| 2084 | outputHeight); |
| 2085 | } |
| 2086 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2087 | std::vector<T> outputImage = originalOutputImage; |
| 2088 | if (layout == armnn::DataLayout::NHWC) |
| 2089 | { |
| 2090 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, |
| 2091 | originalOutputImage.data(), outputImage.data(), sizeof(T)); |
| 2092 | } |
| 2093 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2094 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2095 | |
| 2096 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 2097 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 2098 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2099 | armnn::DepthwiseConvolution2dQueueDescriptor data; |
| 2100 | armnn::WorkloadInfo info; |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 2101 | armnn::ScopedTensorHandle weightsTensor(kernelDesc); |
| 2102 | armnn::ScopedTensorHandle biasTensor(biasDesc); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2103 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2104 | AllocateAndCopyDataToITensorHandle(&weightsTensor, kernelData.data()); |
| 2105 | AllocateAndCopyDataToITensorHandle(&biasTensor, biasV.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2106 | |
| 2107 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 2108 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 2109 | |
| 2110 | data.m_Weight = &weightsTensor; |
| 2111 | data.m_Bias = &biasTensor; // Still set this whether or not bias is enabled. |
| 2112 | data.m_Parameters.m_StrideX = 2; |
| 2113 | data.m_Parameters.m_StrideY = 1; |
| 2114 | data.m_Parameters.m_PadLeft = 0; |
| 2115 | data.m_Parameters.m_PadRight = 0; |
| 2116 | data.m_Parameters.m_PadTop = 1; |
| 2117 | data.m_Parameters.m_PadBottom = 1; |
| 2118 | data.m_Parameters.m_BiasEnabled = biasEnabled; |
| 2119 | data.m_Parameters.m_DataLayout = layout; |
| 2120 | |
| 2121 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateDepthwiseConvolution2d(data, info); |
| 2122 | inputHandle->Allocate(); |
| 2123 | outputHandle->Allocate(); |
| 2124 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2125 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2126 | |
| 2127 | ExecuteWorkload(*workload, memoryManager); |
| 2128 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2129 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2130 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2131 | return LayerTestResult<T, 4>(actualOutput, |
| 2132 | outputImage, |
| 2133 | outputHandle->GetShape(), |
| 2134 | outputTensorInfo.GetShape()); |
| 2135 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2136 | } |
| 2137 | |
| 2138 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 2139 | typename T = armnn::ResolveType<ArmnnType>, typename B = armnn::ResolveType<ArmnnBType>> |
| 2140 | LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl( |
| 2141 | armnn::IWorkloadFactory& workloadFactory, |
| 2142 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2143 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2144 | const std::vector<T>& originalInput, |
| 2145 | const std::vector<T>& originalKernel, |
| 2146 | const std::vector<B>& bias, |
| 2147 | const std::vector<T>& originalOutputExpected, |
| 2148 | const armnn::TensorShape& originalInputShape, |
| 2149 | const armnn::TensorShape& originalKernelShape, |
| 2150 | const armnn::TensorShape& originalOutputExpectedShape, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2151 | float qScale, |
| 2152 | int32_t qOffset, |
| 2153 | const armnn::DataLayout layout = armnn::DataLayout::NCHW, |
| 2154 | uint32_t padLeft = 0, |
| 2155 | uint32_t padTop = 0, |
| 2156 | uint32_t padRight = 0, |
| 2157 | uint32_t padBottom = 0, |
| 2158 | uint32_t strideX = 1, |
| 2159 | uint32_t strideY = 1, |
| 2160 | uint32_t dilationX = 1, |
| 2161 | uint32_t dilationY = 1) |
| 2162 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2163 | unsigned int inputHeight = armnn::numeric_cast<unsigned int>(originalInputShape[2]); |
| 2164 | unsigned int inputWidth = armnn::numeric_cast<unsigned int>(originalInputShape[3]); |
| 2165 | unsigned int inputChannels = armnn::numeric_cast<unsigned int>(originalInputShape[1]); |
| 2166 | unsigned int inputNum = armnn::numeric_cast<unsigned int>(originalInputShape[0]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2167 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2168 | unsigned int outputHeight = armnn::numeric_cast<unsigned int>(originalOutputExpectedShape[2]); |
| 2169 | unsigned int outputWidth = armnn::numeric_cast<unsigned int>(originalOutputExpectedShape[3]); |
| 2170 | unsigned int outputChannels = armnn::numeric_cast<unsigned int>(originalOutputExpectedShape[1]); |
| 2171 | unsigned int outputNum = armnn::numeric_cast<unsigned int>(originalOutputExpectedShape[0]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2172 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2173 | unsigned int kernelHeight = armnn::numeric_cast<unsigned int>(originalKernelShape[2]); |
| 2174 | unsigned int kernelWidth = armnn::numeric_cast<unsigned int>(originalKernelShape[3]); |
| 2175 | unsigned int kernelChannels = armnn::numeric_cast<unsigned int>(originalKernelShape[1]); |
| 2176 | unsigned int kernelDepthMul = armnn::numeric_cast<unsigned int>(originalKernelShape[0]); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2177 | |
| 2178 | bool biasEnabled = bias.size() > 0; |
| 2179 | |
| 2180 | // 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] | 2181 | ARMNN_ASSERT(inputNum == 1); |
| 2182 | ARMNN_ASSERT(outputNum == 1); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2183 | |
| 2184 | // 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] | 2185 | ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2186 | |
| 2187 | |
| 2188 | // Note these tensors will use two (identical) batches. |
| 2189 | armnn::TensorInfo inputTensorInfo = |
| 2190 | armnnUtils::GetTensorInfo(2*inputNum, inputChannels, inputHeight, inputWidth, layout, ArmnnType); |
| 2191 | armnn::TensorInfo outputTensorInfo = |
| 2192 | armnnUtils::GetTensorInfo(2*outputNum, outputChannels, outputHeight, outputWidth, layout, ArmnnType); |
| 2193 | |
| 2194 | // Kernel must be NCHW layout always, independently of the layout of the input and output for depthwise convolution. |
| 2195 | armnn::TensorInfo kernelDesc({kernelDepthMul, kernelChannels, kernelHeight, kernelWidth}, ArmnnType); |
| 2196 | |
| 2197 | armnn::TensorInfo biasDesc({static_cast<unsigned int>(bias.size())}, ArmnnBType); |
| 2198 | |
| 2199 | // Set quantization parameters if the requested type is a quantized type. |
| 2200 | if(armnn::IsQuantizedType<T>()) |
| 2201 | { |
| 2202 | inputTensorInfo.SetQuantizationScale(qScale); |
| 2203 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 2204 | outputTensorInfo.SetQuantizationScale(qScale); |
| 2205 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 2206 | kernelDesc.SetQuantizationScale(qScale); |
| 2207 | kernelDesc.SetQuantizationOffset(qOffset); |
| 2208 | biasDesc.SetQuantizationScale(qScale*qScale); |
| 2209 | biasDesc.SetQuantizationOffset(0); |
| 2210 | } |
| 2211 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2212 | // Construct input data |
| 2213 | std::vector<T> input; |
| 2214 | input.assign(originalInput.data(), originalInput.data() + 1*inputChannels*inputHeight*inputWidth); |
| 2215 | std::vector<T> inputData; |
| 2216 | inputData.insert(inputData.end(), input.begin(), input.end()); |
| 2217 | inputData.insert(inputData.end(), input.begin(), input.end()); |
| 2218 | |
| 2219 | // at this point if we require it permute the input data |
| 2220 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
| 2221 | if (layout == armnn::DataLayout::NHWC) |
| 2222 | { |
| 2223 | std::vector<T> tmp(inputData.size()); |
| 2224 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(T)); |
| 2225 | inputData = tmp; |
| 2226 | } |
| 2227 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2228 | std::vector<T> output; |
| 2229 | output.assign(originalOutputExpected.data(), |
| 2230 | originalOutputExpected.data() + outputChannels*outputHeight*outputWidth); |
| 2231 | |
| 2232 | // Apply bias to output data if it is enabled. |
| 2233 | if(biasEnabled) |
| 2234 | { |
| 2235 | std::vector<T> biasV; |
| 2236 | biasV.assign(bias.data(), bias.data() + outputChannels); |
| 2237 | ApplyBias(output, outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset(), |
| 2238 | biasV, biasDesc.GetQuantizationScale(), biasDesc.GetQuantizationOffset(), |
| 2239 | outputWidth, outputHeight); |
| 2240 | } |
| 2241 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2242 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
| 2243 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2244 | // Construct expected output data |
| 2245 | std::vector<T> outputData; |
| 2246 | outputData.insert(outputData.end(), output.begin(), output.end()); |
| 2247 | outputData.insert(outputData.end(), output.begin(), output.end()); |
| 2248 | |
| 2249 | // at this point if we require it permute the expected output |
| 2250 | if (layout == armnn::DataLayout::NHWC) |
| 2251 | { |
| 2252 | std::vector<T> tmp(outputData.size()); |
| 2253 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp.data(), sizeof(T)); |
| 2254 | outputData = tmp; |
| 2255 | } |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2256 | |
| 2257 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 2258 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 2259 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2260 | armnn::DepthwiseConvolution2dQueueDescriptor data; |
| 2261 | armnn::WorkloadInfo info; |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 2262 | armnn::ScopedTensorHandle weightsTensor(kernelDesc); |
| 2263 | armnn::ScopedTensorHandle biasTensor(biasDesc); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2264 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2265 | AllocateAndCopyDataToITensorHandle(&weightsTensor, originalKernel.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2266 | |
| 2267 | if(biasEnabled) |
| 2268 | { |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2269 | AllocateAndCopyDataToITensorHandle(&biasTensor, bias.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2270 | } |
| 2271 | |
| 2272 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 2273 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 2274 | |
| 2275 | data.m_Weight = &weightsTensor; |
| 2276 | data.m_Bias = &biasTensor; // Still set this whether or not bias is enabled - can be a source of bugs. |
| 2277 | data.m_Parameters.m_StrideX = strideX; |
| 2278 | data.m_Parameters.m_StrideY = strideY; |
| 2279 | data.m_Parameters.m_PadLeft = padLeft; |
| 2280 | data.m_Parameters.m_PadRight = padRight; |
| 2281 | data.m_Parameters.m_PadTop = padTop; |
| 2282 | data.m_Parameters.m_PadBottom = padBottom; |
| 2283 | data.m_Parameters.m_BiasEnabled = biasEnabled; |
| 2284 | data.m_Parameters.m_DataLayout = layout; |
| 2285 | data.m_Parameters.m_DilationX = dilationX; |
| 2286 | data.m_Parameters.m_DilationY = dilationY; |
| 2287 | |
| 2288 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateDepthwiseConvolution2d(data, info); |
| 2289 | inputHandle->Allocate(); |
| 2290 | outputHandle->Allocate(); |
| 2291 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2292 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2293 | |
| 2294 | ExecuteWorkload(*workload, memoryManager); |
| 2295 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2296 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2297 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2298 | return LayerTestResult<T, 4>(actualOutput, |
| 2299 | outputData, |
| 2300 | outputHandle->GetShape(), |
| 2301 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2302 | } |
| 2303 | |
| 2304 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 2305 | typename T = armnn::ResolveType<ArmnnType>> |
| 2306 | LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestCommon( |
| 2307 | armnn::IWorkloadFactory& workloadFactory, |
| 2308 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2309 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2310 | float qScale, |
| 2311 | int32_t qOffset, |
| 2312 | bool biasEnabled, |
| 2313 | const armnn::DataLayout layout) |
| 2314 | { |
| 2315 | // Use a single-batch 2-channel 5x5 image as input. |
| 2316 | armnn::TensorInfo inputTensorInfo({ 1, 2, 5, 5 }, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2317 | auto input = QuantizedVector<T>( |
| 2318 | { |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2319 | 0, 1, 2, 3, 4, |
| 2320 | 5, 6, 7, 8, 9, |
| 2321 | 10, 11, 12, 13, 14, |
| 2322 | 15, 16, 17, 18, 19, |
| 2323 | 20, 21, 22, 23, 24, |
| 2324 | |
| 2325 | 25, 26, 27, 28, 29, |
| 2326 | 30, 31, 32, 33, 34, |
| 2327 | 35, 36, 37, 38, 39, |
| 2328 | 40, 41, 42, 43, 44, |
| 2329 | 45, 46, 47, 48, 49 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2330 | }, |
| 2331 | inputTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2332 | inputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2333 | |
| 2334 | // Use a depth multiplier of 1 on a 2-channel 4x4 kernel. |
| 2335 | armnn::TensorInfo kernelTensorInfo({ 1, 2, 4, 4 }, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2336 | auto kernel = QuantizedVector<T>( |
| 2337 | { |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2338 | 32, 31, 30, 29, |
| 2339 | 28, 27, 26, 25, |
| 2340 | 24, 23, 22, 21, |
| 2341 | 20, 19, 18, 17, |
| 2342 | |
| 2343 | 16, 15, 14, 13, |
| 2344 | 12, 11, 10, 9, |
| 2345 | 8, 7, 6, 5, |
| 2346 | 4, 3, 2, 1 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2347 | }, |
| 2348 | kernelTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2349 | kernelTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2350 | |
| 2351 | // Expected output is 1 batch of a 2-channel 5x5 image. |
| 2352 | // Calculated using the python tensorflow library with strideX=1, strideY=1. |
| 2353 | armnn::TensorInfo outputTensorInfo({ 1, 2, 5, 5 }, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2354 | auto expectedOutput = QuantizedVector<T>( |
| 2355 | { |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2356 | 1062, 1580, 1850, 1530, 1117, |
| 2357 | 2140, 3108, 3500, 2842, 2042, |
| 2358 | 3580, 5068, 5460, 4342, 3062, |
| 2359 | 3618, 5072, 5390, 4248, 2971, |
| 2360 | 3074, 4282, 4510, 3533, 2457, |
| 2361 | |
| 2362 | 1550, 2284, 2362, 1955, 1428, |
| 2363 | 2910, 4206, 4342, 3528, 2536, |
| 2364 | 3390, 4886, 5022, 4068, 2916, |
| 2365 | 3566, 5056, 5182, 4133, 2922, |
| 2366 | 3100, 4352, 4452, 3517, 2465 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2367 | }, |
| 2368 | outputTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2369 | outputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2370 | |
| 2371 | return DepthwiseConvolution2dAsymmetricTestImpl<ArmnnType, ArmnnBType>( |
| 2372 | workloadFactory, |
| 2373 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2374 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2375 | input, |
| 2376 | kernel, |
| 2377 | GetBias2<ArmnnBType>(biasEnabled, qScale * qScale), |
| 2378 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2379 | inputTensorInfo.GetShape(), |
| 2380 | kernelTensorInfo.GetShape(), |
| 2381 | outputTensorInfo.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2382 | qScale, |
| 2383 | qOffset, |
| 2384 | layout, |
| 2385 | 1, // Padding left. |
| 2386 | 1, // Padding top. |
| 2387 | 2, // Padding right. |
| 2388 | 2, // Padding bottom. |
| 2389 | 1, // strideX |
| 2390 | 1); // strideY |
| 2391 | } |
| 2392 | |
| 2393 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 2394 | typename T = armnn::ResolveType<ArmnnType>> |
| 2395 | LayerTestResult<T, 4> DepthwiseConvolution2dNhwcTestCommon( |
| 2396 | armnn::IWorkloadFactory& workloadFactory, |
| 2397 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2398 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2399 | float qScale, |
| 2400 | int32_t qOffset, |
| 2401 | bool biasEnabled) |
| 2402 | { |
| 2403 | auto layout = armnn::DataLayout::NHWC; |
| 2404 | |
| 2405 | armnn::TensorInfo inputTensorInfo({ 1, 2, 5, 5}, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2406 | auto input = QuantizedVector<T>( |
| 2407 | { |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2408 | 0, 1, 2, 3, 4, |
| 2409 | 5, 6, 7, 8, 9, |
| 2410 | 10, 11, 12, 13, 14, |
| 2411 | 15, 16, 17, 18, 19, |
| 2412 | 20, 21, 22, 23, 24, |
| 2413 | |
| 2414 | 25, 26, 27, 28, 29, |
| 2415 | 30, 31, 32, 33, 34, |
| 2416 | 35, 36, 37, 38, 39, |
| 2417 | 40, 41, 42, 43, 44, |
| 2418 | 45, 46, 47, 48, 49 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2419 | }, |
| 2420 | inputTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2421 | inputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2422 | |
| 2423 | armnn::TensorInfo kernelTensorInfo({ 1, 2, 4, 4 }, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2424 | auto kernel = QuantizedVector<T>( |
| 2425 | { |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2426 | 32, 31, 30, 29, |
| 2427 | 28, 27, 26, 25, |
| 2428 | 24, 23, 22, 21, |
| 2429 | 20, 19, 18, 17, |
| 2430 | |
| 2431 | 16, 15, 14, 13, |
| 2432 | 12, 11, 10, 9, |
| 2433 | 8, 7, 6, 5, |
| 2434 | 4, 3, 2, 1 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2435 | }, |
| 2436 | kernelTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2437 | kernelTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2438 | |
| 2439 | armnn::TensorInfo outputTensorInfo({ 1, 2, 5, 5}, ArmnnType); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2440 | auto expectedOutput = QuantizedVector<T>( |
| 2441 | { |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2442 | 1062, 1580, 1850, 1530, 1117, |
| 2443 | 2140, 3108, 3500, 2842, 2042, |
| 2444 | 3580, 5068, 5460, 4342, 3062, |
| 2445 | 3618, 5072, 5390, 4248, 2971, |
| 2446 | 3074, 4282, 4510, 3533, 2457, |
| 2447 | |
| 2448 | 1550, 2284, 2362, 1955, 1428, |
| 2449 | 2910, 4206, 4342, 3528, 2536, |
| 2450 | 3390, 4886, 5022, 4068, 2916, |
| 2451 | 3566, 5056, 5182, 4133, 2922, |
| 2452 | 3100, 4352, 4452, 3517, 2465 |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2453 | }, |
| 2454 | outputTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2455 | outputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2456 | |
| 2457 | return DepthwiseConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 2458 | workloadFactory, |
| 2459 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2460 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2461 | input, |
| 2462 | kernel, |
| 2463 | GetBias2<ArmnnBType>(biasEnabled, qScale * qScale), |
| 2464 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2465 | inputTensorInfo.GetShape(), |
| 2466 | kernelTensorInfo.GetShape(), |
| 2467 | outputTensorInfo.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2468 | qScale, |
| 2469 | qOffset, |
| 2470 | layout, |
| 2471 | 1, // Padding left. |
| 2472 | 1, // Padding top. |
| 2473 | 2, // Padding right. |
| 2474 | 2, // Padding bottom. |
| 2475 | 1, // strideX |
| 2476 | 1); // strideY |
| 2477 | } |
| 2478 | |
| 2479 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, |
| 2480 | typename T = armnn::ResolveType<ArmnnType>> |
| 2481 | LayerTestResult<T, 4> SimpleDepthwiseConvolution2d3x3Dilation3x3NhwcTestCommon( |
| 2482 | armnn::IWorkloadFactory& workloadFactory, |
| 2483 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2484 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2485 | float qScale, |
| 2486 | int32_t qOffset, |
| 2487 | bool biasEnabled) |
| 2488 | { |
| 2489 | auto layout = armnn::DataLayout::NHWC; |
| 2490 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2491 | armnn::TensorInfo inputTensorInfo({ 1, 1, 9, 9 }, ArmnnType); |
| 2492 | auto input = QuantizedVector<T>( |
| 2493 | { |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2494 | 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2495 | 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2496 | 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2497 | 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2498 | 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2499 | 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2500 | 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2501 | 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2502 | 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| 2503 | }, |
| 2504 | inputTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2505 | inputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2506 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2507 | armnn::TensorInfo kernelTensorInfo({ 1, 1, 3, 3 }, ArmnnType); |
| 2508 | auto kernel = QuantizedVector<T>( |
| 2509 | { |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2510 | 1, 2, 3, |
| 2511 | 4, 5, 6, |
| 2512 | 7, 8, 9 |
| 2513 | }, |
| 2514 | kernelTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2515 | kernelTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2516 | |
| 2517 | uint32_t padLeft = 0; |
| 2518 | uint32_t padTop = 0; |
| 2519 | uint32_t padRight = 0; |
| 2520 | uint32_t padBottom = 0; |
| 2521 | uint32_t strideX = 1; |
| 2522 | uint32_t strideY = 1; |
| 2523 | uint32_t dilationX = 3; |
| 2524 | uint32_t dilationY = 3; |
| 2525 | |
| 2526 | // 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^] | 2527 | armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, ArmnnType); |
| 2528 | auto expectedOutput = QuantizedVector<T>( |
| 2529 | { |
Aron Virginas-Tar | 48623a0 | 2019-10-22 10:00:28 +0100 | [diff] [blame] | 2530 | 5, 5, 5, |
| 2531 | 5, 5, 5, |
| 2532 | 5, 5, 5 |
| 2533 | }, |
| 2534 | outputTensorInfo.GetQuantizationScale(), |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2535 | outputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2536 | |
| 2537 | return DepthwiseConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 2538 | workloadFactory, |
| 2539 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2540 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2541 | input, |
| 2542 | kernel, |
| 2543 | GetBias2<ArmnnBType>(biasEnabled, qScale * qScale), |
| 2544 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2545 | inputTensorInfo.GetShape(), |
| 2546 | kernelTensorInfo.GetShape(), |
| 2547 | outputTensorInfo.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2548 | qScale, |
| 2549 | qOffset, |
| 2550 | layout, |
| 2551 | padLeft, |
| 2552 | padTop, |
| 2553 | padRight, |
| 2554 | padBottom, |
| 2555 | strideX, |
| 2556 | strideY, |
| 2557 | dilationX, |
| 2558 | dilationY); |
| 2559 | } |
| 2560 | |
| 2561 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> |
| 2562 | LayerTestResult<T, 4> DepthwiseConvolution2d3x3DilationTestCommon( |
| 2563 | armnn::IWorkloadFactory& workloadFactory, |
| 2564 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2565 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2566 | const std::vector<float>& inputNoQuantizedValues, |
| 2567 | armnn::TensorInfo& inputTensorInfo, |
| 2568 | const std::vector<float>& kernelNoQuantizedValues, |
| 2569 | armnn::TensorInfo& kernelTensorInfo, |
| 2570 | const std::vector<float>& outputExpectedNoQuantizedValues, |
| 2571 | armnn::TensorInfo& outputTensorInfo, |
| 2572 | uint32_t dilationX, |
| 2573 | uint32_t dilationY, |
| 2574 | armnn::DataLayout layout = armnn::DataLayout::NCHW, |
| 2575 | bool biasEnabled = false) |
| 2576 | { |
| 2577 | float qScale; |
| 2578 | int32_t qOffset; |
| 2579 | switch (ArmnnType) |
| 2580 | { |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 2581 | case armnn::DataType::QAsymmS8: |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 2582 | case armnn::DataType::QAsymmU8: |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2583 | { |
| 2584 | qScale = 0.1f; |
| 2585 | qOffset = 128; |
| 2586 | break; |
| 2587 | } |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 2588 | case armnn::DataType::QSymmS16: |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2589 | { |
| 2590 | qScale = 0.1f; |
| 2591 | qOffset = 0; |
| 2592 | break; |
| 2593 | } |
| 2594 | case armnn::DataType::Float32: |
| 2595 | default: |
| 2596 | { |
| 2597 | qScale = 0.f; |
| 2598 | qOffset = 0; |
| 2599 | break; |
| 2600 | } |
| 2601 | } |
| 2602 | |
| 2603 | inputTensorInfo.SetQuantizationScale(qScale); |
| 2604 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 2605 | kernelTensorInfo.SetQuantizationScale(qScale); |
| 2606 | kernelTensorInfo.SetQuantizationOffset(qOffset); |
| 2607 | outputTensorInfo.SetQuantizationScale(qScale); |
| 2608 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 2609 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2610 | auto input = QuantizedVector<T>(inputNoQuantizedValues, |
| 2611 | inputTensorInfo.GetQuantizationScale(), |
| 2612 | inputTensorInfo.GetQuantizationOffset()); |
| 2613 | auto kernel = QuantizedVector<T>(kernelNoQuantizedValues, |
| 2614 | kernelTensorInfo.GetQuantizationScale(), |
| 2615 | kernelTensorInfo.GetQuantizationOffset()); |
| 2616 | auto expectedOutput = QuantizedVector<T>(outputExpectedNoQuantizedValues, |
| 2617 | outputTensorInfo.GetQuantizationScale(), |
| 2618 | outputTensorInfo.GetQuantizationOffset()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2619 | |
| 2620 | uint32_t padLeft = 0; |
| 2621 | uint32_t padTop = 0; |
| 2622 | uint32_t padRight = 0; |
| 2623 | uint32_t padBottom = 0; |
| 2624 | uint32_t strideX = 1; |
| 2625 | uint32_t strideY = 1; |
| 2626 | |
| 2627 | return DepthwiseConvolution2dTestImpl<ArmnnType, ArmnnBType>( |
| 2628 | workloadFactory, |
| 2629 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2630 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2631 | input, |
| 2632 | kernel, |
| 2633 | GetBias<ArmnnBType>(biasEnabled, qScale * qScale, outputTensorInfo, layout), |
| 2634 | expectedOutput, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 2635 | inputTensorInfo.GetShape(), |
| 2636 | kernelTensorInfo.GetShape(), |
| 2637 | outputTensorInfo.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2638 | qScale, |
| 2639 | qOffset, |
| 2640 | layout, |
| 2641 | padLeft, |
| 2642 | padTop, |
| 2643 | padRight, |
| 2644 | padBottom, |
| 2645 | strideX, |
| 2646 | strideY, |
| 2647 | dilationX, |
| 2648 | dilationY); |
| 2649 | } |
| 2650 | |
| 2651 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T> |
| 2652 | LayerTestResult<T, 4> DepthwiseConvolution2d3x3Dilation3x3Test( |
| 2653 | armnn::IWorkloadFactory& workloadFactory, |
| 2654 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2655 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2656 | bool biasEnabled, |
| 2657 | const armnn::DataLayout layout) |
| 2658 | { |
| 2659 | armnn::TensorInfo inputTensorInfo({1, 1, 10, 10}, ArmnnType); |
| 2660 | std::vector<float> inputNoQuantizedValues = |
| 2661 | { |
| 2662 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2663 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2664 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2665 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2666 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2667 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2668 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2669 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2670 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2671 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| 2672 | }; |
| 2673 | |
| 2674 | armnn::TensorInfo kernelTensorInfo({ 1, 1, 3, 3}, ArmnnType); |
| 2675 | std::vector<float> kernelNoQuantizedValues = |
| 2676 | { |
| 2677 | 1, 2, 3, |
| 2678 | 4, 5, 6, |
| 2679 | 7, 8, 9 |
| 2680 | }; |
| 2681 | |
| 2682 | // Since the dilation rate is 3 this will dilate the kernel to be like 7x7, |
| 2683 | // therefore the output will be 4x4: (I−K+2P)/S +1 => (10-7 +0)/1 +1 |
| 2684 | armnn::TensorInfo outputTensorInfo({ 1, 1, 4, 4}, ArmnnType); |
| 2685 | std::vector<float> outputExpectedNoQuantizedValues = |
| 2686 | { |
| 2687 | 6., 5., 5., 5., |
| 2688 | 6., 5., 5., 5., |
| 2689 | 6., 5., 5., 5., |
| 2690 | 3., 2., 2., 2. |
| 2691 | }; |
| 2692 | |
| 2693 | return DepthwiseConvolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( |
| 2694 | workloadFactory, |
| 2695 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2696 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2697 | inputNoQuantizedValues, |
| 2698 | inputTensorInfo, |
| 2699 | kernelNoQuantizedValues, |
| 2700 | kernelTensorInfo, |
| 2701 | outputExpectedNoQuantizedValues, |
| 2702 | outputTensorInfo, |
| 2703 | 3, |
| 2704 | 3, |
| 2705 | layout, |
| 2706 | biasEnabled); |
| 2707 | } |
| 2708 | |
| 2709 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T> |
| 2710 | LayerTestResult<T, 4> DepthwiseConvolution2d2x3x3Dilation3x3Test( |
| 2711 | armnn::IWorkloadFactory& workloadFactory, |
| 2712 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2713 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2714 | bool biasEnabled, |
| 2715 | const armnn::DataLayout layout) |
| 2716 | { |
| 2717 | armnn::TensorInfo inputTensorInfo({1, 2, 10, 10}, ArmnnType); |
| 2718 | std::vector<float> inputNoQuantizedValues = |
| 2719 | { |
| 2720 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2721 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2722 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2723 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2724 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2725 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2726 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2727 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2728 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2729 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2730 | |
| 2731 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2732 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2733 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2734 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2735 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2736 | 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, |
| 2737 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2738 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2739 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 2740 | 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| 2741 | }; |
| 2742 | |
| 2743 | armnn::TensorInfo kernelTensorInfo({ 1, 2, 3, 3}, ArmnnType); |
| 2744 | std::vector<float> kernelNoQuantizedValues = |
| 2745 | { |
| 2746 | 1, 2, 3, |
| 2747 | 4, 5, 6, |
| 2748 | 7, 8, 9, |
| 2749 | |
| 2750 | 1, 2, 3, |
| 2751 | 4, 5, 6, |
| 2752 | 7, 8, 9 |
| 2753 | }; |
| 2754 | |
| 2755 | // Since the dilation rate is 3 this will dilate the kernel to be like 7x7, |
| 2756 | // therefore the output will be 2x4x4: (I−K+2P)/S +1 => (10-7 +0)/1 +1 |
| 2757 | armnn::TensorInfo outputTensorInfo({ 1, 2, 4, 4}, ArmnnType); |
| 2758 | std::vector<float> outputExpectedNoQuantizedValues = |
| 2759 | { |
| 2760 | 6., 5., 5., 5., |
| 2761 | 6., 5., 5., 5., |
| 2762 | 6., 5., 5., 5., |
| 2763 | 3., 2., 2., 2., |
| 2764 | |
| 2765 | 6., 5., 5., 5., |
| 2766 | 6., 5., 5., 5., |
| 2767 | 6., 5., 5., 5., |
| 2768 | 3., 2., 2., 2. |
| 2769 | }; |
| 2770 | |
| 2771 | return DepthwiseConvolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( |
| 2772 | workloadFactory, |
| 2773 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2774 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2775 | inputNoQuantizedValues, |
| 2776 | inputTensorInfo, |
| 2777 | kernelNoQuantizedValues, |
| 2778 | kernelTensorInfo, |
| 2779 | outputExpectedNoQuantizedValues, |
| 2780 | outputTensorInfo, |
| 2781 | 3, |
| 2782 | 3, |
| 2783 | layout, |
| 2784 | biasEnabled); |
| 2785 | } |
| 2786 | |
| 2787 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T> |
| 2788 | LayerTestResult<T, 4> DepthwiseConvolution2dMult4Test( |
| 2789 | armnn::IWorkloadFactory& workloadFactory, |
| 2790 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2791 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2792 | bool biasEnabled, |
| 2793 | const armnn::DataLayout layout) |
| 2794 | { |
| 2795 | armnn::TensorInfo inputTensorInfo({1, 2, 3, 3}, ArmnnType); |
| 2796 | std::vector<float> inputNoQuantizedValues = |
| 2797 | { |
| 2798 | 10.0, 10.0, 10.0, |
| 2799 | 10.0, 10.0, 10.0, |
| 2800 | 10.0, 10.0, 10.0, |
| 2801 | |
| 2802 | 21.0, 22.0, 23.0, |
| 2803 | 24.0, 25.0, 26.0, |
| 2804 | 27.0, 28.0, 29.0 |
| 2805 | }; |
| 2806 | |
| 2807 | armnn::TensorInfo kernelTensorInfo({ 4, 2, 2, 2}, ArmnnType); |
| 2808 | |
| 2809 | std::vector<float> kernelNoQuantizedValues = |
| 2810 | { |
| 2811 | 0.25f, 0.25f, |
| 2812 | 0.25f, 0.25f, |
| 2813 | |
| 2814 | 0.25f, 0.25f, |
| 2815 | 0.25f, 0.25f, |
| 2816 | |
| 2817 | 0.0f , 0.0f, |
| 2818 | 0.0f , 0.1f, |
| 2819 | |
| 2820 | 0.0f , 0.0f, |
| 2821 | 0.0f , 0.1f, |
| 2822 | |
| 2823 | 0.2f , 0.0f, |
| 2824 | 0.0f , 0.0f, |
| 2825 | |
| 2826 | 0.2f , 0.0f, |
| 2827 | 0.0f , 0.0f, |
| 2828 | |
| 2829 | 0.0f , 0.3f, |
| 2830 | 0.0f , 0.0f, |
| 2831 | |
| 2832 | 0.0f , 0.3f, |
| 2833 | 0.0f , 0.0f |
| 2834 | }; |
| 2835 | |
| 2836 | armnn::TensorInfo outputTensorInfo({ 1, 8, 2, 2}, ArmnnType); |
| 2837 | std::vector<float> outputExpectedNoQuantizedValues = |
| 2838 | { |
| 2839 | 10.f, 10.f, |
| 2840 | 10.f, 10.f, |
| 2841 | |
| 2842 | 1.f, 1.f, |
| 2843 | 1.f, 1.f, |
| 2844 | |
| 2845 | 2.f, 2.f, |
| 2846 | 2.f, 2.f, |
| 2847 | |
| 2848 | 3.f, 3.f, |
| 2849 | 3.f, 3.f, |
| 2850 | |
| 2851 | 23.f, 24.f, |
| 2852 | 26.f, 27.f, |
| 2853 | |
| 2854 | 2.5f, 2.6000001f, |
| 2855 | 2.8f, 2.9f, |
| 2856 | |
| 2857 | 4.2000003f, 4.4f, |
| 2858 | 4.8f, 5.f, |
| 2859 | |
| 2860 | 6.6000004f, 6.9f, |
| 2861 | 7.5000005f, 7.8f |
| 2862 | }; |
| 2863 | |
| 2864 | |
| 2865 | return DepthwiseConvolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( |
| 2866 | workloadFactory, |
| 2867 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2868 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2869 | inputNoQuantizedValues, |
| 2870 | inputTensorInfo, |
| 2871 | kernelNoQuantizedValues, |
| 2872 | kernelTensorInfo, |
| 2873 | outputExpectedNoQuantizedValues, |
| 2874 | outputTensorInfo, |
| 2875 | 1, |
| 2876 | 1, |
| 2877 | layout, |
| 2878 | biasEnabled); |
| 2879 | } |
| 2880 | |
| 2881 | template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T> |
| 2882 | LayerTestResult<T, 4> DepthwiseConvolution2dMult2Test( |
| 2883 | armnn::IWorkloadFactory& workloadFactory, |
| 2884 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2885 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2886 | bool biasEnabled, |
| 2887 | const armnn::DataLayout layout) |
| 2888 | { |
| 2889 | armnn::TensorInfo inputTensorInfo({1, 2, 3, 3}, ArmnnType); |
| 2890 | std::vector<float> inputNoQuantizedValues = |
| 2891 | { |
| 2892 | 10.0, 10.0, 10.0, |
| 2893 | 10.0, 10.0, 10.0, |
| 2894 | 10.0, 10.0, 10.0, |
| 2895 | |
| 2896 | 21.0, 22.0, 23.0, |
| 2897 | 24.0, 25.0, 26.0, |
| 2898 | 27.0, 28.0, 29.0 |
| 2899 | }; |
| 2900 | |
| 2901 | armnn::TensorInfo kernelTensorInfo({ 2, 2, 2, 2}, ArmnnType); |
| 2902 | |
| 2903 | std::vector<float> kernelNoQuantizedValues = |
| 2904 | { |
| 2905 | 0.25f, 0.25f, |
| 2906 | 0.25f, 0.25f, |
| 2907 | |
| 2908 | 0.2f , 0.0f, |
| 2909 | 0.0f , 0.0f, |
| 2910 | |
| 2911 | 0.0f , 0.0f, |
| 2912 | 0.0f , 0.1f, |
| 2913 | |
| 2914 | 0.0f , 0.3f, |
| 2915 | 0.0f , 0.0f |
| 2916 | |
| 2917 | }; |
| 2918 | |
| 2919 | armnn::TensorInfo outputTensorInfo({ 1, 4, 2, 2}, ArmnnType); |
| 2920 | std::vector<float> outputExpectedNoQuantizedValues = |
| 2921 | { |
| 2922 | 10.f, 10.f, |
| 2923 | 10.f, 10.f, |
| 2924 | |
| 2925 | 1.f, 1.f, |
| 2926 | 1.f, 1.f, |
| 2927 | |
| 2928 | 4.2000003f, 4.4f, |
| 2929 | 4.8f, 5.f, |
| 2930 | |
| 2931 | 6.6000004f, 6.9f, |
| 2932 | 7.5000005f, 7.8f |
| 2933 | }; |
| 2934 | |
| 2935 | |
| 2936 | return DepthwiseConvolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( |
| 2937 | workloadFactory, |
| 2938 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2939 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2940 | inputNoQuantizedValues, |
| 2941 | inputTensorInfo, |
| 2942 | kernelNoQuantizedValues, |
| 2943 | kernelTensorInfo, |
| 2944 | outputExpectedNoQuantizedValues, |
| 2945 | outputTensorInfo, |
| 2946 | 1, |
| 2947 | 1, |
| 2948 | layout, |
| 2949 | biasEnabled); |
| 2950 | } |
| 2951 | |
| 2952 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 2953 | LayerTestResult<T, 4> CompareDepthwiseConvolution2dTestImpl( |
| 2954 | armnn::IWorkloadFactory& workloadFactory, |
| 2955 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 2956 | armnn::IWorkloadFactory& refWorkloadFactory, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 2957 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 2958 | const armnn::ITensorHandleFactory& refTensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2959 | const armnnUtils::DataLayoutIndexed& layout) |
| 2960 | { |
| 2961 | unsigned int inputHeight = 8; |
| 2962 | unsigned int inputWidth = 16; |
| 2963 | unsigned int inputChannels = 3; |
| 2964 | unsigned int inputNum = 5; |
| 2965 | |
| 2966 | unsigned int kernelHeight = 3; |
| 2967 | unsigned int kernelWidth = 3; |
| 2968 | unsigned int channelMultiplier = 1; |
| 2969 | |
| 2970 | unsigned int strideX = 2; |
| 2971 | unsigned int strideY = 3; |
| 2972 | unsigned int padX = 1; |
| 2973 | unsigned int padY = 1; |
| 2974 | |
| 2975 | unsigned int outputNum = inputNum; |
| 2976 | unsigned int outputChannels = inputChannels * channelMultiplier; |
| 2977 | unsigned int outputHeight = (inputHeight + 2 * padY - kernelHeight + strideY) / strideY; |
| 2978 | unsigned int outputWidth = (inputWidth + 2 * padX - kernelWidth + strideX) / strideX; |
| 2979 | |
| 2980 | armnn::TensorInfo inputTensorInfo; |
| 2981 | armnn::TensorInfo outputTensorInfo; |
| 2982 | armnn::TensorInfo kernelDesc; |
| 2983 | armnn::TensorInfo biasDesc; |
| 2984 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 2985 | std::vector<unsigned int> inputShape; |
| 2986 | std::vector<unsigned int> outputShape; |
| 2987 | std::vector<unsigned int> kernelShape{ channelMultiplier, inputChannels, kernelHeight, kernelWidth }; |
| 2988 | std::vector<unsigned int> biasShape{ outputChannels }; |
| 2989 | switch (layout.GetDataLayout()) |
| 2990 | { |
| 2991 | case armnn::DataLayout::NCHW: |
| 2992 | inputShape = { inputNum, inputChannels, inputHeight, inputWidth }; |
| 2993 | outputShape = { outputNum, outputChannels, outputHeight, outputWidth }; |
| 2994 | break; |
| 2995 | case armnn::DataLayout ::NHWC: |
| 2996 | inputShape = { inputNum, inputHeight, inputWidth, inputChannels }; |
| 2997 | outputShape = { outputNum, outputHeight, outputWidth, outputChannels }; |
| 2998 | break; |
| 2999 | default: |
| 3000 | throw armnn::InvalidArgumentException("unknown data layout [" |
| 3001 | + std::to_string(static_cast<int>(layout.GetDataLayout())) + "]"); |
| 3002 | } |
| 3003 | |
| 3004 | float inputsQScale = armnn::IsQuantizedType<T>() ? 1.0f : 0; |
| 3005 | float outputQScale = armnn::IsQuantizedType<T>() ? 2.0f : 0; |
| 3006 | int32_t qOffset = 0; |
| 3007 | |
| 3008 | inputTensorInfo = armnn::TensorInfo(4, inputShape.data(), ArmnnType, inputsQScale, qOffset); |
| 3009 | outputTensorInfo = armnn::TensorInfo(4, outputShape.data(), ArmnnType, outputQScale, qOffset); |
| 3010 | kernelDesc = armnn::TensorInfo(4, kernelShape.data(), ArmnnType, inputsQScale, qOffset); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3011 | biasDesc = armnn::TensorInfo(1, biasShape.data(), armnn::GetBiasDataType(ArmnnType), inputsQScale, qOffset); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3012 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3013 | auto input = MakeRandomTensor<T>(inputTensorInfo, 124908, 0.0f, 255.0f); |
| 3014 | auto kernel = MakeRandomTensor<T>(kernelDesc, 891234, 0.0f, 255.0f); |
| 3015 | 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] | 3016 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3017 | std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
| 3018 | std::vector<T> expectedOutput(outputTensorInfo.GetNumElements()); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3019 | |
| 3020 | std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 3021 | std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 3022 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3023 | armnn::DepthwiseConvolution2dQueueDescriptor data; |
| 3024 | armnn::WorkloadInfo info; |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 3025 | armnn::ScopedTensorHandle weightsTensor(kernelDesc); |
| 3026 | armnn::ScopedTensorHandle biasTensor(biasDesc); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3027 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3028 | AllocateAndCopyDataToITensorHandle(&weightsTensor, kernel.data()); |
| 3029 | AllocateAndCopyDataToITensorHandle(&biasTensor, bias.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3030 | |
| 3031 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 3032 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 3033 | data.m_Weight = &weightsTensor; |
| 3034 | data.m_Bias = &biasTensor; |
| 3035 | data.m_Parameters.m_StrideX = strideX; |
| 3036 | data.m_Parameters.m_StrideY = strideY; |
| 3037 | data.m_Parameters.m_PadLeft = padX; |
| 3038 | data.m_Parameters.m_PadRight = padX; |
| 3039 | data.m_Parameters.m_PadTop = padY; |
| 3040 | data.m_Parameters.m_PadBottom = padY; |
| 3041 | data.m_Parameters.m_BiasEnabled = true; |
| 3042 | data.m_Parameters.m_DataLayout = layout.GetDataLayout(); |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3043 | |
| 3044 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refTensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| 3045 | std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refTensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| 3046 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3047 | armnn::DepthwiseConvolution2dQueueDescriptor refData = data; |
| 3048 | armnn::WorkloadInfo refInfo = info; |
| 3049 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get()); |
| 3050 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 3051 | |
| 3052 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateDepthwiseConvolution2d(data, info); |
| 3053 | std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateDepthwiseConvolution2d(refData, refInfo); |
| 3054 | |
| 3055 | outputHandleRef->Allocate(); |
| 3056 | inputHandleRef->Allocate(); |
| 3057 | |
| 3058 | inputHandle->Allocate(); |
| 3059 | outputHandle->Allocate(); |
| 3060 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3061 | CopyDataToITensorHandle(inputHandle.get(), input.data()); |
| 3062 | CopyDataToITensorHandle(inputHandleRef.get(), input.data()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3063 | |
| 3064 | ExecuteWorkload(*workload, memoryManager); |
| 3065 | |
| 3066 | workloadRef->PostAllocationConfigure(); |
| 3067 | workloadRef->Execute(); |
| 3068 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3069 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
| 3070 | CopyDataFromITensorHandle(expectedOutput.data(), outputHandleRef.get()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3071 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3072 | return LayerTestResult<T, 4>(actualOutput, |
| 3073 | expectedOutput, |
| 3074 | outputHandle->GetShape(), |
| 3075 | outputTensorInfo.GetShape()); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3076 | } |
| 3077 | |
| 3078 | // |
| 3079 | // Explicit template specializations |
| 3080 | // |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3081 | template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> |
| 3082 | Convolution2d3x3Dilation3x3Test<armnn::DataType::BFloat16, armnn::DataType::BFloat16>( |
| 3083 | armnn::IWorkloadFactory&, |
| 3084 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3085 | const armnn::ITensorHandleFactory&, |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3086 | bool, |
| 3087 | armnn::DataLayout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3088 | |
| 3089 | template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> |
| 3090 | Convolution2d3x3Dilation3x3Test<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3091 | armnn::IWorkloadFactory&, |
| 3092 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3093 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3094 | bool, |
| 3095 | armnn::DataLayout); |
| 3096 | |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3097 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 4> |
| 3098 | Convolution2d3x3Dilation3x3Test<armnn::DataType::QAsymmS8, armnn::DataType::Signed32>( |
| 3099 | armnn::IWorkloadFactory&, |
| 3100 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3101 | const armnn::ITensorHandleFactory&, |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3102 | bool, |
| 3103 | armnn::DataLayout); |
| 3104 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3105 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 4> |
| 3106 | Convolution2d3x3Dilation3x3Test<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3107 | armnn::IWorkloadFactory&, |
| 3108 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3109 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3110 | bool, |
| 3111 | armnn::DataLayout); |
| 3112 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3113 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 4> |
| 3114 | Convolution2d3x3Dilation3x3Test<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3115 | armnn::IWorkloadFactory&, |
| 3116 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3117 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3118 | bool, |
| 3119 | armnn::DataLayout); |
| 3120 | |
| 3121 | template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> |
| 3122 | Convolution2d2x3x3Dilation3x3Test<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3123 | armnn::IWorkloadFactory&, |
| 3124 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3125 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3126 | bool, |
| 3127 | armnn::DataLayout); |
| 3128 | |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3129 | template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> |
| 3130 | Convolution2d2x3x3Dilation3x3Test<armnn::DataType::BFloat16, armnn::DataType::BFloat16>( |
| 3131 | armnn::IWorkloadFactory&, |
| 3132 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3133 | const armnn::ITensorHandleFactory&, |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3134 | bool, |
| 3135 | armnn::DataLayout); |
| 3136 | |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3137 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 4> |
| 3138 | Convolution2d2x3x3Dilation3x3Test<armnn::DataType::QAsymmS8, armnn::DataType::Signed32>( |
| 3139 | armnn::IWorkloadFactory&, |
| 3140 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3141 | const armnn::ITensorHandleFactory&, |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3142 | bool, |
| 3143 | armnn::DataLayout); |
| 3144 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3145 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 4> |
| 3146 | Convolution2d2x3x3Dilation3x3Test<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3147 | armnn::IWorkloadFactory&, |
| 3148 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3149 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3150 | bool, |
| 3151 | armnn::DataLayout); |
| 3152 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3153 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 4> |
| 3154 | Convolution2d2x3x3Dilation3x3Test<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3155 | armnn::IWorkloadFactory&, |
| 3156 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3157 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3158 | bool, |
| 3159 | armnn::DataLayout); |
| 3160 | |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3161 | template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> |
| 3162 | Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test<armnn::DataType::BFloat16, armnn::DataType::BFloat16>( |
| 3163 | armnn::IWorkloadFactory &workloadFactory, |
| 3164 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3165 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3166 | bool biasEnabled, |
| 3167 | const armnn::DataLayout layout); |
| 3168 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3169 | template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> |
| 3170 | Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3171 | armnn::IWorkloadFactory &workloadFactory, |
| 3172 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3173 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3174 | bool biasEnabled, |
| 3175 | const armnn::DataLayout layout); |
| 3176 | |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3177 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 4> |
| 3178 | Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test<armnn::DataType::QAsymmS8, armnn::DataType::Signed32>( |
| 3179 | armnn::IWorkloadFactory &workloadFactory, |
| 3180 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3181 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3182 | bool biasEnabled, |
| 3183 | const armnn::DataLayout layout); |
| 3184 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3185 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 4> |
| 3186 | Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3187 | armnn::IWorkloadFactory &workloadFactory, |
| 3188 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3189 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3190 | bool biasEnabled, |
| 3191 | const armnn::DataLayout layout); |
| 3192 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3193 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 4> |
| 3194 | Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3195 | armnn::IWorkloadFactory &workloadFactory, |
| 3196 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3197 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3198 | bool biasEnabled, |
| 3199 | const armnn::DataLayout layout); |
| 3200 | |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3201 | template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> |
| 3202 | DepthwiseConvolution2d3x3Dilation3x3Test<armnn::DataType::BFloat16, armnn::DataType::BFloat16>( |
| 3203 | armnn::IWorkloadFactory&, |
| 3204 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3205 | const armnn::ITensorHandleFactory&, |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3206 | bool, |
| 3207 | armnn::DataLayout); |
| 3208 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3209 | template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> |
| 3210 | DepthwiseConvolution2d3x3Dilation3x3Test<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3211 | armnn::IWorkloadFactory&, |
| 3212 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3213 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3214 | bool, |
| 3215 | armnn::DataLayout); |
| 3216 | |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3217 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 4> |
| 3218 | DepthwiseConvolution2d3x3Dilation3x3Test<armnn::DataType::QAsymmS8, armnn::DataType::Signed32>( |
| 3219 | armnn::IWorkloadFactory&, |
| 3220 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3221 | const armnn::ITensorHandleFactory&, |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3222 | bool, |
| 3223 | armnn::DataLayout); |
| 3224 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3225 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 4> |
| 3226 | DepthwiseConvolution2d3x3Dilation3x3Test<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3227 | armnn::IWorkloadFactory&, |
| 3228 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3229 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3230 | bool, |
| 3231 | armnn::DataLayout); |
| 3232 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3233 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 4> |
| 3234 | DepthwiseConvolution2d3x3Dilation3x3Test<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3235 | armnn::IWorkloadFactory&, |
| 3236 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3237 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3238 | bool, |
| 3239 | armnn::DataLayout); |
| 3240 | |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3241 | template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> |
| 3242 | DepthwiseConvolution2d2x3x3Dilation3x3Test<armnn::DataType::BFloat16, armnn::DataType::BFloat16>( |
| 3243 | armnn::IWorkloadFactory&, |
| 3244 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3245 | const armnn::ITensorHandleFactory&, |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3246 | bool, |
| 3247 | armnn::DataLayout); |
| 3248 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3249 | template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> |
| 3250 | DepthwiseConvolution2d2x3x3Dilation3x3Test<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3251 | armnn::IWorkloadFactory&, |
| 3252 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3253 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3254 | bool, |
| 3255 | armnn::DataLayout); |
| 3256 | |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3257 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmS8>, 4> |
| 3258 | DepthwiseConvolution2d2x3x3Dilation3x3Test<armnn::DataType::QAsymmS8, armnn::DataType::Signed32>( |
| 3259 | armnn::IWorkloadFactory&, |
| 3260 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3261 | const armnn::ITensorHandleFactory&, |
Sadik Armagan | 303980c | 2020-04-17 12:45:14 +0100 | [diff] [blame] | 3262 | bool, |
| 3263 | armnn::DataLayout); |
| 3264 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3265 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 4> |
| 3266 | DepthwiseConvolution2d2x3x3Dilation3x3Test<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3267 | armnn::IWorkloadFactory&, |
| 3268 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3269 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3270 | bool, |
| 3271 | armnn::DataLayout); |
| 3272 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3273 | template LayerTestResult<armnn::ResolveType<armnn::DataType::QSymmS16>, 4> |
| 3274 | DepthwiseConvolution2d2x3x3Dilation3x3Test<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3275 | armnn::IWorkloadFactory&, |
| 3276 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3277 | const armnn::ITensorHandleFactory&, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3278 | bool, |
| 3279 | armnn::DataLayout); |
| 3280 | |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3281 | template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> |
| 3282 | DepthwiseConvolution2dMult4Test<armnn::DataType::BFloat16, armnn::DataType::BFloat16>( |
| 3283 | armnn::IWorkloadFactory &workloadFactory, |
| 3284 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3285 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3286 | bool biasEnabled, |
| 3287 | const armnn::DataLayout layout); |
| 3288 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3289 | template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> |
| 3290 | DepthwiseConvolution2dMult4Test<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3291 | armnn::IWorkloadFactory &workloadFactory, |
| 3292 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3293 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3294 | bool biasEnabled, |
| 3295 | const armnn::DataLayout layout); |
| 3296 | |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3297 | template LayerTestResult<armnn::ResolveType<armnn::DataType::BFloat16>, 4> |
| 3298 | DepthwiseConvolution2dMult2Test<armnn::DataType::BFloat16, armnn::DataType::BFloat16>( |
| 3299 | armnn::IWorkloadFactory &workloadFactory, |
| 3300 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3301 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Narumol Prangnawarat | 44179c3 | 2020-03-11 14:51:27 +0000 | [diff] [blame] | 3302 | bool biasEnabled, |
| 3303 | const armnn::DataLayout layout); |
| 3304 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3305 | template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4> |
| 3306 | DepthwiseConvolution2dMult2Test<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3307 | armnn::IWorkloadFactory &workloadFactory, |
| 3308 | const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3309 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3310 | bool biasEnabled, |
| 3311 | const armnn::DataLayout layout); |
| 3312 | |
| 3313 | // |
| 3314 | // Implementation functions |
| 3315 | // |
| 3316 | |
| 3317 | LayerTestResult<float, 4> SimpleConvolution2d3x5Test( |
| 3318 | armnn::IWorkloadFactory& workloadFactory, |
| 3319 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3320 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3321 | bool biasEnabled, |
| 3322 | const armnn::DataLayout layout) |
| 3323 | { |
| 3324 | return SimpleConvolution2d3x5TestCommon<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3325 | workloadFactory, memoryManager, tensorHandleFactory, 0.f, 0, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3326 | } |
| 3327 | |
| 3328 | LayerTestResult<uint8_t, 4> SimpleConvolution2d3x5Uint8Test( |
| 3329 | armnn::IWorkloadFactory& workloadFactory, |
| 3330 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3331 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3332 | bool biasEnabled, |
| 3333 | const armnn::DataLayout layout) |
| 3334 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3335 | return SimpleConvolution2d3x5TestCommon<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3336 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3337 | } |
| 3338 | |
| 3339 | LayerTestResult<float, 4> SimpleConvolution2d3x3Test( |
| 3340 | armnn::IWorkloadFactory& workloadFactory, |
| 3341 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3342 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3343 | bool biasEnabled, |
| 3344 | const armnn::DataLayout layout) |
| 3345 | { |
| 3346 | return SimpleConvolution2d3x3TestCommon<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3347 | workloadFactory, memoryManager, tensorHandleFactory, 0.f, 0, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3348 | } |
| 3349 | |
| 3350 | LayerTestResult<float, 4> SimpleConvolution2d3x3NhwcTest( |
| 3351 | armnn::IWorkloadFactory& workloadFactory, |
| 3352 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3353 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3354 | bool biasEnabled) |
| 3355 | { |
| 3356 | return SimpleConvolution2d3x3NhwcTestCommon<armnn::DataType::Float32>( |
| 3357 | workloadFactory, |
| 3358 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3359 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3360 | 0.f, |
| 3361 | 0, |
| 3362 | biasEnabled, |
| 3363 | armnn::DataLayout::NHWC); |
| 3364 | } |
| 3365 | |
| 3366 | LayerTestResult<float, 4> SimpleConvolution2d3x3Stride2x2Test( |
| 3367 | armnn::IWorkloadFactory& workloadFactory, |
| 3368 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3369 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3370 | bool biasEnabled, |
| 3371 | const armnn::DataLayout layout) |
| 3372 | { |
| 3373 | return SimpleConvolution2d3x3Stride2x2TestCommon<armnn::DataType::Float32>( |
| 3374 | workloadFactory, |
| 3375 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3376 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3377 | 0.f, |
| 3378 | 0, |
| 3379 | biasEnabled, |
| 3380 | layout); |
| 3381 | } |
| 3382 | |
| 3383 | LayerTestResult<uint8_t, 4> SimpleConvolution2d3x3Uint8Test( |
| 3384 | armnn::IWorkloadFactory& workloadFactory, |
| 3385 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3386 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3387 | bool biasEnabled, |
| 3388 | const armnn::DataLayout layout) |
| 3389 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3390 | return SimpleConvolution2d3x3TestCommon<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3391 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3392 | } |
| 3393 | |
| 3394 | LayerTestResult<int16_t, 4> SimpleConvolution2d3x5QSymm16Test( |
| 3395 | armnn::IWorkloadFactory& workloadFactory, |
| 3396 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3397 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3398 | bool biasEnabled, |
| 3399 | const armnn::DataLayout layout) |
| 3400 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3401 | return SimpleConvolution2d3x5TestCommon<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3402 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3403 | } |
| 3404 | |
| 3405 | LayerTestResult<int16_t, 4> SimpleConvolution2d3x3QSymm16Test( |
| 3406 | armnn::IWorkloadFactory& workloadFactory, |
| 3407 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3408 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3409 | bool biasEnabled, |
| 3410 | const armnn::DataLayout layout) |
| 3411 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3412 | return SimpleConvolution2d3x3TestCommon<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3413 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3414 | } |
| 3415 | |
| 3416 | LayerTestResult<float, 4> Convolution2dAsymmetricPaddingTest( |
| 3417 | armnn::IWorkloadFactory& workloadFactory, |
| 3418 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3419 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3420 | armnn::DataLayout layout) |
| 3421 | { |
| 3422 | return SimpleConvolution2dAsymmetricPaddingTestCommon<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3423 | workloadFactory, memoryManager, tensorHandleFactory, layout, 0.0f, 0); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3424 | } |
| 3425 | |
| 3426 | LayerTestResult<float, 4> Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTest( |
| 3427 | armnn::IWorkloadFactory& workloadFactory, |
| 3428 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3429 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3430 | armnn::DataLayout layout) |
| 3431 | { |
| 3432 | return Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon |
| 3433 | <armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3434 | workloadFactory, memoryManager, tensorHandleFactory, layout, 0.0f, 0); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3435 | } |
| 3436 | |
| 3437 | LayerTestResult<float, 4> Convolution1dTest( |
| 3438 | armnn::IWorkloadFactory& workloadFactory, |
| 3439 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3440 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3441 | bool biasEnabled) |
| 3442 | { |
| 3443 | return Convolution1dTestImpl<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3444 | workloadFactory, memoryManager, tensorHandleFactory, 0.0f, 0, biasEnabled); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3445 | } |
| 3446 | |
| 3447 | LayerTestResult<uint8_t, 4> Convolution1dUint8Test( |
| 3448 | armnn::IWorkloadFactory& workloadFactory, |
| 3449 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3450 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3451 | bool biasEnabled) |
| 3452 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3453 | return Convolution1dTestImpl<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3454 | workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 128, biasEnabled); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3455 | } |
| 3456 | |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3457 | LayerTestResult<uint8_t, 4> Convolution2dPerAxisQuantTest( |
| 3458 | armnn::IWorkloadFactory& workloadFactory, |
| 3459 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3460 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3461 | const armnn::DataLayout layout) |
| 3462 | { |
| 3463 | using namespace armnn; |
| 3464 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3465 | const DataType inputType = DataType::QAsymmU8; |
Derek Lamberti | d466a54 | 2020-01-22 15:37:29 +0000 | [diff] [blame] | 3466 | const DataType kernelType = DataType::QSymmS8; |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3467 | const DataType biasType = DataType::Signed32; |
| 3468 | |
| 3469 | TensorInfo inputInfo ({ 1, 3, 1, 2 }, inputType, 0.5f, 128); |
| 3470 | TensorInfo outputInfo({ 1, 3, 1, 3 }, inputType, 1.0f, 128); |
| 3471 | |
| 3472 | const std::vector<float> quantScales{ 0.5f, 0.75f, 1.0f }; |
| 3473 | constexpr unsigned int quantDimension = 0; |
| 3474 | |
| 3475 | TensorInfo kernelInfo({ 3, 1, 1, 2 }, kernelType, quantScales, quantDimension); |
| 3476 | |
| 3477 | const std::vector<float> biasQuantScales{ 0.25f, 0.375f, 0.5f }; |
| 3478 | TensorInfo biasInfo({ 3 }, biasType, biasQuantScales, quantDimension); |
| 3479 | |
| 3480 | std::vector<uint8_t> inputData = |
| 3481 | { |
| 3482 | 138, 108, 138, 108, 138, 108 |
| 3483 | }; |
| 3484 | |
| 3485 | std::vector<int8_t> kernelData = |
| 3486 | { |
| 3487 | 1, 2, 1, 2, 1, 2 |
| 3488 | }; |
| 3489 | |
| 3490 | std::vector<int32_t> biasData = |
| 3491 | { |
| 3492 | 4, 4, 4 |
| 3493 | }; |
| 3494 | |
| 3495 | std::vector<uint8_t> expectedOutputData = |
| 3496 | { |
| 3497 | 121, 118, 115, 121, 118, 115, 121, 118, 115 |
| 3498 | }; |
| 3499 | |
| 3500 | if (layout == DataLayout::NCHW) |
| 3501 | { |
| 3502 | PermuteTensorNhwcToNchw(inputInfo, inputData); |
| 3503 | PermuteTensorNhwcToNchw(kernelInfo, kernelData); |
| 3504 | PermuteTensorNhwcToNchw(outputInfo, expectedOutputData); |
| 3505 | } |
| 3506 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3507 | std::vector<uint8_t> actualOutput(outputInfo.GetNumElements()); |
| 3508 | |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3509 | Convolution2dDescriptor descriptor; |
| 3510 | descriptor.m_StrideX = 1; |
| 3511 | descriptor.m_StrideY = 1; |
| 3512 | descriptor.m_PadLeft = 0; |
| 3513 | descriptor.m_PadRight = 0; |
| 3514 | descriptor.m_PadTop = 0; |
| 3515 | descriptor.m_PadBottom = 0; |
| 3516 | descriptor.m_BiasEnabled = true; |
| 3517 | descriptor.m_DataLayout = layout; |
| 3518 | |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3519 | std::unique_ptr<ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputInfo); |
| 3520 | std::unique_ptr<ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputInfo); |
| 3521 | |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3522 | WorkloadInfo workloadInfo; |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 3523 | ScopedTensorHandle weightTensor(kernelInfo); |
| 3524 | ScopedTensorHandle biasTensor(biasInfo); |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3525 | |
| 3526 | AllocateAndCopyDataToITensorHandle(&weightTensor, kernelData.data()); |
| 3527 | AllocateAndCopyDataToITensorHandle(&biasTensor, biasData.data()); |
| 3528 | |
| 3529 | Convolution2dQueueDescriptor queueDescriptor; |
| 3530 | queueDescriptor.m_Parameters = descriptor; |
| 3531 | queueDescriptor.m_Weight = &weightTensor; |
| 3532 | queueDescriptor.m_Bias = &biasTensor; |
| 3533 | |
| 3534 | AddInputToWorkload(queueDescriptor, workloadInfo, inputInfo, inputHandle.get()); |
| 3535 | AddOutputToWorkload(queueDescriptor, workloadInfo, outputInfo, outputHandle.get()); |
| 3536 | |
| 3537 | std::unique_ptr<IWorkload> workload = workloadFactory.CreateConvolution2d(queueDescriptor, workloadInfo); |
| 3538 | inputHandle->Allocate(); |
| 3539 | outputHandle->Allocate(); |
| 3540 | |
| 3541 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
| 3542 | |
| 3543 | ExecuteWorkload(*workload, memoryManager); |
| 3544 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3545 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3546 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3547 | return LayerTestResult<uint8_t, 4>(actualOutput, |
| 3548 | expectedOutputData, |
| 3549 | outputHandle->GetShape(), |
| 3550 | outputInfo.GetShape()); |
Aron Virginas-Tar | 5edc881 | 2019-11-05 18:00:21 +0000 | [diff] [blame] | 3551 | } |
| 3552 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3553 | LayerTestResult<float,4> CompareConvolution2dTest( |
| 3554 | armnn::IWorkloadFactory& workloadFactory, |
| 3555 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3556 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 3557 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 3558 | const armnn::ITensorHandleFactory& refTensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3559 | { |
| 3560 | return CompareConvolution2dTestImpl<armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3561 | workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3562 | } |
| 3563 | |
| 3564 | LayerTestResult<float, 4> DepthwiseConvolution2dTest( |
| 3565 | armnn::IWorkloadFactory& workloadFactory, |
| 3566 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3567 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3568 | bool biasEnabled, |
| 3569 | const armnn::DataLayout layout) |
| 3570 | { |
| 3571 | return DepthwiseConvolution2dTestImpl<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3572 | workloadFactory, memoryManager, tensorHandleFactory, 0.0f, 0, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3573 | } |
| 3574 | |
| 3575 | LayerTestResult<float, 4> DepthwiseConvolution2dDepthNhwcTest( |
| 3576 | armnn::IWorkloadFactory& workloadFactory, |
| 3577 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3578 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3579 | bool biasEnabled) |
| 3580 | { |
| 3581 | return DepthwiseConvolution2dNhwcTestCommon<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3582 | workloadFactory, memoryManager, tensorHandleFactory, 0.0f, 0, biasEnabled); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3583 | } |
| 3584 | |
| 3585 | LayerTestResult<float, 4> DepthwiseConvolution2dDepthMul1Test( |
| 3586 | armnn::IWorkloadFactory& workloadFactory, |
| 3587 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3588 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3589 | bool biasEnabled, |
| 3590 | const armnn::DataLayout layout) |
| 3591 | { |
| 3592 | return DepthwiseConvolution2dDepthMul1TestImpl<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3593 | workloadFactory, memoryManager, tensorHandleFactory, 0.0f, 0, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3594 | } |
| 3595 | |
| 3596 | LayerTestResult<float, 4> DepthwiseConvolution2dDepthMul64Test( |
| 3597 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3598 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3599 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3600 | { |
| 3601 | armnn::TensorInfo inputTensorInfo({ 1, 1, 2, 2 }, armnn::DataType::Float32); |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3602 | 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] | 3603 | |
| 3604 | std::vector<float> kernelData; |
| 3605 | std::vector<float> singleDepthKernel{ 1.f, -1.f, -1.f, 1.f }; |
| 3606 | for (unsigned int i = 0; i < 64; ++i) |
| 3607 | { |
| 3608 | kernelData.insert(kernelData.end(), singleDepthKernel.begin(), singleDepthKernel.end()); |
| 3609 | } |
| 3610 | armnn::TensorInfo kernelTensorInfo({ 64, 1, 2, 2 }, armnn::DataType::Float32); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3611 | |
| 3612 | std::vector<float> expectedOutputData(64, 0.f); |
| 3613 | armnn::TensorInfo outputTensorInfo({ 1, 64, 1, 1 }, armnn::DataType::Float32); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3614 | |
| 3615 | return DepthwiseConvolution2dTestImpl<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3616 | workloadFactory, |
| 3617 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3618 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3619 | input, |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3620 | kernelData, |
| 3621 | std::vector<float>(), |
| 3622 | expectedOutputData, |
| 3623 | inputTensorInfo.GetShape(), |
| 3624 | kernelTensorInfo.GetShape(), |
| 3625 | outputTensorInfo.GetShape(), |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3626 | 0.f, |
| 3627 | 0, |
| 3628 | armnn::DataLayout::NCHW); |
| 3629 | } |
| 3630 | |
| 3631 | LayerTestResult<float, 4> DepthwiseConvolution2dAsymmetricTest( |
| 3632 | armnn::IWorkloadFactory& workloadFactory, |
| 3633 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3634 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3635 | bool biasEnabled, |
| 3636 | const armnn::DataLayout layout) |
| 3637 | { |
| 3638 | return DepthwiseConvolution2dAsymmetricTestCommon<armnn::DataType::Float32, armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3639 | workloadFactory, memoryManager, tensorHandleFactory, 0.0f, 0, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3640 | } |
| 3641 | |
| 3642 | LayerTestResult<uint8_t, 4> DepthwiseConvolution2dUint8Test( |
| 3643 | armnn::IWorkloadFactory& workloadFactory, |
| 3644 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3645 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3646 | bool biasEnabled, |
| 3647 | const armnn::DataLayout layout) |
| 3648 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3649 | return DepthwiseConvolution2dTestImpl<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3650 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3651 | } |
| 3652 | |
| 3653 | LayerTestResult<uint8_t, 4> DepthwiseConvolution2dDepthMul1Uint8Test( |
| 3654 | armnn::IWorkloadFactory& workloadFactory, |
| 3655 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3656 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3657 | bool biasEnabled, |
| 3658 | const armnn::DataLayout layout) |
| 3659 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3660 | return DepthwiseConvolution2dDepthMul1TestImpl<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3661 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3662 | } |
| 3663 | |
| 3664 | LayerTestResult<float, 4> SimpleDepthwiseConvolution2d3x3Dilation3x3NhwcTest( |
| 3665 | armnn::IWorkloadFactory& workloadFactory, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3666 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3667 | const armnn::ITensorHandleFactory& tensorHandleFactory) |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3668 | { |
| 3669 | return SimpleDepthwiseConvolution2d3x3Dilation3x3NhwcTestCommon<armnn::DataType::Float32, armnn::DataType::Float32>( |
| 3670 | workloadFactory, |
| 3671 | memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3672 | tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3673 | 0.f, |
| 3674 | 0, |
| 3675 | false); |
| 3676 | } |
| 3677 | |
| 3678 | LayerTestResult<int16_t, 4> DepthwiseConvolution2dInt16Test( |
| 3679 | armnn::IWorkloadFactory& workloadFactory, |
| 3680 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3681 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3682 | bool biasEnabled, |
| 3683 | const armnn::DataLayout layout) |
| 3684 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3685 | return DepthwiseConvolution2dTestImpl<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3686 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3687 | } |
| 3688 | |
| 3689 | LayerTestResult<int16_t, 4> DepthwiseConvolution2dDepthMul1Int16Test( |
| 3690 | armnn::IWorkloadFactory& workloadFactory, |
| 3691 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3692 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3693 | bool biasEnabled, |
| 3694 | const armnn::DataLayout layout) |
| 3695 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3696 | return DepthwiseConvolution2dDepthMul1TestImpl<armnn::DataType::QSymmS16, armnn::DataType::Signed32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3697 | workloadFactory, memoryManager, tensorHandleFactory, 0.5f, 50, biasEnabled, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3698 | } |
| 3699 | |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3700 | LayerTestResult<uint8_t, 4> DepthwiseConvolution2dPerAxisQuantTest( |
| 3701 | armnn::IWorkloadFactory& workloadFactory, |
| 3702 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3703 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3704 | const armnn::DataLayout layout) |
| 3705 | { |
| 3706 | using namespace armnn; |
| 3707 | |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3708 | const DataType inputType = DataType::QAsymmU8; |
Derek Lamberti | d466a54 | 2020-01-22 15:37:29 +0000 | [diff] [blame] | 3709 | const DataType kernelType = DataType::QSymmS8; |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3710 | const DataType biasType = DataType::Signed32; |
| 3711 | |
| 3712 | TensorInfo inputInfo ({ 1, 3, 3, 2 }, inputType, 0.5f, 128); // N H W C |
| 3713 | TensorInfo outputInfo({ 1, 2, 2, 4 }, inputType, 1.0f, 128); // N H W C |
| 3714 | |
| 3715 | const std::vector<float> quantScales{ 1.0f, 0.5f, 1.0f, 0.5f }; |
| 3716 | const unsigned int quantDimension = 0; |
| 3717 | TensorInfo kernelInfo({ 2, 2, 2, 2 }, kernelType, quantScales, quantDimension); // M I H W |
| 3718 | |
| 3719 | const std::vector<float> biasQuantScales{ 0.5f, 0.25f, 0.5f, 0.25f }; |
| 3720 | constexpr unsigned int biasQuantDimension = 0; |
| 3721 | TensorInfo biasInfo({ 4 }, biasType, biasQuantScales, biasQuantDimension); |
| 3722 | |
| 3723 | std::vector<uint8_t> inputData = |
| 3724 | { |
| 3725 | 129, 130, |
| 3726 | 129, 130, |
| 3727 | 129, 130, |
| 3728 | 129, 130, |
| 3729 | 129, 130, |
| 3730 | 129, 130, |
| 3731 | 129, 130, |
| 3732 | 129, 130, |
| 3733 | 129, 130 |
| 3734 | }; |
| 3735 | |
| 3736 | std::vector<int8_t> kernelData = |
| 3737 | { |
| 3738 | 1, 1, 1, 1, |
| 3739 | 1, 1, 1, 1, |
| 3740 | 1, 1, 1, 1, |
| 3741 | 1, 1, 1, 1 |
| 3742 | }; |
| 3743 | |
| 3744 | std::vector<int32_t> biasData = |
| 3745 | { |
| 3746 | 4, 4, 4, 4 |
| 3747 | }; |
| 3748 | |
| 3749 | std::vector<uint8_t> expectedOutputData = |
| 3750 | { |
| 3751 | 132, 130, 134, 131, |
| 3752 | 132, 130, 134, 131, |
| 3753 | 132, 130, 134, 131, |
| 3754 | 132, 130, 134, 131 |
| 3755 | }; |
| 3756 | |
| 3757 | if (layout == DataLayout::NCHW) |
| 3758 | { |
| 3759 | PermuteTensorNhwcToNchw(inputInfo, inputData); |
| 3760 | PermuteTensorNhwcToNchw(outputInfo, expectedOutputData); |
| 3761 | } |
| 3762 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3763 | std::vector<uint8_t> actualOutput(outputInfo.GetNumElements()); |
| 3764 | |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3765 | DepthwiseConvolution2dDescriptor descriptor; |
| 3766 | descriptor.m_StrideX = 1; |
| 3767 | descriptor.m_StrideY = 1; |
| 3768 | descriptor.m_PadLeft = 0; |
| 3769 | descriptor.m_PadRight = 0; |
| 3770 | descriptor.m_PadTop = 0; |
| 3771 | descriptor.m_PadBottom = 0; |
| 3772 | descriptor.m_DilationX = 1; |
| 3773 | descriptor.m_DilationY = 1; |
| 3774 | descriptor.m_BiasEnabled = true; |
| 3775 | descriptor.m_DataLayout = layout; |
| 3776 | |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3777 | std::unique_ptr<ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputInfo); |
| 3778 | std::unique_ptr<ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputInfo); |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3779 | |
| 3780 | WorkloadInfo workloadInfo; |
James Conroy | 1f58f03 | 2021-04-27 17:13:27 +0100 | [diff] [blame] | 3781 | ScopedTensorHandle weightTensor(kernelInfo); |
| 3782 | ScopedTensorHandle biasTensor(biasInfo); |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3783 | |
| 3784 | AllocateAndCopyDataToITensorHandle(&weightTensor, kernelData.data()); |
| 3785 | AllocateAndCopyDataToITensorHandle(&biasTensor, biasData.data()); |
| 3786 | |
| 3787 | DepthwiseConvolution2dQueueDescriptor queueDescriptor; |
| 3788 | queueDescriptor.m_Parameters = descriptor; |
| 3789 | queueDescriptor.m_Weight = &weightTensor; |
| 3790 | queueDescriptor.m_Bias = &biasTensor; |
| 3791 | |
| 3792 | AddInputToWorkload(queueDescriptor, workloadInfo, inputInfo, inputHandle.get()); |
| 3793 | AddOutputToWorkload(queueDescriptor, workloadInfo, outputInfo, outputHandle.get()); |
| 3794 | |
| 3795 | std::unique_ptr<IWorkload> workload = workloadFactory.CreateDepthwiseConvolution2d(queueDescriptor, workloadInfo); |
| 3796 | inputHandle->Allocate(); |
| 3797 | outputHandle->Allocate(); |
| 3798 | |
| 3799 | CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
| 3800 | |
| 3801 | ExecuteWorkload(*workload, memoryManager); |
| 3802 | |
| 3803 | LayerTestResult<uint8_t, 4> ret(outputInfo); |
| 3804 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3805 | CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3806 | |
Sadik Armagan | 483c811 | 2021-06-01 09:24:52 +0100 | [diff] [blame^] | 3807 | return LayerTestResult<uint8_t, 4>(actualOutput, |
| 3808 | expectedOutputData, |
| 3809 | outputHandle->GetShape(), |
| 3810 | outputInfo.GetShape()); |
Teresa Charlin | d8df026 | 2019-11-11 12:28:15 +0000 | [diff] [blame] | 3811 | } |
| 3812 | |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3813 | LayerTestResult<float, 4> CompareDepthwiseConvolution2dFloatTest( |
| 3814 | armnn::IWorkloadFactory& workloadFactory, |
| 3815 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3816 | armnn::IWorkloadFactory& refWorkloadFactory, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3817 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 3818 | const armnn::ITensorHandleFactory& refTensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3819 | const armnn::DataLayout layout) |
| 3820 | { |
| 3821 | return CompareDepthwiseConvolution2dTestImpl<armnn::DataType::Float32>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3822 | workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3823 | } |
| 3824 | |
| 3825 | LayerTestResult<uint8_t, 4> CompareDepthwiseConvolution2dUint8Test( |
| 3826 | armnn::IWorkloadFactory& workloadFactory, |
| 3827 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3828 | armnn::IWorkloadFactory& refWorkloadFactory, |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3829 | const armnn::ITensorHandleFactory& tensorHandleFactory, |
| 3830 | const armnn::ITensorHandleFactory& refTensorHandleFactory, |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3831 | const armnn::DataLayout layout) |
| 3832 | { |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 3833 | return CompareDepthwiseConvolution2dTestImpl<armnn::DataType::QAsymmU8>( |
Keith Davis | f500d6c | 2020-08-31 08:32:55 +0100 | [diff] [blame] | 3834 | workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory, layout); |
Aron Virginas-Tar | 00d306e | 2019-08-28 18:08:46 +0100 | [diff] [blame] | 3835 | } |