Laurent Carlier | 749294b | 2020-06-01 09:03:17 +0100 | [diff] [blame] | 1 | // |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2 | // Copyright © 2017 Arm Ltd. All rights reserved. |
David Beck | ecb56cd | 2018-09-05 12:52:57 +0100 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4 | // |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 5 | #include <aclCommon/ArmComputeTensorUtils.hpp> |
| 6 | #include <aclCommon/ArmComputeUtils.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7 | |
Francis Murtagh | 351d13d | 2018-09-24 15:01:18 +0100 | [diff] [blame] | 8 | #include "armnn/Exceptions.hpp" |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 9 | #include <armnn/Descriptors.hpp> |
| 10 | |
| 11 | namespace armnn |
| 12 | { |
| 13 | namespace armcomputetensorutils |
| 14 | { |
| 15 | |
Derek Lamberti | d466a54 | 2020-01-22 15:37:29 +0000 | [diff] [blame] | 16 | arm_compute::DataType GetArmComputeDataType(armnn::DataType dataType, bool multiScales) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 17 | { |
| 18 | switch(dataType) |
| 19 | { |
Narumol Prangnawarat | 250d392 | 2020-03-30 16:11:04 +0100 | [diff] [blame] | 20 | case armnn::DataType::BFloat16: |
| 21 | return arm_compute::DataType::BFLOAT16; |
Mike Kelly | 130ec60 | 2019-11-08 12:08:35 +0000 | [diff] [blame] | 22 | case armnn::DataType::Boolean: |
| 23 | return arm_compute::DataType::U8; |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 24 | case armnn::DataType::Float16: |
| 25 | return arm_compute::DataType::F16; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 26 | case armnn::DataType::Float32: |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 27 | return arm_compute::DataType::F32; |
Ryan OShea | 9add120 | 2020-02-07 10:06:33 +0000 | [diff] [blame] | 28 | case armnn::DataType::QAsymmS8: |
| 29 | return arm_compute::DataType::QASYMM8_SIGNED; |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 30 | case armnn::DataType::QAsymmU8: |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 31 | return arm_compute::DataType::QASYMM8; |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 32 | case armnn::DataType::QSymmS16: |
Aron Virginas-Tar | 7a3e2fe | 2019-06-27 18:54:47 +0100 | [diff] [blame] | 33 | return arm_compute::DataType::QSYMM16; |
Inki Dae | d4619e2 | 2020-09-10 15:33:54 +0900 | [diff] [blame] | 34 | case armnn::DataType::Signed64: |
| 35 | return arm_compute::DataType::S64; |
Finn Williams | fd27106 | 2019-12-04 14:27:27 +0000 | [diff] [blame] | 36 | case armnn::DataType::QSymmS8: |
Derek Lamberti | d466a54 | 2020-01-22 15:37:29 +0000 | [diff] [blame] | 37 | { |
| 38 | return multiScales ? arm_compute::DataType::QSYMM8_PER_CHANNEL : arm_compute::DataType::QSYMM8; |
| 39 | } |
| 40 | ARMNN_NO_DEPRECATE_WARN_BEGIN |
Mike Kelly | 130ec60 | 2019-11-08 12:08:35 +0000 | [diff] [blame] | 41 | case armnn::DataType::QuantizedSymm8PerAxis: |
| 42 | return arm_compute::DataType::QSYMM8_PER_CHANNEL; |
Derek Lamberti | d466a54 | 2020-01-22 15:37:29 +0000 | [diff] [blame] | 43 | ARMNN_NO_DEPRECATE_WARN_END |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 44 | case armnn::DataType::Signed32: |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 45 | return arm_compute::DataType::S32; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 46 | default: |
Narumol Prangnawarat | ac2770a | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 47 | ARMNN_ASSERT_MSG(false, "Unknown data type"); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 48 | return arm_compute::DataType::UNKNOWN; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 49 | } |
| 50 | } |
| 51 | |
Matthew Bentham | fd89996 | 2018-12-31 15:49:42 +0000 | [diff] [blame] | 52 | arm_compute::Coordinates BuildArmComputeReductionCoordinates(size_t inputDimensions, |
| 53 | unsigned int originalInputRank, |
| 54 | const std::vector<unsigned int>& armnnAxes) |
| 55 | { |
| 56 | arm_compute::Coordinates outAclCoords; |
| 57 | |
| 58 | if (armnnAxes.empty()) |
| 59 | { |
| 60 | // If no reduction axes were provided, then the input must be reduced along all dimensions. |
| 61 | // Since Compute Library does not accept an empty vector as the reduction dimensions, we then |
| 62 | // manually create a vector including all the input dimensions (in reversed order) as: |
| 63 | // |
| 64 | // { inputDimensions - 1, inputDimensions - 2, ..., 1, 0 } |
| 65 | // |
| 66 | outAclCoords.set_num_dimensions(inputDimensions); |
| 67 | std::generate(outAclCoords.begin(), outAclCoords.end(), [d = inputDimensions - 1] () mutable { return d--; }); |
| 68 | } |
| 69 | else |
| 70 | { |
| 71 | // Create a vector of reduction dimensions (in reversed order) with the given reduction axes. |
| 72 | // |
| 73 | // Adjust the given reduction axes according to the original rank of the input tensor (before ACL applied any |
| 74 | // dimension correction). |
| 75 | // For example, if the input tensor originally had 4 dimensions, and one of the reduction axes was 2, then the |
| 76 | // new value for that reduction axis should be 1. |
| 77 | // |
| 78 | // Example: |
| 79 | // ArmNN input shape = { 1, 1, 3, 2 } -> ACL input shape = { 2, 3 } |
| 80 | // ArmNN reduction axis = { 2 } -> ACL reduction axis = { 1 } |
| 81 | // ArmNN reduction axis = { 3 } -> ACL reduction axis = { 0 } |
| 82 | // |
| 83 | // The transformation: ACL reduction axis index = original rank - ArmNN reduction axis index - 1 |
| 84 | // |
| 85 | outAclCoords.set_num_dimensions(armnnAxes.size()); |
| 86 | std::transform(armnnAxes.begin(), armnnAxes.end(), |
| 87 | outAclCoords.begin(), |
| 88 | [originalInputRank](unsigned int i){ return originalInputRank - i - 1; }); |
| 89 | } |
| 90 | |
| 91 | return outAclCoords; |
| 92 | } |
| 93 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 94 | arm_compute::TensorShape BuildArmComputeTensorShape(const armnn::TensorShape& tensorShape) |
| 95 | { |
| 96 | arm_compute::TensorShape shape; |
| 97 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 98 | // armnn tensors are (batch, channels, height, width). |
| 99 | // arm_compute tensors are (width, height, channels, batch). |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 100 | for (unsigned int i = 0; i < tensorShape.GetNumDimensions(); i++) |
| 101 | { |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 102 | // Note that our dimensions are stored in the opposite order to ACL's. |
Matthew Bentham | 8910528 | 2018-11-20 14:33:33 +0000 | [diff] [blame] | 103 | shape.set(tensorShape.GetNumDimensions() - i - 1, tensorShape[i], false); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 104 | |
| 105 | // TensorShape::set() flattens leading ones, so that batch size 1 cannot happen. |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 106 | // arm_compute tensors expect this. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 107 | } |
| 108 | |
| 109 | // prevent arm_compute issue where tensor is flattened to nothing |
| 110 | if (shape.num_dimensions() == 0) |
| 111 | { |
| 112 | shape.set_num_dimensions(1); |
| 113 | } |
| 114 | |
| 115 | return shape; |
| 116 | } |
| 117 | |
| 118 | // Utility function used to build a TensorInfo object, that can be used to initialise |
| 119 | // ARM Compute Tensor and CLTensor allocators. |
| 120 | arm_compute::TensorInfo BuildArmComputeTensorInfo(const armnn::TensorInfo& tensorInfo) |
| 121 | { |
Derek Lamberti | d466a54 | 2020-01-22 15:37:29 +0000 | [diff] [blame] | 122 | bool multiScales = tensorInfo.HasMultipleQuantizationScales(); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 123 | const arm_compute::TensorShape aclTensorShape = BuildArmComputeTensorShape(tensorInfo.GetShape()); |
Derek Lamberti | d466a54 | 2020-01-22 15:37:29 +0000 | [diff] [blame] | 124 | const arm_compute::DataType aclDataType = GetArmComputeDataType(tensorInfo.GetDataType(), multiScales); |
Aron Virginas-Tar | 13b653f | 2019-11-01 11:40:39 +0000 | [diff] [blame] | 125 | |
Derek Lamberti | d466a54 | 2020-01-22 15:37:29 +0000 | [diff] [blame] | 126 | const arm_compute::QuantizationInfo aclQuantizationInfo = multiScales ? |
Aron Virginas-Tar | 13b653f | 2019-11-01 11:40:39 +0000 | [diff] [blame] | 127 | arm_compute::QuantizationInfo(tensorInfo.GetQuantizationScales()) : |
| 128 | arm_compute::QuantizationInfo(tensorInfo.GetQuantizationScale(), tensorInfo.GetQuantizationOffset()); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 129 | |
| 130 | return arm_compute::TensorInfo(aclTensorShape, 1, aclDataType, aclQuantizationInfo); |
| 131 | } |
| 132 | |
Francis Murtagh | 351d13d | 2018-09-24 15:01:18 +0100 | [diff] [blame] | 133 | arm_compute::TensorInfo BuildArmComputeTensorInfo(const armnn::TensorInfo& tensorInfo, |
| 134 | armnn::DataLayout dataLayout) |
| 135 | { |
Aron Virginas-Tar | 13b653f | 2019-11-01 11:40:39 +0000 | [diff] [blame] | 136 | arm_compute::TensorInfo aclTensorInfo = BuildArmComputeTensorInfo(tensorInfo); |
| 137 | aclTensorInfo.set_data_layout(ConvertDataLayout(dataLayout)); |
Francis Murtagh | 351d13d | 2018-09-24 15:01:18 +0100 | [diff] [blame] | 138 | |
Aron Virginas-Tar | 13b653f | 2019-11-01 11:40:39 +0000 | [diff] [blame] | 139 | return aclTensorInfo; |
Francis Murtagh | 351d13d | 2018-09-24 15:01:18 +0100 | [diff] [blame] | 140 | } |
| 141 | |
Matteo Martincigh | 747ef82 | 2018-12-18 09:26:39 +0000 | [diff] [blame] | 142 | arm_compute::DataLayout ConvertDataLayout(armnn::DataLayout dataLayout) |
| 143 | { |
| 144 | switch(dataLayout) |
| 145 | { |
| 146 | case armnn::DataLayout::NHWC : return arm_compute::DataLayout::NHWC; |
| 147 | |
| 148 | case armnn::DataLayout::NCHW : return arm_compute::DataLayout::NCHW; |
| 149 | |
| 150 | default: throw InvalidArgumentException("Unknown armnn::DataLayout: [" + |
| 151 | std::to_string(static_cast<int>(dataLayout)) + "]"); |
| 152 | } |
| 153 | } |
| 154 | |
Sadik Armagan | a3600ba | 2019-10-10 10:43:20 +0100 | [diff] [blame] | 155 | arm_compute::PoolingLayerInfo BuildArmComputePoolingLayerInfo(const Pooling2dDescriptor& descriptor, |
| 156 | bool fpMixedPrecision) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 157 | { |
| 158 | using arm_compute::PoolingType; |
| 159 | using arm_compute::DimensionRoundingType; |
| 160 | using arm_compute::PadStrideInfo; |
| 161 | using arm_compute::PoolingLayerInfo; |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 162 | using arm_compute::Size2D; |
Teresa Charlin | c809a29 | 2020-01-31 10:21:44 +0000 | [diff] [blame] | 163 | using arm_compute::DataLayout; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 164 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 165 | // Resolve ARM Compute layer parameters. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 166 | const PoolingType poolingType = ConvertPoolingAlgorithmToAclPoolingType(descriptor.m_PoolType); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 167 | |
Teresa Charlin | c809a29 | 2020-01-31 10:21:44 +0000 | [diff] [blame] | 168 | const DataLayout dataLayout = ConvertDataLayout(descriptor.m_DataLayout); |
| 169 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 170 | bool isGlobalPooling = (descriptor.m_StrideX==0 && descriptor.m_StrideY==0); |
| 171 | //use specific constructor if global pooling |
| 172 | if(isGlobalPooling) |
| 173 | { |
Teresa Charlin | c809a29 | 2020-01-31 10:21:44 +0000 | [diff] [blame] | 174 | return arm_compute::PoolingLayerInfo(poolingType, dataLayout); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 175 | } |
| 176 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 177 | const DimensionRoundingType rounding = ConvertOutputShapeRoundingToAclDimensionRoundingType( |
| 178 | descriptor.m_OutputShapeRounding); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 179 | const PadStrideInfo padStrideInfo(descriptor.m_StrideX, |
| 180 | descriptor.m_StrideY, |
| 181 | descriptor.m_PadLeft, |
| 182 | descriptor.m_PadRight, |
| 183 | descriptor.m_PadTop, |
| 184 | descriptor.m_PadBottom, |
| 185 | rounding); |
| 186 | |
| 187 | const bool excludePadding = (descriptor.m_PaddingMethod == PaddingMethod::Exclude); |
| 188 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 189 | const Size2D poolSize(descriptor.m_PoolWidth, descriptor.m_PoolHeight); |
| 190 | |
Teresa Charlin | c809a29 | 2020-01-31 10:21:44 +0000 | [diff] [blame] | 191 | return arm_compute::PoolingLayerInfo(poolingType, poolSize, dataLayout, padStrideInfo, excludePadding, |
| 192 | fpMixedPrecision); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 193 | } |
| 194 | |
| 195 | arm_compute::NormalizationLayerInfo BuildArmComputeNormalizationLayerInfo(const NormalizationDescriptor& descriptor) |
| 196 | { |
| 197 | const arm_compute::NormType normType = |
| 198 | ConvertNormalizationAlgorithmChannelToAclNormType(descriptor.m_NormChannelType); |
| 199 | return arm_compute::NormalizationLayerInfo(normType, |
| 200 | descriptor.m_NormSize, |
| 201 | descriptor.m_Alpha, |
| 202 | descriptor.m_Beta, |
| 203 | descriptor.m_K, |
| 204 | false); |
| 205 | } |
| 206 | |
| 207 | arm_compute::PermutationVector BuildArmComputePermutationVector(const armnn::PermutationVector& perm) |
| 208 | { |
| 209 | arm_compute::PermutationVector aclPerm; |
| 210 | |
| 211 | unsigned int start = 0; |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 212 | while ((start < perm.GetSize()) && (start == perm[start])) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 213 | { |
| 214 | ++start; |
| 215 | } |
| 216 | |
| 217 | for (unsigned int i = start; i < perm.GetSize(); ++i) |
| 218 | { |
| 219 | aclPerm.set(i - start, perm[i] - start); |
| 220 | } |
Mike Kelly | c9ea45a | 2020-02-28 18:11:58 +0000 | [diff] [blame] | 221 | return aclPerm; |
| 222 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 223 | |
Mike Kelly | c9ea45a | 2020-02-28 18:11:58 +0000 | [diff] [blame] | 224 | arm_compute::PermutationVector BuildArmComputeTransposeVector(const armnn::PermutationVector& perm) |
| 225 | { |
| 226 | arm_compute::PermutationVector aclPerm; |
| 227 | std::map<unsigned int, unsigned int> permuteMappings; |
| 228 | for (unsigned int i = 0; i < perm.GetSize(); ++i) |
| 229 | { |
| 230 | permuteMappings[perm[i]] = i; |
| 231 | } |
| 232 | |
| 233 | std::vector<unsigned int> permuteVector; |
| 234 | for (unsigned int i = 0; i < perm.GetSize(); ++i) |
| 235 | { |
| 236 | permuteVector.push_back(permuteMappings.at(i)); |
| 237 | } |
| 238 | |
| 239 | unsigned int start = 0; |
| 240 | while ((start < perm.GetSize()) && (start == permuteVector[start])) |
| 241 | { |
| 242 | ++start; |
| 243 | } |
| 244 | |
| 245 | for (unsigned int i = start; i < perm.GetSize(); ++i) |
| 246 | { |
| 247 | aclPerm.set(i - start, permuteVector[i] - start); |
| 248 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 249 | return aclPerm; |
| 250 | } |
| 251 | |
Sadik Armagan | f446432 | 2018-12-20 16:19:12 +0000 | [diff] [blame] | 252 | arm_compute::Size2D BuildArmComputeSize2D(const unsigned int width, const unsigned int height) |
| 253 | { |
| 254 | return arm_compute::Size2D(width, height); |
| 255 | } |
| 256 | |
Mike Kelly | 0a08ec6 | 2019-07-25 08:39:31 +0100 | [diff] [blame] | 257 | arm_compute::PixelValue GetPixelValue(arm_compute::ITensor& input, float pixelValue) |
| 258 | { |
| 259 | switch (input.info()->data_type()) |
| 260 | { |
Mike Kelly | 0a08ec6 | 2019-07-25 08:39:31 +0100 | [diff] [blame] | 261 | case arm_compute::DataType::F16: |
| 262 | return arm_compute::PixelValue(static_cast<Half>(pixelValue)); |
| 263 | case arm_compute::DataType::F32: |
| 264 | return arm_compute::PixelValue(pixelValue); |
Mike Kelly | 130ec60 | 2019-11-08 12:08:35 +0000 | [diff] [blame] | 265 | case arm_compute::DataType::QASYMM8: |
| 266 | return arm_compute::PixelValue(static_cast<uint8_t>(pixelValue)); |
| 267 | case arm_compute::DataType::QSYMM16: |
| 268 | return arm_compute::PixelValue(static_cast<int16_t>(pixelValue)); |
Sadik Armagan | e5d0b93 | 2020-04-09 15:48:44 +0100 | [diff] [blame] | 269 | case arm_compute::DataType::QASYMM8_SIGNED: |
Mike Kelly | 130ec60 | 2019-11-08 12:08:35 +0000 | [diff] [blame] | 270 | case arm_compute::DataType::QSYMM8_PER_CHANNEL: |
| 271 | return arm_compute::PixelValue(static_cast<int8_t>(pixelValue)); |
Sadik Armagan | a792a05 | 2020-06-23 16:22:23 +0100 | [diff] [blame] | 272 | case arm_compute::DataType::S32: |
| 273 | return arm_compute::PixelValue(static_cast<int32_t>(pixelValue)); |
Mike Kelly | 0a08ec6 | 2019-07-25 08:39:31 +0100 | [diff] [blame] | 274 | default: |
| 275 | throw InvalidArgumentException("Unsupported DataType: [" + |
| 276 | std::to_string(static_cast<int>(input.info()->data_type())) + "]"); |
| 277 | } |
| 278 | } |
| 279 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 280 | } // namespace armcomputetensorutils |
| 281 | } // namespace armnn |