Matthew Sloyan | 2e5d0b2 | 2021-10-21 14:05:31 +0100 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2021 Arm Ltd and Contributors. All rights reserved. |
| 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #include "MirrorPad.hpp" |
| 7 | |
| 8 | #include "BaseIterator.hpp" |
| 9 | #include "Decoders.hpp" |
| 10 | #include "Encoders.hpp" |
| 11 | |
| 12 | namespace |
| 13 | { |
| 14 | |
| 15 | // Convert a linear index into n-dimensional coordinates. |
| 16 | // E.g. index = 2 returns [0, 0, 2]. |
| 17 | inline std::vector<unsigned int> IndexToCoord(const armnn::TensorShape& shape, unsigned int index) |
| 18 | { |
| 19 | unsigned int numOfElements = shape.GetNumElements(); |
| 20 | |
| 21 | ARMNN_ASSERT_MSG(index <= numOfElements, "Index has to be in [0, num_elements]"); |
| 22 | ARMNN_ASSERT_MSG(numOfElements != 0, "Cannot create coordinate from empty shape"); |
| 23 | |
| 24 | std::vector<unsigned int> coord(shape.GetNumDimensions()); |
| 25 | for(unsigned int i = 0; i < shape.GetNumDimensions(); ++i) |
| 26 | { |
| 27 | numOfElements /= shape[i]; |
| 28 | coord[i] = index / numOfElements; |
| 29 | index %= numOfElements; |
| 30 | } |
| 31 | |
| 32 | return coord; |
| 33 | } |
| 34 | |
| 35 | // Returns the index of a given coordinate. |
| 36 | // E.g. [0, 0, 2] returns 2. |
| 37 | inline unsigned int CoordToIndex(const armnn::TensorShape& shape, const std::vector<unsigned int>& coord) |
| 38 | { |
| 39 | ARMNN_ASSERT_MSG(shape.GetNumDimensions() != 0, "Cannot get index from empty shape"); |
| 40 | ARMNN_ASSERT_MSG(coord.size() != 0, "Cannot get index of empty coordinate"); |
| 41 | |
| 42 | unsigned int index = 0; |
| 43 | unsigned int dimSize = 1; |
| 44 | |
| 45 | for (unsigned int i = shape.GetNumDimensions(); i > 0; --i) |
| 46 | { |
| 47 | index += coord[i - 1] * dimSize; |
| 48 | dimSize *= shape[i - 1]; |
| 49 | } |
| 50 | |
| 51 | return index; |
| 52 | } |
| 53 | |
| 54 | } // anonymous namespace |
| 55 | |
| 56 | namespace armnn |
| 57 | { |
| 58 | |
| 59 | void MirrorPad(const TensorInfo& inputInfo, |
| 60 | const TensorInfo& outputInfo, |
| 61 | const ITensorHandle* inputHandle, |
| 62 | ITensorHandle* outputHandle, |
| 63 | const PadQueueDescriptor& data) |
| 64 | { |
| 65 | auto padList = data.m_Parameters.m_PadList; |
| 66 | PaddingMode paddingMode = data.m_Parameters.m_PaddingMode; |
| 67 | |
| 68 | TensorShape outputShape = outputInfo.GetShape(); |
| 69 | TensorShape inputShape = inputInfo.GetShape(); |
| 70 | |
| 71 | unsigned int numOutputElements = outputInfo.GetNumElements(); |
| 72 | unsigned int numInputDimensions = inputShape.GetNumDimensions(); |
| 73 | assert(numInputDimensions == outputShape.GetNumDimensions()); |
| 74 | |
| 75 | // If padding mode is Reflect then both paddings must be no greater than inputShape(i) - 1. |
| 76 | // If padding mode is Symmetric then both paddings must be no greater than inputShape(i). |
| 77 | const unsigned int isReflect = static_cast<unsigned int>(paddingMode == PaddingMode::Reflect); |
| 78 | for(unsigned int i = 0; i < padList.size(); ++i) |
| 79 | { |
| 80 | if(padList.at(i).first > (inputShape[i] - isReflect) || |
| 81 | padList.at(i).second > (inputShape[i] - isReflect)) |
| 82 | { |
| 83 | throw armnn::InvalidArgumentException("Paddings must be less (Reflect) or " |
| 84 | "equal (Symmetric) to the dimension size."); |
| 85 | } |
| 86 | } |
| 87 | |
| 88 | auto inputData = MakeDecoder<float>(inputInfo, inputHandle->Map()); |
| 89 | auto outData = MakeEncoder<float>(outputInfo, outputHandle->Map()); |
| 90 | |
| 91 | Decoder<float>& input = *inputData; |
| 92 | Encoder<float>& output = *outData; |
| 93 | |
| 94 | for(unsigned int idx = 0; idx < numOutputElements; ++idx) |
| 95 | { |
| 96 | // Get the coordinates of the current index in vector form. E.g inx 1 = [0, 0, 0, 1 ] |
| 97 | const std::vector<unsigned int> coord = IndexToCoord(outputShape, idx); |
| 98 | |
| 99 | std::vector<unsigned int> dimensions; |
| 100 | std::vector<unsigned int> coords; |
| 101 | |
| 102 | for(unsigned int i = 0; i < numInputDimensions; ++i) |
| 103 | { |
| 104 | dimensions.emplace_back(i); |
| 105 | coords.emplace_back(coord[i]); |
| 106 | } |
| 107 | |
| 108 | auto isInPadding = [&](unsigned int i) |
| 109 | { |
| 110 | return (coords[i] < padList[i].first || coords[i] > inputShape[i] + padList[i].first - 1); |
| 111 | }; |
| 112 | |
| 113 | auto getReflectIndex = [&](unsigned int i) -> unsigned int |
| 114 | { |
| 115 | if(isInPadding(i)) |
| 116 | { |
| 117 | if(coords[i] < padList[i].first) |
| 118 | { |
| 119 | return padList[i].first - coords[i]; |
| 120 | } |
| 121 | else |
| 122 | { |
| 123 | return 2 * inputShape[i] + padList[i].first - 2 - coords[i]; |
| 124 | } |
| 125 | } |
| 126 | return coords[i] - padList[i].first; |
| 127 | }; |
| 128 | |
| 129 | auto getSymmetricIndex = [&](unsigned int i) -> unsigned int |
| 130 | { |
| 131 | if(isInPadding(i)) |
| 132 | { |
| 133 | if(coords[i] < padList[i].first) |
| 134 | { |
| 135 | return padList[i].first - coords[i] - 1; |
| 136 | } |
| 137 | else |
| 138 | { |
| 139 | return 2 * inputShape[i] + padList[i].first - 1 - coords[i]; |
| 140 | } |
| 141 | } |
| 142 | return coords[i] - padList[i].first; |
| 143 | }; |
| 144 | |
| 145 | // Location of the value in the input tensor to use in the output. |
| 146 | std::vector<unsigned int> coordOfInput; |
| 147 | |
| 148 | // any_of works as a loop here to check if any of the dimensions are in the padding. |
| 149 | // If dimensions is in the padding area, then create the coordinates of the location in the |
| 150 | // input tensor to use in the output. |
| 151 | // E.g. |
| 152 | // Input tensor = [ 1, 2, 3 ], Rank = 1. |
| 153 | // Output tensor = [ 2, 1, 2, 3, 1 ] if Reflect or [ 1, 1, 2, 3, 3 ] if Symmetric with a padding of (1, 1). |
| 154 | // So it will either return [ 1 ] or [ 0 ] which is used to set the first value in the output tensor and so on. |
| 155 | if(std::any_of(dimensions.begin(), dimensions.end(), isInPadding)) |
| 156 | { |
| 157 | switch(paddingMode) |
| 158 | { |
| 159 | case PaddingMode::Reflect: |
| 160 | { |
| 161 | for(unsigned int i = 0; i < numInputDimensions; ++i) |
| 162 | { |
| 163 | coordOfInput.emplace_back(getReflectIndex(i)); |
| 164 | } |
| 165 | break; |
| 166 | } |
| 167 | case PaddingMode::Symmetric: |
| 168 | { |
| 169 | for(unsigned int i = 0; i < numInputDimensions; ++i) |
| 170 | { |
| 171 | coordOfInput.emplace_back(getSymmetricIndex(i)); |
| 172 | } |
| 173 | break; |
| 174 | } |
| 175 | default: |
| 176 | throw InvalidArgumentException("Padding mode not supported."); |
| 177 | break; |
| 178 | } |
| 179 | } |
| 180 | else |
| 181 | { |
| 182 | for(unsigned int i = 0; i < numInputDimensions; ++i) |
| 183 | { |
| 184 | coordOfInput.emplace_back(coord[i] - padList[i].first); |
| 185 | } |
| 186 | } |
| 187 | |
| 188 | // Set output value using the coordinate of the input value to use. |
| 189 | const unsigned int indexOfInput = CoordToIndex(inputShape, coordOfInput); |
| 190 | |
| 191 | input[indexOfInput]; |
| 192 | auto inputValue = input.Get(); |
| 193 | |
| 194 | output[idx]; |
| 195 | output.Set(inputValue); |
| 196 | } |
| 197 | } |
| 198 | |
| 199 | } //namespace armnn |