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Diffstat (limited to 'OutputShapeUtils.cpp')
| -rw-r--r-- | OutputShapeUtils.cpp | 199 |
1 files changed, 0 insertions, 199 deletions
diff --git a/OutputShapeUtils.cpp b/OutputShapeUtils.cpp deleted file mode 100644 index ecec0b92..00000000 --- a/OutputShapeUtils.cpp +++ /dev/null @@ -1,199 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#include "OutputShapeUtils.hpp" - -#include <DataLayoutIndexed.hpp> - -#include <algorithm> -#include <numeric> -#include <vector> - -namespace -{ - -using namespace armnn; - -TensorShape CalculateMaxShape(const TensorShape& inShape0, const TensorShape& inShape1) -{ - // NOTE: The inferred output size will be the maximum size along each dimension - // of inShape0 and inShape1, starting with the trailing dimensions, and working its way forward. - // - // Example: inShape0={4, 1, 2}, inShape1={5, 4, 3, 1} => outputShape={5, 4, 3, 2} - - const unsigned int numInput0Dims = inShape0.GetNumDimensions(); - const unsigned int numInput1Dims = inShape1.GetNumDimensions(); - - const unsigned int maxNumDims = std::max(numInput0Dims, numInput1Dims); - - TensorShape outputShape = TensorShape(maxNumDims); - for (unsigned int reverseIdx = 1u; reverseIdx <= maxNumDims; ++reverseIdx) - { - const int input0Idx = numInput0Dims - reverseIdx; - const int input1Idx = numInput1Dims - reverseIdx; - - const unsigned int input0DimSize = input0Idx >= 0 ? inShape0[input0Idx] : 0u; - const unsigned int input1DimSize = input1Idx >= 0 ? inShape1[input1Idx] : 0u; - - const unsigned int outputIdx = maxNumDims - reverseIdx; - outputShape[outputIdx] = std::max(input0DimSize, input1DimSize); - } - - return outputShape; -} - -template<typename ConvolutionDescriptor> -TensorShape InferConvolution2dOutputShapeImpl(const TensorShape& inputShape, - const TensorShape& kernelShape, - const ConvolutionDescriptor& descriptor, - bool isDepthwiseConvolution) -{ - if (inputShape.GetNumDimensions() != 4) - { - throw InvalidArgumentException("Input shape must be 4D"); - } - - armnnUtils::DataLayoutIndexed dataLayoutIndex(descriptor.m_DataLayout); - - const unsigned int cIndex = dataLayoutIndex.GetChannelsIndex(); - const unsigned int wIndex = dataLayoutIndex.GetWidthIndex(); - const unsigned int hIndex = dataLayoutIndex.GetHeightIndex(); - - const unsigned int wInput = inputShape[wIndex]; - const unsigned int hInput = inputShape[hIndex]; - - const unsigned int wKernel = isDepthwiseConvolution ? kernelShape[2] : kernelShape[wIndex]; - const unsigned int wDilated = wKernel + (descriptor.m_DilationX - 1) * (wKernel - 1); - - const unsigned int wRead = (wInput + descriptor.m_PadLeft + descriptor.m_PadRight) - wDilated; - const unsigned int wOutput = 1 + (wRead / descriptor.m_StrideX); - - const unsigned int hKernel = isDepthwiseConvolution ? kernelShape[3] : kernelShape[hIndex]; - const unsigned int hDilated = hKernel + (descriptor.m_DilationY - 1) * (hKernel - 1); - - const unsigned int hRead = (hInput + descriptor.m_PadTop + descriptor.m_PadBottom) - hDilated; - const unsigned int hOutput = 1 + (hRead / descriptor.m_StrideY); - - TensorShape outputShape(4); - outputShape[0] = inputShape[0]; - outputShape[cIndex] = kernelShape[0]; - outputShape[wIndex] = wOutput; - outputShape[hIndex] = hOutput; - - if (isDepthwiseConvolution) - { - outputShape[cIndex] *= inputShape[cIndex]; - } - - return outputShape; -} - -} // anonymous namespace - -namespace armnn_driver -{ - -using namespace armnn; - -TensorShape InferConvolution2dOutputShape(const TensorShape& inputShape, - const TensorShape& kernelShape, - const Convolution2dDescriptor& descriptor) -{ - return InferConvolution2dOutputShapeImpl(inputShape, kernelShape, descriptor, false); -} - -TensorShape InferDepthwiseConvolution2dOutputShape(const TensorShape& inputShape, - const TensorShape& kernelShape, - const DepthwiseConvolution2dDescriptor& descriptor) -{ - return InferConvolution2dOutputShapeImpl(inputShape, kernelShape, descriptor, true); -} - -TensorShape InferMaximumOutputShape(const armnn::TensorShape& input0Shape, - const armnn::TensorShape& input1Shape) -{ - return CalculateMaxShape(input0Shape, input1Shape); -} - -TensorShape InferMinimumOutputShape(const armnn::TensorShape& input0Shape, - const armnn::TensorShape& input1Shape) -{ - return CalculateMaxShape(input0Shape, input1Shape); -} - -TensorShape InferPadOutputShape(const TensorShape& inputShape, - const std::vector<std::pair<unsigned int, unsigned int>>& padList) -{ - const unsigned int numDims = inputShape.GetNumDimensions(); - - std::vector<unsigned int> outputDims; - TensorShape outputShape = TensorShape(numDims); - for (unsigned int dim = 0; dim < numDims; ++dim) - { - unsigned int dimSize = inputShape[dim]; - const std::pair<unsigned int, unsigned int>& dimPadding = padList[dim]; - dimSize += dimPadding.first; - dimSize += dimPadding.second; - outputShape[dim] = dimSize; - } - return outputShape; -} - -TensorShape InferPreluOutputShape(const TensorShape& inputShape, const TensorShape& alphaShape) -{ - return CalculateMaxShape(inputShape, alphaShape); -} - -TensorShape InferResizeOutputShape(const TensorShape& inputShape, const ResizeDescriptor& descriptor) -{ - if (inputShape.GetNumDimensions() != 4) - { - throw InvalidArgumentException("Input shape for Resize must be 4D"); - } - - armnnUtils::DataLayoutIndexed dataLayoutIndexed(descriptor.m_DataLayout); - - const unsigned int cIndex = dataLayoutIndexed.GetChannelsIndex(); - const unsigned int wIndex = dataLayoutIndexed.GetWidthIndex(); - const unsigned int hIndex = dataLayoutIndexed.GetHeightIndex(); - - TensorShape outputShape(4); - outputShape[0] = inputShape[0]; - outputShape[cIndex] = inputShape[cIndex]; - outputShape[wIndex] = descriptor.m_TargetWidth; - outputShape[hIndex] = descriptor.m_TargetHeight; - - return outputShape; -} - -TensorShape InferSpaceToDepthOutputShape(const TensorShape& inputShape, const SpaceToDepthDescriptor& descriptor) -{ - TensorShape outputShape(inputShape); - - armnnUtils::DataLayoutIndexed dataLayoutIndexed(descriptor.m_DataLayout); - - const unsigned int cIndex = dataLayoutIndexed.GetChannelsIndex(); - const unsigned int wIndex = dataLayoutIndexed.GetWidthIndex(); - const unsigned int hIndex = dataLayoutIndexed.GetHeightIndex(); - - if (descriptor.m_BlockSize == 0) - { - throw InvalidArgumentException("Block size must be greater than zero"); - } - - outputShape[cIndex] = inputShape[cIndex] * descriptor.m_BlockSize * descriptor.m_BlockSize; - - outputShape[hIndex] = inputShape[hIndex] / descriptor.m_BlockSize; - outputShape[wIndex] = inputShape[wIndex] / descriptor.m_BlockSize; - - return outputShape; -} - -TensorShape InferSubOutputShape(const TensorShape& input0Shape, const TensorShape& input1Shape) -{ - return CalculateMaxShape(input0Shape, input1Shape); -} - -} // namespace armnn_driver |