| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "OutputShapeUtils.hpp" |
| |
| #include <algorithm> |
| #include <vector> |
| |
| namespace armnn_driver |
| { |
| |
| using namespace armnn; |
| |
| bool IsDynamicOutput(const TensorInfo& outputInfo) |
| { |
| return outputInfo.GetNumElements() == 0u; |
| } |
| |
| 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) |
| { |
| // NOTE: The inferred PReLU output size will be the maximum size along each dimension |
| // of input and alpha, starting with the trailing dimensions, and working its way forward. |
| // |
| // Example: inputShape={4, 1, 2}, alphaShape={5, 4, 3, 1} => outputShape={5, 4, 3, 2} |
| |
| const unsigned int numInputDims = inputShape.GetNumDimensions(); |
| const unsigned int numAlphaDims = alphaShape.GetNumDimensions(); |
| |
| const unsigned int maxNumDims = std::max(numInputDims, numAlphaDims); |
| |
| TensorShape outputShape = TensorShape(maxNumDims); |
| for (unsigned int reverseIdx = 1u; reverseIdx <= maxNumDims; ++reverseIdx) |
| { |
| const int inputIdx = numInputDims - reverseIdx; |
| const int alphaIdx = numAlphaDims - reverseIdx; |
| |
| const unsigned int inputDimSize = inputIdx >= 0 ? inputShape[inputIdx] : 0u; |
| const unsigned int alphaDimSize = alphaIdx >= 0 ? alphaShape[alphaIdx] : 0u; |
| |
| const unsigned int outputIdx = maxNumDims - reverseIdx; |
| outputShape[outputIdx] = std::max(inputDimSize, alphaDimSize); |
| } |
| |
| return outputShape; |
| } |
| |
| } // namespace armnn_driver |