| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "Stack.hpp" |
| #include "RefWorkloadUtils.hpp" |
| |
| namespace armnn |
| { |
| |
| void Stack(const StackQueueDescriptor& data, |
| std::vector<std::unique_ptr<Decoder<float>>>& inputs, |
| Encoder<float>& output, |
| const TensorInfo& inputInfo, |
| const TensorInfo& outputInfo) |
| { |
| unsigned int outputNumDims = outputInfo.GetNumDimensions(); |
| unsigned int inputNumDims = inputInfo.GetNumDimensions(); |
| |
| const armnn::TensorShape& outputDims = outputInfo.GetShape(); |
| const armnn::TensorShape& inputDims = inputInfo.GetShape(); |
| |
| unsigned int axis = data.m_Parameters.m_Axis; |
| |
| // Can perform a simple concatenation when axis == 0 |
| if (!axis) |
| { |
| unsigned int numInputs = data.m_Parameters.m_NumInputs; |
| unsigned int inputLength = inputInfo.GetNumElements(); |
| |
| for (unsigned int inputIdx=0; inputIdx<numInputs; ++inputIdx) |
| { |
| for (unsigned int elmt=0; elmt<inputLength; ++elmt) |
| { |
| (*inputs[inputIdx])[elmt]; |
| output[(inputIdx * inputLength) + elmt]; |
| output.Set(inputs[inputIdx]->Get()); |
| } |
| } |
| return; |
| } |
| |
| // Initialise output data |
| unsigned int numOutputElements = 1; |
| for (unsigned int i=0; i<outputNumDims; ++i) |
| { |
| numOutputElements *= outputDims[i]; |
| } |
| |
| const unsigned int iNumTensors = static_cast<unsigned int>(data.m_Inputs.size()); |
| const unsigned int iBatchSize = inputDims[0]; |
| const unsigned int iChannels = (inputNumDims > 1) ? inputDims[1] : 1; |
| const unsigned int iHeight = (inputNumDims > 2) ? inputDims[2] : 1; |
| const unsigned int iWidth = (inputNumDims > 3) ? inputDims[3] : 1; |
| |
| const unsigned int oBatchSize = outputDims[1]; |
| const unsigned int oChannels = (outputNumDims > 2) ? outputDims[2] : 1; |
| const unsigned int oHeight = (outputNumDims > 3) ? outputDims[3] : 1; |
| const unsigned int oWidth = (outputNumDims > 4) ? outputDims[4] : 1; |
| |
| // Array to store the input coordinates |
| // iCoordinates[0] = i, iCoordinates[1] = bi, iCoordinates[2] = ci |
| // iCoordinates[3] = hi, iCoordinates[4] = wi, iCoordinates[5] = 0 |
| // iCoordinates[5] will be always zero and used for not incrementing |
| // the output when the input has less than 4 dimensions |
| std::array<unsigned int, 6> iCoordinates{ 0 }; |
| |
| // Array of pointers used to map the output coordinates to the input ones, in accordance with the axis |
| // This array is initialized with &iCoordinates[5] since this will be always zero |
| std::array<unsigned int *, 5> oCoordinates = { &iCoordinates[5], |
| &iCoordinates[5], |
| &iCoordinates[5], |
| &iCoordinates[5], |
| &iCoordinates[5] }; |
| |
| // Set the axis coordinate |
| oCoordinates[axis] = &iCoordinates[0]; |
| |
| // Map the output coordinates, accounting for the axis |
| unsigned int dim_shift = 0; |
| for(unsigned int dim = 0; dim < inputNumDims; ++dim) |
| { |
| if(dim == axis) |
| { |
| dim_shift++; |
| } |
| oCoordinates[dim + dim_shift] = &iCoordinates[dim + 1]; |
| } |
| |
| // Alias for the input coordinates |
| unsigned int &i = iCoordinates[0]; |
| unsigned int &bi = iCoordinates[1]; |
| unsigned int &ci = iCoordinates[2]; |
| unsigned int &hi = iCoordinates[3]; |
| unsigned int &wi = iCoordinates[4]; |
| |
| // Alias for the output coordinates |
| unsigned int &o = *(oCoordinates[0]); |
| unsigned int &bo = *(oCoordinates[1]); |
| unsigned int &co = *(oCoordinates[2]); |
| unsigned int &ho = *(oCoordinates[3]); |
| unsigned int &wo = *(oCoordinates[4]); |
| |
| // Stack tensors |
| for(; i < iNumTensors; ++(i)) |
| { |
| for(bi = 0; bi < iBatchSize; ++(bi)) |
| { |
| for(ci = 0; ci < iChannels; ++(ci)) |
| { |
| for(hi = 0; hi < iHeight; ++(hi)) |
| { |
| for(wi = 0; wi < iWidth; ++(wi)) |
| { |
| output[o * oWidth * oHeight * oChannels * oBatchSize + |
| bo * oWidth * oHeight * oChannels + |
| co * oWidth * oHeight + |
| ho * oWidth + |
| wo]; |
| |
| output.Set(inputs[i]->Get()); |
| |
| ++(*(inputs[i])); |
| } |
| } |
| } |
| } |
| } |
| } |
| |
| } // namespace armnn |