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Diffstat (limited to 'src/backends/reference/workloads/Conv3dImpl.cpp')
| -rw-r--r-- | src/backends/reference/workloads/Conv3dImpl.cpp | 151 |
1 files changed, 151 insertions, 0 deletions
diff --git a/src/backends/reference/workloads/Conv3dImpl.cpp b/src/backends/reference/workloads/Conv3dImpl.cpp new file mode 100644 index 0000000000..484d887cfc --- /dev/null +++ b/src/backends/reference/workloads/Conv3dImpl.cpp @@ -0,0 +1,151 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "Conv3dImpl.hpp" + +namespace armnn +{ + +void Convolve3d(const TensorShape& rInputShape, + Decoder<float>& rInputDecoder, + const TensorShape& rOutputShape, + Encoder<float>& rOutputEncoder, + const TensorShape& rFilterShape, + Decoder<float>& rFilterDecoder, + bool biasEnabled, + Decoder<float>* pBiasDecoder, + DataLayout dataLayout, + unsigned int paddingTop, + unsigned int paddingLeft, + unsigned int paddingFront, + unsigned int xStride, + unsigned int yStride, + unsigned int zStride, + unsigned int xDilation, + unsigned int yDilation, + unsigned int zDilation) +{ + if (biasEnabled && !pBiasDecoder) + { + throw InvalidArgumentException("Bias is enabled but the bias data is invalid"); + } + const armnnUtils::DataLayoutIndexed dataLayoutIndexed(dataLayout); + + const unsigned int channelsIndex = dataLayoutIndexed.GetChannelsIndex(); + const unsigned int heightIndex = dataLayoutIndexed.GetHeightIndex(); + const unsigned int widthIndex = dataLayoutIndexed.GetWidthIndex(); + const unsigned int depthIndex = dataLayoutIndexed.GetDepthIndex(); + + const unsigned int inChannels = rInputShape[channelsIndex]; + const unsigned int outChannels = rOutputShape[channelsIndex]; + + const unsigned int batchSize = rOutputShape[0]; + const unsigned int outputHeight = rOutputShape[heightIndex]; + const unsigned int outputWidth = rOutputShape[widthIndex]; + const unsigned int outputDepth = rOutputShape[depthIndex]; + const unsigned int inputHeight = rInputShape[heightIndex]; + const unsigned int inputWidth = rInputShape[widthIndex]; + const unsigned int inputDepth = rInputShape[depthIndex]; + + // Conv3d weights layout: [D,H,W,I,O] + const unsigned int filterDepth = rFilterShape[0]; + const unsigned int filterHeight = rFilterShape[1]; + const unsigned int filterWidth = rFilterShape[2]; + + const std::vector<float> inputVec = rInputDecoder.DecodeTensor(rInputShape); + const std::vector<float> filterVec = rFilterDecoder.DecodeTensor(rFilterShape); + + const TensorShape biasShape{outChannels}; + const std::vector<float> biasVec = biasEnabled ? pBiasDecoder->DecodeTensor(biasShape) : std::vector<float>(); + + for (unsigned int batchIdx = 0; batchIdx < batchSize; batchIdx++) + { + for (unsigned int zOutput = 0; zOutput < outputDepth; zOutput++) + { + for (unsigned int xOutput = 0; xOutput < outputWidth; xOutput++) + { + for (unsigned int yOutput = 0; yOutput < outputHeight; yOutput++) + { + for (unsigned int cOutput = 0; cOutput < outChannels; cOutput++) + { + // This loop goes over each output element. + float sum = 0.0f; + + // Loop over each input channel. + for (unsigned int zFilter = 0; zFilter < filterDepth; zFilter++) + { + for (unsigned int yFilter = 0; yFilter < filterHeight; yFilter++) + { + for (unsigned int xFilter = 0; xFilter < filterWidth; xFilter++) + { + for (unsigned int cInput = 0; cInput < inChannels; cInput++) + { + // This loop goes over each input element for each output element. + unsigned int filterIndex = 0; + + // Conv3d weights layout: [D,H,W,I,O] + // Keep this implementation, as using DataLayoutIndexed::GetIndex + // causes large performance regression. + filterIndex = zFilter * filterHeight * filterWidth * inChannels * outChannels + + yFilter * filterWidth * inChannels * outChannels + + xFilter * inChannels * outChannels + + cInput * outChannels + + cOutput; + + unsigned int yInput = yOutput * yStride + yFilter * yDilation; + unsigned int xInput = xOutput * xStride + xFilter * xDilation; + unsigned int zInput = zOutput * zStride + zFilter * zDilation; + + float inputValue; + + // Check if we're in the padding. + if (yInput < paddingTop || yInput >= inputHeight + paddingTop || + xInput < paddingLeft || xInput >= inputWidth + paddingLeft || + zInput < paddingFront || zInput >= inputDepth + paddingFront) + { + inputValue = 0.0f; + } + else + { + unsigned int inputIndex = 0; + + // Keep this implementation, as using DataLayoutIndexed::GetIndex + // causes large performance regression. + inputIndex = batchIdx * inputDepth * inputHeight * inputWidth * inChannels + + (zInput-paddingFront) * inputHeight * inputWidth * inChannels + + (yInput-paddingTop) * inputWidth * inChannels + + (xInput-paddingLeft) * inChannels + + cInput; + + inputValue = inputVec[inputIndex]; + } + + sum += filterVec[filterIndex] * inputValue; + } + } + } + } + + if (biasEnabled) + { + sum += biasVec[cOutput]; + } + + unsigned int outIdx = batchIdx * outputDepth * outputHeight * outputWidth * outChannels + + zOutput * outputHeight * outputWidth * outChannels + + yOutput * outputWidth * outChannels + + xOutput * outChannels + + cOutput; + + rOutputEncoder[outIdx]; + rOutputEncoder.Set(sum); + } + } + } + } + } +} + +} // namespace armnn |