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Diffstat (limited to 'src/backends/RefWorkloads/Softmax.cpp')
-rw-r--r-- | src/backends/RefWorkloads/Softmax.cpp | 49 |
1 files changed, 49 insertions, 0 deletions
diff --git a/src/backends/RefWorkloads/Softmax.cpp b/src/backends/RefWorkloads/Softmax.cpp new file mode 100644 index 0000000000..4f1016e86c --- /dev/null +++ b/src/backends/RefWorkloads/Softmax.cpp @@ -0,0 +1,49 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "Softmax.hpp" + +#include <cmath> +#include <vector> + +namespace armnn +{ + +/// Computes the softmax function on some inputs, into outputs, with a shape given by tensorInfo. +void Softmax(const float* in, float* out, const TensorInfo& tensorInfo, float beta) +{ + unsigned int numChannels = tensorInfo.GetShape()[1]; + for (unsigned int n = 0; n < tensorInfo.GetShape()[0]; n++) + { + // Find maximum channel. + float max = in[n * numChannels]; + for (unsigned int c = 1; c < numChannels; c++) + { + float val = in[n * numChannels + c]; + if (val > max) + { + max = val; + } + } + + // Exponentiate all values and sum. + std::vector<float> exponentials(numChannels); + float sum = 0.0f; + for (unsigned int c = 0; c < numChannels; c++) + { + float val = in[n * numChannels + c]; + exponentials[c] = expf((val - max) * beta); + sum += exponentials[c]; + } + + // Divide exponentials by sum to give outputs. + for (unsigned int c = 0; c < numChannels; c++) + { + out[n * numChannels + c] = exponentials[c] / sum; + } + } +} + +} //namespace armnn |