diff options
Diffstat (limited to 'src/backends/reference/workloads/LstmUtils.hpp')
| -rw-r--r-- | src/backends/reference/workloads/LstmUtils.hpp | 218 |
1 files changed, 218 insertions, 0 deletions
diff --git a/src/backends/reference/workloads/LstmUtils.hpp b/src/backends/reference/workloads/LstmUtils.hpp new file mode 100644 index 0000000000..db02a84a45 --- /dev/null +++ b/src/backends/reference/workloads/LstmUtils.hpp @@ -0,0 +1,218 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "BaseIterator.hpp" +#include <backendsCommon/CpuTensorHandle.hpp> + +namespace +{ + +// Helper functions ported from the Android code base +// Refer to: android/external/tensorflow/tensorflow/contrib/lite/kernels/internal/reference/portable_tensor_utils.cc + +void MatrixBatchVectorMultiplyAccumulate(armnn::Decoder<float>& matrix, + uint32_t mRows, + uint32_t mCols, + armnn::Decoder<float>& vector, + uint32_t nBatch, + armnn::Encoder<float>& outResult) +{ + for (uint32_t b = 0; b < nBatch; b++) + { + for (uint32_t r = 0; r < mRows; r++) + { + vector += b * mCols; + for (uint32_t c = 0; c < mCols; c++) + { + outResult.Set(outResult.Get() + matrix.Get() * vector.Get()); + ++matrix; + ++vector; + } + outResult += 1; + vector -= (b+1) * mCols; + } + matrix -= (mRows * mCols); + } + outResult -= (mRows * nBatch); +} + +void VectorBatchVectorAssign(armnn::Decoder<float>& vector, + uint32_t vSize, + uint32_t nBatch, + armnn::Encoder<float>& outBatchVector) +{ + for (uint32_t b = 0; b < nBatch; b++) + { + for (uint32_t v = 0; v < vSize; v++) + { + outBatchVector.Set(vector.Get()); + ++outBatchVector; + ++vector; + } + vector -= vSize; + } + outBatchVector -= (nBatch * vSize); +} + +void VectorBatchVectorCwiseProductAccumulate(armnn::Decoder<float>& vector, + uint32_t vSize, + armnn::Decoder<float>& batchVector, + uint32_t nBatch, + armnn::Encoder<float>& outResult) +{ + for (uint32_t b = 0; b < nBatch; b++) + { + for (uint32_t v = 0; v < vSize; v++) + { + outResult.Set(outResult.Get() + vector.Get() * batchVector.Get()); + ++outResult; + ++vector; + ++batchVector; + } + vector -= vSize; + } + batchVector -= vSize * nBatch; + outResult -= vSize * nBatch; +} + +void Sub1Vector(armnn::Decoder<float>& vector, + uint32_t vSize, + armnn::Encoder<float>& result) +{ + for (uint32_t v = 0; v < vSize; v++) + { + result.Set(1.0f - vector.Get()); + ++vector; + ++result; + } + vector -= vSize; + result -= vSize; +} + +void VectorVectorCwiseProduct(armnn::Decoder<float>& vector1, + armnn::Decoder<float>& vector2, + uint32_t vSize, + armnn::Encoder<float>& outResult) +{ + for (uint32_t v = 0; v < vSize; v++) + { + outResult.Set(vector1.Get() * vector2.Get()); + ++outResult; + ++vector1; + ++vector2; + } + outResult -= vSize; + vector1 -= vSize; + vector2 -= vSize; +} + +void VectorVectorCwiseProductAccumulate(armnn::Decoder<float>& vector1, + armnn::Decoder<float>& vector2, + uint32_t vSize, + armnn::Encoder<float>& outResult) +{ + for (uint32_t v = 0; v < vSize; v++) + { + outResult.Set(outResult.Get() + vector1.Get() * vector2.Get()); + ++outResult; + ++vector1; + ++vector2; + } + outResult -= vSize; + vector1 -= vSize; + vector2 -= vSize; +} + +float Clip(float f, + float absLimit) +{ + float result = (absLimit < f) ? absLimit : f; + result = (-absLimit > result) ? -absLimit : result; + return result; +} + +void ClipVector(armnn::Decoder<float>& vector, + uint32_t vSize, + float absLimit, + armnn::Encoder<float>& outResult) +{ + for (uint32_t v = 0; v < vSize; v++) + { + outResult.Set(Clip(vector.Get(), absLimit)); + ++vector; + ++outResult; + } + vector -= vSize; + outResult -= vSize; +} + +void CopyVector(armnn::Decoder<float>& vector, + uint32_t vSize, + armnn::Encoder<float>& outResult) +{ + for (uint32_t v = 0; v < vSize; v++) + { + outResult.Set(vector.Get()); + ++outResult; + ++vector; + } + outResult -= vSize; + vector -= vSize; +} + +void SetActivationParameters(uint32_t activation, + armnn::ActivationFunction& outArmnnActivation, + float& outA, + float& outB) +{ + switch (activation) + { + case 0: // None + outA = 0; + outB = 0; + return; + + case 1: // Relu + outArmnnActivation = armnn::ActivationFunction::ReLu; + outA = 0; + outB = 0; + return; + + case 3: // Relu6 + outArmnnActivation = armnn::ActivationFunction::BoundedReLu; + outA = 6; + outB = 0; + return; + + case 4: // Tanh + outArmnnActivation = armnn::ActivationFunction::TanH; + outA = 1; + outB = 1; + return; + + case 6: // Sigmoid + outArmnnActivation = armnn::ActivationFunction::Sigmoid; + outA = 0; + outB = 0; + return; + + default: + throw armnn::Exception("Unsupported activation function: " + std::to_string(activation)); + } +} + +std::unique_ptr<armnn::ScopedCpuTensorHandle> AssignScopedCpuTensorHandle(const armnn::ConstCpuTensorHandle* ptr) +{ + if (!ptr) + { + return nullptr; + } + + return std::make_unique<armnn::ScopedCpuTensorHandle>(*ptr); +} + +} // anonymous namespace |