diff options
Diffstat (limited to 'src/backends/reference/workloads/RefElementwiseWorkload.cpp')
-rw-r--r-- | src/backends/reference/workloads/RefElementwiseWorkload.cpp | 69 |
1 files changed, 69 insertions, 0 deletions
diff --git a/src/backends/reference/workloads/RefElementwiseWorkload.cpp b/src/backends/reference/workloads/RefElementwiseWorkload.cpp new file mode 100644 index 0000000000..8e312a7dd1 --- /dev/null +++ b/src/backends/reference/workloads/RefElementwiseWorkload.cpp @@ -0,0 +1,69 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "RefElementwiseWorkload.hpp" +#include "ElementwiseFunction.hpp" +#include "RefWorkloadUtils.hpp" +#include "Profiling.hpp" +#include <vector> + +namespace armnn +{ + +template <typename ParentDescriptor, typename Functor> +void BaseFloat32ElementwiseWorkload<ParentDescriptor, Functor>::ExecuteImpl(const char * debugString) const +{ + ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, debugString); + + auto data = Float32Workload<ParentDescriptor>::GetData(); + const TensorShape& inShape0 = GetTensorInfo(data.m_Inputs[0]).GetShape(); + const TensorShape& inShape1 = GetTensorInfo(data.m_Inputs[1]).GetShape(); + const TensorShape& outShape = GetTensorInfo(data.m_Outputs[0]).GetShape(); + + const float* inData0 = GetInputTensorDataFloat(0, data); + const float* inData1 = GetInputTensorDataFloat(1, data); + float* outData = GetOutputTensorDataFloat(0, data); + + ElementwiseFunction<Functor>(inShape0, inShape1, outShape, inData0, inData1, outData); +} + +template <typename ParentDescriptor, typename Functor> +void BaseUint8ElementwiseWorkload<ParentDescriptor, Functor>::ExecuteImpl(const char * debugString) const +{ + ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, debugString); + + auto data = Uint8Workload<ParentDescriptor>::GetData(); + const TensorInfo& inputInfo0 = GetTensorInfo(data.m_Inputs[0]); + const TensorInfo& inputInfo1 = GetTensorInfo(data.m_Inputs[1]); + const TensorInfo& outputInfo = GetTensorInfo(data.m_Outputs[0]); + + auto dequant0 = Dequantize(GetInputTensorDataU8(0, data), inputInfo0); + auto dequant1 = Dequantize(GetInputTensorDataU8(1, data), inputInfo1); + + std::vector<float> results(outputInfo.GetNumElements()); + + ElementwiseFunction<Functor>(inputInfo0.GetShape(), + inputInfo1.GetShape(), + outputInfo.GetShape(), + dequant0.data(), + dequant1.data(), + results.data()); + + Quantize(GetOutputTensorDataU8(0, data), results.data(), outputInfo); +} + +} + +template class armnn::BaseFloat32ElementwiseWorkload<armnn::AdditionQueueDescriptor, std::plus<float>>; +template class armnn::BaseUint8ElementwiseWorkload<armnn::AdditionQueueDescriptor, std::plus<float>>; + +template class armnn::BaseFloat32ElementwiseWorkload<armnn::SubtractionQueueDescriptor, std::minus<float>>; +template class armnn::BaseUint8ElementwiseWorkload<armnn::SubtractionQueueDescriptor, std::minus<float>>; + +template class armnn::BaseFloat32ElementwiseWorkload<armnn::MultiplicationQueueDescriptor, std::multiplies<float>>; +template class armnn::BaseUint8ElementwiseWorkload<armnn::MultiplicationQueueDescriptor, std::multiplies<float>>; + +template class armnn::BaseFloat32ElementwiseWorkload<armnn::DivisionQueueDescriptor, std::divides<float>>; +template class armnn::BaseUint8ElementwiseWorkload<armnn::DivisionQueueDescriptor, std::divides<float>>; |