| // |
| // 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>>; |
| |
| template class armnn::BaseFloat32ElementwiseWorkload<armnn::MaximumQueueDescriptor, armnn::maximum<float>>; |
| template class armnn::BaseUint8ElementwiseWorkload<armnn::MaximumQueueDescriptor, armnn::maximum<float>>; |
| |
| template class armnn::BaseFloat32ElementwiseWorkload<armnn::MinimumQueueDescriptor, armnn::minimum<float>>; |
| template class armnn::BaseUint8ElementwiseWorkload<armnn::MinimumQueueDescriptor, armnn::minimum<float>>; |