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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "RefFullyConnectedWorkload.hpp"
#include "FullyConnected.hpp"
#include "RefWorkloadUtils.hpp"
#include "Profiling.hpp"
namespace armnn
{
RefFullyConnectedWorkload::RefFullyConnectedWorkload(
const FullyConnectedQueueDescriptor& descriptor, const WorkloadInfo& info)
: RefBaseWorkload<FullyConnectedQueueDescriptor>(descriptor, info)
{
}
void RefFullyConnectedWorkload::PostAllocationConfigure()
{
PostAllocationConfigure(m_Data.m_Inputs, m_Data.m_Outputs);
}
void RefFullyConnectedWorkload::PostAllocationConfigure(std::vector<ITensorHandle*> inputs,
std::vector<ITensorHandle*> outputs)
{
const TensorInfo& inputInfo = GetTensorInfo(inputs[0]);
ARMNN_ASSERT(inputInfo.GetNumDimensions() > 1);
m_InputShape = inputInfo.GetShape();
const TensorInfo& rWeightInfo = GetTensorInfo(inputs[1]);
ARMNN_ASSERT(inputInfo.GetNumDimensions() > 1);
m_WeightShape = rWeightInfo.GetShape();
m_WeightDecoder = MakeDecoder<float>(rWeightInfo);
if (m_Data.m_Parameters.m_BiasEnabled)
{
const TensorInfo& biasInfo = GetTensorInfo(inputs[2]);
m_BiasDecoder = MakeDecoder<float>(biasInfo);
}
const TensorInfo& outputInfo = GetTensorInfo(outputs[0]);
m_OutputShape = outputInfo.GetShape();
m_NumActivations = 1; // Total number of activations in the input.
for (unsigned int i = 1; i < inputInfo.GetNumDimensions(); i++)
{
m_NumActivations *= inputInfo.GetShape()[i];
}
}
void RefFullyConnectedWorkload::Execute() const
{
Execute(m_Data.m_Inputs, m_Data.m_Outputs);
}
void RefFullyConnectedWorkload::ExecuteAsync(WorkingMemDescriptor &workingMemDescriptor)
{
PostAllocationConfigure(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
Execute(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
}
void RefFullyConnectedWorkload::Execute(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs) const
{
ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefFullyConnectedWorkload_Execute");
std::unique_ptr<Decoder<float>> inputDecoder = MakeDecoder<float>(GetTensorInfo(inputs[0]), inputs[0]->Map());
std::unique_ptr<Encoder<float>> OutputEncoder = MakeEncoder<float>(GetTensorInfo(outputs[0]), outputs[0]->Map());
m_WeightDecoder->Reset(inputs[1]->Map());
if (m_Data.m_Parameters.m_BiasEnabled)
{
m_BiasDecoder->Reset(inputs[2]->Map());
}
FullyConnected(m_InputShape,
*inputDecoder,
m_OutputShape,
*OutputEncoder,
m_WeightShape,
*m_WeightDecoder,
m_BiasDecoder.get(),
m_Data.m_Parameters.m_BiasEnabled,
m_NumActivations,
m_Data.m_Parameters.m_TransposeWeightMatrix);
}
} //namespace armnn
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