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//
// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ClFullyConnectedWorkload.hpp"
#include <cl/ClTensorHandle.hpp>
#include <armnn/backends/TensorHandle.hpp>
#include <aclCommon/ArmComputeTensorUtils.hpp>
#include <aclCommon/ArmComputeUtils.hpp>
#include <cl/ClLayerSupport.hpp>
#include "ClWorkloadUtils.hpp"
namespace armnn
{
using namespace armcomputetensorutils;
arm_compute::Status ClFullyConnectedWorkloadValidate(const TensorInfo& input,
const TensorInfo& output,
const TensorInfo& weights,
const Optional<TensorInfo>& biases,
const FullyConnectedDescriptor& descriptor,
const ActivationDescriptor* activationDescriptor)
{
// The CL implemented workload does support both const and non const
// weights. However, in the case of non const weights we'd have to call
// prepare or configure for each inference which we're not setup to do just yet.
if (!weights.IsConstant())
{
return arm_compute::Status{arm_compute::ErrorCode::RUNTIME_ERROR,
"Arm NN ClFullyConnectedWorkload does not support non constant weights."};
}
const arm_compute::TensorInfo aclInput = BuildArmComputeTensorInfo(input);
const arm_compute::TensorInfo aclOutput = BuildArmComputeTensorInfo(output);
arm_compute::TensorInfo aclWeights = BuildArmComputeTensorInfo(weights);
aclWeights.set_are_values_constant(weights.IsConstant());
arm_compute::TensorInfo aclBiases;
arm_compute::TensorInfo* optionalAclBiases = nullptr;
if (descriptor.m_BiasEnabled)
{
ARMNN_ASSERT(biases.has_value());
// Same for bias as weights. We don't currently support non const.
if (!biases.value().IsConstant())
{
return arm_compute::Status{arm_compute::ErrorCode::RUNTIME_ERROR,
"Arm NN ClFullyConnectedWorkload does not support non constant bias."};
}
aclBiases = BuildArmComputeTensorInfo(biases.value());
aclBiases.set_are_values_constant(biases.value().IsConstant());
optionalAclBiases = &aclBiases;
}
const arm_compute::FullyConnectedLayerInfo fullyConnectedLayerInfo =
ConvertFullyConnectedDescriptorToAclFullyConnectedLayerInfo(descriptor, activationDescriptor);
return arm_compute::CLFullyConnectedLayer::validate(&aclInput,
&aclWeights,
optionalAclBiases,
&aclOutput,
fullyConnectedLayerInfo);
}
ClFullyConnectedWorkload::ClFullyConnectedWorkload(
const FullyConnectedQueueDescriptor& descriptor,
const WorkloadInfo& info,
std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager,
const arm_compute::CLCompileContext& clCompileContext)
: ClBaseWorkload<FullyConnectedQueueDescriptor>(descriptor, info), m_FullyConnectedLayer(memoryManager)
{
// Add details for profiling output
WorkloadInfo detailsInfo;
detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos;
detailsInfo.m_OutputTensorInfos = info.m_OutputTensorInfos;
detailsInfo.m_WeightsTensorInfo = armnn::Optional<armnn::TensorInfo>(descriptor.m_Weight->GetTensorInfo());
if (descriptor.m_Parameters.m_BiasEnabled)
{
detailsInfo.m_BiasTensorInfo = armnn::Optional<armnn::TensorInfo>(descriptor.m_Bias->GetTensorInfo());
}
// Report Profiling Details
ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClFullyConnectedWorkload_Construct",
descriptor.m_Parameters,
detailsInfo,
this->GetGuid());
m_Data.ValidateInputsOutputs("ClFullyConnectedWorkload", descriptor.m_Parameters.GetNumInputs(),
1);
arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
arm_compute::ICLTensor& weights = PolymorphicDowncast<IClTensorHandle*>(m_Data.m_Inputs[1])->GetTensor();
arm_compute::ICLTensor* bias = nullptr;
if (m_Data.m_Parameters.m_BiasEnabled)
{
bias = &PolymorphicDowncast<IClTensorHandle*>(m_Data.m_Inputs[2])->GetTensor();
}
const arm_compute::ActivationLayerInfo activationInfo = ConvertAdditionalInfoToAclActivationLayerInfo(descriptor);
arm_compute::FullyConnectedLayerInfo fc_info =
ConvertFullyConnectedDescriptorToAclFullyConnectedLayerInfo(descriptor.m_Parameters,
activationInfo);
{
ARMNN_SCOPED_PROFILING_EVENT(Compute::Undefined, "ClFullyConnectedWorkload_configure");
m_FullyConnectedLayer.configure(clCompileContext,
&input,
&weights,
bias,
&output,
fc_info);
}
}
void ClFullyConnectedWorkload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClFullyConnectedWorkload_Execute", this->GetGuid());
RunClFunction(m_FullyConnectedLayer, CHECK_LOCATION());
}
} //namespace armnn
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