blob: f218fa4db61a19685be9afb874996884eefdd0c4 [file] [log] [blame]
//
// Copyright © 2017-2018,2020-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ClNormalizationFloatWorkload.hpp"
#include <cl/ClTensorHandle.hpp>
#include <armnn/backends/TensorHandle.hpp>
#include <cl/ClLayerSupport.hpp>
#include <aclCommon/ArmComputeUtils.hpp>
#include <aclCommon/ArmComputeTensorUtils.hpp>
#include "ClWorkloadUtils.hpp"
using namespace armnn::armcomputetensorutils;
namespace armnn
{
arm_compute::Status ClNormalizationWorkloadValidate(const TensorInfo& input,
const TensorInfo& output,
const NormalizationDescriptor& descriptor)
{
const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout);
arm_compute::NormalizationLayerInfo layerInfo = BuildArmComputeNormalizationLayerInfo(descriptor);
return arm_compute::CLNormalizationLayer::validate(&aclInputInfo, &aclOutputInfo, layerInfo);
}
ClNormalizationFloatWorkload::ClNormalizationFloatWorkload(const NormalizationQueueDescriptor& descriptor,
const WorkloadInfo& info,
const arm_compute::CLCompileContext& clCompileContext)
: FloatWorkload<NormalizationQueueDescriptor>(descriptor, info)
{
// Report Profiling Details
ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClNormalizationWorkload_Construct",
descriptor.m_Parameters,
info,
this->GetGuid());
m_Data.ValidateInputsOutputs("ClNormalizationFloatWorkload", 1, 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::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
input.info()->set_data_layout(aclDataLayout);
output.info()->set_data_layout(aclDataLayout);
arm_compute::NormalizationLayerInfo normalizationInfo = BuildArmComputeNormalizationLayerInfo(m_Data.m_Parameters);
{
ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID("ClNormalizationFloatWorkload_configure");
m_NormalizationLayer.configure(clCompileContext, &input, &output, normalizationInfo);
}
};
void ClNormalizationFloatWorkload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID("ClNormalizationFloatWorkload_Execute");
RunClFunction(m_NormalizationLayer, CHECK_LOCATION());
}
void ClNormalizationFloatWorkload::ReplaceInputTensorHandle(ITensorHandle* tensorHandle, unsigned int slot)
{
ITensorHandle* backupHandle = this->m_Data.m_Inputs[slot];
this->m_Data.m_Inputs[slot] = tensorHandle;
try
{
Reconfigure();
}
catch(armnn::UnimplementedException& e)
{
// Cannot reconfigure, revert the slot back and throw the exception.
this->m_Data.m_Inputs[slot] = backupHandle;
throw e;
}
}
// Replace output tensor handle with the given TensorHandle
void ClNormalizationFloatWorkload::ReplaceOutputTensorHandle(ITensorHandle* tensorHandle, unsigned int slot)
{
ITensorHandle* backupHandle = this->m_Data.m_Inputs[slot];
this->m_Data.m_Inputs[slot] = tensorHandle;
try
{
Reconfigure();
}
catch(armnn::UnimplementedException& e)
{
// Cannot reconfigure, revert the slot back and throw the exception.
this->m_Data.m_Inputs[slot] = backupHandle;
throw e;
}
}
void ClNormalizationFloatWorkload::Reconfigure()
{
throw armnn::UnimplementedException("Reconfigure not implemented for this workload");
}
} //namespace armnn