patch/23.02/_cl_normalization_float_workload_8cpp_source.xhtml

 //
 // Copyright © 2017 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(Compute::Undefined, "ClNormalizationFloatWorkload_configure");
         m_NormalizationLayer.configure(clCompileContext, &input, &output, normalizationInfo);
     }
 };

 void ClNormalizationFloatWorkload::Execute() const
 {
     ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClNormalizationFloatWorkload_Execute", this->GetGuid());
     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
ARMNN_SCOPED_PROFILING_EVENT_CL_GUID
#define ARMNN_SCOPED_PROFILING_EVENT_CL_GUID(name, guid)
Definition: ClWorkloadUtils.hpp:28

-armnn::DataLayout
DataLayout
Definition: Types.hpp:62

-ArmComputeUtils.hpp

-armnn::ClNormalizationFloatWorkload::ReplaceInputTensorHandle
void ReplaceInputTensorHandle(ITensorHandle *tensorHandle, unsigned int slot) override
Definition: ClNormalizationFloatWorkload.cpp:65

-TensorHandle.hpp

-armnn::TensorInfo
Definition: Tensor.hpp:152

-armnn::ClNormalizationFloatWorkload::Execute
void Execute() const override
Definition: ClNormalizationFloatWorkload.cpp:59

-armnn::RunClFunction
void RunClFunction(arm_compute::IFunction &function, const CheckLocation &location)
Definition: ClWorkloadUtils.hpp:160

-armnn::BaseWorkload::GetGuid
arm::pipe::ProfilingGuid GetGuid() const final
Definition: Workload.hpp:61

-armnn::UnimplementedException
Definition: Exceptions.hpp:98

-ArmComputeTensorUtils.hpp

-ClNormalizationFloatWorkload.hpp

-armnn::QueueDescriptor::ValidateInputsOutputs
void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
Definition: WorkloadData.cpp:475

-armnn::NormalizationDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Definition: Descriptors.hpp:773

-armnn
Copyright (c) 2021 ARM Limited and Contributors.
Definition: 01_00_quick_start.dox:6

-armnn::ClNormalizationFloatWorkload::ClNormalizationFloatWorkload
ClNormalizationFloatWorkload(const NormalizationQueueDescriptor &descriptor, const WorkloadInfo &info, const arm_compute::CLCompileContext &clCompileContext)
Definition: ClNormalizationFloatWorkload.cpp:31

-armnn::QueueDescriptorWithParameters::m_Parameters
LayerDescriptor m_Parameters
Definition: WorkloadData.hpp:66

-ARMNN_SCOPED_PROFILING_EVENT
#define ARMNN_SCOPED_PROFILING_EVENT(backendId, name)
Definition: Profiling.hpp:220

-armnn::ClNormalizationWorkloadValidate
arm_compute::Status ClNormalizationWorkloadValidate(const TensorInfo &input, const TensorInfo &output, const NormalizationDescriptor &descriptor)
Definition: ClNormalizationFloatWorkload.cpp:19

-armnn::ITensorHandle
Definition: ITensorHandle.hpp:15

-armnn::BaseWorkload::m_Data
QueueDescriptor m_Data
Definition: Workload.hpp:83

-armnn::Compute::Undefined

-armnn::Status
Status
enumeration
Definition: Types.hpp:42

-armnn::TypedWorkload
Definition: Workload.hpp:94

-CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203

-ClTensorHandle.hpp

-armnn::QueueDescriptor::m_Outputs
std::vector< ITensorHandle * > m_Outputs
Definition: WorkloadData.hpp:27

-armnn::BoostLogSeverityMapping::info

-armnn::ClNormalizationFloatWorkload::ReplaceOutputTensorHandle
void ReplaceOutputTensorHandle(ITensorHandle *tensorHandle, unsigned int slot) override
Definition: ClNormalizationFloatWorkload.cpp:82

-armnn::IClTensorHandle
Definition: IClTensorHandle.hpp:13

-ARMNN_REPORT_PROFILING_WORKLOAD_DESC
#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)
Definition: Profiling.hpp:227

-armnn::WorkloadInfo
Contains information about TensorInfos of a layer.
Definition: WorkloadInfo.hpp:16

-armnn::QueueDescriptor::m_Inputs
std::vector< ITensorHandle * > m_Inputs
Definition: WorkloadData.hpp:26

-armnn::NormalizationDescriptor
A NormalizationDescriptor for the NormalizationLayer.
Definition: Descriptors.hpp:737

-armnn::armcomputetensorutils
Definition: ArmComputeTensorUtils.cpp:16

-ClWorkloadUtils.hpp

-armnn::NormalizationQueueDescriptor
Definition: WorkloadData.hpp:247

-ClLayerSupport.hpp

+Go to the documentation of this file. //

+ // Copyright © 2017 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(Compute::Undefined, "ClNormalizationFloatWorkload_configure");

+         m_NormalizationLayer.configure(clCompileContext, &input, &output, normalizationInfo);

+     }

+ };

+

+ void ClNormalizationFloatWorkload::Execute() const

+ {

+     ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClNormalizationFloatWorkload_Execute", this->GetGuid());

+     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