ArmNN
 24.08
NeonBatchToSpaceNdWorkload Class Reference

#include <NeonBatchToSpaceNdWorkload.hpp>

Inheritance diagram for NeonBatchToSpaceNdWorkload:
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Collaboration diagram for NeonBatchToSpaceNdWorkload:
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Public Member Functions

 NeonBatchToSpaceNdWorkload (const BatchToSpaceNdQueueDescriptor &descriptor, const WorkloadInfo &info)
 
virtual void Execute () const override
 
- Public Member Functions inherited from NeonBaseWorkload< BatchToSpaceNdQueueDescriptor >
 NeonBaseWorkload (const BatchToSpaceNdQueueDescriptor &descriptor, const WorkloadInfo &info)
 
void ReplaceInputTensorHandle (ITensorHandle *tensorHandle, unsigned int slot) override
 
void ReplaceOutputTensorHandle (ITensorHandle *tensorHandle, unsigned int slot) override
 
- Public Member Functions inherited from BaseWorkload< BatchToSpaceNdQueueDescriptor >
 BaseWorkload (const BatchToSpaceNdQueueDescriptor &descriptor, const WorkloadInfo &info)
 
virtual const std::string & GetName () const override
 
void ExecuteAsync (ExecutionData &executionData) override
 
void PostAllocationConfigure () override
 
const BatchToSpaceNdQueueDescriptorGetData () const
 
arm::pipe::ProfilingGuid GetGuid () const final
 
virtual bool SupportsTensorHandleReplacement () const override
 
- Public Member Functions inherited from IWorkload
virtual ~IWorkload ()
 
virtual arm::pipe::ProfilingGuid GetGuid () const =0
 
virtual bool SupportsTensorHandleReplacement () const =0
 
virtual const std::string & GetName () const =0
 
virtual void RegisterDebugCallback (const DebugCallbackFunction &)
 
virtual armnn::Optional< armnn::MemoryRequirementsGetMemoryRequirements ()
 

Additional Inherited Members

- Protected Member Functions inherited from NeonBaseWorkload< BatchToSpaceNdQueueDescriptor >
virtual void Reconfigure ()
 
- Protected Attributes inherited from BaseWorkload< BatchToSpaceNdQueueDescriptor >
BatchToSpaceNdQueueDescriptor m_Data
 
const arm::pipe::ProfilingGuid m_Guid
 
const std::string m_Name
 

Detailed Description

Definition at line 21 of file NeonBatchToSpaceNdWorkload.hpp.

Constructor & Destructor Documentation

◆ NeonBatchToSpaceNdWorkload()

NeonBatchToSpaceNdWorkload ( const BatchToSpaceNdQueueDescriptor descriptor,
const WorkloadInfo info 
)

Definition at line 86 of file NeonBatchToSpaceNdWorkload.cpp.

88  : NeonBaseWorkload<BatchToSpaceNdQueueDescriptor>(descriptor, info)
89 {
90  // Report Profiling Details
91  ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonBatchToSpaceWorkload_Construct",
92  descriptor.m_Parameters,
93  info,
94  this->GetGuid());
95 
96  m_Data.ValidateInputsOutputs("NeonBatchToSpaceNdWorkload", 1, 1);
97 
98  arm_compute::ITensor& input = PolymorphicPointerDowncast<IAclTensorHandle>(m_Data.m_Inputs[0])->GetTensor();
99  arm_compute::ITensor& output = PolymorphicPointerDowncast<IAclTensorHandle>(m_Data.m_Outputs[0])->GetTensor();
100 
101  arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
102  input.info()->set_data_layout(aclDataLayout);
103  output.info()->set_data_layout(aclDataLayout);
104 
105  arm_compute::TensorInfo aclReshapeInputInfo = BuildArmComputeTensorInfo(info.m_InputTensorInfos[0],
107  arm_compute::TensorInfo aclReshapeOutputInfo = BuildArmComputeTensorInfo(info.m_OutputTensorInfos[0],
109 
110  const unsigned int rank = info.m_InputTensorInfos[0].GetNumDimensions();
111  if (rank == 3)
112  {
113  const arm_compute::TensorShape inputShape = input.info()->tensor_shape();
114  const arm_compute::TensorShape outputShape = output.info()->tensor_shape();
115 
116  // When a spacial dimension is missing set W to 1
118  {
119  // In ACL dimensions are right to left: C, W, H, N
120  aclReshapeInputInfo.set_tensor_shape({inputShape.x(), 1, inputShape.y(), inputShape.z()});
121  aclReshapeOutputInfo.set_tensor_shape({outputShape.x(), 1, outputShape.y(), outputShape.z()});
122  }
124  {
125  // In ACL dimensions are right to left: W, H, C, N
126  aclReshapeInputInfo.set_tensor_shape({1, inputShape.x(), inputShape.y(), inputShape.z()});
127  aclReshapeOutputInfo.set_tensor_shape({1, outputShape.x(), outputShape.y(), outputShape.z()});
128  }
129  else
130  {
131  throw InvalidArgumentException("Unsupported or unknown DataLayout", CHECK_LOCATION());
132  }
133 
134  m_ReshapeInputTensor.allocator()->init(aclReshapeInputInfo);
135  m_ReshapeOutputTensor.allocator()->init(aclReshapeOutputInfo);
136 
137  InitialiseArmComputeTensorEmpty(m_ReshapeInputTensor);
138  InitialiseArmComputeTensorEmpty(m_ReshapeOutputTensor);
139 
140  m_LayerReshapeInput.reset(new arm_compute::NEReshapeLayer());
141  m_LayerReshapeOutput.reset(new arm_compute::NEReshapeLayer());
142 
143  m_LayerReshapeInput->configure(&input, &m_ReshapeInputTensor);
144  m_LayerReshapeOutput->configure(&m_ReshapeOutputTensor, &output);
145  }
146 
147  // ArmNN blockShape is [H, W] ACl asks for W, H
148  int32_t blockHeight = armnn::numeric_cast<int32_t>(descriptor.m_Parameters.m_BlockShape[0]);
149  int32_t blockWidth = (rank == 3) ? 1 : armnn::numeric_cast<int32_t>(descriptor.m_Parameters.m_BlockShape[1]);
150 
151  const arm_compute::CropInfo cropInfo = BuildArmComputeCropInfo(descriptor.m_Parameters, rank);
152 
153  m_Layer.reset(new arm_compute::NEBatchToSpaceLayer());
154  m_Layer->configure(rank == 3 ? &m_ReshapeInputTensor : &input,
155  blockWidth,
156  blockHeight,
157  rank == 3 ? &m_ReshapeOutputTensor : &output,
158  cropInfo);
159  m_Layer->prepare();
160 }

References ARMNN_REPORT_PROFILING_WORKLOAD_DESC, armnn::info, BaseWorkload< BatchToSpaceNdQueueDescriptor >::m_Data, QueueDescriptor::m_Inputs, QueueDescriptor::m_Outputs, QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters, and QueueDescriptor::ValidateInputsOutputs().

Member Function Documentation

◆ Execute()

void Execute ( ) const
overridevirtual

Implements IWorkload.

Definition at line 162 of file NeonBatchToSpaceNdWorkload.cpp.

163 {
164  ARMNN_SCOPED_PROFILING_EVENT_NEON_NAME_GUID("NeonBatchToSpaceNdWorkload_Execute");
165  if (m_LayerReshapeInput)
166  {
167  m_LayerReshapeInput->run();
168  }
169  if (m_Layer)
170  {
171  m_Layer->run();
172  }
173  if (m_LayerReshapeOutput)
174  {
175  m_LayerReshapeOutput->run();
176  }
177 }

References ARMNN_SCOPED_PROFILING_EVENT_NEON_NAME_GUID.


The documentation for this class was generated from the following files:
armnn::DataLayout
DataLayout
Definition: Types.hpp:62
armnn::DataLayout::NHWC
@ NHWC
armnn::QueueDescriptor::ValidateInputsOutputs
void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
Definition: WorkloadData.cpp:447
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
armnn::QueueDescriptorWithParameters::m_Parameters
LayerDescriptor m_Parameters
Definition: WorkloadData.hpp:66
armnn::BoostLogSeverityMapping::info
@ info
armnn::QueueDescriptor::m_Outputs
std::vector< ITensorHandle * > m_Outputs
Definition: WorkloadData.hpp:27
ARMNN_REPORT_PROFILING_WORKLOAD_DESC
#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)
Definition: Profiling.hpp:227
armnn::BaseWorkload< BatchToSpaceNdQueueDescriptor >::m_Data
BatchToSpaceNdQueueDescriptor m_Data
Definition: Workload.hpp:89
armnn::BatchToSpaceNdDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Definition: Descriptors.hpp:902
ARMNN_SCOPED_PROFILING_EVENT_NEON_NAME_GUID
#define ARMNN_SCOPED_PROFILING_EVENT_NEON_NAME_GUID(label)
Creates a profiling event that uses GetGuid() and GetName() from the calling class.
Definition: NeonWorkloadUtils.hpp:33
armnn::QueueDescriptor::m_Inputs
std::vector< ITensorHandle * > m_Inputs
Definition: WorkloadData.hpp:26
armnn::DataLayout::NCHW
@ NCHW