ArmNN
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NeonConvolution2dWorkload Class Reference

#include <NeonConvolution2dWorkload.hpp>

Inheritance diagram for NeonConvolution2dWorkload:
NeonBaseWorkload< Convolution2dQueueDescriptor > BaseWorkload< Convolution2dQueueDescriptor > IWorkload

Public Member Functions

 NeonConvolution2dWorkload (const Convolution2dQueueDescriptor &descriptor, const WorkloadInfo &info, std::shared_ptr< arm_compute::MemoryManagerOnDemand > &memoryManager, const bool isFastMathENabled=false)
 
void Execute () const override
 
arm_compute::ConvolutionMethod GetConvolutionMethod () const
 
- Public Member Functions inherited from NeonBaseWorkload< Convolution2dQueueDescriptor >
 NeonBaseWorkload (const Convolution2dQueueDescriptor &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< Convolution2dQueueDescriptor >
 BaseWorkload (const Convolution2dQueueDescriptor &descriptor, const WorkloadInfo &info)
 
void ExecuteAsync (ExecutionData &executionData) override
 
void PostAllocationConfigure () override
 
const Convolution2dQueueDescriptor & GetData () 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 void RegisterDebugCallback (const DebugCallbackFunction &)
 
virtual armnn::Optional< armnn::MemoryRequirements > GetMemoryRequirements ()
 

Additional Inherited Members

- Protected Member Functions inherited from NeonBaseWorkload< Convolution2dQueueDescriptor >
virtual void Reconfigure ()
 
- Protected Attributes inherited from BaseWorkload< Convolution2dQueueDescriptor >
Convolution2dQueueDescriptor m_Data
 
const arm::pipe::ProfilingGuid m_Guid
 

Detailed Description

Definition at line 27 of file NeonConvolution2dWorkload.hpp.

Constructor & Destructor Documentation

◆ NeonConvolution2dWorkload()

NeonConvolution2dWorkload ( const Convolution2dQueueDescriptor &  descriptor,
const WorkloadInfo &  info,
std::shared_ptr< arm_compute::MemoryManagerOnDemand > &  memoryManager,
const bool  isFastMathENabled = false 
)

Definition at line 73 of file NeonConvolution2dWorkload.cpp.

78  : NeonBaseWorkload<Convolution2dQueueDescriptor>(descriptor, info)
79 {
80  using arm_compute::NEConvolutionLayer;
81 
82  uint32_t numInputs = m_Data.m_Parameters.m_BiasEnabled ? 3: 2;
83  m_Data.ValidateInputsOutputs("NeonConvolution2dWorkload", numInputs, 1);
84 
85  arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
86  arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
87 
88  arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
89  input.info()->set_data_layout(aclDataLayout);
90  output.info()->set_data_layout(aclDataLayout);
91 
92  m_KernelTensor = std::make_unique<arm_compute::Tensor>();
93  BuildArmComputeTensor(*m_KernelTensor, info.m_InputTensorInfos[1], m_Data.m_Parameters.m_DataLayout);
94  m_KernelTensor->info()->set_are_values_constant(info.m_InputTensorInfos[1].IsConstant());
95  if (m_Data.m_Parameters.m_BiasEnabled)
96  {
97  m_BiasTensor = std::make_unique<arm_compute::Tensor>();
98  BuildArmComputeTensor(*m_BiasTensor, info.m_InputTensorInfos[2], m_Data.m_Parameters.m_DataLayout);
99  m_BiasTensor->info()->set_are_values_constant(info.m_InputTensorInfos[2].IsConstant());
100  // We do not support dynamic bias
101  ARMNN_ASSERT(info.m_InputTensorInfos[2].IsConstant() == true);
102  }
103 
104  arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(m_Data.m_Parameters);
105 
106  const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(m_Data.m_Parameters.m_DilationX,
107  m_Data.m_Parameters.m_DilationY);
108 
109  const arm_compute::ActivationLayerInfo activationInfo = ConvertAdditionalInfoToAclActivationLayerInfo(descriptor);
110 
111  auto convolutionLayer = std::make_unique<arm_compute::NEConvolutionLayer>(memoryManager);
112  convolutionLayer->configure(&input,
113  m_KernelTensor.get(),
114  m_BiasTensor.get(),
115  &output,
116  padStrideInfo,
117  arm_compute::WeightsInfo(),
118  aclDilationInfo,
119  activationInfo,
120  isFastMathEnabled);
121 
122  m_ConvolutionMethod =
123  convolutionLayer->get_convolution_method(input.info(),
124  m_KernelTensor->info(),
125  output.info(),
126  padStrideInfo,
127  arm_compute::WeightsInfo(),
128  aclDilationInfo,
129  activationInfo,
130  isFastMathEnabled);
131 
132  // Add details for profiling output
133  WorkloadInfo detailsInfo;
134 
135  detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos;
136  detailsInfo.m_OutputTensorInfos = info.m_OutputTensorInfos;
137  detailsInfo.m_WeightsTensorInfo = armnn::Optional<armnn::TensorInfo>(info.m_InputTensorInfos[1]);
138  detailsInfo.m_ConvolutionMethod = armnn::Optional<std::string>(GetConvolutionMethodString(m_ConvolutionMethod));
139 
140  if (descriptor.m_Parameters.m_BiasEnabled)
141  {
142  detailsInfo.m_BiasTensorInfo = armnn::Optional<armnn::TensorInfo>(info.m_InputTensorInfos[2]);
143  }
144 
145  // Report Profiling Details
146  ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonConvolution2dWorkload_Construct",
147  descriptor.m_Parameters,
148  detailsInfo,
149  GetGuid());
150 
151  m_ConvolutionLayer.reset(convolutionLayer.release());
152 
153  ARMNN_ASSERT(m_ConvolutionLayer);
154  m_KernelTensorInfo = info.m_InputTensorInfos[1];
155 
156  if (m_Data.m_Parameters.m_BiasEnabled)
157  {
158  m_BiasTensorInfo = info.m_InputTensorInfos[2];
159  }
160 }

References armnn::info, Convolution2dDescriptor::m_BiasEnabled, BaseWorkload< Convolution2dQueueDescriptor >::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 NeonConvolution2dWorkload.cpp.

163 {
164  ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonConvolution2dWorkload_Execute", this->GetGuid());
165  // The constant tensors may not be fully in place until the workload is Executed
166  if (!prepared)
167  {
168  InitializeArmComputeTensorData(*m_KernelTensor, m_KernelTensorInfo, m_Data.m_Inputs[1]);
169 
170  if (m_Data.m_Parameters.m_BiasEnabled)
171  {
172  InitializeArmComputeTensorData(*m_BiasTensor, m_BiasTensorInfo, m_Data.m_Inputs[2]);
173  }
174  m_ConvolutionLayer->prepare();
175  FreeTensorIfUnused(m_KernelTensor);
176  FreeTensorIfUnused(m_BiasTensor);
177  prepared = true;
178  }
179  m_ConvolutionLayer->run();
180 }

References ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID, BaseWorkload< Convolution2dQueueDescriptor >::GetGuid(), armnn::InitializeArmComputeTensorData(), Convolution2dDescriptor::m_BiasEnabled, BaseWorkload< Convolution2dQueueDescriptor >::m_Data, QueueDescriptor::m_Inputs, and QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters.

◆ GetConvolutionMethod()

arm_compute::ConvolutionMethod GetConvolutionMethod ( ) const

Definition at line 182 of file NeonConvolution2dWorkload.cpp.

183 {
184  return m_ConvolutionMethod;
185 }
The documentation for this class was generated from the following files:
armnn::Convolution2dDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Definition: Descriptors.hpp:572
armnn::Convolution2dDescriptor::m_BiasEnabled
bool m_BiasEnabled
Enable/disable bias.
Definition: Descriptors.hpp:570
armnn::BaseWorkload< Convolution2dQueueDescriptor >::GetGuid
arm::pipe::ProfilingGuid GetGuid() const final
Definition: Workload.hpp:61
armnn::QueueDescriptor::ValidateInputsOutputs
void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
Definition: WorkloadData.cpp:472
armnn::DataLayout
DataLayout
Definition: Types.hpp:62
armnn::Convolution2dDescriptor::m_DilationY
uint32_t m_DilationY
Dilation along y axis.
Definition: Descriptors.hpp:568
armnn::Convolution2dDescriptor::m_DilationX
uint32_t m_DilationX
Dilation along x axis.
Definition: Descriptors.hpp:566
armnn::BaseWorkload< Convolution2dQueueDescriptor >::m_Data
Convolution2dQueueDescriptor m_Data
Definition: Workload.hpp:83
armnn::InitializeArmComputeTensorData
void InitializeArmComputeTensorData(arm_compute::Tensor &tensor, TensorInfo tensorInfo, const ITensorHandle *handle)
Definition: NeonWorkloadUtils.hpp:60
ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID
#define ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID(name, guid)
Definition: NeonWorkloadUtils.hpp:24
armnn::ConvertAdditionalInfoToAclActivationLayerInfo
arm_compute::ActivationLayerInfo ConvertAdditionalInfoToAclActivationLayerInfo(const QueueDescriptor &queueDescriptor)
Definition: ArmComputeUtils.hpp:103
armnn::QueueDescriptorWithParameters::m_Parameters
LayerDescriptor m_Parameters
Definition: WorkloadData.hpp:66
ARMNN_ASSERT
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
ARMNN_REPORT_PROFILING_WORKLOAD_DESC
#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)
Definition: Profiling.hpp:227
armnn::Optional< armnn::TensorInfo >
armnn::QueueDescriptor::m_Outputs
std::vector< ITensorHandle * > m_Outputs
Definition: WorkloadData.hpp:27
armnn::GetConvolutionMethodString
std::string GetConvolutionMethodString(arm_compute::ConvolutionMethod &convolutionMethod)
Definition: ClWorkloadUtils.hpp:38
armnn::QueueDescriptor::m_Inputs
std::vector< ITensorHandle * > m_Inputs
Definition: WorkloadData.hpp:26
armnn::BoostLogSeverityMapping::info
@ info