ArmNN
 20.05
NeonConvolution2dWorkload Class Reference

#include <NeonConvolution2dWorkload.hpp>

Inheritance diagram for NeonConvolution2dWorkload:
BaseWorkload< Convolution2dQueueDescriptor > IWorkload

Public Member Functions

 NeonConvolution2dWorkload (const Convolution2dQueueDescriptor &descriptor, const WorkloadInfo &info, std::shared_ptr< arm_compute::MemoryManagerOnDemand > &memoryManager)
 
void Execute () const override
 
- Public Member Functions inherited from BaseWorkload< Convolution2dQueueDescriptor >
 BaseWorkload (const Convolution2dQueueDescriptor &descriptor, const WorkloadInfo &info)
 
void PostAllocationConfigure () override
 
const Convolution2dQueueDescriptorGetData () const
 
profiling::ProfilingGuid GetGuid () const final
 
- Public Member Functions inherited from IWorkload
virtual ~IWorkload ()
 
virtual void RegisterDebugCallback (const DebugCallbackFunction &)
 

Additional Inherited Members

- Protected Attributes inherited from BaseWorkload< Convolution2dQueueDescriptor >
const Convolution2dQueueDescriptor m_Data
 
const profiling::ProfilingGuid m_Guid
 

Detailed Description

Definition at line 25 of file NeonConvolution2dWorkload.hpp.

Constructor & Destructor Documentation

◆ NeonConvolution2dWorkload()

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

Definition at line 58 of file NeonConvolution2dWorkload.cpp.

References BaseWorkload< Convolution2dQueueDescriptor >::m_Data, QueueDescriptor::m_Inputs, QueueDescriptor::m_Outputs, and QueueDescriptor::ValidateInputsOutputs().

61  : BaseWorkload<Convolution2dQueueDescriptor>(descriptor, info)
62 {
63  using arm_compute::NEDirectConvolutionLayer;
64 
65  m_Data.ValidateInputsOutputs("NeonConvolution2dWorkload", 1, 1);
66 
67  // todo: check tensor shapes match.
68 
69  arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
70  arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
71 
72  arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
73  input.info()->set_data_layout(aclDataLayout);
74  output.info()->set_data_layout(aclDataLayout);
75 
76  m_KernelTensor = std::make_unique<arm_compute::Tensor>();
77  BuildArmComputeTensor(*m_KernelTensor, m_Data.m_Weight->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout);
78 
80  {
81  m_BiasTensor = std::make_unique<arm_compute::Tensor>();
82  BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout);
83  }
84 
85  arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(m_Data.m_Parameters);
86 
87  const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(m_Data.m_Parameters.m_DilationX,
89 
90  auto convolutionLayer = std::make_unique<arm_compute::NEConvolutionLayer>(memoryManager);
91  convolutionLayer->configure(&input,
92  m_KernelTensor.get(),
93  m_BiasTensor.get(),
94  &output,
95  padStrideInfo,
96  arm_compute::WeightsInfo(),
97  aclDilationInfo);
98 
99  m_ConvolutionLayer.reset(convolutionLayer.release());
100 
101  ARMNN_ASSERT(m_ConvolutionLayer);
102 
104 
106  {
108  }
109 
110  m_ConvolutionLayer->prepare();
111  FreeUnusedTensors();
112 }
bool m_BiasEnabled
Enable/disable bias.
const ConstCpuTensorHandle * m_Bias
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
DataLayout
Definition: Types.hpp:49
const Convolution2dQueueDescriptor m_Data
Definition: Workload.hpp:46
void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
uint32_t m_DilationY
Dilation along y axis.
const ConstCpuTensorHandle * m_Weight
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
void InitializeArmComputeTensorData(arm_compute::Tensor &tensor, const ConstCpuTensorHandle *handle)
uint32_t m_DilationX
Dilation along x axis.
std::vector< ITensorHandle * > m_Outputs
std::vector< ITensorHandle * > m_Inputs
const TensorInfo & GetTensorInfo() const

Member Function Documentation

◆ Execute()

void Execute ( ) const
overridevirtual

Implements IWorkload.

Definition at line 114 of file NeonConvolution2dWorkload.cpp.

References ARMNN_SCOPED_PROFILING_EVENT_NEON.

115 {
116  ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonConvolution2dWorkload_Execute");
117  m_ConvolutionLayer->run();
118 }
#define ARMNN_SCOPED_PROFILING_EVENT_NEON(name)

The documentation for this class was generated from the following files: