ArmNN
 20.11
CreateNetworkImpl< IParser > Struct Template Reference

#include <InferenceModel.hpp>

Public Types

using Params = InferenceModelInternal::Params
 

Static Public Member Functions

static armnn::INetworkPtr Create (const Params &params, std::vector< armnn::BindingPointInfo > &inputBindings, std::vector< armnn::BindingPointInfo > &outputBindings)
 

Detailed Description

template<typename IParser>
struct CreateNetworkImpl< IParser >

Definition at line 118 of file InferenceModel.hpp.

Member Typedef Documentation

◆ Params

Definition at line 121 of file InferenceModel.hpp.

Member Function Documentation

◆ Create()

static armnn::INetworkPtr Create ( const Params params,
std::vector< armnn::BindingPointInfo > &  inputBindings,
std::vector< armnn::BindingPointInfo > &  outputBindings 
)
inlinestatic

Definition at line 123 of file InferenceModel.hpp.

References ARMNN_ASSERT, ARMNN_SCOPED_HEAP_PROFILING, CHECK_LOCATION, BindingPointInfo::m_BindingId, Params::m_InferOutputShape, Params::m_InputBindings, Params::m_InputShapes, Params::m_IsModelBinary, Params::m_ModelPath, Params::m_OutputBindings, Params::m_ParseUnsupported, Params::m_SubgraphId, BindingPointInfo::m_TensorInfo, and armnn::numeric_cast().

Referenced by InferenceModel< IParser, TDataType >::InferenceModel().

126  {
127  const std::string& modelPath = params.m_ModelPath;
128 
129  // Create a network from a file on disk
130  auto parser(IParser::Create());
131 
132  std::map<std::string, armnn::TensorShape> inputShapes;
133  if (!params.m_InputShapes.empty())
134  {
135  const size_t numInputShapes = params.m_InputShapes.size();
136  const size_t numInputBindings = params.m_InputBindings.size();
137  if (numInputShapes < numInputBindings)
138  {
139  throw armnn::Exception(fmt::format(
140  "Not every input has its tensor shape specified: expected={0}, got={1}",
141  numInputBindings, numInputShapes));
142  }
143 
144  for (size_t i = 0; i < numInputShapes; i++)
145  {
146  inputShapes[params.m_InputBindings[i]] = params.m_InputShapes[i];
147  }
148  }
149 
150  std::vector<std::string> requestedOutputs = params.m_OutputBindings;
151  armnn::INetworkPtr network{nullptr, [](armnn::INetwork *){}};
152 
153  {
154  ARMNN_SCOPED_HEAP_PROFILING("Parsing");
155  // Handle text and binary input differently by calling the corresponding parser function
156  network = (params.m_IsModelBinary ?
157  parser->CreateNetworkFromBinaryFile(modelPath.c_str(), inputShapes, requestedOutputs) :
158  parser->CreateNetworkFromTextFile(modelPath.c_str(), inputShapes, requestedOutputs));
159  }
160 
161  for (const std::string& inputLayerName : params.m_InputBindings)
162  {
163  inputBindings.push_back(parser->GetNetworkInputBindingInfo(inputLayerName));
164  }
165 
166  for (const std::string& outputLayerName : params.m_OutputBindings)
167  {
168  outputBindings.push_back(parser->GetNetworkOutputBindingInfo(outputLayerName));
169  }
170 
171  return network;
172  }
Main network class which provides the interface for building up a neural network. ...
Definition: INetwork.hpp:105
#define ARMNN_SCOPED_HEAP_PROFILING(TAG)
Base class for all ArmNN exceptions so that users can filter to just those.
Definition: Exceptions.hpp:46
std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr
Definition: INetwork.hpp:101

The documentation for this struct was generated from the following file: