onert::backend::train::BackendContext Class Reference

#include <BackendContext.h>

Collaboration diagram for onert::backend::train::BackendContext:

Public Member Functions
	BackendContext (const ITrainableBackend *backend, std::unique_ptr< TrainableContextData > &&tdata, std::shared_ptr< backend::train::ITensorRegistry > tensor_registry=nullptr, std::shared_ptr< TensorBuilder > tensor_builder=nullptr, std::unique_ptr< exec::train::optimizer::Optimizer > optimizer=nullptr, std::shared_ptr< KernelGenerator > kernel_gen=nullptr)
	BackendContext (const BackendContext &)=delete
	~BackendContext ()=default
BackendContext &	operator= (const BackendContext &)=delete
FunctionMap	gen () override
std::shared_ptr< ExternalContext >	external_context ()
const exec::train::optimizer::Optimizer *	optimizer () const
Public Member Functions inherited from onert::backend::train::TrainableBackendContext
	TrainableBackendContext (const ITrainableBackend *backend, std::unique_ptr< TrainableContextData > &&tdata, std::shared_ptr< ITensorRegistry > tensor_registry=nullptr)
virtual	~TrainableBackendContext ()=default
const ir::train::TrainableGraph *	trainable_graph () const
const TrainableContextData *	data () const
const ITrainableBackend *	backend () const
const util::Set< ir::OperandIndex > &	external_operands () const
const ir::OperandIndexMap< ir::Layout > &	operand_layouts () const
std::shared_ptr< ITensorRegistry >	tensor_registry ()

Data Fields
std::shared_ptr< KernelGenerator >	kernel_gen

Additional Inherited Members
Protected Attributes inherited from onert::backend::train::TrainableBackendContext
std::unique_ptr< TrainableContextData >	_tdata
std::shared_ptr< ITensorRegistry >	_tensor_registry

Detailed Description

Definition at line 47 of file BackendContext.h.

Constructor & Destructor Documentation

BackendContext() [1/2]

onert::backend::train::BackendContext::BackendContext ( const ITrainableBackend *  backend, std::unique_ptr< TrainableContextData > &&  tdata, std::shared_ptr< backend::train::ITensorRegistry >  tensor_registry = nullptr, std::shared_ptr< TensorBuilder >  tensor_builder = nullptr, std::unique_ptr< exec::train::optimizer::Optimizer >  optimizer = nullptr, std::shared_ptr< KernelGenerator >  kernel_gen = nullptr  )

inline

Definition at line 50 of file BackendContext.h.

    : onert::backend::train::TrainableBackendContext(backend, std::move(tdata), tensor_registry),
      kernel_gen{kernel_gen}, _external_context(new ExternalContext),
      _tensor_builder{tensor_builder}, _optimizer{std::move(optimizer)}
  {
  }

BackendContext() [2/2]

onert::backend::train::BackendContext::BackendContext ( const BackendContext &  )

delete

~BackendContext()

onert::backend::train::BackendContext::~BackendContext ( )

default

Member Function Documentation

external_context()

std::shared_ptr< ExternalContext > onert::backend::train::BackendContext::external_context ( )

inline

Definition at line 75 of file BackendContext.h.

{ return _external_context; }

gen()

FunctionMap onert::backend::train::BackendContext::gen ( )

overridevirtual

Implements onert::backend::train::TrainableBackendContext.

Definition at line 135 of file BackendContext.cc.

{
  planForwardTensors();
  planBackwardTensors();
 
  _tensor_builder->allocate();
  _tensor_builder->allocateBackward();
 
  auto fn_map = generateFunctionMap();
 
  // Initialize TrainableTensors
  trainable_graph()->operands().iterate(
    [&](const ir::OperandIndex &ind, const ir::Operand &operand) {
      if (external_operands().contains(ind) || !operand.isConstant())
        return;
 
      auto tensor = tensor_registry()->getNativeITensor(ind);
      assert(tensor != nullptr);
 
      VERBOSE(FillOperandData) << "Fill data for " << ind << std::endl;
 
      auto data = operand.shareData();
      assert(data && data->base());
      auto trainable_tensor = dynamic_cast<TrainableTensor *>(tensor);
 
      if (trainable_tensor == nullptr)
        throw std::runtime_error{"This tensor is not trainable tensor"};
 
      trainable_tensor->fillBuffer(data);
    });
 
  // NOTE For memory optimization, we want to free some operand data
  const_cast<ir::train::TrainableGraph &>(*_tdata->tgraph)
    .operands()
    .iterate([&](const ir::OperandIndex &, ir::Operand &obj) { obj.releaseData(); });
 
  // TODO Enable
  // for (auto &&it : ret)
  // {
  //   auto &fn_seq = it.second;
  //   fn_seq->iterate([&](exec::IFunction &ifunc) { ifunc.prepare(); });
  // }
 
  // NOTE: Since LayerScopeTensors is defined in each kernel(layer),
  //       It should be planned and allocated after the kernels generated.
  planLayerScopeTensors(fn_map);
  _tensor_builder->allocateLayerScope();
 
  return fn_map;
}

References onert::backend::train::TrainableBackendContext::_tdata, onert::backend::train::TrainableBackendContext::data(), onert::backend::train::TrainableBackendContext::external_operands(), onert::backend::basic::train::TrainableTensor::fillBuffer(), onert::ir::Operand::isConstant(), onert::util::ObjectManager< Index, Object >::iterate(), onert::ir::train::TrainableGraph::operands(), onert::ir::Operand::shareData(), onert::backend::train::TrainableBackendContext::tensor_registry(), onert::backend::train::TrainableBackendContext::trainable_graph(), and VERBOSE.

operator=()

BackendContext & onert::backend::train::BackendContext::operator= ( const BackendContext &  )

delete

optimizer()

const exec::train::optimizer::Optimizer * onert::backend::train::BackendContext::optimizer ( ) const

inline

Definition at line 77 of file BackendContext.h.

{ return _optimizer.get(); }

Referenced by session.TrainSession::_print_training_parameters(), session.TrainSession::compile(), session.TrainSession::train(), and session.TrainSession::train_step().

Field Documentation

kernel_gen

std::shared_ptr<KernelGenerator> onert::backend::train::BackendContext::kernel_gen

Definition at line 84 of file BackendContext.h.

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

• runtime/onert/backend/train/BackendContext.h
• runtime/onert/backend/train/BackendContext.cc