onert::backend::train Namespace Reference

Namespaces
namespace	ops
namespace	optimizer

Data Structures
class	Backend
class	BackendContext
class	BumpPlanner
	Class to plan memory by bump way. More...
class	Config
class	DisposableMemoryManager
class	DisposableTensorIndex
	Class that is index of DisposableTensor. More...
class	DummyBackendContext
class	FirstFitPlanner
	Class to plan memory by firstfit way. More...
class	ITensorRegistry
struct	ITrainableBackend
class	ITrainableTensor
	A tensor class that can be trained. More...
class	KernelGenerator
class	KernelGeneratorBase
class	LayerScopeMemoryManager
class	LayerScopeTensor
class	LayerScopeTensorIndex
class	MemoryPlannerFactory
class	PortableTensorRegistryTemplate
class	Tensor
class	TensorBuilder
class	TensorManager
class	TensorPlanner
class	TensorRegistry
class	TrainableBackendContext
struct	TrainableContextData
class	TrainableMemoryManager
class	WICPlanner
	Class to plan memory by Weighted Interval Color algorithm. More...

Typedefs
using	ExternalContext = cpu::ExternalContext
using	MemoryManager = backend::basic::MemoryManager
using	TrainableTensor = basic::train::TrainableTensor
using	BackPropTensor = Tensor
using	GradientTensor = Tensor
using	LayerScopeTensors = std::vector< std::shared_ptr< LayerScopeTensor > >
using	FunctionMap = std::unordered_map< ir::OperationIndex, std::unique_ptr< exec::train::TrainableFnSequence > >
using	TrainableBackendContexts = std::unordered_map< const Backend *, std::unique_ptr< TrainableBackendContext > >

Enumerations
enum class	LayerScopeTensorLifeTime : unsigned char { BACKWARD , FORWARD_TO_BACKWARD }

Functions
std::ostream &	operator<< (std::ostream &o, const DisposableTensorIndex &i)
std::ostream &	operator<< (std::ostream &o, const LayerScopeTensorIndex &i)
std::unique_ptr< exec::train::optimizer::Optimizer >	createOptimizer (const ir::train::OptimizerInfo &optim_info)

Typedef Documentation

BackPropTensor

using onert::backend::train::BackPropTensor = typedef Tensor

Definition at line 43 of file Tensor.h.

ExternalContext

using onert::backend::train::ExternalContext = typedef cpu::ExternalContext

Definition at line 25 of file ExternalContext.h.

FunctionMap

using onert::backend::train::FunctionMap = typedef std::unordered_map<ir::OperationIndex, std::unique_ptr<exec::train::TrainableFnSequence> >

Definition at line 32 of file TrainableBackendContext.h.

GradientTensor

using onert::backend::train::GradientTensor = typedef Tensor

Definition at line 44 of file Tensor.h.

LayerScopeTensors

using onert::backend::train::LayerScopeTensors = typedef std::vector<std::shared_ptr<LayerScopeTensor> >

Definition at line 57 of file LayerScopeTensor.h.

MemoryManager

using onert::backend::train::MemoryManager = typedef backend::basic::MemoryManager

Definition at line 28 of file MemoryManager.h.

TrainableBackendContexts

using onert::backend::train::TrainableBackendContexts = typedef std::unordered_map<const Backend *, std::unique_ptr<TrainableBackendContext> >

Definition at line 87 of file TrainableBackendContext.h.

TrainableTensor

using onert::backend::train::TrainableTensor = typedef basic::train::TrainableTensor

Definition at line 42 of file Tensor.h.

Enumeration Type Documentation

LayerScopeTensorLifeTime

enum class onert::backend::train::LayerScopeTensorLifeTime : unsigned char

strong

Enumerator
BACKWARD
FORWARD_TO_BACKWARD

Definition at line 25 of file LayerScopeTensor.h.

{
  BACKWARD,            // alive during backward()
  FORWARD_TO_BACKWARD, // alive from forward() to backward()
};

Function Documentation

createOptimizer()

std::unique_ptr< exec::train::optimizer::Optimizer > onert::backend::train::createOptimizer

(

const ir::train::OptimizerInfo &

optim_info

)

Definition at line 29 of file Optimizers.h.

{
  // TODO Set properties of optimizer
  if (optim_info.optim_code == ir::train::OptimizerCode::SGD)
  {
    return std::make_unique<optimizer::SGD>(optim_info.learning_rate);
  }
  else if (optim_info.optim_code == ir::train::OptimizerCode::Adam)
  {
    return std::make_unique<optimizer::Adam>(optim_info.learning_rate);
  }
  else
    throw std::runtime_error("Invalid optimizer type, " +
                             ir::train::toString(optim_info.optim_code));
}

References onert::ir::train::Adam, onert::ir::train::OptimizerInfo::learning_rate, onert::ir::train::OptimizerInfo::optim_code, onert::ir::train::SGD, and onert::ir::train::toString().

Referenced by onert::backend::train::Backend::newContext().

operator<<() [1/2]

std::ostream & onert::backend::train::operator<< ( std::ostream &  o, const DisposableTensorIndex &  i  )

inline

Definition at line 87 of file DisposableTensorIndex.h.

{
  return operator<<(o, i.operand_index());
}

References onert::backend::train::DisposableTensorIndex::operand_index(), and operator<<().

Referenced by operator<<().

operator<<() [2/2]

std::ostream & onert::backend::train::operator<< ( std::ostream &  o, const LayerScopeTensorIndex &  i  )

inline

Definition at line 51 of file LayerScopeTensorIndex.h.

{
  o << i.op_index() << "-" << i.sub_index();
  return o;
}

References onert::backend::train::LayerScopeTensorIndex::op_index(), and onert::backend::train::LayerScopeTensorIndex::sub_index().