onert::exec::train::TrainableExecutors Class Reference

Class to gather executor set for trainable model NN package. More...

#include <TrainableExecutors.h>

Collaboration diagram for onert::exec::train::TrainableExecutors:

Public Member Functions
	TrainableExecutors (void)=default
	Construct a new TrainableExecutors object.
	TrainableExecutors (const TrainableExecutors &)=delete
	TrainableExecutors (TrainableExecutors &&)=default
	~TrainableExecutors ()=default
	Destroy the TrainableExecutors object.
TrainableExecutors &	operator= (const TrainableExecutors &)=delete
TrainableExecutors &	operator= (TrainableExecutors &&)=default
void	emplace (const ir::ModelIndex &model_index, const ir::SubgraphIndex &subg_index, std::unique_ptr< IExecutor > exec) override
	Insert executor in executor set.
TrainableExecutor *	at (const ir::ModelIndex &model_index, const ir::SubgraphIndex &subg_index) const override
	Return executor of index.
TrainableExecutor *	entryExecutor () const
uint32_t	inputSize () const override
	Return executor set's number of input.
uint32_t	outputSize () const override
	Return executor set's number of output.
const ir::OperandInfo &	inputInfo (const ir::IOIndex &index) const override
	Return NN package input tensor info.
const ir::OperandInfo &	outputInfo (const ir::IOIndex &index) const override
	Return NN package output tensor info.
void	execute (const ExecutionContext &ctx) override
	Execute NN package executor set.
void	train (const ExecutionContext &ctx, uint32_t training_step)
	Train.
float	getLoss (const ir::IOIndex &index) const
void	iterateTrainableTensors (const std::function< void(const ir::OperandIndex &, const backend::train::ITrainableTensor *)> &fn) const
Public Member Functions inherited from onert::exec::IExecutors
virtual	~IExecutors ()=default
	Virtual IExecutors destructor.
IExecutor *	entryExecutor () const

Detailed Description

Class to gather executor set for trainable model NN package.

Definition at line 30 of file TrainableExecutors.h.

Constructor & Destructor Documentation

TrainableExecutors() [1/3]

onert::exec::train::TrainableExecutors::TrainableExecutors ( void  )

default

Construct a new TrainableExecutors object.

TrainableExecutors() [2/3]

onert::exec::train::TrainableExecutors::TrainableExecutors ( const TrainableExecutors &  )

delete

TrainableExecutors() [3/3]

onert::exec::train::TrainableExecutors::TrainableExecutors ( TrainableExecutors &&  )

default

~TrainableExecutors()

onert::exec::train::TrainableExecutors::~TrainableExecutors ( )

default

Destroy the TrainableExecutors object.

Member Function Documentation

at()

TrainableExecutor * onert::exec::train::TrainableExecutors::at ( const ir::ModelIndex &  model_index, const ir::SubgraphIndex &  subg_index  ) const

overridevirtual

Return executor of index.

Parameters

[in]	model_index	Model index
[in]	subg_index	Subgraph index

Returns

Executor

Implements onert::exec::IExecutors.

Definition at line 34 of file TrainableExecutors.cc.

{
  return _executors.at(subg_index).get();
}

Referenced by entryExecutor().

emplace()

void onert::exec::train::TrainableExecutors::emplace ( const ir::ModelIndex &  model_index, const ir::SubgraphIndex &  subg_index, std::unique_ptr< IExecutor >  exec  )

overridevirtual

Insert executor in executor set.

Parameters

[in]	model_index	Model index
[in]	subg_index	Subgraph index
[in]	exec	Executor to insert

Implements onert::exec::IExecutors.

Definition at line 26 of file TrainableExecutors.cc.

{
  std::unique_ptr<TrainableExecutor> t_exec{
    nnfw::misc::polymorphic_downcast<TrainableExecutor *>(exec.release())};
  _executors.emplace(subg_index, std::move(t_exec));
}

entryExecutor()

TrainableExecutor * onert::exec::train::TrainableExecutors::entryExecutor ( ) const

inline

Definition at line 56 of file TrainableExecutors.h.

{ return at(ir::ModelIndex{0}, ir::SubgraphIndex{0}); }

References at().

Referenced by getLoss(), inputInfo(), inputSize(), iterateTrainableTensors(), outputInfo(), outputSize(), and train().

execute()

void onert::exec::train::TrainableExecutors::execute ( const ExecutionContext &  ctx )

overridevirtual

Execute NN package executor set.

Parameters

[in]

ctx

Execution context

Implements onert::exec::IExecutors.

Definition at line 54 of file TrainableExecutors.cc.

{
  if (_executors.size() > 1)
    throw std::runtime_error("TrainableExecutors does not support multiple executors yet");
 
  // UserTensor for Input/Output
  std::vector<std::unique_ptr<backend::builtin::UserTensor>> tensorpool;
 
  // Allocate UserTensor and call executor forward
  forward(ctx, tensorpool, false);
 
  // TODO Support multple executors
}

getLoss()

float onert::exec::train::TrainableExecutors::getLoss

(

const ir::IOIndex &

index

)

const

Definition at line 122 of file TrainableExecutors.cc.

{
  if (_executors.size() > 1)
    throw std::runtime_error("TrainableExecutors does not support multiple executors yet");
  return entryExecutor()->getLoss(index);
}

References entryExecutor(), and onert::exec::train::TrainableExecutor::getLoss().

Referenced by onert::exec::Execution::getLoss().

inputInfo()

const ir::OperandInfo & onert::exec::train::TrainableExecutors::inputInfo ( const ir::IOIndex &  index ) const

overridevirtual

Return NN package input tensor info.

Parameters

[in]

index

Input index

Returns

Tensor info

Implements onert::exec::IExecutors.

Definition at line 44 of file TrainableExecutors.cc.

{
  return entryExecutor()->inputInfo(index.value());
}

References entryExecutor(), and onert::exec::train::TrainableExecutor::inputInfo().

inputSize()

uint32_t onert::exec::train::TrainableExecutors::inputSize ( ) const

overridevirtual

Return executor set's number of input.

Returns

Number of input

Implements onert::exec::IExecutors.

Definition at line 40 of file TrainableExecutors.cc.

{ return entryExecutor()->inputSize(); }

References entryExecutor(), and onert::exec::train::TrainableExecutor::inputSize().

iterateTrainableTensors()

void onert::exec::train::TrainableExecutors::iterateTrainableTensors

(

const std::function< void(const ir::OperandIndex &, const backend::train::ITrainableTensor *)> &

fn

)

const

Definition at line 129 of file TrainableExecutors.cc.

{
  return entryExecutor()->iterateTrainableTensors(fn);
}

References entryExecutor(), and onert::exec::train::TrainableExecutor::iterateTrainableTensors().

Referenced by onert::exec::Execution::iterateTrainableTensors().

operator=() [1/2]

TrainableExecutors & onert::exec::train::TrainableExecutors::operator= ( const TrainableExecutors &  )

delete

operator=() [2/2]

TrainableExecutors & onert::exec::train::TrainableExecutors::operator= ( TrainableExecutors &&  )

default

outputInfo()

const ir::OperandInfo & onert::exec::train::TrainableExecutors::outputInfo ( const ir::IOIndex &  index ) const

overridevirtual

Return NN package output tensor info.

Parameters

[in]

index

Output index

Returns

Tensor info

Implements onert::exec::IExecutors.

Definition at line 49 of file TrainableExecutors.cc.

{
  return entryExecutor()->outputInfo(index.value());
}

References entryExecutor(), and onert::exec::train::TrainableExecutor::outputInfo().

outputSize()

uint32_t onert::exec::train::TrainableExecutors::outputSize ( ) const

overridevirtual

Return executor set's number of output.

Returns

Number of output

Implements onert::exec::IExecutors.

Definition at line 42 of file TrainableExecutors.cc.

{ return entryExecutor()->outputSize(); }

References entryExecutor(), and onert::exec::train::TrainableExecutor::outputSize().

train()

void onert::exec::train::TrainableExecutors::train	(	const ExecutionContext &	ctx,
		uint32_t	training_step
	)

Train.

Parameters

ctx	Execution context
training_step	The number of iterations of an training process. In other words, the number of gradient update.

Definition at line 68 of file TrainableExecutors.cc.

{
  if (_executors.size() > 1)
    throw std::runtime_error("TrainableExecutors does not support multiple executors yet");
 
  // UserTensor for Input/Output
  std::vector<std::unique_ptr<backend::builtin::UserTensor>> tensorpool;
 
  // Allocate UserTensor and call executor forward and backward
  forward(ctx, tensorpool, true);
  entryExecutor()->backward(ctx.options, training_step);
 
  // TODO Support multple executors
}

References onert::exec::train::TrainableExecutor::backward(), entryExecutor(), and onert::exec::ExecutionContext::options.

Referenced by onert::exec::Execution::train().

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

• runtime/onert/core/src/exec/train/TrainableExecutors.h
• runtime/onert/core/src/exec/train/TrainableExecutors.cc