Class to define execution instance to collect input/output information for inference and prepare executor run (TODO) More...

#include <Execution.h>

Public Member Functions
	Execution (const std::shared_ptr< IExecutors > &executors)
	Construct a new Execution object.

const ir::Graph &	primary_subgraph () const
	Returns primary graph object.

void	changeInputShape (const ir::IOIndex &index, const ir::Shape &new_shape)
	Change input shape.

void	setInput (const ir::IOIndex &index, const void *buffer, size_t length)
	Set input data's information.

void	setInput (const ir::IOIndex &index, const ir::Shape &shape, const void *buffer, size_t length)
	Set input data's information, especially to specify unknown dimensions on model build time.

void	setOutput (const ir::IOIndex &index, void *buffer, size_t length)
	Set output data's information.

void	setOutput (const ir::IOIndex &index, const ir::Shape &shape, void *buffer, size_t length)
	Set output data's information, especially to specify unknown dimensions on model build time.

void	setInputLayout (const ir::IOIndex &index, ir::Layout layout)
	Set input data's data format.

void	setOutputLayout (const ir::IOIndex &index, ir::Layout layout)
	Set output data's data format.

void	setInputType (const ir::IOIndex &index, const ir::TypeInfo &typeInfo)
	Set input type information.

void	setOutputType (const ir::IOIndex &index, const ir::TypeInfo &typeInfo)
	Set output type information.

void	execute ()
	Execution.

void	startExecute (void)
	Start asynchronous execution.

void	waitFinish (void)
	Return when execution is finished.

bool	isFinished (void) const
	Check execution is finished.

void	train (uint32_t training_step)
	Train.

float	getLoss (const ir::IOIndex &ind)
	Get loss.

void	iterateTrainableTensors (const std::function< void(const ir::OperandIndex &, const backend::train::ITrainableTensor *)> &fn) const
	Iterate trainable tensors.

ir::Shape	getInputShape (ir::IOIndex ind) const

ir::Shape	getOutputShape (ir::IOIndex ind) const

size_t	getInputTotalSize (ir::IOIndex ind) const

size_t	getOutputTotalSize (ir::IOIndex ind) const

const void *	getInputBuffer (ir::IOIndex ind) const
	Get pointer of Input Buffer.

void *	getOutputBuffer (ir::IOIndex ind)
	Get pointer of Output Buffer.

ExecutionOptions &	executionOptions ()

Detailed Description

Class to define execution instance to collect input/output information for inference and prepare executor run (TODO)

Definition at line 40 of file Execution.h.

Constructor & Destructor Documentation

◆ Execution()

onert::exec::Execution::Execution ( const std::shared_ptr< IExecutors > & executors )

Construct a new Execution object.

Parameters

[in] executor Model executor

Definition at line 26 of file Execution.cc.

                                                               : _executors{executors}
{
  assert(executors != nullptr);
  assert(executors->entryExecutor() != nullptr);
 
  // Initialize I/O description
  _ctx.desc.inputs.resize(_executors->inputSize());
  for (uint32_t i = 0; i < _executors->inputSize(); ++i)
    _ctx.desc.inputs.at(i) = std::make_unique<InputDesc>(_executors->inputInfo(ir::IOIndex(i)));
 
  _ctx.desc.outputs.resize(_executors->outputSize());
  for (uint32_t i = 0; i < _executors->outputSize(); ++i)
    _ctx.desc.outputs.at(i) = std::make_unique<OutputDesc>(_executors->outputInfo(ir::IOIndex(i)));
  _ctx.shape_updated = false;
 
  // Initialize options
  ExecutionOptions::fromGlobalConfig(_ctx.options);
}

References onert::exec::ExecutionContext::desc, onert::exec::ExecutionOptions::fromGlobalConfig(), onert::exec::IODescription::inputs, onert::exec::ExecutionContext::options, onert::exec::IODescription::outputs, and onert::exec::ExecutionContext::shape_updated.

Member Function Documentation

◆ changeInputShape()

void onert::exec::Execution::changeInputShape	(	const ir::IOIndex &	index,
		const ir::Shape &	new_shape
	)

Change input shape.

Parameters

[in]	index	Input index
[in]	new_shape	shape to change

Definition at line 45 of file Execution.cc.

{
  // This will be used later to set input tensor dynamic
  // Note that 'compiled' model will not be updated with new_shape
  // but new_shape will change model input shape while 'running' the model
  auto &input_desc = _ctx.desc.inputs.at(index.value());
  if (new_shape != input_desc->info.shape())
  {
    input_desc->info.shape(new_shape);
    _ctx.shape_updated = true;
 
    VERBOSE(Execution) << "Model input shape will be changed at the start of execute()"
                       << "(index: " << index << ")" << std::endl;
  }
}

References onert::exec::ExecutionContext::desc, onert::exec::IODescription::inputs, onert::exec::ExecutionContext::shape_updated, and VERBOSE.

Referenced by setInput().

◆ execute()

void onert::exec::Execution::execute ( )

Execution.

Note: It should be called after setting input and output buffer

Definition at line 118 of file Execution.cc.

{
  VERBOSE(Execution) << "Start execution" << std::endl;
 
  // Input length validation check
  for (const auto &input : _ctx.desc.inputs)
  {
    if (input->info.total_size() > input->size)
      throw std::runtime_error{"Too small input buffer length"};
  }
 
  // Output length validation check
  if (!_ctx.shape_updated)
  {
    for (const auto &output : _ctx.desc.outputs)
    {
      if (output->info.total_size() > output->size)
        throw std::runtime_error{"Too small output buffer length"};
    }
  }
 
  _executors->execute(_ctx);
  finished = true;
 
  VERBOSE(Execution) << "Execution finished" << std::endl;
}

References onert::exec::ExecutionContext::desc, onert::exec::IODescription::inputs, onert::exec::IODescription::outputs, onert::exec::ExecutionContext::shape_updated, and VERBOSE.

Referenced by startExecute().

◆ executionOptions()

ExecutionOptions & onert::exec::Execution::executionOptions ( )

inline

Definition at line 191 of file Execution.h.

191{ return _ctx.options; }

References onert::exec::ExecutionContext::options.

◆ getInputBuffer()

const void * onert::exec::Execution::getInputBuffer ( ir::IOIndex ind ) const

Get pointer of Input Buffer.

Parameters

[in] index Input index

Returns: Pointer of Input Buffer

Definition at line 224 of file Execution.cc.

{
  return _ctx.desc.inputs.at(ind.value())->buffer;
}

References onert::exec::ExecutionContext::desc, onert::exec::IODescription::inputs, and onert::util::Index< T, DummyTag >::value().

◆ getInputShape()

ir::Shape onert::exec::Execution::getInputShape ( ir::IOIndex ind ) const

Definition at line 197 of file Execution.cc.

{
  return _ctx.desc.inputs.at(ind.value())->info.shape();
}

References onert::exec::ExecutionContext::desc, onert::exec::IODescription::inputs, and onert::util::Index< T, DummyTag >::value().

◆ getInputTotalSize()

size_t onert::exec::Execution::getInputTotalSize ( ir::IOIndex ind ) const

Definition at line 213 of file Execution.cc.

{
  // TODO Support dynamic shape
  return _ctx.desc.inputs.at(ind.value())->info.total_size();
}

References onert::exec::ExecutionContext::desc, onert::exec::IODescription::inputs, and onert::util::Index< T, DummyTag >::value().

◆ getLoss()

float onert::exec::Execution::getLoss ( const ir::IOIndex & ind )

Get loss.

Note: It should be called after training

Parameters

[in] ind Output index

Returns: float Loss value

Definition at line 174 of file Execution.cc.

{
  auto execs = dynamic_cast<exec::train::TrainableExecutors *>(_executors.get());
  if (!execs)
  {
    throw std::runtime_error{"Supported only TrainableExecutors"};
  }
 
  return execs->getLoss(ind);
}

References onert::exec::train::TrainableExecutors::getLoss().

◆ getOutputBuffer()

void * onert::exec::Execution::getOutputBuffer ( ir::IOIndex ind )

Get pointer of Output Buffer.

Parameters

[in] index Output index

Returns: Pointer of Output Buffer

Definition at line 229 of file Execution.cc.

{
  return _ctx.desc.outputs.at(ind.value())->buffer;
}

References onert::exec::ExecutionContext::desc, onert::exec::IODescription::outputs, and onert::util::Index< T, DummyTag >::value().

◆ getOutputShape()

ir::Shape onert::exec::Execution::getOutputShape ( ir::IOIndex ind ) const

Definition at line 208 of file Execution.cc.

{
  return _ctx.desc.outputs.at(ind.value())->info.shape();
}

References onert::exec::ExecutionContext::desc, onert::exec::IODescription::outputs, and onert::util::Index< T, DummyTag >::value().

◆ getOutputTotalSize()

size_t onert::exec::Execution::getOutputTotalSize ( ir::IOIndex ind ) const

Definition at line 219 of file Execution.cc.

{
  return _ctx.desc.outputs.at(ind.value())->info.total_size();
}

References onert::exec::ExecutionContext::desc, onert::exec::IODescription::outputs, and onert::util::Index< T, DummyTag >::value().

◆ isFinished()

bool onert::exec::Execution::isFinished ( void ) const

Check execution is finished.

Returns: true if execution is finished, otherwise false

Definition at line 160 of file Execution.cc.

160{ return finished; }

◆ iterateTrainableTensors()

void onert::exec::Execution::iterateTrainableTensors ( const std::function< void(const ir::OperandIndex &, const backend::train::ITrainableTensor *)> & fn ) const

Iterate trainable tensors.

Note: It should be called after training

Parameters

[in] fn function to be called with OperandIndex and a pointer to ITrainableTensor

Definition at line 185 of file Execution.cc.

{
  auto execs = dynamic_cast<exec::train::TrainableExecutors *>(_executors.get());
  if (!execs)
  {
    throw std::runtime_error{"Supported only TrainableExecutors"};
  }
  execs->iterateTrainableTensors(fn);
}

References onert::exec::train::TrainableExecutors::iterateTrainableTensors().

◆ primary_subgraph()

const ir::Graph & onert::exec::Execution::primary_subgraph ( ) const

inline

Returns primary graph object.

Returns: Graph object

Definition at line 55 of file Execution.h.

55{ return entryExecutor()->graph(); }

onert::exec::IExecutor::graph

virtual const ir::Graph & graph() const =0

Returns graph object.

References onert::exec::IExecutor::graph().

◆ setInput() [1/2]

void onert::exec::Execution::setInput	(	const ir::IOIndex &	index,
		const ir::Shape &	shape,
		const void *	buffer,
		size_t	length
	)

Set input data's information, especially to specify unknown dimensions on model build time.

Parameters

[in]	index	Input index
[in]	shape	Input data's shape
[in]	buffer	Input data's buffer pointer
[in]	length	Input data's length

Definition at line 70 of file Execution.cc.

{
  changeInputShape(index, shape);
  setInput(index, buffer, length);
}

References changeInputShape(), and setInput().

◆ setInput() [2/2]

void onert::exec::Execution::setInput	(	const ir::IOIndex &	index,
		const void *	buffer,
		size_t	length
	)

Set input data's information.

Parameters

[in]	index	Input index
[in]	buffer	Input data's buffer pointer
[in]	length	Input data's length

Definition at line 62 of file Execution.cc.

{
  // Length validation in execute(): datatype can be changed by API call
  auto &input_desc = _ctx.desc.inputs.at(index.value());
  input_desc->buffer = buffer;
  input_desc->size = length;
}

References onert::exec::ExecutionContext::desc, and onert::exec::IODescription::inputs.

Referenced by setInput().

◆ setInputLayout()

void onert::exec::Execution::setInputLayout	(	const ir::IOIndex &	index,
		ir::Layout	layout
	)

Set input data's data format.

Parameters

[in]	index	Input index
[in]	layout	Input data's data format

Definition at line 96 of file Execution.cc.

{
  _ctx.desc.inputs.at(index.value())->layout = layout;
}

References onert::exec::ExecutionContext::desc, and onert::exec::IODescription::inputs.

◆ setInputType()

void onert::exec::Execution::setInputType	(	const ir::IOIndex &	index,
		const ir::TypeInfo &	typeInfo
	)

Set input type information.

Parameters

[in]	index	Input index
[in]	typeInfo	Input type information

Definition at line 106 of file Execution.cc.

{
  _ctx.desc.inputs.at(index.value())->info.typeInfo(typeInfo);
  _ctx.shape_updated = true;
}

References onert::exec::ExecutionContext::desc, onert::exec::IODescription::inputs, and onert::exec::ExecutionContext::shape_updated.

◆ setOutput() [1/2]

void onert::exec::Execution::setOutput	(	const ir::IOIndex &	index,
		const ir::Shape &	shape,
		void *	buffer,
		size_t	length
	)

Set output data's information, especially to specify unknown dimensions on model build time.

Parameters

[in]	index	Output index
[in]	shape	Output data's shape
[in]	buffer	Output data's buffer pointer
[in]	length	Output data's length

Definition at line 87 of file Execution.cc.

{
  auto &output_desc = _ctx.desc.outputs.at(index.value());
  output_desc->info.shape(shape);
 
  setOutput(index, buffer, length);
}

References onert::exec::ExecutionContext::desc, onert::exec::IODescription::outputs, and setOutput().

◆ setOutput() [2/2]

void onert::exec::Execution::setOutput	(	const ir::IOIndex &	index,
		void *	buffer,
		size_t	length
	)

Set output data's information.

Parameters

[in]	index	Output index
[in]	buffer	Output data's buffer pointer
[in]	length	Output data's length

Definition at line 77 of file Execution.cc.

{
  // Length validation in execute()
  // - datatype can be changed by API call
  // - shape can be changed by dynamic shape inference
  auto &output_desc = _ctx.desc.outputs.at(index.value());
  output_desc->buffer = buffer;
  output_desc->size = length;
}

References onert::exec::ExecutionContext::desc, and onert::exec::IODescription::outputs.

Referenced by setOutput().

◆ setOutputLayout()

void onert::exec::Execution::setOutputLayout	(	const ir::IOIndex &	index,
		ir::Layout	layout
	)

Set output data's data format.

Parameters

[in]	index	Output index
[in]	layout	Output data's data format

Definition at line 101 of file Execution.cc.

{
  _ctx.desc.outputs.at(index.value())->layout = layout;
}

References onert::exec::ExecutionContext::desc, and onert::exec::IODescription::outputs.

◆ setOutputType()

void onert::exec::Execution::setOutputType	(	const ir::IOIndex &	index,
		const ir::TypeInfo &	typeInfo
	)

Set output type information.

Parameters

[in]	index	Output index
[in]	typeInfo	Output type information

Definition at line 112 of file Execution.cc.

{
  _ctx.desc.outputs.at(index.value())->info.typeInfo(typeInfo);
  _ctx.shape_updated = true;
}

References onert::exec::ExecutionContext::desc, onert::exec::IODescription::outputs, and onert::exec::ExecutionContext::shape_updated.

◆ startExecute()

void onert::exec::Execution::startExecute ( void )

Start asynchronous execution.

Note: It returns after execution thread is started It should be called after setting input and output buffer

Definition at line 145 of file Execution.cc.

{
  VERBOSE(Execution) << "Create asynchronous execution thread" << std::endl;
 
  _exec_thread = std::make_unique<std::thread>(&Execution::execute, this);
}

References execute(), and VERBOSE.

◆ train()

void onert::exec::Execution::train ( uint32_t training_step )

Train.

Note: It should be called after setting input and output buffer

Parameters

training_step The number of iterations of the training process. In other words, the number of gradient update.

Definition at line 162 of file Execution.cc.

{
  auto execs = dynamic_cast<exec::train::TrainableExecutors *>(_executors.get());
  if (!execs)
  {
    throw std::runtime_error{"Supported only TrainableExecutors"};
  }
 
  execs->train(_ctx, training_step);
  finished = true;
}

References onert::exec::train::TrainableExecutors::train().

◆ waitFinish()

void onert::exec::Execution::waitFinish ( void )

Return when execution is finished.

Note: It waits until execution is finished

Definition at line 152 of file Execution.cc.

{
  VERBOSE(Execution) << "Wait to finish execution" << std::endl;
 
  _exec_thread->join();
  finished = true;
}

References VERBOSE.

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

runtime/onert/core/include/exec/Execution.h
runtime/onert/core/src/exec/Execution.cc

Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ Execution()

Member Function Documentation

◆ changeInputShape()

◆ execute()

◆ executionOptions()

◆ getInputBuffer()

◆ getInputShape()

◆ getInputTotalSize()

◆ getLoss()

◆ getOutputBuffer()

◆ getOutputShape()

◆ getOutputTotalSize()

◆ isFinished()

◆ iterateTrainableTensors()

◆ primary_subgraph()

◆ setInput() [1/2]

◆ setInput() [2/2]

◆ setInputLayout()

◆ setInputType()

◆ setOutput() [1/2]

◆ setOutput() [2/2]

◆ setOutputLayout()

◆ setOutputType()

◆ startExecute()

◆ train()

◆ waitFinish()