onert-micro.cpp File Reference

#include <string>
#include <memory>
#include <thread>
#include <vector>
#include <iostream>
#include <fstream>
#include "OMTrainingInterpreter.h"
#include "onert-micro.h"
#include <circle-generated/circle/schema_generated.h>
#include <circle-generated/circle/traininfo_generated.h>

Go to the source code of this file.

Data Structures
struct	nnfw_session

Macros
#define	NNFW_RETURN_ERROR_IF_NULL(p)

Typedefs
using	DataBuffer = std::vector< char >

Functions
DataBuffer	readFile (const char *path)
NNFW_STATUS	nnfw_create_session (nnfw_session **session)
	Create a new session instance.
NNFW_STATUS	nnfw_load_model_from_file (nnfw_session *session, const char *package_file_path)
	Load model from nnpackage file or directory.
NNFW_STATUS	nnfw_train_prepare (nnfw_session *session)
	Prepare session to be ready for training.
NNFW_STATUS	nnfw_train (nnfw_session *session, bool update_weights)
	Train the model.
NNFW_STATUS	nnfw_train_export_circle (nnfw_session *session, const char *path)
	Export current training model into circle model.
NNFW_STATUS	nnfw_train_export_checkpoint (nnfw_session *session, const char *path)
	Export circle checkpoint.
NNFW_STATUS	nnfw_train_import_checkpoint (nnfw_session *session, const char *path)
	Import circle checkpoint.
NNFW_STATUS	nnfw_train_set_input (nnfw_session *session, uint32_t index, void *input, const nnfw_tensorinfo *input_info)
	Set training input.
NNFW_STATUS	nnfw_train_set_expected (nnfw_session *session, uint32_t index, void *expected, const nnfw_tensorinfo *expected_info)
	Set training expected output.
NNFW_STATUS	nnfw_train_get_loss (nnfw_session *session, uint32_t index, float *loss)
	Get loss value for expected output.
NNFW_STATUS	nnfw_train_set_traininfo (nnfw_session *session, const nnfw_train_info *info)
	Set training information.
NNFW_STATUS	nnfw_train_set_output (nnfw_session *session, uint32_t index, NNFW_TYPE type, void *buffer, size_t length)
	Set training output buffer.

Macro Definition Documentation

NNFW_RETURN_ERROR_IF_NULL

#define NNFW_RETURN_ERROR_IF_NULL

(

p

)

Value:

  do                                      \
  {                                       \
    if ((p) == NULL)                      \
      return NNFW_STATUS_UNEXPECTED_NULL; \
  } while (0)

Definition at line 29 of file onert-micro.cpp.

  {                                       \
    if ((p) == NULL)                      \
      return NNFW_STATUS_UNEXPECTED_NULL; \
  } while (0)

Typedef Documentation

DataBuffer

using DataBuffer = std::vector<char>

Definition at line 37 of file onert-micro.cpp.

Function Documentation

nnfw_create_session()

NNFW_STATUS nnfw_create_session

(

nnfw_session **

session

)

Create a new session instance.

This only creates a session. Model is loaded after nnfw_load_model_from_file is invoked. And inference is performed after nnfw_run is invoked.

nnfw_close_session should be called once if session is no longer needed

Parameters

[out]

session

The session to be created

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 390 of file onert-micro.cpp.

{ return nnfw_session::create(session); }

nnfw_load_model_from_file()

NNFW_STATUS nnfw_load_model_from_file	(	nnfw_session *	session,
		const char *	package_file_path
	)

Load model from nnpackage file or directory.

Load model from path to model or nnpackage.

The length of package_file_path must not exceed 1024 bytes including zero at the end.

Parameters

[in]	session	nnfw_session loading the given nnpackage file/dir
[in]	package_file_path	Path to the nnpackage file or unzipped directory to be loaded

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 392 of file onert-micro.cpp.

{
  return session->load_model_from_file(package_file_path);
}

nnfw_train()

NNFW_STATUS nnfw_train	(	nnfw_session *	session,
		bool	update_weights
	)

Train the model.

Note

This function should be called after nnfw_train_set_input and nnfw_train_set_expected for each input and expected output

In order to use update_weights as false, it should be called after nnfw_train_set_output.

Parameters

[in]	session	The session to be trained
[in]	update_weights	If true, update weights of the model If false, do not update weights of the model (for validation)

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 399 of file onert-micro.cpp.

{
  return session->train_run(update_weights);
}

nnfw_train_export_checkpoint()

NNFW_STATUS nnfw_train_export_checkpoint	(	nnfw_session *	session,
		const char *	path
	)

Export circle checkpoint.

Note

This function should be called on training mode This function should be called after nnfw_train

Parameters

[in]	session	The session to export a checkpoint
[in]	path	The path to export a checkpoint

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 409 of file onert-micro.cpp.

{
  return session->train_export_checkpoint(path);
}

nnfw_train_export_circle()

NNFW_STATUS nnfw_train_export_circle	(	nnfw_session *	session,
		const char *	path
	)

Export current training model into circle model.

Export circle model.

Note

This function should be called on training mode This function should be called after nnfw_train

Parameters

[in]	session	The session to export inference model
[in]	path	The path to export inference model

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 404 of file onert-micro.cpp.

{
  return session->train_export_circle(path);
}

nnfw_train_get_loss()

NNFW_STATUS nnfw_train_get_loss	(	nnfw_session *	session,
		uint32_t	index,
		float *	loss
	)

Get loss value for expected output.

Note

This function should be called after nnfw_train

Parameters

[in]	session	The session to get loss value
[in]	index	The index of loss value [0, number of expected outputs)
[out]	loss	The loss value

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 433 of file onert-micro.cpp.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->train_get_loss(index, loss);
}

nnfw_train_import_checkpoint()

NNFW_STATUS nnfw_train_import_checkpoint	(	nnfw_session *	session,
		const char *	path
	)

Import circle checkpoint.

Note

This function should be called on training mode This function should be called before nnfw_train

Parameters

[in]	session	The session to export a checkpoint
[in]	path	The path to export a checkpoint

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 414 of file onert-micro.cpp.

{
  return session->train_import_checkpoint(path);
}

nnfw_train_prepare()

NNFW_STATUS nnfw_train_prepare

(

nnfw_session *

session

)

Prepare session to be ready for training.

Note

The session will be entered into training mode

   If training info is NOT set in session, this function returns @c NNFW_STATUS_ERROR .
   You should set training info using {@link nnfw_train_set_traininfo}.

Parameters

[in]

session

The session to be prepared for training

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 397 of file onert-micro.cpp.

{ return session->train_prepare(); }

nnfw_train_set_expected()

NNFW_STATUS nnfw_train_set_expected	(	nnfw_session *	session,
		uint32_t	index,
		void *	expected,
		const nnfw_tensorinfo *	expected_info
	)

Set training expected output.

Note

This function should be called after nnfw_train_prepare

Parameters

session	The session to be set training inputs and expected model outputs
index	The index of training expected output
expected	The expected buffers for training
expected_info	The shape and type of expected buffer If it is nullptr, it will not change shape and batch size

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 426 of file onert-micro.cpp.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->train_set_expected(index, expected);
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_train_set_input()

NNFW_STATUS nnfw_train_set_input	(	nnfw_session *	session,
		uint32_t	index,
		void *	input,
		const nnfw_tensorinfo *	input_info
	)

Set training input.

Note

This function should be called after nnfw_train_prepare

Parameters

[in]	session	The session to be set training inputs and expected model outputs
[in]	index	The index of training input
[in]	input	The input buffers for training
[in]	input_info	The shape and type of input buffer If it is nullptr, it will not change shape and batch size

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 419 of file onert-micro.cpp.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->train_set_input(index, input);
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_train_set_output()

NNFW_STATUS nnfw_train_set_output	(	nnfw_session *	session,
		uint32_t	index,
		NNFW_TYPE	type,
		void *	buffer,
		size_t	length
	)

Set training output buffer.

This function must be called after nnfw_train_prepare, buffer given to this function can be reused for training. length must be greater or equal than the operand requires. An output operand can have unspecified shape and deduced dynamically during the execution. You must provide buffer large enough.

Parameters

[in]	session	Session from inference output is to be extracted
[in]	index	Index of output to be set (0-indexed)
[in]	type	Type of the output
[out]	buffer	Raw buffer for output
[in]	length	Size of bytes of output buffer

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 445 of file onert-micro.cpp.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->train_set_output(index, type, buffer, length);
}

nnfw_train_set_traininfo()

NNFW_STATUS nnfw_train_set_traininfo	(	nnfw_session *	session,
		const nnfw_train_info *	info
	)

Set training information.

Note

This function should be called after calling nnfw_load_model_from_file and before calling nnfw_train_prepare

Parameters

[in]	session	The session to be set training information
[in]	info	The training information

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 439 of file onert-micro.cpp.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->train_set_traininfo(info);
}

readFile()

DataBuffer readFile

(

const char *

path

)

Definition at line 39 of file onert-micro.cpp.

{
  std::ifstream file(path, std::ios::binary | std::ios::in);
  if (!file.good())
  {
    std::string errmsg = "Failed to open file";
    std::cerr << errmsg << std::endl;
    exit(-1); // FIXME: proper way
  }
 
  file.seekg(0, std::ios::end);
  auto fileSize = file.tellg();
  file.seekg(0, std::ios::beg);
 
  // reserve capacity
  DataBuffer model_data(fileSize);
 
  // read the data
  file.read(model_data.data(), fileSize);
  if (file.fail())
  {
    std::string errmsg = "Failed to read file";
    std::cerr << errmsg << std::endl;
    exit(-1); // FIXME: proper way
  }
 
  return model_data;
}

Referenced by entry(), and nnfw_session::load_model_from_file().