nnfw_api.cc File Reference

#include "nnfw.h"
#include "nnfw_experimental.h"
#include "nnfw_version.h"
#include "nnfw_session.h"

Go to the source code of this file.

Macros
#define	STATIC_ASSERT_ENUM_CHECK(ENUM, VAL)   static_assert((ENUM) == (VAL), #ENUM " has changed")
#define	NNFW_RETURN_ERROR_IF_NULL(p)

Functions
	STATIC_ASSERT_ENUM_CHECK (NNFW_TYPE_TENSOR_FLOAT32, 0)
	STATIC_ASSERT_ENUM_CHECK (NNFW_TYPE_TENSOR_INT32, 1)
	STATIC_ASSERT_ENUM_CHECK (NNFW_TYPE_TENSOR_QUANT8_ASYMM, 2)
	STATIC_ASSERT_ENUM_CHECK (NNFW_TYPE_TENSOR_BOOL, 3)
	STATIC_ASSERT_ENUM_CHECK (NNFW_TYPE_TENSOR_UINT8, 4)
	STATIC_ASSERT_ENUM_CHECK (NNFW_TYPE_TENSOR_INT64, 5)
	STATIC_ASSERT_ENUM_CHECK (NNFW_TYPE_TENSOR_QUANT8_ASYMM_SIGNED, 6)
	STATIC_ASSERT_ENUM_CHECK (NNFW_TYPE_TENSOR_QUANT16_SYMM_SIGNED, 7)
	STATIC_ASSERT_ENUM_CHECK (NNFW_STATUS_NO_ERROR, 0)
	STATIC_ASSERT_ENUM_CHECK (NNFW_STATUS_ERROR, 1)
	STATIC_ASSERT_ENUM_CHECK (NNFW_STATUS_UNEXPECTED_NULL, 2)
	STATIC_ASSERT_ENUM_CHECK (NNFW_STATUS_INVALID_STATE, 3)
	STATIC_ASSERT_ENUM_CHECK (NNFW_STATUS_OUT_OF_MEMORY, 4)
	STATIC_ASSERT_ENUM_CHECK (NNFW_STATUS_INSUFFICIENT_OUTPUT_SIZE, 5)
	STATIC_ASSERT_ENUM_CHECK (NNFW_LAYOUT_NONE, 0)
	STATIC_ASSERT_ENUM_CHECK (NNFW_LAYOUT_CHANNELS_LAST, 1)
	STATIC_ASSERT_ENUM_CHECK (NNFW_LAYOUT_CHANNELS_FIRST, 2)
	STATIC_ASSERT_ENUM_CHECK (NNFW_INFO_ID_VERSION, 0)
NNFW_STATUS	nnfw_create_session (nnfw_session **session)
	Create a new session instance.
NNFW_STATUS	nnfw_close_session (nnfw_session *session)
	Close a session instance.
NNFW_STATUS	nnfw_load_model_from_file (nnfw_session *session, const char *path)
	Load model from nnpackage file or directory.
NNFW_STATUS	nnfw_prepare (nnfw_session *session)
	Prepare session to be ready for inference.
NNFW_STATUS	nnfw_run (nnfw_session *session)
	Run inference.
NNFW_STATUS	nnfw_run_async (nnfw_session *session)
	Run inference asynchronously.
NNFW_STATUS	nnfw_await (nnfw_session *session)
	Wait for asynchronous run to finish.
NNFW_STATUS	nnfw_set_input (nnfw_session *session, uint32_t index, NNFW_TYPE type, const void *buffer, size_t length)
	Set input buffer.
NNFW_STATUS	nnfw_set_output (nnfw_session *session, uint32_t index, NNFW_TYPE type, void *buffer, size_t length)
	Set output buffer.
NNFW_STATUS	nnfw_input_size (nnfw_session *session, uint32_t *number)
	Get the number of inputs.
NNFW_STATUS	nnfw_output_size (nnfw_session *session, uint32_t *number)
	Get the number of outputs.
NNFW_STATUS	nnfw_set_input_layout (nnfw_session *session, uint32_t index, NNFW_LAYOUT layout)
	Set the layout of an input.
NNFW_STATUS	nnfw_set_output_layout (nnfw_session *session, uint32_t index, NNFW_LAYOUT layout)
	Set the layout of an output.
NNFW_STATUS	nnfw_input_tensorinfo (nnfw_session *session, uint32_t index, nnfw_tensorinfo *tensor_info)
	Get i-th input tensor info.
NNFW_STATUS	nnfw_output_tensorinfo (nnfw_session *session, uint32_t index, nnfw_tensorinfo *tensor_info)
	Get i-th output tensor info.
NNFW_STATUS	nnfw_register_custom_op_info (nnfw_session *session, const char *id, custom_kernel_registration_info *info)
NNFW_STATUS	nnfw_apply_tensorinfo (nnfw_session *, uint32_t, nnfw_tensorinfo)
	Apply i-th input's tensor info to resize input tensor.
NNFW_STATUS	nnfw_set_input_tensorinfo (nnfw_session *session, uint32_t index, const nnfw_tensorinfo *tensor_info)
	Set input model's tensor info for resizing.
NNFW_STATUS	nnfw_set_available_backends (nnfw_session *session, const char *backends)
	Set available backends.
NNFW_STATUS	nnfw_set_op_backend (nnfw_session *, const char *, const char *)
	Set the operation's backend.
NNFW_STATUS	nnfw_query_info_u32 (nnfw_session *session, NNFW_INFO_ID id, uint32_t *val)
	Retrieve uint32 type of nnfw information for given information ID.
NNFW_STATUS	nnfw_input_tensorindex (nnfw_session *session, const char *tensorname, uint32_t *index)
	Get the input tensor index by name.
NNFW_STATUS	nnfw_output_tensorindex (nnfw_session *session, const char *tensorname, uint32_t *index)
	Get the input tensor index by name.
NNFW_STATUS	nnfw_set_backends_per_operation (nnfw_session *session, const char *backend_settings)
	Set the backend for each operation in the session.
NNFW_STATUS	nnfw_prepare_pipeline (nnfw_session *, const char *)
	Prepare session to be ready for inference.
NNFW_STATUS	nnfw_push_pipeline_input (nnfw_session *, void *, void *)
	Set input buffer.
NNFW_STATUS	nnfw_pop_pipeline_output (nnfw_session *, void *)
	Get last outputs of partitioned model in session.
NNFW_STATUS	nnfw_set_workspace (nnfw_session *session, const char *dir)
	Set runtime's workspace directory.
NNFW_STATUS	nnfw_train_get_traininfo (nnfw_session *session, nnfw_train_info *info)
	Get training information.
NNFW_STATUS	nnfw_train_set_traininfo (nnfw_session *session, const nnfw_train_info *info)
	Set training information.
NNFW_STATUS	nnfw_train_prepare (nnfw_session *session)
	Prepare session to be ready for training.
NNFW_STATUS	nnfw_train_input_tensorinfo (nnfw_session *session, uint32_t index, nnfw_tensorinfo *info)
	Get the training model input information.
NNFW_STATUS	nnfw_train_expected_tensorinfo (nnfw_session *session, uint32_t index, nnfw_tensorinfo *info)
	Get the training model expected output information.
NNFW_STATUS	nnfw_train_set_input (nnfw_session *session, uint32_t index, const void *input, const nnfw_tensorinfo *input_info)
	Set training input.
NNFW_STATUS	nnfw_train_set_expected (nnfw_session *session, uint32_t index, const void *expected, const nnfw_tensorinfo *expected_info)
	Set training expected 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.
NNFW_STATUS	nnfw_train (nnfw_session *session, bool update_weights)
	Train the model.
NNFW_STATUS	nnfw_train_get_loss (nnfw_session *session, uint32_t index, float *loss)
	Get loss value for expected output.
NNFW_STATUS	nnfw_train_export_circle (nnfw_session *session, const char *path)
	Export current training model into circle model.
NNFW_STATUS	nnfw_train_import_checkpoint (nnfw_session *session, const char *path)
	Import circle checkpoint.
NNFW_STATUS	nnfw_train_export_checkpoint (nnfw_session *session, const char *path)
	Export circle checkpoint.
NNFW_STATUS	nnfw_set_quantization_type (nnfw_session *session, NNFW_QUANTIZE_TYPE qtype)
	Set quantization type.
NNFW_STATUS	nnfw_set_quantized_model_path (nnfw_session *session, const char *path)
	Set exported quantized model path.
NNFW_STATUS	nnfw_quantize (nnfw_session *session)
	Quantize circle model.
NNFW_STATUS	nnfw_set_codegen_model_path (nnfw_session *session, const char *path)
	Set exported codegen model path.
NNFW_STATUS	nnfw_codegen (nnfw_session *session, const char *target, NNFW_CODEGEN_PREF pref)
	Generate target-dependent code.
NNFW_STATUS	nnfw_set_odc_param_minmax_records_count (nnfw_session *session, int minmax_records_count)
	Set MinMax records count in auto compilation mode with on-device compiler.
NNFW_STATUS	nnfw_odc_delete_minmax_file (nnfw_session *session)
	Delete MinMax file for on-device compiler.
NNFW_STATUS	nnfw_run_with_auto_compilation (nnfw_session *session, const char *target, NNFW_CODEGEN_PREF pref)
	Run inference with auto compilation.
NNFW_STATUS	nnfw_set_prepare_config (nnfw_session *session, const NNFW_PREPARE_CONFIG key, const char *value)
	Set prepare configuration.
NNFW_STATUS	nnfw_reset_prepare_config (nnfw_session *session)
	Reset prepare configurations.
NNFW_STATUS	nnfw_set_execute_config (nnfw_session *session, const NNFW_RUN_CONFIG key, const char *value)
	Set execution (run or train) configuration.
NNFW_STATUS	nnfw_reset_execute_config (nnfw_session *session)
	Reset execution (run or train) configurations.

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 51 of file nnfw_api.cc.

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

STATIC_ASSERT_ENUM_CHECK

#define STATIC_ASSERT_ENUM_CHECK	(		ENUM,
			VAL
	)		static_assert((ENUM) == (VAL), #ENUM " has changed")

Definition at line 25 of file nnfw_api.cc.

Function Documentation

nnfw_apply_tensorinfo()

NNFW_STATUS nnfw_apply_tensorinfo	(	nnfw_session *	session,
		uint32_t	index,
		nnfw_tensorinfo	tensor_info
	)

Apply i-th input's tensor info to resize input tensor.

This function should be called before nnfw_prepare is invoked, and should be called after nnfw_load_model_from_file is invoked See nnfw_prepare for information applying updated tensor info If this function is called many times for same index, tensor info is overwritten

Parameters

[in]	session	Session to the input tensor info is to be set
[in]	index	Index of input to be applied (0-indexed)
[in]	tensor_info	Tensor info to be applied

Returns

NNFW_STATUS_NO_ERROR if successful, otherwise return NNFW_STATUS_ERROR

Definition at line 155 of file nnfw_api.cc.

{
  return nnfw_session::deprecated("nnfw_apply_tensorinfo: Deprecated");
}

References nnfw_session::deprecated().

nnfw_await()

NNFW_STATUS nnfw_await

(

nnfw_session *

session

)

Wait for asynchronous run to finish.

This function must be called after calling nnfw_run_async, and can be called only once for a nnfw_run_async call.

When this function returns, it means that this session has finished the asynchronous run. Then the user can safely use the output data.

This function returns after the asynchronous inference is finished.

Parameters

[in]

session

The session to run inference

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 90 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->await();
}

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by NNFW_SESSION::wait().

nnfw_close_session()

NNFW_STATUS nnfw_close_session

(

nnfw_session *

session

)

Close a session instance.

After called, access to closed session by application will be invalid

Parameters

[in]

session

The session to be closed

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 60 of file nnfw_api.cc.

{
  delete session;
  return NNFW_STATUS_NO_ERROR;
}

References NNFW_STATUS_NO_ERROR.

Referenced by NNFW_SESSION::close_session(), and main().

nnfw_codegen()

NNFW_STATUS nnfw_codegen	(	nnfw_session *	session,
		const char *	target,
		NNFW_CODEGEN_PREF	pref
	)

Generate target-dependent code.

This function opens a dynamic shared object. It searches for the object as flollows ld.so(8) search rules. If the nnfw_set_codegen_model_path is not called before this function, the codegen model path is automatically defined and used using the same directory of the original model/package with the target backend extension.

Parameters

[in]	session	nnfw_session the session which contains information about compilation
[in]	target	Target backend to generate code This target string will be used to find a backend library. The name of target backend library should follow the following rules: 'lib' + {backend extension} + '-gen' + {lib extension} And the target string should be a name except 'lib' and {lib extension}. For example, if the backend extension is 'aaa', the backend library should be 'libaaa-gen.so', and the target string should be 'aaa-gen'.
[in]	pref	NNFW_CODEGEN_PREF

Returns

NNFW_STATUS_NO_ERROR if successful, otherwise return NNFW_STATUS_ERROR

Definition at line 347 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->codegen(target, pref);
}

References NNFW_RETURN_ERROR_IF_NULL.

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 58 of file nnfw_api.cc.

{ return nnfw_session::create(session); }

References nnfw_session::create().

Referenced by main(), and NNFW_SESSION::NNFW_SESSION().

nnfw_input_size()

NNFW_STATUS nnfw_input_size	(	nnfw_session *	session,
		uint32_t *	number
	)

Get the number of inputs.

Application can call this function to get number of inputs defined in loaded model. This function should be called after nnfw_load_model_from_file is invoked to load model

Parameters

[in]	session	Session from input information is to be extracted
[out]	number	Variable which the number of inputs is put into

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 110 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->input_size(number);
}

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by NNFW_SESSION::input_size().

nnfw_input_tensorindex()

NNFW_STATUS nnfw_input_tensorindex	(	nnfw_session *	session,
		const char *	tensorname,
		uint32_t *	index
	)

Get the input tensor index by name.

This function finds an input tensor of the given name. If found, the index value is set to the address that index points to, and returns NNFW_STATUS_NO_ERROR. Otherwise, index is unchanged and returns NNFW_STATUS_ERROR .

Note

If two or more input tensors are of the same name, the one with the lowest index is always returned.

Parameters

[in]	session	the session object
[in]	tensorname	the name of the tensor to find, a null terminated char pointer string
[out]	index	the index to be ret

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 197 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->input_tensorindex(tensorname, index);
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_input_tensorinfo()

NNFW_STATUS nnfw_input_tensorinfo	(	nnfw_session *	session,
		uint32_t	index,
		nnfw_tensorinfo *	tensor_info
	)

Get i-th input tensor info.

Before nnfw_prepare is invoked, this function return tensor info in model, so updated tensor info by nnfw_apply_tensorinfo is not returned.

After nnfw_prepare is invoked, this function return updated tensor info if tensor info is updated by nnfw_apply_tensorinfo.

Parameters

[in]	session	Session from input information is to be extracted
[in]	index	Index of input
[out]	tensor_info	Tensor info (shape, type, etc)

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 134 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->input_tensorinfo(index, tensor_info);
}

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by NNFW_SESSION::input_tensorinfo(), main(), and NNFW_SESSION::set_input().

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 66 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->load_model_from_path(path);
}

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by main(), and NNFW_SESSION::NNFW_SESSION().

nnfw_odc_delete_minmax_file()

NNFW_STATUS nnfw_odc_delete_minmax_file

(

nnfw_session *

session

)

Delete MinMax file for on-device compiler.

Parameters

[in]

session

nnfw_session

Returns

NNFW_STATUS_NO_ERROR if successful, otherwise return NNFW_STATUS_ERROR

Definition at line 359 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->delete_odc_minmax_file();
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_output_size()

NNFW_STATUS nnfw_output_size	(	nnfw_session *	session,
		uint32_t *	number
	)

Get the number of outputs.

Application can call this function to get number of outputs defined in loaded model. This function should be called after nnfw_load_model_from_file is invoked to load model

Parameters

[in]	session	Session from output information is to be extracted
[out]	number	Variable which the number of outputs is put into

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 116 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->output_size(number);
}

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by NNFW_SESSION::output_size().

nnfw_output_tensorindex()

NNFW_STATUS nnfw_output_tensorindex	(	nnfw_session *	session,
		const char *	tensorname,
		uint32_t *	index
	)

Get the input tensor index by name.

This function finds an input tensor of the given name. If found, the index value is set to the address that index points to, and returns NNFW_STATUS_NO_ERROR. Otherwise, index is unchanged and returns NNFW_STATUS_ERROR .

Note

If two or more input tensors are of the same name, the one with the lowest index is always returned.

Parameters

[in]	session	the session object
[in]	tensorname	the name of the tensor to find, a null terminated char pointer string
[out]	index	the index to be ret

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 203 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->output_tensorindex(tensorname, index);
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_output_tensorinfo()

NNFW_STATUS nnfw_output_tensorinfo	(	nnfw_session *	session,
		uint32_t	index,
		nnfw_tensorinfo *	tensor_info
	)

Get i-th output tensor info.

After nnfw_load_model_from_file and before nnfw_prepare is invoked, it returns tensor info in the model.

After nnfw_prepare and before nnfw_run is invoked, this function returns updated tensor info if tensor info is updated by nnfw_set_input_tensorinfo.

After nnfw_run is invoked(at least once), it returns the updated tensor info during the latest execution.

Parameters

[in]	session	Session from output information is to be extracted
[in]	index	Index of output
[out]	tensor_info	Tensor info (shape, type, etc)

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 141 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->output_tensorinfo(index, tensor_info);
}

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by main(), NNFW_SESSION::output_tensorinfo(), and NNFW_SESSION::set_output().

nnfw_pop_pipeline_output()

NNFW_STATUS nnfw_pop_pipeline_output	(	nnfw_session *	session,
		void *	outputs
	)

Get last outputs of partitioned model in session.

This function must be called after nnfw_prepare_pipeline, outputs given to this function must be cleared for memory management.

Parameters

[in]	session	Session from last outputs is to be extracted
[out]	outputs	Raw buffer for outputs, it must be std::vector<void *> type pointer for multiple output model

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 225 of file nnfw_api.cc.

{
  return nnfw_session::deprecated("nnfw_pop_pipeline_output: Deprecated");
}

References nnfw_session::deprecated().

nnfw_prepare()

NNFW_STATUS nnfw_prepare

(

nnfw_session *

session

)

Prepare session to be ready for inference.

This phase may finalize model compilation, scheduling, and additional settings. If nnfw_apply_tensorinfo is called to apply input tensor info different with model before this function, tries to resize all tensors.

Parameters

[in]

session

the session to be prepared

Returns

NNFW_STATUS_NO_ERROR if successful, otherwise return NNFW_STATUS_ERROR

Definition at line 72 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->prepare();
}

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by main(), and NNFW_SESSION::NNFW_SESSION().

nnfw_prepare_pipeline()

NNFW_STATUS nnfw_prepare_pipeline	(	nnfw_session *	session,
		const char *	map_file_path = nullptr
	)

Prepare session to be ready for inference.

This phase may finalize model compilation, scheduling, and additional settings.

Parameters

session

the session to be prepared

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 215 of file nnfw_api.cc.

{
  return nnfw_session::deprecated("nnfw_prepare_pipeline: Deprecated");
}

References nnfw_session::deprecated().

nnfw_push_pipeline_input()

NNFW_STATUS nnfw_push_pipeline_input	(	nnfw_session *	session,
		void *	inputs,
		void *	lengths
	)

Set input buffer.

This function must be called after nnfw_prepare_pipeline, inputs given to this function can be reused for many inferences. lengths must be greater or equal than the operand requires. if you give empty inputs to this function, then this function will join all threads.

Parameters

[in]	session	Session to the input is to be set
[in]	inputs	Raw buffers for input, it must be std::vector<void *> type pointer for multiple input model
[in]	lengths	Size of bytes of input buffers, it must be std::vector<uint32_t> type pointer for multiple input model

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 220 of file nnfw_api.cc.

{
  return nnfw_session::deprecated("nnfw_push_pipeline_input: Deprecated");
}

References nnfw_session::deprecated().

nnfw_quantize()

NNFW_STATUS nnfw_quantize

(

nnfw_session *

session

)

Quantize circle model.

Parameters

[in]

session

nnfw_session to quantize

Returns

ODC_STATUS_NO_ERROR if successful, otherwise return ODC_STATUS_ERROR

Definition at line 335 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->quantize();
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_query_info_u32()

NNFW_STATUS nnfw_query_info_u32	(	nnfw_session *	session,
		NNFW_INFO_ID	id,
		uint32_t *	val
	)

Retrieve uint32 type of nnfw information for given information ID.

Retrieves the information of property given by information id

Note

: The input session could be null for global information (e.g. runtime version).*

Parameters

[in]	session	session to be queried on.
[in]	id	ID to be queried
[out]	val	uint32 value to be returned.

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 178 of file nnfw_api.cc.

{
  (void)session;
  switch (id)
  {
    case NNFW_INFO_ID_VERSION:
      if (val)
      {
        *val = NNFW_VERSION;
        return NNFW_STATUS_NO_ERROR;
      }
      break;
    default:
      return NNFW_STATUS_ERROR;
  }
  // It should not be reached.
  return NNFW_STATUS_ERROR;
}

References NNFW_INFO_ID_VERSION, NNFW_STATUS_ERROR, NNFW_STATUS_NO_ERROR, and NNFW_VERSION.

nnfw_register_custom_op_info()

NNFW_STATUS nnfw_register_custom_op_info	(	nnfw_session *	session,
		const char *	id,
		custom_kernel_registration_info *	info
	)

Definition at line 148 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->register_custom_operation(id, info->eval_function);
}

References info, and NNFW_RETURN_ERROR_IF_NULL.

nnfw_reset_execute_config()

NNFW_STATUS nnfw_reset_execute_config

(

nnfw_session *

session

)

Reset execution (run or train) configurations.

This function reset all execution configuration.

Parameters

[in]

session

nnfw_session to reset all execution configurations

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 394 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->reset_execute_config();
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_reset_prepare_config()

NNFW_STATUS nnfw_reset_prepare_config

(

nnfw_session *

session

)

Reset prepare configurations.

This function reset all prepare configuration.

Parameters

[in]

session

nnfw_session to reset all prepare configurations

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 381 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->reset_prepare_config();
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_run()

NNFW_STATUS nnfw_run

(

nnfw_session *

session

)

Run inference.

This function should be called after model is loaded by nnfw_load_model_from_file, session is prepared for inference by nnfw_prepare, set input and output buffers by nnfw_set_input and nnfw_set_output.

This function return after inference is finished.

Parameters

[in]

session

The session to run inference

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 78 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->run();
}

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by main(), and NNFW_SESSION::run().

nnfw_run_async()

NNFW_STATUS nnfw_run_async

(

nnfw_session *

session

)

Run inference asynchronously.

This function must be called after model is loaded by nnfw_load_model_from_file, session is prepared for inference by nnfw_prepare, set input and output buffers by nnfw_set_input and nnfw_set_output.

This function returns immediately after starting a thread to run the inference. To get the result of it or to do the next inference with nnfw_run or nnfw_run_async, nnfw_await must be called to ensure the current asynchronous inference has finished. Only one asynchronous inference is allowed at a time for a session. If this function is called while the previous one is still running, it returns an error.

Parameters

[in]

session

The session to run inference

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 84 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->run_async();
}

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by NNFW_SESSION::run_async().

nnfw_run_with_auto_compilation()

NNFW_STATUS nnfw_run_with_auto_compilation	(	nnfw_session *	session,
		const char *	target,
		NNFW_CODEGEN_PREF	pref
	)

Run inference with auto compilation.

This function runs inference with automatic compilation and replaces the original model with a quantized or compiled model inside. During the inference the minmax statistics is collected and after that quantization is performed. If quantization was successful, try to code generating for target backend, otherwise run original float model. If compilation was successful, run compiled model, otherwise run quantized model. On-device compiler (ODC) provides quantization and compilation functionality. Function should be called after model is loaded by nnfw_load_model_from_file, session is prepared for inference by nnfw_prepare, set input and output buffers by nnfw_set_input and nnfw_set_output.

Additionally the following parameters should be set up :

1. Quantization type nnfw_set_quantization_type
2. Quantizated model path nnfw_set_quantized_model_path
3. Minmax records threshold for quantization nnfw_set_odc_param_minmax_records_count

1. File with minMax statistics can be removed by nnfw_odc_delete_minmax_file
2. Compiled model path nnfw_set_codegen_model_path

Parameters

[in]	session	nnfw_session
[in]	target	Target backend to generate code as in nnfw_codegen
[in]	pref	NNFW_CODEGEN_PREF

Returns

NNFW_STATUS_NO_ERROR if successful, otherwise return NNFW_STATUS_ERROR

Definition at line 365 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->run_with_auto_compilation(target, pref);
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_set_available_backends()

NNFW_STATUS nnfw_set_available_backends	(	nnfw_session *	session,
		const char *	backends
	)

Set available backends.

This function should be called before nnfw_prepare is invoked.

Supported backends differs on each platforms. For example, x86_64 supports "cpu" only. Multiple backends can be set and they must be separated by a semicolon (ex: "acl_cl;cpu"). For each backend string, libbackend_{backend}.so will be dynamically loaded during nnfw_prepare. Among the multiple backends, the 1st element is used as the default backend.

Parameters

[in]	session	session to which avilable backends are set
[in]	backends	available backends on which nnfw uses

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 167 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->set_available_backends(backends);
}

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by NNFW_SESSION::NNFW_SESSION().

nnfw_set_backends_per_operation()

NNFW_STATUS nnfw_set_backends_per_operation	(	nnfw_session *	session,
		const char *	backend_settings
	)

Set the backend for each operation in the session.

This function assigns backends (acl_cl, acl_neon, cpu) to each operation in the session. If successful,the function returns NNFW_STATUS_NO_ERROR. Otherwise, the function returns NNFW_STATUS_ERROR.

Note

The argument specifying backends must be in the format "OP_BACKEND_MAP=\"0=acl_cl;1=cpu;2=acl_cl\"".

Parameters

[in]	session	the session object
[in]	backend_settings	String containing backend assignments indexed by operation sequence

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 209 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->set_backends_per_operation(backend_settings);
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_set_codegen_model_path()

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

Set exported codegen model path.

This function should be called before nnfw_codegen is invoked.

Parameters

[in]	session	nnfw_session to set codegen model path
[in]	path	Target-dependent model path

Returns

NNFW_STATUS_NO_ERROR if successful, otherwise return NNFW_STATUS_ERROR

Definition at line 341 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->set_codegen_model_path(path);
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_set_execute_config()

NNFW_STATUS nnfw_set_execute_config	(	nnfw_session *	session,
		const NNFW_RUN_CONFIG	key,
		const char *	value
	)

Set execution (run or train) configuration.

This function set execution configuration to dump execution data to workspace. If you enable configuration to dump execution data into workspace and want to change workspace, refer nnfw_set_workspace to use workspace directory.

Parameters

[in]	session	nnfw_session to set execution configuration
[in]	key	execution configuration key
[in]	value	execution configuration value if needed, otherwise set NULL

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 387 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->set_execute_config(key, value);
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_set_input()

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

Set input buffer.

This function must be called after nnfw_prepare, buffer given to this function can be reused for many inferences. length must be greater or equal than the operand requires. To specify an optional input, you can either not call this for that input or call this with buffer of NULL and length of 0. If you set NNFW_TYPE_TENSOR_FLOAT32 type and model has quantized input type on given index, runtime will set quantized data type model input by converting from float buffer data internally.

Parameters

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

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 96 of file nnfw_api.cc.

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

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by main(), and NNFW_SESSION::set_input().

nnfw_set_input_layout()

NNFW_STATUS nnfw_set_input_layout	(	nnfw_session *	session,
		uint32_t	index,
		NNFW_LAYOUT	layout
	)

Set the layout of an input.

The input that does not call this has NNFW_LAYOUT_NHWC layout

Parameters

[in]	session	session from inference input is to be extracted
[in]	index	index of input to be set (0-indexed)
[in]	layout	layout to set to target input

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 122 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->set_input_layout(index, layout);
}

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by NNFW_SESSION::set_input_layout().

nnfw_set_input_tensorinfo()

NNFW_STATUS nnfw_set_input_tensorinfo	(	nnfw_session *	session,
		uint32_t	index,
		const nnfw_tensorinfo *	tensor_info
	)

Set input model's tensor info for resizing.

This function can be called at any time after calling nnfw_load_model_from_file. Changing input tensor's shape will cause shape inference for the model. There are two different types of shape inference - static and dynamic. Which one to use is depend on the current state of the session. When it is called after calling nnfw_load_model_from_file and before calling nnfw_prepare, this info will be used when nnfw_prepare. And it will perform static shape inference for all tensors. When it is called after calling nnfw_prepare or even after nnfw_run, this info will be used when nnfw_run. And the shapes of the tensors are determined on the fly. If this function is called many times for the same index, it is overwritten. tensor_info's dtype field is ignored.

Parameters

[in]	session	Session to the input tensor info is to be set
[in]	index	Index of input to be set (0-indexed)
[in]	tensor_info	Tensor info to be set

Returns

NNFW_STATUS_NO_ERROR if successful, otherwise return NNFW_STATUS_ERROR

Definition at line 160 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->set_input_tensorinfo(index, tensor_info);
}

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by NNFW_SESSION::set_input_tensorinfo().

nnfw_set_odc_param_minmax_records_count()

NNFW_STATUS nnfw_set_odc_param_minmax_records_count	(	nnfw_session *	session,
		int	minmax_records_count
	)

Set MinMax records count in auto compilation mode with on-device compiler.

This function set MinMax records count for quantization in auto compilation mode. To enable automatic compilation mode, use nnfw_run_with_auto_compilation

Parameters

[in]	session	nnfw_session
[in]	minmax_records_count	minmax records count

Returns

NNFW_STATUS_NO_ERROR if successful, otherwise return NNFW_STATUS_ERROR

Definition at line 353 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->set_odc_param_minmax_records_count(minmax_records_count);
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_set_op_backend()

NNFW_STATUS nnfw_set_op_backend	(	nnfw_session *	session,
		const char *	op,
		const char *	backend
	)

Set the operation's backend.

This function should be called before nnfw_prepare is invoked.

The backend for op has higher priority than available backends specified by nnfw_set_available_backends.

Parameters

[in]	session	session to be modified
[in]	op	operation to be set
[in]	backend	bakcend on which operation run

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 173 of file nnfw_api.cc.

{
  return nnfw_session::deprecated("nnfw_set_op_backend: Deprecated");
}

References nnfw_session::deprecated().

Referenced by main().

nnfw_set_output()

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

Set output buffer.

This function must be called after nnfw_prepare, buffer given to this function can be reused for many inferences. 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. If you set NNFW_TYPE_TENSOR_FLOAT32 type and model has quantized output type on given index, runtime will set dequantized float buffer data from quantize data type model output internally.

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 103 of file nnfw_api.cc.

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

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by main(), and NNFW_SESSION::set_output().

nnfw_set_output_layout()

NNFW_STATUS nnfw_set_output_layout	(	nnfw_session *	session,
		uint32_t	index,
		NNFW_LAYOUT	layout
	)

Set the layout of an output.

The output that does not call this has NNFW_LAYOUT_NHWC layout

Parameters

[in]	session	session from inference output is to be extracted
[in]	index	index of output to be set (0-indexed)
[in]	layout	layout to set to target output

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 128 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->set_output_layout(index, layout);
}

References NNFW_RETURN_ERROR_IF_NULL.

Referenced by NNFW_SESSION::set_output_layout().

nnfw_set_prepare_config()

NNFW_STATUS nnfw_set_prepare_config	(	nnfw_session *	session,
		NNFW_PREPARE_CONFIG	key,
		const char *	value
	)

Set prepare configuration.

This function set prepare configuration to decide additional compiling and scheduing feature. If you enable configuration to prepare dumping execution data into workspace, refer nnfw_set_workspace to use workspace directory.

Parameters

[in]	session	nnfw_session to set prepare configuration
[in]	key	prepare configuration key
[in]	value	prepare configuration value

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 374 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->set_prepare_config(key, value);
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_set_quantization_type()

NNFW_STATUS nnfw_set_quantization_type	(	nnfw_session *	session,
		NNFW_QUANTIZE_TYPE	qtype
	)

Set quantization type.

This function should be called before nnfw_quantize is invoked.

Parameters

[in]	session	nnfw_session to set quantization type
[in]	pref	NNFW_QUANTIZE_TYPE

Returns

NNFW_STATUS_NO_ERROR if successful, NNFW_STATUS_UNEXPECTED_NULL if session is null, otherwise return NNFW_STATUS_ERROR

Definition at line 323 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->set_quantization_type(qtype);
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_set_quantized_model_path()

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

Set exported quantized model path.

This function should be called before nnfw_quantize is invoked.

TODO: If this function is not called, quantized model will not be exported

Parameters

[in]	session	nnfw_session to set quantized model path
[in]	path	Quantized model path

Returns

NNFW_STATUS_NO_ERROR if successful, otherwise return NNFW_STATUS_ERROR

Definition at line 329 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->set_quantized_model_path(path);
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_set_workspace()

NNFW_STATUS nnfw_set_workspace	(	nnfw_session *	session,
		const char *	dir
	)

Set runtime's workspace directory.

This function sets the directory to be used as a workspace. System should allow read and write access to the directory for the runtime. Default workspace is running directory of the application. This function should be called before nnfw_load_model_from_file is invoked.

Parameters

[in]	session	session to be queried on.
[in]	dir	workspace directory path

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 230 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->set_workspace(dir);
}

References NNFW_RETURN_ERROR_IF_NULL.

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 291 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->train_run(update_weights);
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_train_expected_tensorinfo()

NNFW_STATUS nnfw_train_expected_tensorinfo	(	nnfw_session *	session,
		uint32_t	index,
		nnfw_tensorinfo *	info
	)

Get the training model expected output information.

Note

This function should be called after nnfw_train_prepare

Parameters

[in]	session	The session to get the training model expected output information
[in]	index	The index of training model expected output
[out]	info	The shape and type of training model expected output

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 263 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->train_expected_tensorinfo(index, info);
}

References info, and NNFW_RETURN_ERROR_IF_NULL.

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 315 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->train_export_checkpoint(path);
}

References NNFW_RETURN_ERROR_IF_NULL.

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 303 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->train_export_circle(path);
}

References NNFW_RETURN_ERROR_IF_NULL.

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 297 of file nnfw_api.cc.

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

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_train_get_traininfo()

NNFW_STATUS nnfw_train_get_traininfo	(	nnfw_session *	session,
		nnfw_train_info *	info
	)

Get training information.

Note

This function should be called after calling nnfw_load_model_from_file

   For the field which is not set in training information, it returns training information
   filled with default value. The default value of each field is as follows :
   learning_rate = 0.0f, batch_size = 0, *_UNDEF for other enums

Parameters

[in]	session	The session to get training information
[out]	info	Training information

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 238 of file nnfw_api.cc.

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

References info, and NNFW_RETURN_ERROR_IF_NULL.

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 309 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->train_import_checkpoint(path);
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_train_input_tensorinfo()

NNFW_STATUS nnfw_train_input_tensorinfo	(	nnfw_session *	session,
		uint32_t	index,
		nnfw_tensorinfo *	info
	)

Get the training model input information.

Note

This function should be called after nnfw_train_prepare

Parameters

[in]	session	The session to get the training model input information
[in]	index	The index of training model input
[out]	info	The shape and type of training model input

Returns

NNFW_STATUS_NO_ERROR if successful

Definition at line 256 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->train_input_tensorinfo(index, info);
}

References info, and NNFW_RETURN_ERROR_IF_NULL.

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 250 of file nnfw_api.cc.

{
  NNFW_RETURN_ERROR_IF_NULL(session);
  return session->train_prepare();
}

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_train_set_expected()

NNFW_STATUS nnfw_train_set_expected	(	nnfw_session *	session,
		uint32_t	index,
		const 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 277 of file nnfw_api.cc.

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

References NNFW_RETURN_ERROR_IF_NULL.

nnfw_train_set_input()

NNFW_STATUS nnfw_train_set_input	(	nnfw_session *	session,
		uint32_t	index,
		const 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 270 of file nnfw_api.cc.

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

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 284 of file nnfw_api.cc.

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

References NNFW_RETURN_ERROR_IF_NULL.

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 244 of file nnfw_api.cc.

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

References info, and NNFW_RETURN_ERROR_IF_NULL.

STATIC_ASSERT_ENUM_CHECK() [1/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_INFO_ID_VERSION	,
		0
	)

STATIC_ASSERT_ENUM_CHECK() [2/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_LAYOUT_CHANNELS_FIRST	,
		2
	)

STATIC_ASSERT_ENUM_CHECK() [3/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_LAYOUT_CHANNELS_LAST	,
		1
	)

STATIC_ASSERT_ENUM_CHECK() [4/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_LAYOUT_NONE	,
		0
	)

STATIC_ASSERT_ENUM_CHECK() [5/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_STATUS_ERROR	,
		1
	)

STATIC_ASSERT_ENUM_CHECK() [6/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_STATUS_INSUFFICIENT_OUTPUT_SIZE	,
		5
	)

STATIC_ASSERT_ENUM_CHECK() [7/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_STATUS_INVALID_STATE	,
		3
	)

STATIC_ASSERT_ENUM_CHECK() [8/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_STATUS_NO_ERROR	,
		0
	)

STATIC_ASSERT_ENUM_CHECK() [9/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_STATUS_OUT_OF_MEMORY	,
		4
	)

STATIC_ASSERT_ENUM_CHECK() [10/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_STATUS_UNEXPECTED_NULL	,
		2
	)

STATIC_ASSERT_ENUM_CHECK() [11/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_TYPE_TENSOR_BOOL	,
		3
	)

STATIC_ASSERT_ENUM_CHECK() [12/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_TYPE_TENSOR_FLOAT32	,
		0
	)

STATIC_ASSERT_ENUM_CHECK() [13/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_TYPE_TENSOR_INT32	,
		1
	)

STATIC_ASSERT_ENUM_CHECK() [14/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_TYPE_TENSOR_INT64	,
		5
	)

STATIC_ASSERT_ENUM_CHECK() [15/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_TYPE_TENSOR_QUANT16_SYMM_SIGNED	,
		7
	)

STATIC_ASSERT_ENUM_CHECK() [16/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_TYPE_TENSOR_QUANT8_ASYMM	,
		2
	)

STATIC_ASSERT_ENUM_CHECK() [17/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_TYPE_TENSOR_QUANT8_ASYMM_SIGNED	,
		6
	)

STATIC_ASSERT_ENUM_CHECK() [18/18]

STATIC_ASSERT_ENUM_CHECK	(	NNFW_TYPE_TENSOR_UINT8	,
		4
	)