dnn_backend_common.h File Reference

#include "queue.h"
#include "../dnn_interface.h"
#include "libavutil/thread.h"

Go to the source code of this file.

Data Structures
struct	TaskItem
struct	LastLevelTaskItem
struct	DNNAsyncExecModule
	Common Async Execution Mechanism for the DNN Backends. More...

Macros
#define	DNN_BACKEND_COMMON_OPTIONS

Functions
int	ff_check_exec_params (void *ctx, DNNBackendType backend, DNNFunctionType func_type, DNNExecBaseParams *exec_params)
DNNReturnType	ff_dnn_fill_task (TaskItem *task, DNNExecBaseParams *exec_params, void *backend_model, int async, int do_ioproc)
	Fill the Task for Backend Execution. More...
DNNReturnType	ff_dnn_async_module_cleanup (DNNAsyncExecModule *async_module)
	Join the Async Execution thread and set module pointers to NULL. More...
DNNReturnType	ff_dnn_start_inference_async (void *ctx, DNNAsyncExecModule *async_module)
	Start asynchronous inference routine for the TensorFlow model on a detached thread. More...
DNNAsyncStatusType	ff_dnn_get_result_common (Queue *task_queue, AVFrame **in, AVFrame **out)
	Extract input and output frame from the Task Queue after asynchronous inference. More...
DNNReturnType	ff_dnn_fill_gettingoutput_task (TaskItem *task, DNNExecBaseParams *exec_params, void *backend_model, int input_height, int input_width, void *ctx)
	Allocate input and output frames and fill the Task with execution parameters. More...

Detailed Description

DNN common functions different backends.

Definition in file dnn_backend_common.h.

Macro Definition Documentation

DNN_BACKEND_COMMON_OPTIONS

#define DNN_BACKEND_COMMON_OPTIONS

Value:

    { "nireq",           "number of request",             OFFSET(options.nireq),           AV_OPT_TYPE_INT,    { .i64 = 0 },     0, INT_MAX, FLAGS }, \
    { "async",           "use DNN async inference",       OFFSET(options.async),           AV_OPT_TYPE_BOOL,   { .i64 = 1 },     0,       1, FLAGS },

Definition at line 31 of file dnn_backend_common.h.

Function Documentation

ff_check_exec_params()

int ff_check_exec_params	(	void *	ctx,
		DNNBackendType	backend,
		DNNFunctionType	func_type,
		DNNExecBaseParams *	exec_params
	)

Definition at line 29 of file dnn_backend_common.c.

Referenced by ff_dnn_execute_model_native(), ff_dnn_execute_model_ov(), and ff_dnn_execute_model_tf().

ff_dnn_fill_task()

DNNReturnType ff_dnn_fill_task	(	TaskItem *	task,
		DNNExecBaseParams *	exec_params,
		void *	backend_model,
		int	async,
		int	do_ioproc
	)

Fill the Task for Backend Execution.

It should be called after checking execution parameters using ff_check_exec_params.

Parameters

task	pointer to the allocated task
exec_param	pointer to execution parameters
backend_model	void pointer to the backend model
async	flag for async execution. Must be 0 or 1
do_ioproc	flag for IO processing. Must be 0 or 1

Return values

DNN_SUCCESS	if successful
DNN_ERROR	if flags are invalid or any parameter is NULL

Definition at line 56 of file dnn_backend_common.c.

Referenced by ff_dnn_execute_model_native(), ff_dnn_execute_model_ov(), ff_dnn_execute_model_tf(), and ff_dnn_fill_gettingoutput_task().

ff_dnn_async_module_cleanup()

DNNReturnType ff_dnn_async_module_cleanup

(

DNNAsyncExecModule *

async_module

)

Join the Async Execution thread and set module pointers to NULL.

Parameters

async_module

pointer to DNNAsyncExecModule module

Return values

DNN_SUCCESS	if successful
DNN_ERROR	if async_module is NULL

Definition at line 92 of file dnn_backend_common.c.

Referenced by destroy_request_item().

ff_dnn_start_inference_async()

DNNReturnType ff_dnn_start_inference_async	(	void *	ctx,
		DNNAsyncExecModule *	async_module
	)

Start asynchronous inference routine for the TensorFlow model on a detached thread.

It calls the completion callback after the inference completes. Completion callback and inference function must be set before calling this function.

If POSIX threads aren't supported, the execution rolls back to synchronous mode, calling completion callback after inference.

Parameters

ctx	pointer to the backend context
async_module	pointer to DNNAsyncExecModule module

Return values

DNN_SUCCESS	on the start of async inference.
DNN_ERROR	in case async inference cannot be started

Definition at line 111 of file dnn_backend_common.c.

Referenced by execute_model_tf(), and ff_dnn_flush_tf().

ff_dnn_get_result_common()

DNNAsyncStatusType ff_dnn_get_result_common	(	Queue *	task_queue,
		AVFrame **	in,
		AVFrame **	out
	)

Extract input and output frame from the Task Queue after asynchronous inference.

Parameters

task_queue	pointer to the task queue of the backend
in	double pointer to the input frame
out	double pointer to the output frame

Return values

DAST_EMPTY_QUEUE	if task queue is empty
DAST_NOT_READY	if inference not completed yet.
DAST_SUCCESS	if result successfully extracted

Definition at line 141 of file dnn_backend_common.c.

Referenced by ff_dnn_get_result_native(), ff_dnn_get_result_ov(), and ff_dnn_get_result_tf().

ff_dnn_fill_gettingoutput_task()

DNNReturnType ff_dnn_fill_gettingoutput_task	(	TaskItem *	task,
		DNNExecBaseParams *	exec_params,
		void *	backend_model,
		int	input_height,
		int	input_width,
		void *	ctx
	)

Allocate input and output frames and fill the Task with execution parameters.

Parameters

task	pointer to the allocated task
exec_params	pointer to execution parameters
backend_model	void pointer to the backend model
input_height	height of input frame
input_width	width of input frame
ctx	pointer to the backend context

Return values

DNN_SUCCESS	if successful
DNN_ERROR	if allocation fails

Definition at line 161 of file dnn_backend_common.c.

Referenced by get_output_native(), get_output_ov(), and get_output_tf().