network.cpp File Reference

Include dependency graph for network.cpp:

Functions
void	backward_network (network net, Darknet::NetworkState state)
void	calculate_binary_weights (network net)
network	combine_train_valid_networks (network net_train, network net_map)
void	compare_networks (network n1, network n2, data test)
void	copy_cudnn_descriptors (const Darknet::Layer &src, Darknet::Layer *dst)
void	copy_weights_net (network net_train, network *net_map)
void	custom_get_region_detections (const Darknet::Layer &l, int w, int h, int net_w, int net_h, float thresh, int *map, float hier, int relative, detection *dets, int letter)
char *	detection_to_json (detection *dets, int nboxes, int classes, char **names, long long int frame_id, char *filename)
void	ema_apply (network net)
void	ema_update (network net, float ema_alpha)
void	fill_network_boxes (network *net, int w, int h, float thresh, float hier, int *map, int relative, detection *dets, int letter)
void	fill_network_boxes_batch (network *net, int w, int h, float thresh, float hier, int *map, int relative, detection *dets, int letter, int batch)
void	fill_network_boxes_v3 (network *net, int w, int h, float thresh, float hier, int *map, int relative, detection *dets, int letter, Darknet::Output_Object_Cache &cache)
void	forward_blank_layer (Darknet::Layer &l, Darknet::NetworkState state)
void	forward_network (network net, Darknet::NetworkState state)
void	free_batch_detections (det_num_pair *det_num_pairs, int n)
void	free_detections (detection *dets, int n)
void	free_network (network net)
void	free_network_ptr (network *net)
void	free_network_recurrent_state (network net)
void	fuse_conv_batchnorm (network net)
int	get_current_batch (network net)
int64_t	get_current_iteration (network net)
float	get_current_rate (network net)
float	get_current_seq_subdivisions (network net)
detection *	get_network_boxes (network *net, int w, int h, float thresh, float hier, int *map, int relative, int *num, int letter)
float	get_network_cost (network net)
Darknet::Image	get_network_image (network net)
Darknet::Image	get_network_image_layer (network net, int i)
int	get_network_input_size (network net)
Darknet::Layer *	get_network_layer (network *net, int i)
float *	get_network_output (network net)
int	get_network_output_size (network net)
int	get_predicted_class_network (network net)
int	get_sequence_value (network net)
int	is_ema_initialized (network net)
static float	lrelu (float src)
network	make_network (int n)
detection *	make_network_boxes (network *net, float thresh, int *num)
detection *	make_network_boxes_batch (network *net, float thresh, int *num, int batch)
detection *	make_network_boxes_v3 (network *net, const float thresh, int *num, Darknet::Output_Object_Cache &cache)
float *	network_accuracies (network net, data d, int n)
float	network_accuracy (network net, data d)
float	network_accuracy_multi (network net, data d, int n)
int	network_height (network *net)
float *	network_predict (network net, float *input)
det_num_pair *	network_predict_batch (network *net, Darknet::Image im, int batch_size, int w, int h, float thresh, float hier, int *map, int relative, int letter)
matrix	network_predict_data (network net, data test)
matrix	network_predict_data_multi (network net, data test, int n)
float *	network_predict_image (network *net, Darknet::Image im)
float *	network_predict_image_letterbox (network *net, Darknet::Image im)
float *	network_predict_ptr (network *net, float *input)
int	network_width (network *net)
int	num_detections (network *net, float thresh)
int	num_detections_batch (network *net, float thresh, int batch)
int	num_detections_v3 (network *net, float thresh, Darknet::Output_Object_Cache &cache)
void	print_network (network net)
void	randomize_network_recurrent_state (network net)
int	recalculate_workspace_size (network *net)
void	reject_similar_weights (network net, float sim_threshold)
void	remember_network_recurrent_state (network net)
void	reset_network_state (network *net, int b)
void	reset_rnn (network *net)
int	resize_network (network *net, int w, int h)
void	restore_network_recurrent_state (network net)
void	set_batch_network (network *net, int b)
void	top_predictions (network net, int k, int *index)
float	train_network (network net, data d)
float	train_network_batch (network net, data d, int n)
float	train_network_datum (network net, float *x, float *y)
float	train_network_waitkey (network net, data d, int wait_key)
void	update_network (network net)
void	visualize_network (network net)

Function Documentation

backward_network()

void backward_network	(	network	net,
		Darknet::NetworkState	state
	)

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calculate_binary_weights()

void calculate_binary_weights

(

network

net

)

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combine_train_valid_networks()

network combine_train_valid_networks	(	network	net_train,
		network	net_map
	)

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compare_networks()

void compare_networks	(	network	n1,
		network	n2,
		data	test
	)

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copy_cudnn_descriptors()

void copy_cudnn_descriptors	(	const Darknet::Layer &	src,
		Darknet::Layer *	dst
	)

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copy_weights_net()

void copy_weights_net	(	network	net_train,
		network *	net_map
	)

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custom_get_region_detections()

void custom_get_region_detections	(	const Darknet::Layer &	l,
		int	w,
		int	h,
		int	net_w,
		int	net_h,
		float	thresh,
		int *	map,
		float	hier,
		int	relative,
		detection *	dets,
		int	letter
	)

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detection_to_json()

char * detection_to_json	(	detection *	dets,
		int	nboxes,
		int	classes,
		char **	names,
		long long int	frame_id,
		char *	filename
	)

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ema_apply()

void ema_apply

(

network

net

)

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ema_update()

void ema_update	(	network	net,
		float	ema_alpha
	)

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fill_network_boxes()

void fill_network_boxes	(	network *	net,
		int	w,
		int	h,
		float	thresh,
		float	hier,
		int *	map,
		int	relative,
		detection *	dets,
		int	letter
	)

Todo:

V3 JAZZ 845 milliseconds

Todo:

V3 JAZZ 830 milliseconds: most of the time is spent in this function

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fill_network_boxes_batch()

void fill_network_boxes_batch	(	network *	net,
		int	w,
		int	h,
		float	thresh,
		float	hier,
		int *	map,
		int	relative,
		detection *	dets,
		int	letter,
		int	batch
	)

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fill_network_boxes_v3()

void fill_network_boxes_v3	(	network *	net,
		int	w,
		int	h,
		float	thresh,
		float	hier,
		int *	map,
		int	relative,
		detection *	dets,
		int	letter,
		Darknet::Output_Object_Cache &	cache
	)

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V3 JAZZ 79 milliseconds

Todo:

This assumes that "GAUSSIAN_YOLO", "REGION", and "DETECTION" layers don't exist, which is wrong. But they only exist in much older configurations which are hopefully not used anymore? Should we deprecate these?

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forward_blank_layer()

void forward_blank_layer	(	Darknet::Layer &	l,
		Darknet::NetworkState	state
	)

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forward_network()

void forward_network	(	network	net,
		Darknet::NetworkState	state
	)

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free_batch_detections()

void free_batch_detections	(	det_num_pair *	det_num_pairs,
		int	n
	)

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free_detections()

void free_detections	(	detection *	dets,
		int	n
	)

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free_network()

void free_network

(

network

net

)

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free_network_ptr()

void free_network_ptr

(

network *

net

)

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free_network_recurrent_state()

void free_network_recurrent_state

(

network

net

)

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fuse_conv_batchnorm()

void fuse_conv_batchnorm

(

network

net

)

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get_current_batch()

int get_current_batch

(

network

net

)

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get_current_iteration()

int64_t get_current_iteration

(

network

net

)

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get_current_rate()

float get_current_rate

(

network

net

)

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get_current_seq_subdivisions()

float get_current_seq_subdivisions

(

network

net

)

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get_network_boxes()

detection * get_network_boxes	(	network *	net,
		int	w,
		int	h,
		float	thresh,
		float	hier,
		int *	map,
		int	relative,
		int *	num,
		int	letter
	)

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V3 JAZZ 808 milliseconds

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get_network_cost()

float get_network_cost

(

network

net

)

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get_network_image()

Darknet::Image get_network_image

(

network

net

)

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get_network_image_layer()

Darknet::Image get_network_image_layer	(	network	net,
		int	i
	)

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get_network_input_size()

int get_network_input_size

(

network

net

)

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get_network_layer()

Darknet::Layer * get_network_layer	(	network *	net,
		int	i
	)

get_network_output()

float * get_network_output

(

network

net

)

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get_network_output_size()

int get_network_output_size

(

network

net

)

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get_predicted_class_network()

int get_predicted_class_network

(

network

net

)

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get_sequence_value()

int get_sequence_value

(

network

net

)

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is_ema_initialized()

int is_ema_initialized

(

network

net

)

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lrelu()

static float lrelu ( float  src )

static

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make_network()

network make_network

(

int

n

)

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make_network_boxes()

detection * make_network_boxes	(	network *	net,
		float	thresh,
		int *	num
	)

See also

make_network_boxes_batch()

Todo:

V3 JAZZ 766 milliseconds

Todo:

V3 JAZZ 740 milliseconds – this is where we spend all our time

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make_network_boxes_batch()

detection * make_network_boxes_batch	(	network *	net,
		float	thresh,
		int *	num,
		int	batch
	)

See also

make_network_boxes()

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make_network_boxes_v3()

detection * make_network_boxes_v3	(	network *	net,
		const float	thresh,
		int *	num,
		Darknet::Output_Object_Cache &	cache
	)

Todo:

V3 JAZZ 718 milliseconds

Todo:

Is anything but YOLO still used as an output layer in a modern .cfg file? Should these be removed?

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V3 JAZZ 694 milliseconds meaning 97% of this function is spent in this next line

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network_accuracies()

float * network_accuracies	(	network	net,
		data	d,
		int	n
	)

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network_accuracy()

float network_accuracy	(	network	net,
		data	d
	)

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network_accuracy_multi()

float network_accuracy_multi	(	network	net,
		data	d,
		int	n
	)

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network_height()

int network_height

(

network *

net

)

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network_predict()

float * network_predict	(	network	net,
		float *	input
	)

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network_predict_batch()

det_num_pair * network_predict_batch	(	network *	net,
		Darknet::Image	im,
		int	batch_size,
		int	w,
		int	h,
		float	thresh,
		float	hier,
		int *	map,
		int	relative,
		int	letter
	)

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network_predict_data()

matrix network_predict_data	(	network	net,
		data	test
	)

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network_predict_data_multi()

matrix network_predict_data_multi	(	network	net,
		data	test,
		int	n
	)

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network_predict_image()

float * network_predict_image	(	network *	net,
		Darknet::Image	im
	)

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network_predict_image_letterbox()

float * network_predict_image_letterbox	(	network *	net,
		Darknet::Image	im
	)

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network_predict_ptr()

float * network_predict_ptr	(	network *	net,
		float *	input
	)

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network_width()

int network_width

(

network *

net

)

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num_detections()

int num_detections	(	network *	net,
		float	thresh
	)

Todo:

V3 JAZZ 740 milliseconds

Todo:

V3 JAZZ 725 milliseconds – this is where we spend all our time

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num_detections_batch()

int num_detections_batch	(	network *	net,
		float	thresh,
		int	batch
	)

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num_detections_v3()

int num_detections_v3	(	network *	net,
		float	thresh,
		Darknet::Output_Object_Cache &	cache
	)

Todo:

V3 JAZZ 694 milliseconds

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V3 JAZZ 687 milliseconds – this is where we spend all our time

Todo:

Is this still used in a modern .cfg file? Should it be removed?

Todo:

Is this still used in a modern .cfg file? Should it be removed?

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print_network()

void print_network

(

network

net

)

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randomize_network_recurrent_state()

void randomize_network_recurrent_state

(

network

net

)

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recalculate_workspace_size()

int recalculate_workspace_size

(

network *

net

)

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reject_similar_weights()

void reject_similar_weights	(	network	net,
		float	sim_threshold
	)

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remember_network_recurrent_state()

void remember_network_recurrent_state

(

network

net

)

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reset_network_state()

void reset_network_state	(	network *	net,
		int	b
	)

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reset_rnn()

void reset_rnn

(

network *

net

)

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resize_network()

int resize_network	(	network *	net,
		int	w,
		int	h
	)

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restore_network_recurrent_state()

void restore_network_recurrent_state

(

network

net

)

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set_batch_network()

void set_batch_network	(	network *	net,
		int	b
	)

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top_predictions()

void top_predictions	(	network	net,
		int	k,
		int *	index
	)

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train_network()

float train_network	(	network	net,
		data	d
	)

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train_network_batch()

float train_network_batch	(	network	net,
		data	d,
		int	n
	)

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train_network_datum()

float train_network_datum	(	network	net,
		float *	x,
		float *	y
	)

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train_network_waitkey()

float train_network_waitkey	(	network	net,
		data	d,
		int	wait_key
	)

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update_network()

void update_network

(

network

net

)

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visualize_network()

void visualize_network

(

network

net

)

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