network.hpp File Reference

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Classes
struct	Darknet::NetworkState

Namespaces
namespace	Darknet
	The namespace for the C++ Darknet API.

Functions
void	backward_network (network net, Darknet::NetworkState state)
void	backward_network_gpu (network net, Darknet::NetworkState state)
network	combine_train_valid_networks (network net_train, network net_map)
void	compare_networks (network n1, network n2, data d)
void	copy_weights_net (network net_train, network *net_map)
void	ema_apply (network net)
void	ema_update (network net, float ema_alpha)
void	forward_backward_network_gpu (network net, float *x, float *y)
void	forward_network (network net, Darknet::NetworkState state)
void	forward_network_gpu (network net, Darknet::NetworkState state)
void	free_network_recurrent_state (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)
int	get_network_background (network net)
float	get_network_cost (network net)
float *	get_network_delta (network net)
float *	get_network_delta_gpu_layer (network net, int i)
float *	get_network_delta_layer (network net, int i)
Darknet::Image	get_network_image (network net)
Darknet::Image	get_network_image_layer (network net, int i)
int	get_network_input_size (network net)
int	get_network_nuisance (network net)
float *	get_network_output (network net)
float *	get_network_output_gpu (network net)
float *	get_network_output_gpu_layer (network net, int i)
float *	get_network_output_layer (network net, int i)
int	get_network_output_size (network net)
int	get_network_output_size_layer (network net, int i)
int	get_predicted_class_network (network net)
int	get_sequence_value (network net)
int	is_ema_initialized (network net)
network	make_network (int n)
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)
matrix	network_predict_data (network net, data test)
float *	network_predict_gpu (network net, float *input)
void	print_network (network net)
void	randomize_network_recurrent_state (network net)
void	reject_similar_weights (network net, float sim_threshold)
void	remember_network_recurrent_state (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	sync_nets (network *nets, int n, int interval)
void	top_predictions (network net, int n, 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_datum_gpu (network net, float *x, float *y)
float	train_network_waitkey (network net, data d, int wait_key)
float	train_networks (network *nets, int n, data d, int interval)
void	update_network (network net)
void	update_network_gpu (network net)
void	visualize_network (network net)

Function Documentation

backward_network()

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

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backward_network_gpu()

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

Todo:

V3 benchmark layers

Todo:

V3 benchmark layers

Todo:

replace qsort() unknown priority

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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	d
	)

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copy_weights_net()

void copy_weights_net	(	network	net_train,
		network *	net_map
	)

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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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forward_backward_network_gpu()

void forward_backward_network_gpu	(	network	net,
		float *	x,
		float *	y
	)

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forward_network()

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

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forward_network_gpu()

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

Todo:

in previous versions we did not CHECK_CUDA here – was that intentional?

Todo:

V3 benchmark layers

Todo:

V3 benchmark layers

Todo:

replace qsort() low priority

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free_network_recurrent_state()

void free_network_recurrent_state

(

network

net

)

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get_current_batch()

int get_current_batch

(

network

net

)

get_current_iteration()

int64_t get_current_iteration

(

network

net

)

get_current_rate()

float get_current_rate

(

network

net

)

get_current_seq_subdivisions()

float get_current_seq_subdivisions

(

network

net

)

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get_network_background()

int get_network_background

(

network

net

)

get_network_cost()

float get_network_cost

(

network

net

)

get_network_delta()

float * get_network_delta

(

network

net

)

get_network_delta_gpu_layer()

float * get_network_delta_gpu_layer	(	network	net,
		int	i
	)

get_network_delta_layer()

float * get_network_delta_layer	(	network	net,
		int	i
	)

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

)

get_network_nuisance()

int get_network_nuisance

(

network

net

)

get_network_output()

float * get_network_output

(

network

net

)

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get_network_output_gpu()

float * get_network_output_gpu

(

network

net

)

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get_network_output_gpu_layer()

float * get_network_output_gpu_layer	(	network	net,
		int	i
	)

get_network_output_layer()

float * get_network_output_layer	(	network	net,
		int	i
	)

get_network_output_size()

int get_network_output_size

(

network

net

)

get_network_output_size_layer()

int get_network_output_size_layer	(	network	net,
		int	i
	)

get_predicted_class_network()

int get_predicted_class_network

(

network

net

)

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get_sequence_value()

int get_sequence_value

(

network

net

)

is_ema_initialized()

int is_ema_initialized

(

network

net

)

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make_network()

network make_network

(

int

n

)

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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_predict_data()

matrix network_predict_data	(	network	net,
		data	test
	)

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network_predict_gpu()

float * network_predict_gpu	(	network	net,
		float *	input
	)

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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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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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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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sync_nets()

void sync_nets	(	network *	nets,
		int	n,
		int	interval
	)

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top_predictions()

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

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train_network()

float train_network	(	network	net,
		data	d
	)

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_datum_gpu()

float train_network_datum_gpu	(	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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train_networks()

float train_networks	(	network *	nets,
		int	n,
		data	d,
		int	interval
	)

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update_network()

void update_network

(

network

net

)

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update_network_gpu()

void update_network_gpu

(

network

net

)

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visualize_network()

void visualize_network

(

network

net

)

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