Darknet::Network Struct Reference

Neural network structure. Contains all of the layers. Created by Darknet::CfgFile::create_network(). More...

#include "darknet_network.hpp"

Collaboration diagram for Darknet::Network:

Public Attributes
int	adam
int	adversarial
float	adversarial_lr
float	angle
float	aspect
int	attention
int	augment_speed
float	B1
float	B2
float *	badlabels_reject_threshold
float	badlabels_rejection_percentage
int	batch
int	batches_cycle_mult
int	batches_per_cycle
int	benchmark_layers
int	blur
int	burn_in
int	c
	The number of channels for the network. Typically 3 when working with RGB images.
int	center
float	clip
int	contrastive
int	contrastive_color
int	contrastive_jit_flip
float *	cost
void *	cuda_graph
void *	cuda_graph_exec
int *	cuda_graph_ready
int	cudnn_half
int *	cur_iteration
int	current_subdivision
float	decay
float *	delta
float *	delta_gpu
float *	delta_rolling_avg
float *	delta_rolling_max
float *	delta_rolling_std
Darknet::NetworkDetails *	details
int	dynamic_minibatch
float	ema_alpha
float	eps
int	equidistant_point
float	exposure
int	flip
	horizontal flip 50% probability augmentaiont for classifier training (default = 1)
float	gamma
int	gaussian_noise
float *	global_delta_gpu
int	gpu_index
int	h
	The height of the network. Must be divisible by 32. E.g, 480.
Darknet::Tree *	hierarchy
float	hue
int	index
int	init_sequential_subdivisions
float *	input
float **	input16_gpu
float **	input_gpu
float *	input_pinned_cpu
	memory allocated using cudaHostAlloc() which is used to transfer between the GPU and CPU
int	input_pinned_cpu_flag
float *	input_state_gpu
int	inputs
float	label_smooth_eps
Darknet::Layer *	layers
	Each section in the .cfg file is converted into a layer.
float	learning_rate
float	learning_rate_max
float	learning_rate_min
int	letter_box
float	loss_scale
int	max_batches
float	max_chart_loss
size_t	max_delta_gpu_size
size_t *	max_input16_size
size_t *	max_output16_size
int	mixup
float	momentum
int	mosaic_bound
int	n
	The number of layers in the network.
int	num_boxes
float	num_sigmas_reject_badlabels
int	num_steps
int	optimized_memory
float *	output
float **	output16_gpu
float *	output_gpu
int	outputs
learning_rate_policy	policy
float	power
int	resize_step
int *	rewritten_bbox
float	saturation
float	scale
float *	scales
uint64_t *	seen
float *	seq_scales
int	sequential_subdivisions
float *	state_delta_gpu
int	step
int *	steps
int	subdivisions
int *	t
int	time_steps
int *	total_bbox
int	track
int	train
int	train_images_num
float *	truth
float **	truth_gpu
int	truths
int	try_fix_nan
int	use_cuda_graph
int	w
	The width of the network. Must be divisible by 32. E.g., 640.
int	wait_stream
int	weights_reject_freq
float *	workspace
size_t	workspace_size_limit

Detailed Description

Neural network structure. Contains all of the layers. Created by Darknet::CfgFile::create_network().

Member Data Documentation

adam

int Darknet::Network::adam

adversarial

int Darknet::Network::adversarial

adversarial_lr

float Darknet::Network::adversarial_lr

angle

float Darknet::Network::angle

aspect

float Darknet::Network::aspect

attention

int Darknet::Network::attention

augment_speed

int Darknet::Network::augment_speed

B1

float Darknet::Network::B1

B2

float Darknet::Network::B2

badlabels_reject_threshold

float* Darknet::Network::badlabels_reject_threshold

badlabels_rejection_percentage

float Darknet::Network::badlabels_rejection_percentage

batch

int Darknet::Network::batch

batches_cycle_mult

int Darknet::Network::batches_cycle_mult

batches_per_cycle

int Darknet::Network::batches_per_cycle

benchmark_layers

int Darknet::Network::benchmark_layers

blur

int Darknet::Network::blur

burn_in

int Darknet::Network::burn_in

c

int Darknet::Network::c

The number of channels for the network. Typically 3 when working with RGB images.

center

int Darknet::Network::center

clip

float Darknet::Network::clip

contrastive

int Darknet::Network::contrastive

contrastive_color

int Darknet::Network::contrastive_color

contrastive_jit_flip

int Darknet::Network::contrastive_jit_flip

cost

float* Darknet::Network::cost

cuda_graph

void* Darknet::Network::cuda_graph

cuda_graph_exec

void* Darknet::Network::cuda_graph_exec

cuda_graph_ready

int* Darknet::Network::cuda_graph_ready

cudnn_half

int Darknet::Network::cudnn_half

cur_iteration

int* Darknet::Network::cur_iteration

current_subdivision

int Darknet::Network::current_subdivision

decay

float Darknet::Network::decay

delta

float* Darknet::Network::delta

delta_gpu

float* Darknet::Network::delta_gpu

delta_rolling_avg

float* Darknet::Network::delta_rolling_avg

delta_rolling_max

float* Darknet::Network::delta_rolling_max

delta_rolling_std

float* Darknet::Network::delta_rolling_std

details

Darknet::NetworkDetails* Darknet::Network::details

dynamic_minibatch

int Darknet::Network::dynamic_minibatch

ema_alpha

float Darknet::Network::ema_alpha

eps

float Darknet::Network::eps

equidistant_point

int Darknet::Network::equidistant_point

exposure

float Darknet::Network::exposure

flip

int Darknet::Network::flip

horizontal flip 50% probability augmentaiont for classifier training (default = 1)

gamma

float Darknet::Network::gamma

gaussian_noise

int Darknet::Network::gaussian_noise

global_delta_gpu

float* Darknet::Network::global_delta_gpu

gpu_index

int Darknet::Network::gpu_index

h

int Darknet::Network::h

The height of the network. Must be divisible by 32. E.g, 480.

hierarchy

Darknet::Tree* Darknet::Network::hierarchy

hue

float Darknet::Network::hue

index

int Darknet::Network::index

init_sequential_subdivisions

int Darknet::Network::init_sequential_subdivisions

input

float* Darknet::Network::input

input16_gpu

float** Darknet::Network::input16_gpu

input_gpu

float** Darknet::Network::input_gpu

input_pinned_cpu

float* Darknet::Network::input_pinned_cpu

memory allocated using cudaHostAlloc() which is used to transfer between the GPU and CPU

input_pinned_cpu_flag

int Darknet::Network::input_pinned_cpu_flag

input_state_gpu

float* Darknet::Network::input_state_gpu

inputs

int Darknet::Network::inputs

label_smooth_eps

float Darknet::Network::label_smooth_eps

layers

Darknet::Layer* Darknet::Network::layers

Each section in the .cfg file is converted into a layer.

See also

n

learning_rate

float Darknet::Network::learning_rate

learning_rate_max

float Darknet::Network::learning_rate_max

learning_rate_min

float Darknet::Network::learning_rate_min

letter_box

int Darknet::Network::letter_box

loss_scale

float Darknet::Network::loss_scale

max_batches

int Darknet::Network::max_batches

max_chart_loss

float Darknet::Network::max_chart_loss

max_delta_gpu_size

size_t Darknet::Network::max_delta_gpu_size

max_input16_size

size_t* Darknet::Network::max_input16_size

max_output16_size

size_t* Darknet::Network::max_output16_size

mixup

int Darknet::Network::mixup

momentum

float Darknet::Network::momentum

mosaic_bound

int Darknet::Network::mosaic_bound

n

int Darknet::Network::n

The number of layers in the network.

See also

layers

num_boxes

int Darknet::Network::num_boxes

num_sigmas_reject_badlabels

float Darknet::Network::num_sigmas_reject_badlabels

num_steps

int Darknet::Network::num_steps

optimized_memory

int Darknet::Network::optimized_memory

output

float* Darknet::Network::output

output16_gpu

float** Darknet::Network::output16_gpu

output_gpu

float* Darknet::Network::output_gpu

outputs

int Darknet::Network::outputs

policy

learning_rate_policy Darknet::Network::policy

power

float Darknet::Network::power

resize_step

int Darknet::Network::resize_step

rewritten_bbox

int* Darknet::Network::rewritten_bbox

saturation

float Darknet::Network::saturation

scale

float Darknet::Network::scale

scales

float* Darknet::Network::scales

seen

uint64_t* Darknet::Network::seen

seq_scales

float* Darknet::Network::seq_scales

sequential_subdivisions

int Darknet::Network::sequential_subdivisions

state_delta_gpu

float* Darknet::Network::state_delta_gpu

step

int Darknet::Network::step

steps

int* Darknet::Network::steps

subdivisions

int Darknet::Network::subdivisions

t

int* Darknet::Network::t

time_steps

int Darknet::Network::time_steps

total_bbox

int* Darknet::Network::total_bbox

track

int Darknet::Network::track

train

int Darknet::Network::train

train_images_num

int Darknet::Network::train_images_num

truth

float* Darknet::Network::truth

truth_gpu

float** Darknet::Network::truth_gpu

truths

int Darknet::Network::truths

try_fix_nan

int Darknet::Network::try_fix_nan

use_cuda_graph

int Darknet::Network::use_cuda_graph

w

int Darknet::Network::w

The width of the network. Must be divisible by 32. E.g., 640.

wait_stream

int Darknet::Network::wait_stream

weights_reject_freq

int Darknet::Network::weights_reject_freq

workspace

float* Darknet::Network::workspace

workspace_size_limit

size_t Darknet::Network::workspace_size_limit

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The documentation for this struct was generated from the following file:

• darknet_network.hpp