Collaboration diagram for layer:

[legend]

Public Attributes
LAYER_TYPE	type

ACTIVATION	activation

ACTIVATION	lstm_activation

COST_TYPE	cost_type

void(*	forward )(struct layer, struct network_state)

void(*	backward )(struct layer, struct network_state)

void(*	update )(struct layer, int, float, float, float)

void(*	forward_gpu )(struct layer, struct network_state)

void(*	backward_gpu )(struct layer, struct network_state)

void(*	update_gpu )(struct layer, int, float, float, float, float)

layer *	share_layer

int	train

int	avgpool

int	batch_normalize

int	shortcut

int	batch

int	dynamic_minibatch

int	forced

int	flipped

int	inputs

int	outputs

float	mean_alpha

int	nweights

int	nbiases
	unused? Seems to be no references to this in the codebase. More...

int	extra

int	truths

int	h

int	w

int	c

int	out_h

int	out_w

int	out_c

int	n

int	max_boxes

int	truth_size

int	groups

int	group_id

int	size

int	side

int	stride

int	stride_x

int	stride_y

int	dilation

int	antialiasing

int	maxpool_depth

int	maxpool_zero_nonmax

int	out_channels

float	reverse

int	coordconv

int	flatten

int	spatial

int	pad

int	sqrt

int	flip

int	index

int	scale_wh

int	binary

int	xnor

int	peephole

int	use_bin_output

int	keep_delta_gpu

int	optimized_memory

int	steps

int	history_size

int	bottleneck

float	time_normalizer

int	state_constrain

int	hidden

int	truth

float	smooth

float	dot

int	deform

int	grad_centr

int	sway

int	rotate

int	stretch

int	stretch_sway

float	angle

float	jitter

float	resize

float	saturation

float	exposure

float	shift

float	ratio

float	learning_rate_scale

float	clip

int	focal_loss

float *	classes_multipliers

float	label_smooth_eps

int	noloss

int	softmax

int	classes

int	detection

int	embedding_layer_id

float *	embedding_output

int	embedding_size

float	sim_thresh

int	track_history_size

int	dets_for_track

int	dets_for_show

float	track_ciou_norm

int	coords

int	background

int	rescore

int	objectness

int	does_cost

int	joint

int	noadjust

int	reorg

int	log

int	tanh

int *	mask

int	total

float	bflops

int	adam

float	B1

float	B2

float	eps

int	t

float	alpha

float	beta

float	kappa

float	coord_scale

float	object_scale

float	noobject_scale

float	mask_scale

float	class_scale

int	bias_match

float	random

float	ignore_thresh

float	truth_thresh

float	iou_thresh

float	thresh

float	focus

int	classfix

int	absolute

int	assisted_excitation

int	onlyforward

int	stopbackward

int	train_only_bn

int	dont_update

int	burnin_update

int	dontload

int	dontsave

int	dontloadscales

int	numload

float	temperature

float	probability

float	dropblock_size_rel

int	dropblock_size_abs

int	dropblock

float	scale

int	receptive_w

int	receptive_h

int	receptive_w_scale

int	receptive_h_scale

char *	cweights

int *	indexes

int *	input_layers

int *	input_sizes

float **	layers_output

float **	layers_delta

WEIGHTS_TYPE_T	weights_type

WEIGHTS_NORMALIZATION_T	weights_normalization

int *	map

int *	counts

float **	sums

float *	rand

float *	cost

int *	labels

int *	class_ids

int	contrastive_neg_max

float *	cos_sim

float *	exp_cos_sim

float *	p_constrastive

contrastive_params *	contrast_p_gpu

float *	state

float *	prev_state

float *	forgot_state

float *	forgot_delta

float *	state_delta

float *	combine_cpu

float *	combine_delta_cpu

float *	concat

float *	concat_delta

float *	binary_weights

float *	biases

float *	bias_updates

float *	scales

float *	scale_updates

float *	weights_ema

float *	biases_ema

float *	scales_ema

float *	weights

float *	weight_updates

float	scale_x_y

int	objectness_smooth

int	new_coords

int	show_details

float	max_delta

float	uc_normalizer

float	iou_normalizer

float	obj_normalizer

float	cls_normalizer

float	delta_normalizer

IOU_LOSS	iou_loss

IOU_LOSS	iou_thresh_kind

NMS_KIND	nms_kind

float	beta_nms

YOLO_POINT	yolo_point

char *	align_bit_weights_gpu

float *	mean_arr_gpu

float *	align_workspace_gpu

float *	transposed_align_workspace_gpu

int	align_workspace_size

char *	align_bit_weights

float *	mean_arr

int	align_bit_weights_size

int	lda_align

int	new_lda

int	bit_align

float *	col_image

float *	delta

float *	output

float *	activation_input

int	delta_pinned

int	output_pinned

float *	loss

float *	squared

float *	norms

float *	spatial_mean

float *	mean

float *	variance

float *	mean_delta

float *	variance_delta

float *	rolling_mean

float *	rolling_variance

float *	x

float *	x_norm

float *	m

float *	v

float *	bias_m

float *	bias_v

float *	scale_m

float *	scale_v

float *	z_cpu

float *	r_cpu

float *	h_cpu

float *	stored_h_cpu

float *	prev_state_cpu

float *	temp_cpu

float *	temp2_cpu

float *	temp3_cpu

float *	dh_cpu

float *	hh_cpu

float *	prev_cell_cpu

float *	cell_cpu

float *	f_cpu

float *	i_cpu

float *	g_cpu

float *	o_cpu

float *	c_cpu

float *	stored_c_cpu

float *	dc_cpu

float *	binary_input

uint32_t *	bin_re_packed_input

char *	t_bit_input

struct layer *	input_layer

struct layer *	self_layer

struct layer *	output_layer

struct layer *	reset_layer

struct layer *	update_layer

struct layer *	state_layer

struct layer *	input_gate_layer

struct layer *	state_gate_layer

struct layer *	input_save_layer

struct layer *	state_save_layer

struct layer *	input_state_layer

struct layer *	state_state_layer

struct layer *	input_z_layer

struct layer *	state_z_layer

struct layer *	input_r_layer

struct layer *	state_r_layer

struct layer *	input_h_layer

struct layer *	state_h_layer

struct layer *	wz

struct layer *	uz

struct layer *	wr

struct layer *	ur

struct layer *	wh

struct layer *	uh

struct layer *	uo

struct layer *	wo

struct layer *	vo

struct layer *	uf

struct layer *	wf

struct layer *	vf

struct layer *	ui

struct layer *	wi

struct layer *	vi

struct layer *	ug

struct layer *	wg

tree *	softmax_tree

size_t	workspace_size

int *	indexes_gpu

int	stream

int	wait_stream_id

float *	z_gpu

float *	r_gpu

float *	h_gpu

float *	stored_h_gpu

float *	bottelneck_hi_gpu

float *	bottelneck_delta_gpu

float *	temp_gpu

float *	temp2_gpu

float *	temp3_gpu

float *	dh_gpu

float *	hh_gpu

float *	prev_cell_gpu

float *	prev_state_gpu

float *	last_prev_state_gpu

float *	last_prev_cell_gpu

float *	cell_gpu

float *	f_gpu

float *	i_gpu

float *	g_gpu

float *	o_gpu

float *	c_gpu

float *	stored_c_gpu

float *	dc_gpu

float *	m_gpu

float *	v_gpu

float *	bias_m_gpu

float *	scale_m_gpu

float *	bias_v_gpu

float *	scale_v_gpu

float *	combine_gpu

float *	combine_delta_gpu

float *	forgot_state_gpu

float *	forgot_delta_gpu

float *	state_gpu

float *	state_delta_gpu

float *	gate_gpu

float *	gate_delta_gpu

float *	save_gpu

float *	save_delta_gpu

float *	concat_gpu

float *	concat_delta_gpu

float *	binary_input_gpu

float *	binary_weights_gpu

float *	bin_conv_shortcut_in_gpu

float *	bin_conv_shortcut_out_gpu

float *	mean_gpu

float *	variance_gpu

float *	m_cbn_avg_gpu

float *	v_cbn_avg_gpu

float *	rolling_mean_gpu

float *	rolling_variance_gpu

float *	variance_delta_gpu

float *	mean_delta_gpu

float *	col_image_gpu

float *	x_gpu

float *	x_norm_gpu

float *	weights_gpu

float *	weight_updates_gpu

float *	weight_deform_gpu

float *	weight_change_gpu

float *	weights_gpu16

float *	weight_updates_gpu16

float *	biases_gpu

float *	bias_updates_gpu

float *	bias_change_gpu

float *	scales_gpu

float *	scale_updates_gpu

float *	scale_change_gpu

float *	input_antialiasing_gpu

float *	output_gpu

float *	output_avg_gpu

float *	activation_input_gpu

float *	loss_gpu

float *	delta_gpu

float *	cos_sim_gpu

float *	rand_gpu

float *	drop_blocks_scale

float *	drop_blocks_scale_gpu

float *	squared_gpu

float *	norms_gpu

float *	gt_gpu

float *	a_avg_gpu

int *	input_sizes_gpu

float **	layers_output_gpu

float **	layers_delta_gpu

cudnnTensorDescriptor_t	srcTensorDesc

cudnnTensorDescriptor_t	dstTensorDesc

cudnnTensorDescriptor_t	srcTensorDesc16

cudnnTensorDescriptor_t	dstTensorDesc16

cudnnTensorDescriptor_t	dsrcTensorDesc

cudnnTensorDescriptor_t	ddstTensorDesc

cudnnTensorDescriptor_t	dsrcTensorDesc16

cudnnTensorDescriptor_t	ddstTensorDesc16

cudnnTensorDescriptor_t	normTensorDesc

cudnnTensorDescriptor_t	normDstTensorDesc

cudnnTensorDescriptor_t	normDstTensorDescF16

cudnnFilterDescriptor_t	weightDesc

cudnnFilterDescriptor_t	weightDesc16

cudnnFilterDescriptor_t	dweightDesc

cudnnFilterDescriptor_t	dweightDesc16

cudnnConvolutionDescriptor_t	convDesc

cudnnConvolutionFwdAlgo_t	fw_algo

cudnnConvolutionFwdAlgo_t	fw_algo16

cudnnConvolutionBwdDataAlgo_t	bd_algo

cudnnConvolutionBwdDataAlgo_t	bd_algo16

cudnnConvolutionBwdFilterAlgo_t	bf_algo

cudnnConvolutionBwdFilterAlgo_t	bf_algo16

cudnnPoolingDescriptor_t	poolingDesc

Member Data Documentation

◆ type

LAYER_TYPE layer::type

See also: get_layer_string()

◆ activation

ACTIVATION layer::activation

◆ lstm_activation

ACTIVATION layer::lstm_activation

◆ cost_type

COST_TYPE layer::cost_type

◆ forward

void(* layer::forward) (struct layer, struct network_state)

◆ backward

void(* layer::backward) (struct layer, struct network_state)

◆ update

void(* layer::update) (struct layer, int, float, float, float)

◆ forward_gpu

void(* layer::forward_gpu) (struct layer, struct network_state)

◆ backward_gpu

void(* layer::backward_gpu) (struct layer, struct network_state)

◆ update_gpu

void(* layer::update_gpu) (struct layer, int, float, float, float, float)

◆ share_layer

layer* layer::share_layer

◆ train

int layer::train

◆ avgpool

int layer::avgpool

◆ batch_normalize

int layer::batch_normalize

◆ shortcut

int layer::shortcut

◆ batch

int layer::batch

◆ dynamic_minibatch

int layer::dynamic_minibatch

◆ forced

int layer::forced

◆ flipped

int layer::flipped

◆ inputs

int layer::inputs

◆ outputs

int layer::outputs

◆ mean_alpha

float layer::mean_alpha

◆ nweights

int layer::nweights

◆ nbiases

int layer::nbiases

unused? Seems to be no references to this in the codebase.

◆ extra

int layer::extra

◆ truths

int layer::truths

◆ h

int layer::h

◆ w

int layer::w

◆ c

int layer::c

◆ out_h

int layer::out_h

◆ out_w

int layer::out_w

◆ out_c

int layer::out_c

◆ n

int layer::n

◆ max_boxes

int layer::max_boxes

◆ truth_size

int layer::truth_size

◆ groups

int layer::groups

◆ group_id

int layer::group_id

◆ size

int layer::size

◆ side

int layer::side

◆ stride

int layer::stride

◆ stride_x

int layer::stride_x

◆ stride_y

int layer::stride_y

◆ dilation

int layer::dilation

◆ antialiasing

int layer::antialiasing

◆ maxpool_depth

int layer::maxpool_depth

◆ maxpool_zero_nonmax

int layer::maxpool_zero_nonmax

◆ out_channels

int layer::out_channels

◆ reverse

float layer::reverse

◆ coordconv

int layer::coordconv

◆ flatten

int layer::flatten

◆ spatial

int layer::spatial

◆ pad

int layer::pad

◆ sqrt

int layer::sqrt

◆ flip

int layer::flip

◆ index

int layer::index

◆ scale_wh

int layer::scale_wh

◆ binary

int layer::binary

◆ xnor

int layer::xnor

◆ peephole

int layer::peephole

◆ use_bin_output

int layer::use_bin_output

◆ keep_delta_gpu

int layer::keep_delta_gpu

◆ optimized_memory

int layer::optimized_memory

◆ steps

int layer::steps

◆ history_size

int layer::history_size

◆ bottleneck

int layer::bottleneck

◆ time_normalizer

float layer::time_normalizer

◆ state_constrain

int layer::state_constrain

◆ hidden

int layer::hidden

◆ truth

int layer::truth

◆ smooth

float layer::smooth

◆ dot

float layer::dot

◆ deform

int layer::deform

◆ grad_centr

int layer::grad_centr

◆ sway

int layer::sway

◆ rotate

int layer::rotate

◆ stretch

int layer::stretch

◆ stretch_sway

int layer::stretch_sway

◆ angle

float layer::angle

◆ jitter

float layer::jitter

◆ resize

float layer::resize

◆ saturation

float layer::saturation

◆ exposure

float layer::exposure

◆ shift

float layer::shift

◆ ratio

float layer::ratio

◆ learning_rate_scale

float layer::learning_rate_scale

◆ clip

float layer::clip

◆ focal_loss

int layer::focal_loss

◆ classes_multipliers

float* layer::classes_multipliers

◆ label_smooth_eps

float layer::label_smooth_eps

◆ noloss

int layer::noloss

◆ softmax

int layer::softmax

◆ classes

int layer::classes

◆ detection

int layer::detection

◆ embedding_layer_id

int layer::embedding_layer_id

◆ embedding_output

float* layer::embedding_output

◆ embedding_size

int layer::embedding_size

◆ sim_thresh

float layer::sim_thresh

◆ track_history_size

int layer::track_history_size

◆ dets_for_track

int layer::dets_for_track

◆ dets_for_show

int layer::dets_for_show

◆ track_ciou_norm

float layer::track_ciou_norm

◆ coords

int layer::coords

◆ background

int layer::background

◆ rescore

int layer::rescore

◆ objectness

int layer::objectness

◆ does_cost

int layer::does_cost

◆ joint

int layer::joint

◆ noadjust

int layer::noadjust

◆ reorg

int layer::reorg

◆ log

int layer::log

◆ tanh

int layer::tanh

◆ mask

int* layer::mask

◆ total

int layer::total

◆ bflops

float layer::bflops

◆ adam

int layer::adam

◆ B1

float layer::B1

◆ B2

float layer::B2

◆ eps

float layer::eps

◆ t

int layer::t

◆ alpha

float layer::alpha

◆ beta

float layer::beta

◆ kappa

float layer::kappa

◆ coord_scale

float layer::coord_scale

◆ object_scale

float layer::object_scale

◆ noobject_scale

float layer::noobject_scale

◆ mask_scale

float layer::mask_scale

◆ class_scale

float layer::class_scale

◆ bias_match

int layer::bias_match

◆ random

float layer::random

◆ ignore_thresh

float layer::ignore_thresh

◆ truth_thresh

float layer::truth_thresh

◆ iou_thresh

float layer::iou_thresh

◆ thresh

float layer::thresh

◆ focus

float layer::focus

◆ classfix

int layer::classfix

◆ absolute

int layer::absolute

◆ assisted_excitation

int layer::assisted_excitation

◆ onlyforward

int layer::onlyforward

◆ stopbackward

int layer::stopbackward

◆ train_only_bn

int layer::train_only_bn

◆ dont_update

int layer::dont_update

◆ burnin_update

int layer::burnin_update

◆ dontload

int layer::dontload

◆ dontsave

int layer::dontsave

◆ dontloadscales

int layer::dontloadscales

◆ numload

int layer::numload

◆ temperature

float layer::temperature

◆ probability

float layer::probability

◆ dropblock_size_rel

float layer::dropblock_size_rel

◆ dropblock_size_abs

int layer::dropblock_size_abs

◆ dropblock

int layer::dropblock

◆ scale

float layer::scale

◆ receptive_w

int layer::receptive_w

◆ receptive_h

int layer::receptive_h

◆ receptive_w_scale

int layer::receptive_w_scale

◆ receptive_h_scale

int layer::receptive_h_scale

◆ cweights

char* layer::cweights

◆ indexes

int* layer::indexes

◆ input_layers

int* layer::input_layers

◆ input_sizes

int* layer::input_sizes

◆ layers_output

float** layer::layers_output

◆ layers_delta

float** layer::layers_delta

◆ weights_type

WEIGHTS_TYPE_T layer::weights_type

◆ weights_normalization

WEIGHTS_NORMALIZATION_T layer::weights_normalization

◆ map

int* layer::map

◆ counts

int* layer::counts

◆ sums

float** layer::sums

◆ rand

float* layer::rand

◆ cost

float* layer::cost

◆ labels

int* layer::labels

◆ class_ids

int* layer::class_ids

◆ contrastive_neg_max

int layer::contrastive_neg_max

◆ cos_sim

float* layer::cos_sim

◆ exp_cos_sim

float* layer::exp_cos_sim

◆ p_constrastive

float* layer::p_constrastive

◆ contrast_p_gpu

contrastive_params* layer::contrast_p_gpu

◆ state

float* layer::state

◆ prev_state

float* layer::prev_state

◆ forgot_state

float* layer::forgot_state

◆ forgot_delta

float* layer::forgot_delta

◆ state_delta

float* layer::state_delta

◆ combine_cpu

float* layer::combine_cpu

◆ combine_delta_cpu

float* layer::combine_delta_cpu

◆ concat

float* layer::concat

◆ concat_delta

float* layer::concat_delta

◆ binary_weights

float* layer::binary_weights

◆ biases

float* layer::biases

◆ bias_updates

float* layer::bias_updates

◆ scales

float* layer::scales

◆ scale_updates

float* layer::scale_updates

◆ weights_ema

float* layer::weights_ema

◆ biases_ema

float* layer::biases_ema

◆ scales_ema

float* layer::scales_ema

◆ weights

float* layer::weights

◆ weight_updates

float* layer::weight_updates

◆ scale_x_y

float layer::scale_x_y

◆ objectness_smooth

int layer::objectness_smooth

◆ new_coords

int layer::new_coords

◆ show_details

int layer::show_details

◆ max_delta

float layer::max_delta

◆ uc_normalizer

float layer::uc_normalizer

◆ iou_normalizer

float layer::iou_normalizer

◆ obj_normalizer

float layer::obj_normalizer

◆ cls_normalizer

float layer::cls_normalizer

◆ delta_normalizer

float layer::delta_normalizer

◆ iou_loss

IOU_LOSS layer::iou_loss

◆ iou_thresh_kind

IOU_LOSS layer::iou_thresh_kind

◆ nms_kind

NMS_KIND layer::nms_kind

◆ beta_nms

float layer::beta_nms

◆ yolo_point

YOLO_POINT layer::yolo_point

◆ align_bit_weights_gpu

char* layer::align_bit_weights_gpu

◆ mean_arr_gpu

float* layer::mean_arr_gpu

◆ align_workspace_gpu

float* layer::align_workspace_gpu

◆ transposed_align_workspace_gpu

float* layer::transposed_align_workspace_gpu

◆ align_workspace_size

int layer::align_workspace_size

◆ align_bit_weights

char* layer::align_bit_weights

◆ mean_arr

float* layer::mean_arr

◆ align_bit_weights_size

int layer::align_bit_weights_size

◆ lda_align

int layer::lda_align

◆ new_lda

int layer::new_lda

◆ bit_align

int layer::bit_align

◆ col_image

float* layer::col_image

◆ delta

float* layer::delta

◆ output

float* layer::output

◆ activation_input

float* layer::activation_input

◆ delta_pinned

int layer::delta_pinned

◆ output_pinned

int layer::output_pinned

◆ loss

float* layer::loss

◆ squared

float* layer::squared

◆ norms

float* layer::norms

◆ spatial_mean

float* layer::spatial_mean

◆ mean

float* layer::mean

◆ variance

float* layer::variance

◆ mean_delta

float* layer::mean_delta

◆ variance_delta

float* layer::variance_delta

◆ rolling_mean

float* layer::rolling_mean

◆ rolling_variance

float* layer::rolling_variance

◆ x

float* layer::x

◆ x_norm

float* layer::x_norm

◆ m

float* layer::m

◆ v

float* layer::v

◆ bias_m

float* layer::bias_m

◆ bias_v

float* layer::bias_v

◆ scale_m

float* layer::scale_m

◆ scale_v

float* layer::scale_v

◆ z_cpu

float* layer::z_cpu

◆ r_cpu

float* layer::r_cpu

◆ h_cpu

float* layer::h_cpu

◆ stored_h_cpu

float* layer::stored_h_cpu

◆ prev_state_cpu

float* layer::prev_state_cpu

◆ temp_cpu

float* layer::temp_cpu

◆ temp2_cpu

float* layer::temp2_cpu

◆ temp3_cpu

float* layer::temp3_cpu

◆ dh_cpu

float* layer::dh_cpu

◆ hh_cpu

float* layer::hh_cpu

◆ prev_cell_cpu

float* layer::prev_cell_cpu

◆ cell_cpu

float* layer::cell_cpu

◆ f_cpu

float* layer::f_cpu

◆ i_cpu

float* layer::i_cpu

◆ g_cpu

float* layer::g_cpu

◆ o_cpu

float* layer::o_cpu

◆ c_cpu

float* layer::c_cpu

◆ stored_c_cpu

float* layer::stored_c_cpu

◆ dc_cpu

float* layer::dc_cpu

◆ binary_input

float* layer::binary_input

◆ bin_re_packed_input

uint32_t* layer::bin_re_packed_input

◆ t_bit_input

char* layer::t_bit_input

◆ input_layer

struct layer* layer::input_layer

◆ self_layer

struct layer* layer::self_layer

◆ output_layer

struct layer* layer::output_layer

◆ reset_layer

struct layer* layer::reset_layer

◆ update_layer

struct layer* layer::update_layer

◆ state_layer

struct layer* layer::state_layer

◆ input_gate_layer

struct layer* layer::input_gate_layer

◆ state_gate_layer

struct layer* layer::state_gate_layer

◆ input_save_layer

struct layer* layer::input_save_layer

◆ state_save_layer

struct layer* layer::state_save_layer

◆ input_state_layer

struct layer* layer::input_state_layer

◆ state_state_layer

struct layer* layer::state_state_layer

◆ input_z_layer

struct layer* layer::input_z_layer

◆ state_z_layer

struct layer* layer::state_z_layer

◆ input_r_layer

struct layer* layer::input_r_layer

◆ state_r_layer

struct layer* layer::state_r_layer

◆ input_h_layer

struct layer* layer::input_h_layer

◆ state_h_layer

struct layer* layer::state_h_layer

◆ wz

struct layer* layer::wz

◆ uz

struct layer* layer::uz

◆ wr

struct layer* layer::wr

◆ ur

struct layer* layer::ur

◆ wh

struct layer* layer::wh

◆ uh

struct layer* layer::uh

◆ uo

struct layer* layer::uo

◆ wo

struct layer* layer::wo

◆ vo

struct layer* layer::vo

◆ uf

struct layer* layer::uf

◆ wf

struct layer* layer::wf

◆ vf

struct layer* layer::vf

◆ ui

struct layer* layer::ui

◆ wi

struct layer* layer::wi

◆ vi

struct layer* layer::vi

◆ ug

struct layer* layer::ug

◆ wg

struct layer* layer::wg

◆ softmax_tree

tree* layer::softmax_tree

◆ workspace_size

size_t layer::workspace_size

◆ indexes_gpu

int* layer::indexes_gpu

◆ stream

int layer::stream

◆ wait_stream_id

int layer::wait_stream_id

◆ z_gpu

float* layer::z_gpu

◆ r_gpu

float* layer::r_gpu

◆ h_gpu

float* layer::h_gpu

◆ stored_h_gpu

float* layer::stored_h_gpu

◆ bottelneck_hi_gpu

float* layer::bottelneck_hi_gpu

◆ bottelneck_delta_gpu

float* layer::bottelneck_delta_gpu

◆ temp_gpu

float* layer::temp_gpu

◆ temp2_gpu

float* layer::temp2_gpu

◆ temp3_gpu

float* layer::temp3_gpu

◆ dh_gpu

float* layer::dh_gpu

◆ hh_gpu

float* layer::hh_gpu

◆ prev_cell_gpu

float* layer::prev_cell_gpu

◆ prev_state_gpu

float* layer::prev_state_gpu

◆ last_prev_state_gpu

float* layer::last_prev_state_gpu

◆ last_prev_cell_gpu

float* layer::last_prev_cell_gpu

◆ cell_gpu

float* layer::cell_gpu

◆ f_gpu

float* layer::f_gpu

◆ i_gpu

float* layer::i_gpu

◆ g_gpu

float* layer::g_gpu

◆ o_gpu

float* layer::o_gpu

◆ c_gpu

float* layer::c_gpu

◆ stored_c_gpu

float* layer::stored_c_gpu

◆ dc_gpu

float* layer::dc_gpu

◆ m_gpu

float* layer::m_gpu

◆ v_gpu

float* layer::v_gpu

◆ bias_m_gpu

float* layer::bias_m_gpu

◆ scale_m_gpu

float* layer::scale_m_gpu

◆ bias_v_gpu

float* layer::bias_v_gpu

◆ scale_v_gpu

float* layer::scale_v_gpu

◆ combine_gpu

float* layer::combine_gpu

◆ combine_delta_gpu

float* layer::combine_delta_gpu

◆ forgot_state_gpu

float* layer::forgot_state_gpu

◆ forgot_delta_gpu

float* layer::forgot_delta_gpu

◆ state_gpu

float* layer::state_gpu

◆ state_delta_gpu

float* layer::state_delta_gpu

◆ gate_gpu

float* layer::gate_gpu

◆ gate_delta_gpu

float* layer::gate_delta_gpu

◆ save_gpu

float* layer::save_gpu

◆ save_delta_gpu

float* layer::save_delta_gpu

◆ concat_gpu

float* layer::concat_gpu

◆ concat_delta_gpu

float* layer::concat_delta_gpu

◆ binary_input_gpu

float* layer::binary_input_gpu

◆ binary_weights_gpu

float* layer::binary_weights_gpu

◆ bin_conv_shortcut_in_gpu

float* layer::bin_conv_shortcut_in_gpu

◆ bin_conv_shortcut_out_gpu

float* layer::bin_conv_shortcut_out_gpu

◆ mean_gpu

float* layer::mean_gpu

◆ variance_gpu

float* layer::variance_gpu

◆ m_cbn_avg_gpu

float* layer::m_cbn_avg_gpu

◆ v_cbn_avg_gpu

float* layer::v_cbn_avg_gpu

◆ rolling_mean_gpu

float* layer::rolling_mean_gpu

◆ rolling_variance_gpu

float* layer::rolling_variance_gpu

◆ variance_delta_gpu

float* layer::variance_delta_gpu

◆ mean_delta_gpu

float* layer::mean_delta_gpu

◆ col_image_gpu

float* layer::col_image_gpu

◆ x_gpu

float* layer::x_gpu

◆ x_norm_gpu

float* layer::x_norm_gpu

◆ weights_gpu

float* layer::weights_gpu

◆ weight_updates_gpu

float* layer::weight_updates_gpu

◆ weight_deform_gpu

float* layer::weight_deform_gpu

◆ weight_change_gpu

float* layer::weight_change_gpu

◆ weights_gpu16

float* layer::weights_gpu16

◆ weight_updates_gpu16

float* layer::weight_updates_gpu16

◆ biases_gpu

float* layer::biases_gpu

◆ bias_updates_gpu

float* layer::bias_updates_gpu

◆ bias_change_gpu

float* layer::bias_change_gpu

◆ scales_gpu

float* layer::scales_gpu

◆ scale_updates_gpu

float* layer::scale_updates_gpu

◆ scale_change_gpu

float* layer::scale_change_gpu

◆ input_antialiasing_gpu

float* layer::input_antialiasing_gpu

◆ output_gpu

float* layer::output_gpu

◆ output_avg_gpu

float* layer::output_avg_gpu

◆ activation_input_gpu

float* layer::activation_input_gpu

◆ loss_gpu

float* layer::loss_gpu

◆ delta_gpu

float* layer::delta_gpu

◆ cos_sim_gpu

float* layer::cos_sim_gpu

◆ rand_gpu

float* layer::rand_gpu

◆ drop_blocks_scale

float* layer::drop_blocks_scale

◆ drop_blocks_scale_gpu

float* layer::drop_blocks_scale_gpu

◆ squared_gpu

float* layer::squared_gpu

◆ norms_gpu

float* layer::norms_gpu

◆ gt_gpu

float* layer::gt_gpu

◆ a_avg_gpu

float* layer::a_avg_gpu

◆ input_sizes_gpu

int* layer::input_sizes_gpu

◆ layers_output_gpu

float** layer::layers_output_gpu

◆ layers_delta_gpu

float** layer::layers_delta_gpu

◆ srcTensorDesc

cudnnTensorDescriptor_t layer::srcTensorDesc

◆ dstTensorDesc

cudnnTensorDescriptor_t layer::dstTensorDesc

◆ srcTensorDesc16

cudnnTensorDescriptor_t layer::srcTensorDesc16

◆ dstTensorDesc16

cudnnTensorDescriptor_t layer::dstTensorDesc16

◆ dsrcTensorDesc

cudnnTensorDescriptor_t layer::dsrcTensorDesc

◆ ddstTensorDesc

cudnnTensorDescriptor_t layer::ddstTensorDesc

◆ dsrcTensorDesc16

cudnnTensorDescriptor_t layer::dsrcTensorDesc16

◆ ddstTensorDesc16

cudnnTensorDescriptor_t layer::ddstTensorDesc16

◆ normTensorDesc

cudnnTensorDescriptor_t layer::normTensorDesc

◆ normDstTensorDesc

cudnnTensorDescriptor_t layer::normDstTensorDesc

◆ normDstTensorDescF16

cudnnTensorDescriptor_t layer::normDstTensorDescF16

◆ weightDesc

cudnnFilterDescriptor_t layer::weightDesc

◆ weightDesc16

cudnnFilterDescriptor_t layer::weightDesc16

◆ dweightDesc

cudnnFilterDescriptor_t layer::dweightDesc

◆ dweightDesc16

cudnnFilterDescriptor_t layer::dweightDesc16

◆ convDesc

cudnnConvolutionDescriptor_t layer::convDesc

◆ fw_algo

cudnnConvolutionFwdAlgo_t layer::fw_algo

◆ fw_algo16

cudnnConvolutionFwdAlgo_t layer::fw_algo16

◆ bd_algo

cudnnConvolutionBwdDataAlgo_t layer::bd_algo

◆ bd_algo16

cudnnConvolutionBwdDataAlgo_t layer::bd_algo16

◆ bf_algo

cudnnConvolutionBwdFilterAlgo_t layer::bf_algo

◆ bf_algo16

cudnnConvolutionBwdFilterAlgo_t layer::bf_algo16

◆ poolingDesc

cudnnPoolingDescriptor_t layer::poolingDesc

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

darknet.h

Public Attributes