batchnorm_layer.cpp File Reference

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Functions
void	backward_batchnorm_layer (Darknet::Layer &l, Darknet::NetworkState state)
void	backward_batchnorm_layer_gpu (Darknet::Layer &l, Darknet::NetworkState state)
void	backward_scale_cpu (float *x_norm, float *delta, int batch, int n, int size, float *scale_updates)
void	forward_batchnorm_layer (Darknet::Layer &l, Darknet::NetworkState state)
void	forward_batchnorm_layer_gpu (Darknet::Layer &l, Darknet::NetworkState state)
void	mean_delta_cpu (float *delta, float *variance, int batch, int filters, int spatial, float *mean_delta)
void	normalize_delta_cpu (float *x, float *mean, float *variance, float *mean_delta, float *variance_delta, int batch, int filters, int spatial, float *delta)
void	pull_batchnorm_layer (Darknet::Layer &l)
void	push_batchnorm_layer (Darknet::Layer &l)
void	resize_batchnorm_layer (Darknet::Layer *l, int w, int h)
void	update_batchnorm_layer (Darknet::Layer &l, int batch, float learning_rate, float momentum, float decay)
void	update_batchnorm_layer_gpu (Darknet::Layer &l, int batch, float learning_rate_init, float momentum, float decay, float loss_scale)
void	variance_delta_cpu (float *x, float *delta, float *mean, float *variance, int batch, int filters, int spatial, float *variance_delta)

Function Documentation

backward_batchnorm_layer()

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

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backward_batchnorm_layer_gpu()

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

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backward_scale_cpu()

void backward_scale_cpu	(	float *	x_norm,
		float *	delta,
		int	batch,
		int	n,
		int	size,
		float *	scale_updates
	)

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forward_batchnorm_layer()

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

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forward_batchnorm_layer_gpu()

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

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mean_delta_cpu()

void mean_delta_cpu	(	float *	delta,
		float *	variance,
		int	batch,
		int	filters,
		int	spatial,
		float *	mean_delta
	)

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normalize_delta_cpu()

void normalize_delta_cpu	(	float *	x,
		float *	mean,
		float *	variance,
		float *	mean_delta,
		float *	variance_delta,
		int	batch,
		int	filters,
		int	spatial,
		float *	delta
	)

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pull_batchnorm_layer()

void pull_batchnorm_layer

(

Darknet::Layer &

l

)

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push_batchnorm_layer()

void push_batchnorm_layer

(

Darknet::Layer &

l

)

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resize_batchnorm_layer()

void resize_batchnorm_layer	(	Darknet::Layer *	l,
		int	w,
		int	h
	)

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update_batchnorm_layer()

void update_batchnorm_layer	(	Darknet::Layer &	l,
		int	batch,
		float	learning_rate,
		float	momentum,
		float	decay
	)

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update_batchnorm_layer_gpu()

void update_batchnorm_layer_gpu	(	Darknet::Layer &	l,
		int	batch,
		float	learning_rate_init,
		float	momentum,
		float	decay,
		float	loss_scale
	)

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variance_delta_cpu()

void variance_delta_cpu	(	float *	x,
		float *	delta,
		float *	mean,
		float *	variance,
		int	batch,
		int	filters,
		int	spatial,
		float *	variance_delta
	)

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