LRN

Classes
struct	dnnl::lrn_forward
	Local response normalization (LRN) forward propagation primitive. More...
struct	dnnl::lrn_backward
	Local response normalization (LRN) backward propagation primitive. More...
struct	dnnl_lrn_desc_t
	A descriptor of a Local Response Normalization (LRN) operation. More...

Functions
dnnl_status_t DNNL_API	dnnl_lrn_forward_desc_init (dnnl_lrn_desc_t *lrn_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *data_desc, dnnl_dim_t local_size, float alpha, float beta, float k)
	Initializes a descriptor for LRN forward propagation primitive.
dnnl_status_t DNNL_API	dnnl_lrn_backward_desc_init (dnnl_lrn_desc_t *lrn_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, dnnl_dim_t local_size, float alpha, float beta, float k)
	Initializes a descriptor for LRN backward propagation primitive.

Detailed Description

A primitive to perform local response normalization (LRN) across or within channels.

See also

Local Response Normalization (LRN) in developer guide

Function Documentation

dnnl_lrn_forward_desc_init()

dnnl_status_t DNNL_API dnnl_lrn_forward_desc_init	(	dnnl_lrn_desc_t *	lrn_desc,
		dnnl_prop_kind_t	prop_kind,
		dnnl_alg_kind_t	alg_kind,
		const dnnl_memory_desc_t *	data_desc,
		dnnl_dim_t	local_size,
		float	alpha,
		float	beta,
		float	k )

Initializes a descriptor for LRN forward propagation primitive.

Inputs:

• src (dnnl_query_src_md, 0)

Outputs:

• dst (dnnl_query_dst_md, 0)
• workspace (dnnl_query_workspace_md, 0), if the underlying implementation requires it; must be queried for using dnnl_primitive_desc_query_md() after a corresponding primitive descriptor is created

Parameters

lrn_desc	Output descriptor for a LRN primitive.
prop_kind	Propagation kind. Possible values are dnnl_forward_training and dnnl_forward_inference.
alg_kind	LRN algorithm kind: either dnnl_lrn_across_channels or dnnl_lrn_within_channel.
data_desc	Source and destination memory descriptor.
local_size	Regularization local size.
alpha	The alpha regularization parameter.
beta	The beta regularization parameter.
k	The k regularization parameter.

Returns

dnnl_success on success and a status describing the error otherwise.

Examples

cnn_inference_f32.c, and cpu_cnn_training_f32.c.

dnnl_lrn_backward_desc_init()

dnnl_status_t DNNL_API dnnl_lrn_backward_desc_init	(	dnnl_lrn_desc_t *	lrn_desc,
		dnnl_alg_kind_t	alg_kind,
		const dnnl_memory_desc_t *	diff_data_desc,
		const dnnl_memory_desc_t *	data_desc,
		dnnl_dim_t	local_size,
		float	alpha,
		float	beta,
		float	k )

Initializes a descriptor for LRN backward propagation primitive.

Inputs:

• src (dnnl_query_src_md, 0)
• diff_dst (dnnl_query_diff_dst_md, 0)
• workspace (dnnl_query_workspace_md, 0), if the underlying implementation requires it; must be queried for using dnnl_primitive_desc_query_md() after a corresponding primitive descriptor is created

Outputs:

• diff_src (dnnl_query_diff_src_md, 0)

Parameters

lrn_desc	Output descriptor for a LRN primitive.
alg_kind	LRN algorithm kind: either dnnl_lrn_across_channels or dnnl_lrn_within_channel.
diff_data_desc	Diff source and diff destination memory descriptor.
data_desc	Source memory descriptor.
local_size	Regularization local size.
alpha	The alpha regularization parameter.
beta	The beta regularization parameter.
k	The k regularization parameter.

Returns

dnnl_success on success and a status describing the error otherwise.

Examples

cpu_cnn_training_f32.c.