mxnet
Public Attributes | List of all members
dnnl_layer_normalization_desc_t Struct Reference

A descriptor of a Layer Normalization operation. More...

#include <dnnl_types.h>

Collaboration diagram for dnnl_layer_normalization_desc_t:
Collaboration graph

Public Attributes

dnnl_primitive_kind_t primitive_kind
 
dnnl_prop_kind_t prop_kind
 
dnnl_memory_desc_t data_desc
 Source and destination memory descriptor. More...
 
dnnl_memory_desc_t diff_data_desc
 Source and destination gradient memory descriptor. More...
 
dnnl_memory_desc_t data_scaleshift_desc
 
dnnl_memory_desc_t diff_data_scaleshift_desc
 
dnnl_memory_desc_t stat_desc
 
float layer_norm_epsilon
 Layer normalization epsilon parameter. More...
 
unsigned flags
 

Detailed Description

A descriptor of a Layer Normalization operation.

Member Data Documentation

dnnl_memory_desc_t dnnl_layer_normalization_desc_t::data_desc

Source and destination memory descriptor.

dnnl_memory_desc_t dnnl_layer_normalization_desc_t::data_scaleshift_desc

Scale and shift data and gradient memory descriptors.

Scaleshift memory descriptor uses 2D dnnl_ab format[2, normalized_dim] where 1-st dimension contains gamma parameter, 2-nd dimension contains beta parameter. Normalized_dim is equal to the last logical dimension of the data tensor across which normalization is performed.

dnnl_memory_desc_t dnnl_layer_normalization_desc_t::diff_data_desc

Source and destination gradient memory descriptor.

dnnl_memory_desc_t dnnl_layer_normalization_desc_t::diff_data_scaleshift_desc
unsigned dnnl_layer_normalization_desc_t::flags
float dnnl_layer_normalization_desc_t::layer_norm_epsilon

Layer normalization epsilon parameter.

dnnl_primitive_kind_t dnnl_layer_normalization_desc_t::primitive_kind

The kind of primitive. Used for self-identifying the primitive descriptor. Must be dnnl_layer_normalization.

dnnl_prop_kind_t dnnl_layer_normalization_desc_t::prop_kind

The kind of propagation. Possible values: dnnl_forward_training, dnnl_forward_inference, dnnl_backward, and dnnl_backward_data.

dnnl_memory_desc_t dnnl_layer_normalization_desc_t::stat_desc

Mean and variance data memory descriptors.

Statistics (mean and variance) memory descriptor is the k-dimensional tensor where k is equal to data_tensor_ndims - 1 and may have any plain (stride[last_dim] == 1) user-provided format.


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