Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN)  1.0.4
Performance library for Deep Learning
Public Attributes | List of all members
mkldnn_batch_normalization_desc_t Struct Reference

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

#include <mkldnn_types.h>

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Public Attributes

mkldnn_primitive_kind_t primitive_kind
 The kind of primitive. More...
 
mkldnn_prop_kind_t prop_kind
 The kind of propagation. More...
 
mkldnn_memory_desc_t data_desc
 Source and destination memory descriptor.
 
mkldnn_memory_desc_t diff_data_desc
 Source and destination gradient memory descriptor.
 
mkldnn_memory_desc_t data_scaleshift_desc
 Scale and shift data and gradient memory descriptors. More...
 
mkldnn_memory_desc_t stat_desc
 Statistics memory descriptor. More...
 
float batch_norm_epsilon
 Batch normalization epsilon parameter.
 

Detailed Description

A descriptor of a Batch Normalization operation.

Member Data Documentation

◆ primitive_kind

mkldnn_primitive_kind_t mkldnn_batch_normalization_desc_t::primitive_kind

The kind of primitive.

Used for self-identifying the primitive descriptor. Must be mkldnn_batch_normalization.

◆ prop_kind

mkldnn_prop_kind_t mkldnn_batch_normalization_desc_t::prop_kind

The kind of propagation.

Possible values: mkldnn_forward_training, mkldnn_forward_inference, mkldnn_backward, and mkldnn_backward_data.

◆ data_scaleshift_desc

mkldnn_memory_desc_t mkldnn_batch_normalization_desc_t::data_scaleshift_desc

Scale and shift data and gradient memory descriptors.

Scaleshift memory descriptor uses 2D mkldnn_nc format[2,Channels]. 1-st dimension contains gamma parameter, 2-nd dimension contains beta parameter.

◆ stat_desc

mkldnn_memory_desc_t mkldnn_batch_normalization_desc_t::stat_desc

Statistics memory descriptor.

Statistics (mean or variance) descriptor use 1D mkldnn_x format[Channels].


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