A descriptor of a Batch Normalization operation. More...
#include <dnnl_types.h>
Public Attributes | |
| dnnl_primitive_kind_t | primitive_kind |
| The kind of primitive. More... | |
| dnnl_prop_kind_t | prop_kind |
| The kind of propagation. More... | |
| dnnl_memory_desc_t | data_desc |
| Source and destination memory descriptor. | |
| dnnl_memory_desc_t | diff_data_desc |
| Source and destination gradient memory descriptor. | |
| dnnl_memory_desc_t | data_scaleshift_desc |
| Scale and shift data and gradient memory descriptors. More... | |
| dnnl_memory_desc_t | stat_desc |
| Statistics memory descriptor. More... | |
| float | batch_norm_epsilon |
| Batch normalization epsilon parameter. | |
A descriptor of a Batch Normalization operation.
| dnnl_primitive_kind_t dnnl_batch_normalization_desc_t::primitive_kind |
The kind of primitive.
Used for self-identifying the primitive descriptor. Must be dnnl_batch_normalization.
| dnnl_prop_kind_t dnnl_batch_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_batch_normalization_desc_t::data_scaleshift_desc |
Scale and shift data and gradient memory descriptors.
Scaleshift memory descriptor uses 2D dnnl_nc format[2,Channels]. 1-st dimension contains gamma parameter, 2-nd dimension contains beta parameter.
| dnnl_memory_desc_t dnnl_batch_normalization_desc_t::stat_desc |
Statistics memory descriptor.
Statistics (mean or variance) descriptor use 1D dnnl_x format[Channels].
