class_docstr: Cross-replica Batch Normalization.
  
  At every step the full batch is used to calculate the batch statistics even
  within a distributed setting (note only with ``snt.(Tpu)Replicator``).
  
  See :class:`BaseBatchNorm` for details.
  
  Attributes:
    scale: If ``create_scale=True``, a trainable :tf:`Variable` holding the
      current scale after the module is connected for the first time.
    offset: If ``create_offset``, a trainable :tf:`Variable` holding the current
      offset after the module is connected for the first time.
code: def _initialize(self, inputs: tf.Tensor):
      super()._initialize(inputs)
  
      # Always use the unfused op here as mean/var are calculated before the op is
      # called so no speed-up is gained from the fused op
      self._fused = False
  
file_path: sonnet/sonnet/src/distribute/distributed_batch_norm.py
imports: from typing import Optional, Tuple
  from sonnet.src import batch_norm
  from sonnet.src import initializers
  from sonnet.src import metrics
  from sonnet.src import once
  from sonnet.src import types
  import tensorflow
label_desc: Use image node_id 2 for calling the CrossReplicaBatchNorm obj's underlying member method code with example usage: obj._initialize(inputs) without return types