variance, and when set to "False", this module does not track
        such statistics, and initializes statistics buffers
        "running_mean" and "running_var" as "None". When these buffers
        are "None", this module always uses batch statistics. in both
        training and eval modes. Default: "True"
  * **process_group** (*Optional**[**Any**]*) -- synchronization
    of stats happen within each process group individually.
    Default behavior is synchronization across the whole world

Shape:
      * Input: (N, C, +)
  * Output: (N, C, +) (same shape as input)

Note:
 Synchronization of batchnorm statistics occurs only while
 training, i.e. synchronization is disabled when "model.eval()" is
 set or if "self.training" is otherwise "False".

Examples:
  >>> # With Learnable Parameters
  >>> m = nn.SyncBatchNorm(100)
  >>> # creating process group (optional)
  >>> # ranks is a list of int identifying rank ids.
