class_docstr: Normalize each channel separately over time and batch.
      
class_docstr_tok: ["Normalize","each","channel","separately","over","time","and","batch","."]
code: def __init__(
      self,
      channels,
      affine=True,
      track_running_stats=True,
      momentum=0.1,
  ):
      super().__init__(
          channels,
          affine=affine,
          track_running_stats=track_running_stats,
          momentum=momentum,
      )
  
file_path: TTS/TTS/tts/layers/generic/normalization.py
imports: import torch
  from torch import nn
label_desc: Use image node_id 1 to create a new TemporalBatchNorm1d object from inherited base classes: nn with example: obj = TemporalBatchNorm1d(channels, affine, track_running_stats, momentum)