class_docstr: LayerNorm for channels of '2D' spatial NCHW tensors 
class_docstr_tok: ["LayerNorm","for","channels","of","'2D","'","spatial","NCHW","tensors"]
code: def __init__(self, num_channels, eps=1e-6, affine=True):
      super().__init__(num_channels, eps=eps, elementwise_affine=affine)
      self._fast_norm = is_fast_norm()
  
imports: import numbers
  from typing import Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from .fast_norm import is_fast_norm, fast_group_norm, fast_layer_norm, fast_rms_norm
label_desc: Use image node_id 1 to create a new LayerNorm2d object from inherited base classes: nn with example: obj = LayerNorm2d(num_channels, eps, affine)