class_docstr: Layer norm with transpose
class_docstr_tok: ["Layer","norm","with","transpose"]
code: def forward(self, input: Tensor) -> Tensor:
      x = input.transpose(-2, -1)
      x = nn.functional.layer_norm(
          x, self.normalized_shape, self.weight, self.bias, self.eps
      )
      x = x.transpose(-2, -1)
      return x
  
imports: import logging
  from typing import List, Optional, Tuple
  import torch
  from torch import nn, Tensor
  from torch.nn import Module, Parameter
  from .wavlm_attention import WavLMSelfAttention
label_desc: Use image node_id 1 for calling the LayerNorm obj's underlying member method code with example usage: obj.forward(input) and returns: x