code: def forward(self, x: Tensor) -> Tensor:
      u = x.mean(1, keepdim=True)
      s = (x - u).pow(2).mean(1, keepdim=True)
      x = (x - u) / (s + self.eps).sqrt()
      x = self.weight[:, None, None] * x + self.bias[:, None, None]
      return x
  
imports: from __future__ import annotations
  import torch
  import torch.nn.functional
  from torch import nn
  from kornia.core import Module, Tensor, pad
label_desc: Use image node_id 2 for calling the LayerNorm2d obj's underlying member method code with example usage: obj.forward(x) and returns: x