code: def forward(self, x: torch.Tensor) -> torch.Tensor:
      out = x - torch.mean(x, dim=1, keepdim=True)
      out = out / torch.sqrt(
          torch.square(out).mean(dim=1, keepdim=True) + self.eps
      )
      if self.elementwise_affine:
          out = out * self.weight.view(1, -1, 1, 1) + self.bias.view(
              1, -1, 1, 1
          )
      return out
  
file_path: kornia/kornia/contrib/models/efficient_vit/nn/norm.py
imports: from __future__ import annotations
  from typing import Any, Optional
  import torch
  from torch import nn
  from kornia.contrib.models.efficient_vit.utils import build_kwargs_from_config
label_desc: Use image node_id 1 for calling the LayerNorm2d obj's underlying member method code with example usage: obj.forward(x) and returns: out