code: def _layer_norm_cf(
      x: torch.Tensor,
      weight: torch.Tensor,
      bias: torch.Tensor,
      eps: float,
  ):
      s, u = torch.var_mean(x, dim=1, unbiased=False, keepdim=True)
      x = (x - u) * torch.rsqrt(s + eps)
      x = x * weight[:, None, None] + bias[:, None, None]
      return x
  
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 2 for calling a global function with example usage: _layer_norm_cf(x, weight, bias, eps) and returns: x