code: def manual_var(
      x, dim: Union[int, Sequence[int]], diff_sqm: bool = False
  ):
      xm = x.mean(dim=dim, keepdim=True)
      if diff_sqm:
          # difference of squared mean and mean squared, faster on TPU can be less stable
          var = ((x * x).mean(dim=dim, keepdim=True) - (xm * xm)).clamp(
              0
          )
      else:
          var = ((x - xm) * (x - xm)).mean(dim=dim, keepdim=True)
      return var
  
imports: from typing import Sequence, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from .create_act import create_act_layer
  from .trace_utils import _assert
label_desc: Use image node_id 4 for calling a global function with example usage: manual_var(x, dim, diff_sqm) and returns: var