code: def forward(self, x):
      if self._fast_norm:
          x = fast_group_norm(
              x, self.num_groups, self.weight, self.bias, self.eps
          )
      else:
          x = F.group_norm(
              x, self.num_groups, self.weight, self.bias, self.eps
          )
      x = self.drop(x)
      x = self.act(x)
      return x
  
imports: from typing import Union, List, Optional, Any
  import torch
  from torch import nn
  from torch.nn import functional
  from torchvision.ops.misc import FrozenBatchNorm2d
  from .create_act import get_act_layer
  from .fast_norm import is_fast_norm, fast_group_norm, fast_layer_norm
  from .trace_utils import _assert
label_desc: Use image node_id 2 for calling the GroupNormAct obj's underlying member method code with example usage: obj.forward(x) and returns: x