code: def forward(self, input_):
      self._check_input_dim(input_)
  
      return group_norm(
          input_,
          self.num_groups,
          self.running_mean,
          self.running_var,
          self.weight,
          self.bias,
          self.training or not self.track_running_stats,
          self.momentum,
          self.eps,
      )
  
file_path: pywick/pywick/functions/group_norm.py
imports: import torch
  import torch.nn.functional
  from torch.nn.modules.batchnorm import _BatchNorm
label_desc: Use image node_id 3 for calling the _GroupNorm obj's underlying member method code with example usage: obj.forward(input_) and returns: group_norm