code: def remove_weight_norm(
      module: T_module, name: str = "weight"
  ) -> T_module:
      r"""Remove the weight normalization reparameterization from a module.
  
      Args:
          module (Module): containing module
          name (str, optional): name of weight parameter
  
      Example:
          >>> m = weight_norm(nn.Linear(20, 40))
          >>> remove_weight_norm(m)
      """
      for k, hook in module._forward_pre_hooks.items():
          if isinstance(hook, WeightNorm) and hook.name == name:
              hook.remove(module)
              del module._forward_pre_hooks[k]
              return module
  
      raise ValueError(f"weight_norm of '{name}' not found in {module}")
  
file_path: pytorch/torch/nn/utils/weight_norm.py
imports: from torch.nn.parameter import Parameter, UninitializedParameter
  from torch import _weight_norm, norm_except_dim
  from typing import Any, TypeVar
  import warnings
  from ..modules import Module
label_desc: Use image node_id 2 for calling a global function with example usage: remove_weight_norm(module, name) and returns: module