code: def WNConvTranspose1d(*args, **kwargs):
      """
      Apply weight normalization to a 1D transposed convolutional layer.
  
      Parameters
      ----------
      *args
          Variable length argument list for nn.ConvTranspose1d.
      **kwargs
          Arbitrary keyword arguments for nn.ConvTranspose1d.
  
      Returns
      -------
      torch.nn.Module
          The weight-normalized nn.ConvTranspose1d layer.
      """
      return weight_norm(nn.ConvTranspose1d(*args, **kwargs))
  
imports: import math
  from pathlib import Path
  from typing import List, Union
  import logging
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.utils.parametrizations import weight_norm
label_desc: Use image node_id 2 for calling a global function with example usage: WNConvTranspose1d() and returns: weight_norm