code: def broadcast_dim(x):
      """
      Auto broadcast input so that it can fits into a Conv1d
      """
  
      if x.dim() == 2:
          x = x[:, None, :]
      elif x.dim() == 1:
          # If nn.DataParallel is used, this broadcast doesn't work
          x = x[None, None, :]
      elif x.dim() == 3:
          pass
      else:
          raise ValueError(
              "Only support input with shape = (batch, len) or shape = (len)"
          )
      return x
  
imports: import sys
  import torch
  from torch.nn.functional import conv1d, fold
  import numpy
  from time import time
  import math
  from scipy.signal import get_window
  from scipy import signal
  from scipy.fftpack import fft
  import warnings
  from nnAudio.librosa_functions import *
label_desc: Use image node_id 11 for calling a global function with example usage: broadcast_dim(x) and returns: x