code: def unsqueeze_1d(value, dim, value_dim):
      """Unsqueezes a 1-D tensor to the specified number of
      dimension preserving one dimension and creating "dummy" dimensions
      elsewhere
  
      Arguments
      ---------
      value: torch.Tensor
          A 1-D tensor
      dim: int
          the number of dimension
      value_dim: int
          the dimension that the value tensor represents
  
  
      Returns
      -------
      result: torch.Tensor
          a dim-dimensional tensor
      """
      unsqueeze_dim = [None] * dim
      unsqueeze_dim[value_dim] = ...
      return value[unsqueeze_dim]
  
imports: import math
  import os
  import re
  import csv
  import shutil
  import urllib.request
  import collections.abc
  import torch
  import tqdm
  import pathlib
  import speechbrain
  from numbers import Number
label_desc: Use image node_id 26 for calling a global function with example usage: unsqueeze_1d(value, dim, value_dim) and returns: value