code: def create_ds_iid(num_points: int, noise_mult: float = 0.25):
      """
      Creates heavy-tailed gaussian iid. Returns tensor of shape (1, 1,
      num_points).
  
      Arguments:
        num_points: int, number of points in the dataset.
        noise_mult: float, standard deviation
      """
      values = np.random.normal(0, noise_mult, size=num_points)
      values = add_spikes(values)
      return torch.tensor(values.reshape(1, 1, -1))
  
file_path: gluonts/src/gluonts/nursery/spliced_binned_pareto/data_functions.py
imports: from typing import List
  import numpy
  from scipy import stats
  import torch
label_desc: Use image node_id 3 for calling a global function with example usage: create_ds_iid(num_points, noise_mult) and returns: torch