code: def create_random_data(shape, rank, noise_level):
      I, J, K = shape  # noqa: E741
      pf2 = tl.random.random_parafac2(
          [(J, K) for i in range(I)], rank=rank, random_state=rng
      )
  
      X = pf2.to_tensor()
      X_norm = [tl.norm(Xi) for Xi in X]
  
      noise = [rng.standard_normal((J, K)) for i in range(I)]
      noise = [
          noise_level * X_norm[i] / tl.norm(E_i)
          for i, E_i in enumerate(noise)
      ]
      return [X_i + E_i for X_i, E_i in zip(X, noise)]
  
imports: from time import monotonic
  import tensorly
  from tensorly.decomposition import parafac2
  import tensorly.preprocessing
label_desc: Use image node_id 1 for calling a global function with example usage: create_random_data(shape, rank, noise_level) and returns: unknown