code: def iter_indices(tensor):
      if tensor.dim() == 0:
          return range(0)
      if tensor.dim() == 1:
          return range(tensor.size(0))
      return product(*(range(s) for s in tensor.size()))
  
imports: import contextlib
  import numbers
  import os
  import re
  import warnings
  from itertools import product
  import numpy
  import pytest
  import torch
  import torch.cuda
  from numpy.testing import assert_allclose
  from pytest import approx
label_desc: Use image node_id 10 for calling a global function with example usage: iter_indices(tensor) and returns: product, range, range