code: def test_nograd():
      # we want this to raise non-differentiability error
      fun = lambda x: np.allclose(x, (x * 3.0) / 3.0)
      with pytest.raises(TypeError):
          with warnings.catch_warnings(record=True) as w:
              grad(fun)(np.array([1.0, 2.0, 3.0]))
  
file_path: autograd/tests/test_logic.py
imports: from __future__ import division
  from contextlib import contextmanager
  import pytest
  import warnings
  import autograd.numpy
  from autograd import grad, deriv
  from autograd.extend import primitive
  from autograd.test_util import check_grads
  from autograd.core import primitive_vjps
label_desc: Use image node_id 2 for calling a global function with example usage: test_nograd() without return types