code: def test_mask_noop(shape):
      d = NormalBomb(0, 1).mask(False)
      if shape is not None:
          d = d.expand(shape)
      x = d.sample()
  
      actual = d.log_prob(x)
      assert_equal(actual, torch.zeros(shape if shape else ()))
  
      actual = d.score_parts(x)
      assert_equal(actual.log_prob, torch.zeros(shape if shape else ()))
  
file_path: pyro/tests/distributions/test_mask.py
imports: import pytest
  import torch
  from torch import tensor
  from torch.distributions import kl_divergence
  from pyro.distributions.torch import Bernoulli, Normal
  from pyro.distributions.util import broadcast_shape, scale_and_mask
  from tests.common import assert_equal
label_desc: Use image node_id 7 for calling a global function with example usage: test_mask_noop(shape) without return types