code: def test_neg_logprob():
      """distribution test"""
      logits = torch.from_numpy(np.random.randn(5))
      dist = BernoulliProbabilityDistribution(
          logits=logits, action_space=spaces.MultiBinary(5)
      )
      sample = dist.sample()
      assert np.allclose(
          dist.neg_log_prob(actions=sample).numpy(),
          -dist.log_prob(actions=sample).numpy(),
      )
  
file_path: maze/maze/test/distributions/test_distribution.py
imports: import numpy
  import pytest
  import torch
  from gym import spaces
  from maze.distributions.bernoulli import BernoulliProbabilityDistribution
  from maze.distributions.distribution import ProbabilityDistribution
label_desc: Use image node_id 1 for calling a global function with example usage: test_neg_logprob() without return types