code: def test_custom_neg_bin_cdf(total_count, probs, value):
      torch_dist = NegativeBinomial(
          total_count=total_count, probs=probs
      )
      scipy_dist = torch_dist.scipy_nbinom
  
      torch_cdf = torch_dist.cdf(torch.as_tensor(value)).numpy()
      scipy_cdf = scipy_dist.cdf(np.asarray(value))
  
      assert np.allclose(torch_cdf, scipy_cdf)
  
imports: import pytest
  import numpy
  import torch
  from gluonts.torch.distributions.negative_binomial import NegativeBinomial
label_desc: Use image node_id 2 for calling a global function with example usage: test_custom_neg_bin_cdf(total_count, probs, value) without return types