code: def test_custom_studentt_icdf(total_count, probs, value):
      torch_dist = NegativeBinomial(
          total_count=total_count, probs=probs
      )
      scipy_dist = torch_dist.scipy_nbinom
  
      torch_icdf = torch_dist.icdf(torch.as_tensor(value)).numpy()
      scipy_icdf = scipy_dist.ppf(np.asarray(value))
  
      assert np.allclose(torch_icdf, scipy_icdf)
  
imports: import pytest
  import numpy
  import torch
  from gluonts.torch.distributions.negative_binomial import NegativeBinomial
label_desc: Use image node_id 3 for calling a global function with example usage: test_custom_studentt_icdf(total_count, probs, value) without return types