code: def test_categorical_exact_large_pseudocount():
      numpy.random.seed(0)
      X = numpy.random.randint(3, size=(50, 8))
  
      structure = _categorical_exact(X, pseudocount=10)
      assert_tuple_equal(structure, ((), (), (), (), (), (), (), ()))
  
      structure = _categorical_exact(X, pseudocount=5)
      assert_tuple_equal(structure, ((), (), (), (), (), (), (), ()))
  
      structure = _categorical_exact(X, pseudocount=2)
      assert_tuple_equal(structure, ((), (), (), (), (), (), (), ()))
  
      structure = _categorical_exact(X, pseudocount=1)
      assert_tuple_equal(structure, ((), (), (), (), (), (), (), ()))
  
      structure = _categorical_exact(X, pseudocount=0.1)
      assert_tuple_equal(structure, ((), (), (), (), (), (), (), ()))
  
      structure = _categorical_exact(X, pseudocount=1e-8)
      assert_tuple_equal(structure, ((), (), (), (), (), (0,), (), ()))
  
imports: import numpy
  import torch
  import pytest
  from pomegranate.bayesian_network import BayesianNetwork
  from pomegranate.bayesian_network import _from_structure
  from pomegranate.bayesian_network import _learn_structure
  from pomegranate.bayesian_network import _categorical_exact
  from pomegranate.bayesian_network import _categorical_chow_liu
  from pomegranate.distributions import Categorical
  from pomegranate.distributions import ConditionalCategorical
  from nose.tools import assert_raises
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 14 for calling a global function with example usage: test_categorical_exact_large_pseudocount() without return types