code: def test_log_probability_dtypes():
      X = numpy.random.uniform(0, 5, size=(10, 3)).astype(numpy.float32)
      X_int = X.astype("int32")
      p = numpy.array([0.1, 5.3, 2.5], dtype=numpy.float32)
  
      y = Normal(p, p, covariance_type="diag").log_probability(X)
      assert y.dtype == torch.float32
  
      y = Normal(p, p, covariance_type="diag").log_probability(X_int)
      assert y.dtype == torch.float32
  
      X = numpy.random.uniform(0, 5, size=(10, 3)).astype(numpy.float64)
      X_int = X.astype("int32")
      p = numpy.array([0.1, 5.3, 2.5], dtype=numpy.float64)
  
      y = Normal(p, p, covariance_type="diag").log_probability(X)
      assert y.dtype == torch.float64
  
      y = Normal(p, p, covariance_type="diag").log_probability(X_int)
      assert y.dtype == torch.float64
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.distributions import Normal
  from ._utils import _test_initialization_raises_two_parameters
  from ._utils import _test_initialization
  from ._utils import _test_predictions
  from ._utils import _test_efd_from_summaries
  from ._utils import _test_raises
  from nose.tools import assert_raises
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 17 for calling a global function with example usage: test_log_probability_dtypes() without return types