code: def test_from_summaries_dtypes(X, probs):
      p = [numpy.array(prob, dtype=numpy.float32) for prob in probs]
      d = ConditionalCategorical(p)
      d.summarize(X)
      d.from_summaries()
      assert d.probs[0].dtype == torch.float32
      assert d._log_probs.dtype == torch.float32
  
      p = [numpy.array(prob, dtype=numpy.float64) for prob in probs]
      d = ConditionalCategorical(p)
      d.summarize(X)
      d.from_summaries()
      assert d.probs[0].dtype == torch.float64
      assert d._log_probs.dtype == torch.float64
  
imports: import numpy
  import torch
  import pytest
  from pomegranate.distributions import ConditionalCategorical
  from ._utils import _test_initialization_raises_one_parameter
  from ._utils import _test_initialization
  from ._utils import _test_predictions
  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 29 for calling a global function with example usage: test_from_summaries_dtypes(X, probs) without return types