code: def test_fit_dtypes(X, means):
      X = numpy.array(X)
      X = X.astype(numpy.float32)
  
      p = numpy.array(means, dtype=numpy.float32)
      d = StudentT(3, p, p)
      d.fit(X)
      assert d.means.dtype == torch.float32
      assert d.covs.dtype == torch.float32
  
      p = numpy.array(means, dtype=numpy.float64)
      d = StudentT(3, p, p)
      d.fit(X)
      assert d.means.dtype == torch.float64
      assert d.covs.dtype == torch.float64
  
      p = numpy.array(means, dtype=numpy.int32)
      d = StudentT(3, p, p)
      d.fit(X)
      assert d.means.dtype == torch.int32
      assert d.covs.dtype == torch.int32
  
      X = numpy.array(X)
      X = X.astype(numpy.float64)
  
      p = numpy.array(means, dtype=numpy.float64)
      d = StudentT(3, p, p)
      d.fit(X)
      assert d.means.dtype == torch.float64
      assert d.covs.dtype == torch.float64
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.distributions import StudentT
  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 37 for calling a global function with example usage: test_fit_dtypes(X, means) without return types