code: def test_fit_raises(model, X, w):
      assert_raises(ValueError, model.fit, [X])
      assert_raises(ValueError, model.fit, X[0])
      assert_raises((ValueError, TypeError), model.fit, X[0][0])
      assert_raises(ValueError, model.fit, [x[:-1] for x in X])
      assert_raises(
          ValueError, model.fit, [[-0.1 for i in range(3)] for x in X]
      )
  
      assert_raises(ValueError, model.fit, [X], w)
      assert_raises(ValueError, model.fit, X, [w])
      assert_raises(ValueError, model.fit, [X], [w])
      assert_raises(ValueError, model.fit, X[: len(X) - 1], w)
      assert_raises(ValueError, model.fit, X, w[: len(w) - 1])
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.gmm import GeneralMixtureModel
  from pomegranate.distributions import Exponential
  from .distributions._utils import _test_initialization_raises_one_parameter
  from .distributions._utils import _test_initialization
  from .distributions._utils import _test_predictions
  from .distributions._utils import _test_efd_from_summaries
  from .distributions._utils import _test_raises
  from nose.tools import assert_raises
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 35 for calling a global function with example usage: test_fit_raises(model, X, w) without return types