code: def _test_multinomialnb_classifer(
      self,
      num_classes,
      alpha=1.0,
      fit_prior=False,
      class_prior=None,
      labels_shift=0,
      backend="torch",
  ):
      model = MultinomialNB(
          alpha=alpha, fit_prior=fit_prior, class_prior=class_prior
      )
      np.random.seed(0)
      X = np.random.rand(100, 200)
      X = np.array(X, dtype=np.float32)
      y = np.random.randint(num_classes, size=100) + labels_shift
  
      model.fit(X, y)
      torch_model = hummingbird.ml.convert(model, backend, X)
      self.assertTrue(torch_model is not None)
      np.testing.assert_allclose(
          model.predict_proba(X),
          torch_model.predict_proba(X),
          rtol=1e-6,
          atol=1e-5,
      )
  
imports: import unittest
  import warnings
  import numpy
  import torch
  from sklearn.naive_bayes import BernoulliNB, GaussianNB, MultinomialNB
  import hummingbird.ml
  from hummingbird.ml._utils import tvm_installed
label_desc: Use image node_id 16 for calling the TestSklearnNBClassifier obj's underlying member method code with example usage: obj._test_multinomialnb_classifer(num_classes, alpha, fit_prior, class_prior, labels_shift, backend) without return types