code: def _test_mean_shift(
      self, bandwidth=None, backend="torch", extra_config={}
  ):
      for cluster_all in [True, False]:
          model = MeanShift(
              bandwidth=bandwidth, cluster_all=cluster_all
          )
          np.random.seed(0)
          X = np.random.rand(100, 200)
          X = np.array(X, dtype=np.float32)
  
          model.fit(X)
          torch_model = hummingbird.ml.convert(
              model, backend, X, extra_config=extra_config
          )
          self.assertTrue(torch_model is not None)
          np.testing.assert_allclose(
              model.predict(X),
              torch_model.predict(X),
              rtol=1e-6,
              atol=1e-6,
          )
  
imports: import unittest
  import warnings
  import numpy
  import torch
  from sklearn.cluster import KMeans
  import hummingbird.ml
  from hummingbird.ml import constants
  from hummingbird.ml._utils import tvm_installed
label_desc: Use image node_id 9 for calling the TestSklearnClustering obj's underlying member method code with example usage: obj._test_mean_shift(bandwidth, backend, extra_config) without return types