code: def test_model_multiple_chunks(client, dtype):
      # tests naive_bayes with n_chunks being greater than one, related to issue
      # https://github.com/rapidsai/cuml/issues/3150
      X = cp.array([[0, 0, 0, 1], [1, 0, 0, 1], [1, 0, 0, 0]])
  
      X = dask.array.from_array(X, chunks=((1, 1, 1), -1)).astype(dtype)
      y = dask.array.from_array(
          [1, 0, 0], asarray=False, fancy=False, chunks=(1)
      ).astype(cp.int32)
  
      model = MultinomialNB()
      model.fit(X, y)
  
      # this test is a code coverage test, it is too small to be a numeric test,
      # but we call score here to exercise the whole model.
      assert 0 <= model.score(X, y) <= 1
  
file_path: cuml/python/cuml/tests/dask/test_dask_naive_bayes.py
imports: from sklearn.metrics import accuracy_score
  from cuml.testing.dask.utils import load_text_corpus
  from cuml.naive_bayes.naive_bayes import MultinomialNB
  from cuml.dask.naive_bayes import MultinomialNB
  import pytest
  import dask.array
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 4 for calling a global function with example usage: test_model_multiple_chunks(client, dtype) without return types