def test_score(client):
X, y = load_text_corpus(client)
model = MultinomialNB()
model.fit(X, y)
y_hat = model.predict(X)
score = model.score(X, y)
y_hat_local = y_hat.compute()
y_local = y.compute()
assert (accuracy_score(y_hat_local.get(), y_local) == score)
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)