Complete cudf support. (#4850)

* Handles missing value.
* Accept all floating point and integer types.
* Move to cudf 9.0 API.
* Remove requirement on `null_count`.
* Arbitrary column types support.

tests/python/test_with_dask.py

@@ -19,7 +19,7 @@ pytestmark = pytest.mark.skipif(**tm.no_dask())
 
 def run_train():
     # Contains one label equal to rank
-    dmat = xgb.DMatrix([[0]], label=[xgb.rabit.get_rank()])
+    dmat = xgb.DMatrix(np.array([[0]]), label=[xgb.rabit.get_rank()])
     bst = xgb.train({"eta": 1.0, "lambda": 0.0}, dmat, 1)
     pred = bst.predict(dmat)
     expected_result = np.average(range(xgb.rabit.get_world_size()))
@@ -78,7 +78,7 @@ def test_get_local_data(client):
 
 def run_sklearn():
     # Contains one label equal to rank
-    X = [[0]]
+    X = np.array([[0]])
     y = [xgb.rabit.get_rank()]
     model = xgb.XGBRegressor(learning_rate=1.0)
     model.fit(X, y)