Take datatable as row major input. (#8472)

* Take datatable as row major input.

Try to avoid a transform with dense table.

tests/python/test_dt.py

@@ -2,52 +2,40 @@ import numpy as np
 import pytest
 
 import xgboost as xgb
-from xgboost import testing as tm
 
-try:
-    import datatable as dt
-    import pandas as pd
-except ImportError:
-    pass
-
-pytestmark = pytest.mark.skipif(
-    tm.no_dt()['condition'] or tm.no_pandas()['condition'],
-    reason=tm.no_dt()['reason'] + ' or ' + tm.no_pandas()['reason'])
+dt = pytest.importorskip("datatable")
+pd = pytest.importorskip("pandas")
 
 
 class TestDataTable:
-
-    def test_dt(self):
-        df = pd.DataFrame([[1, 2., True], [2, 3., False]],
-                          columns=['a', 'b', 'c'])
+    def test_dt(self) -> None:
+        df = pd.DataFrame([[1, 2.0, True], [2, 3.0, False]], columns=["a", "b", "c"])
         dtable = dt.Frame(df)
         labels = dt.Frame([1, 2])
         dm = xgb.DMatrix(dtable, label=labels)
-        assert dm.feature_names == ['a', 'b', 'c']
-        assert dm.feature_types == ['int', 'float', 'i']
+        assert dm.feature_names == ["a", "b", "c"]
+        assert dm.feature_types == ["int", "float", "i"]
         assert dm.num_row() == 2
         assert dm.num_col() == 3
 
         np.testing.assert_array_equal(np.array([1, 2]), dm.get_label())
 
         # overwrite feature_names
-        dm = xgb.DMatrix(dtable, label=pd.Series([1, 2]),
-                         feature_names=['x', 'y', 'z'])
-        assert dm.feature_names == ['x', 'y', 'z']
+        dm = xgb.DMatrix(dtable, label=pd.Series([1, 2]), feature_names=["x", "y", "z"])
+        assert dm.feature_names == ["x", "y", "z"]
         assert dm.num_row() == 2
         assert dm.num_col() == 3
 
         # incorrect dtypes
-        df = pd.DataFrame([[1, 2., 'x'], [2, 3., 'y']],
-                          columns=['a', 'b', 'c'])
+        df = pd.DataFrame([[1, 2.0, "x"], [2, 3.0, "y"]], columns=["a", "b", "c"])
         dtable = dt.Frame(df)
         with pytest.raises(ValueError):
             xgb.DMatrix(dtable)
 
-        df = pd.DataFrame({'A=1': [1, 2, 3], 'A=2': [4, 5, 6]})
+        df = pd.DataFrame({"A=1": [1, 2, 3], "A=2": [4, 5, 6]})
         dtable = dt.Frame(df)
         dm = xgb.DMatrix(dtable)
-        assert dm.feature_names == ['A=1', 'A=2']
-        assert dm.feature_types == ['int', 'int']
+        assert dm.feature_names == ["A=1", "A=2"]
+        assert dm.feature_types == ["int", "int"]
         assert dm.num_row() == 3
         assert dm.num_col() == 2