Merge remote-tracking branch 'origin/master' into fix_freebsd

python-package/xgboost/__init__.py

@@ -5,15 +5,7 @@
 
 from . import tracker  # noqa
 from . import collective, dask
-from .core import (
-    Booster,
-    DataIter,
-    DeviceQuantileDMatrix,
-    DMatrix,
-    QuantileDMatrix,
-    _py_version,
-    build_info,
-)
+from .core import Booster, DataIter, DMatrix, QuantileDMatrix, _py_version, build_info
 from .tracker import RabitTracker  # noqa
 from .training import cv, train
 
@@ -38,7 +30,6 @@
 __all__ = [
     # core
     "DMatrix",
-    "DeviceQuantileDMatrix",
     "QuantileDMatrix",
     "Booster",
     "DataIter",

python-package/xgboost/core.py

@@ -1635,20 +1635,6 @@ def _init(
         self.handle = handle
 
 
-class DeviceQuantileDMatrix(QuantileDMatrix):
-    """Use `QuantileDMatrix` instead.
-
-    .. deprecated:: 1.7.0
-
-    .. versionadded:: 1.1.0
-
-    """
-
-    def __init__(self, *args: Any, **kwargs: Any) -> None:
-        warnings.warn("Please use `QuantileDMatrix` instead.", FutureWarning)
-        super().__init__(*args, **kwargs)
-
-
 Objective = Callable[[np.ndarray, DMatrix], Tuple[np.ndarray, np.ndarray]]
 Metric = Callable[[np.ndarray, DMatrix], Tuple[str, float]]
 
@@ -2650,7 +2636,7 @@ def save_raw(self, raw_format: str = "ubj") -> bytearray:
         Parameters
         ----------
         raw_format :
-            Format of output buffer. Can be `json`, `ubj` or `deprecated`.
+            Format of output buffer. Can be `json` or `ubj`.
 
         Returns
         -------

python-package/xgboost/dask/__init__.py

@@ -711,20 +711,6 @@ def _create_fn_args(self, worker_addr: str) -> Dict[str, Any]:
         return args
 
 
-class DaskDeviceQuantileDMatrix(DaskQuantileDMatrix):
-    """Use `DaskQuantileDMatrix` instead.
-
-    .. deprecated:: 1.7.0
-
-    .. versionadded:: 1.2.0
-
-    """
-
-    def __init__(self, *args: Any, **kwargs: Any) -> None:
-        warnings.warn("Please use `DaskQuantileDMatrix` instead.", FutureWarning)
-        super().__init__(*args, **kwargs)
-
-
 def _create_quantile_dmatrix(
     feature_names: Optional[FeatureNames],
     feature_types: Optional[Union[Any, List[Any]]],

tests/python/test_model_io.py

@@ -75,26 +75,10 @@ def run_model_json_io(self, parameters: dict, ext: str) -> None:
         from_ubjraw = xgb.Booster()
         from_ubjraw.load_model(ubj_raw)
 
-        if parameters.get("multi_strategy", None) != "multi_output_tree":
-            # Old binary model is not supported for vector leaf.
-            with pytest.warns(Warning, match="Model format is default to UBJSON"):
-                old_from_json = from_jraw.save_raw(raw_format="deprecated")
-                old_from_ubj = from_ubjraw.save_raw(raw_format="deprecated")
-
-            assert old_from_json == old_from_ubj
-
         raw_json = bst.save_raw(raw_format="json")
         pretty = json.dumps(json.loads(raw_json), indent=2) + "\n\n"
         bst.load_model(bytearray(pretty, encoding="ascii"))
 
-        if parameters.get("multi_strategy", None) != "multi_output_tree":
-            # old binary model is not supported.
-            with pytest.warns(Warning, match="Model format is default to UBJSON"):
-                old_from_json = from_jraw.save_raw(raw_format="deprecated")
-                old_from_ubj = from_ubjraw.save_raw(raw_format="deprecated")
-
-            assert old_from_json == old_from_ubj
-
         rng = np.random.default_rng()
         X = rng.random(size=from_jraw.num_features() * 10).reshape(
             (10, from_jraw.num_features())
@@ -126,11 +110,6 @@ def test_categorical_model_io(self) -> None:
         predt_0 = booster.predict(Xy)
 
         with tempfile.TemporaryDirectory() as tempdir:
-            path = os.path.join(tempdir, "model.deprecated")
-            with pytest.raises(ValueError, match=r".*JSON/UBJSON.*"):
-                with pytest.warns(Warning, match="Model format is default to UBJSON"):
-                    booster.save_model(path)
-
             path = os.path.join(tempdir, "model.json")
             booster.save_model(path)
             booster = xgb.Booster(model_file=path)
@@ -181,34 +160,6 @@ def test_json_io_schema(self) -> None:
                 objectives_from_schema.add(j_obj["properties"]["name"]["const"])
             assert set(objectives) == objectives_from_schema
 
-    def test_model_binary_io(self) -> None:
-        model_path = "test_model_binary_io.deprecated"
-        parameters = {
-            "tree_method": "hist",
-            "booster": "gbtree",
-            "scale_pos_weight": "0.5",
-        }
-        X = np.random.random((10, 3))
-        y = np.random.random((10,))
-        dtrain = xgb.DMatrix(X, y)
-        bst = xgb.train(parameters, dtrain, num_boost_round=2)
-        with pytest.warns(Warning, match="Model format is default to UBJSON"):
-            bst.save_model(model_path)
-        bst = xgb.Booster(model_file=model_path)
-        os.remove(model_path)
-        config = json.loads(bst.save_config())
-        assert (
-            float(config["learner"]["objective"]["reg_loss_param"]["scale_pos_weight"])
-            == 0.5
-        )
-
-        buf = bst.save_raw()
-        from_raw = xgb.Booster()
-        from_raw.load_model(buf)
-
-        buf_from_raw = from_raw.save_raw()
-        assert buf == buf_from_raw
-
     def test_with_pathlib(self) -> None:
         """Saving and loading model files from paths."""
         save_path = Path("model.ubj")
@@ -269,41 +220,19 @@ def rename(src: str, dst: str) -> None:
             os.rename(src, dst)
 
         with tempfile.TemporaryDirectory() as tmpdir:
-            path_dep = os.path.join(tmpdir, "model.deprecated")
-            # save into deprecated format
-            with pytest.warns(UserWarning, match="UBJSON"):
-                booster.save_model(path_dep)
-
             path_ubj = os.path.join(tmpdir, "model.ubj")
-            rename(path_dep, path_ubj)
-
-            with pytest.raises(ValueError, match="{"):
-                xgb.Booster(model_file=path_ubj)
-
             path_json = os.path.join(tmpdir, "model.json")
+
+            booster.save_model(path_ubj)
             rename(path_ubj, path_json)
 
             with pytest.raises(ValueError, match="{"):
                 xgb.Booster(model_file=path_json)
 
-            # save into ubj format
-            booster.save_model(path_ubj)
-            rename(path_ubj, path_dep)
-            # deprecated is not a recognized format internally, XGBoost can guess the
-            # right format
-            xgb.Booster(model_file=path_dep)
-            rename(path_dep, path_json)
-            with pytest.raises(ValueError, match="Expecting"):
-                xgb.Booster(model_file=path_json)
-
-            # save into JSON format
             booster.save_model(path_json)
-            rename(path_json, path_dep)
-            # deprecated is not a recognized format internally, XGBoost can guess the
-            # right format
-            xgb.Booster(model_file=path_dep)
-            rename(path_dep, path_ubj)
-            with pytest.raises(ValueError, match="Expecting"):
+            rename(path_json, path_ubj)
+
+            with pytest.raises(ValueError, match="{"):
                 xgb.Booster(model_file=path_ubj)
 
             # save model without file extension
@@ -382,11 +311,6 @@ def test_sklearn_model() -> None:
     from sklearn.datasets import load_digits
     from sklearn.model_selection import train_test_split
 
-    with tempfile.TemporaryDirectory() as tempdir:
-        model_path = os.path.join(tempdir, "digits.deprecated")
-        with pytest.warns(Warning, match="Model format is default to UBJSON"):
-            save_load_model(model_path)
-
     with tempfile.TemporaryDirectory() as tempdir:
         model_path = os.path.join(tempdir, "digits.model.json")
         save_load_model(model_path)