[train] Enable deprecation warning for legacy xgboost/lightgbm trainer APIs (#57280)

Emit the deprecation warning for the legacy XGBoostTrainer API, in
preparation for Train V2 migration (which only supports the new custom
training function API).

---------

Signed-off-by: Justin Yu <justinvyu@anyscale.com>
Signed-off-by: elliot-barn <elliot.barnwell@anyscale.com>

Author: justinvyu

python/ray/train/lightgbm/lightgbm_trainer.py

@@ -11,12 +11,13 @@
 from ray.train.lightgbm.config import LightGBMConfig
 from ray.train.lightgbm.v2 import LightGBMTrainer as SimpleLightGBMTrainer
 from ray.train.trainer import GenDataset
+from ray.train.utils import _log_deprecation_warning
 from ray.util.annotations import PublicAPI
 
 logger = logging.getLogger(__name__)
 
 
-LEGACY_LIGHTGBMGBM_TRAINER_DEPRECATION_MESSAGE = (
+LEGACY_LIGHTGBM_TRAINER_DEPRECATION_MESSAGE = (
     "Passing in `lightgbm.train` kwargs such as `params`, `num_boost_round`, "
     "`label_column`, etc. to `LightGBMTrainer` is deprecated "
     "in favor of the new API which accepts a `train_loop_per_worker` argument, "
@@ -228,15 +229,14 @@ def __init__(
                 datasets=datasets,
             )
             train_loop_config = params or {}
-        # TODO(justinvyu): [Deprecated] Legacy XGBoostTrainer API
-        # elif train_kwargs:
-        #     _log_deprecation_warning(
-        #         "Passing `lightgbm.train` kwargs to `LightGBMTrainer` is deprecated. "
-        #         f"Got kwargs: {train_kwargs.keys()}\n"
-        #         "Please pass in a `train_loop_per_worker` function instead, "
-        #         "which has full flexibility on the call to `lightgbm.train(**kwargs)`. "
-        #         f"{LEGACY_LIGHTGBMGBM_TRAINER_DEPRECATION_MESSAGE}"
-        #     )
+        elif train_kwargs:
+            _log_deprecation_warning(
+                "Passing `lightgbm.train` kwargs to `LightGBMTrainer` is deprecated. "
+                f"Got kwargs: {train_kwargs.keys()}\n"
+                "In your training function, you can call `lightgbm.train(**kwargs)` "
+                "with arbitrary arguments. "
+                f"{LEGACY_LIGHTGBM_TRAINER_DEPRECATION_MESSAGE}"
+            )
 
         super(LightGBMTrainer, self).__init__(
             train_loop_per_worker=train_loop_per_worker,
@@ -278,8 +278,7 @@ def _get_legacy_train_fn_per_worker(
 
         num_boost_round = num_boost_round or 10
 
-        # TODO: [Deprecated] Legacy LightGBMTrainer API
-        # _log_deprecation_warning(LEGACY_LIGHTGBMGBM_TRAINER_DEPRECATION_MESSAGE)
+        _log_deprecation_warning(LEGACY_LIGHTGBM_TRAINER_DEPRECATION_MESSAGE)
 
         # Initialize a default Ray Train metrics/checkpoint reporting callback if needed
         callbacks = lightgbm_train_kwargs.get("callbacks", [])

python/ray/train/xgboost/xgboost_trainer.py

@@ -9,6 +9,7 @@
 from ray.train import Checkpoint
 from ray.train.constants import TRAIN_DATASET_KEY
 from ray.train.trainer import GenDataset
+from ray.train.utils import _log_deprecation_warning
 from ray.train.xgboost import RayTrainReportCallback, XGBoostConfig
 from ray.train.xgboost.v2 import XGBoostTrainer as SimpleXGBoostTrainer
 from ray.util.annotations import PublicAPI
@@ -19,7 +20,7 @@
 LEGACY_XGBOOST_TRAINER_DEPRECATION_MESSAGE = (
     "Passing in `xgboost.train` kwargs such as `params`, `num_boost_round`, "
     "`label_column`, etc. to `XGBoostTrainer` is deprecated "
-    "in favor of the new API which accepts a ``train_loop_per_worker`` argument, "
+    "in favor of the new API which accepts a training function, "
     "similar to the other DataParallelTrainer APIs (ex: TorchTrainer). "
     "See this issue for more context: "
     "https://github.com/ray-project/ray/issues/50042"
@@ -228,14 +229,13 @@ def __init__(
                 datasets=datasets,
             )
             train_loop_config = params or {}
-        # TODO(justinvyu): [Deprecated] Legacy XGBoostTrainer API
-        # elif train_kwargs:
-        #     _log_deprecation_warning(
-        #         "Passing `xgboost.train` kwargs to `XGBoostTrainer` is deprecated. "
-        #         "Please pass in a `train_loop_per_worker` function instead, "
-        #         "which has full flexibility on the call to `xgboost.train(**kwargs)`. "
-        #         f"{LEGACY_XGBOOST_TRAINER_DEPRECATION_MESSAGE}"
-        #     )
+        elif train_kwargs:
+            _log_deprecation_warning(
+                "Passing `xgboost.train` kwargs to `XGBoostTrainer` is deprecated. "
+                "In your training function, you can call `xgboost.train(**kwargs)` "
+                "with arbitrary arguments. "
+                f"{LEGACY_XGBOOST_TRAINER_DEPRECATION_MESSAGE}"
+            )
 
         super(XGBoostTrainer, self).__init__(
             train_loop_per_worker=train_loop_per_worker,
@@ -277,8 +277,7 @@ def _get_legacy_train_fn_per_worker(
 
         num_boost_round = num_boost_round or 10
 
-        # TODO(justinvyu): [Deprecated] Legacy XGBoostTrainer API
-        # _log_deprecation_warning(LEGACY_XGBOOST_TRAINER_DEPRECATION_MESSAGE)
+        _log_deprecation_warning(LEGACY_XGBOOST_TRAINER_DEPRECATION_MESSAGE)
 
         # Initialize a default Ray Train metrics/checkpoint reporting callback if needed
         callbacks = xgboost_train_kwargs.get("callbacks", [])