Use new train.report API (#292)

We are converging on using train.report throughout the Ray library code base instead of tune.report.

requirements/test-requirements.txt

@@ -2,12 +2,11 @@ packaging
 petastorm
 pytest
 pyarrow
-ray[tune, data]
+ray[tune, data, default]
 scikit-learn
 modin
 dask
 
 #workaround for now
 protobuf<4.0.0
 tensorboardX==2.2
-aiohttp

xgboost_ray/examples/simple_tune.py

@@ -66,7 +66,7 @@ def main(cpus_per_actor, num_actors, num_samples):
 
     # Load the best model checkpoint.
     best_bst = xgboost_ray.tune.load_model(
-        os.path.join(analysis.best_logdir, "tuned.xgb")
+        os.path.join(analysis.best_trial.local_path, "tuned.xgb")
     )
 
     best_bst.save_model("best_model.xgb")

xgboost_ray/main.py

@@ -557,7 +557,7 @@ def __init__(
 
         self.checkpoint_frequency = checkpoint_frequency
 
-        self._data: Dict[RayDMatrix, xgb.DMatrix] = {}
+        self._data: Dict[RayDMatrix, dict] = {}
         self._local_n: Dict[RayDMatrix, int] = {}
 
         self._stop_event = stop_event

xgboost_ray/tests/test_tune.py

@@ -158,8 +158,13 @@ def testReplaceTuneCheckpoints(self):
 
         replaced = in_dict["callbacks"][0]
         self.assertTrue(isinstance(replaced, TuneReportCheckpointCallback))
-        self.assertSequenceEqual(replaced._report._metrics, ["met"])
-        self.assertEqual(replaced._checkpoint._filename, "test")
+
+        if getattr(replaced, "_report", None):
+            self.assertSequenceEqual(replaced._report._metrics, ["met"])
+            self.assertEqual(replaced._checkpoint._filename, "test")
+        else:
+            self.assertSequenceEqual(replaced._metrics, ["met"])
+            self.assertEqual(replaced._filename, "test")
 
     def testEndToEndCheckpointing(self):
         ray_params = RayParams(cpus_per_actor=1, num_actors=2)

xgboost_ray/tune.py

@@ -3,14 +3,15 @@
 from typing import Dict, Optional
 
 import ray
+from ray.train._internal.session import get_session
 from ray.util.annotations import PublicAPI
 
 from xgboost_ray.session import get_rabit_rank, put_queue
 from xgboost_ray.util import Unavailable, force_on_current_node
 from xgboost_ray.xgb import xgboost as xgb
 
 try:
-    from ray import tune
+    from ray import train, tune
     from ray.tune import is_session_enabled
     from ray.tune.integration.xgboost import (
         TuneReportCallback as OrigTuneReportCallback,
@@ -39,30 +40,53 @@ def is_session_enabled():
     flatten_dict = is_session_enabled
     TUNE_INSTALLED = False
 
+
 if TUNE_INSTALLED:
-    # New style callbacks.
-    class TuneReportCallback(OrigTuneReportCallback):
-        def after_iteration(self, model, epoch: int, evals_log: Dict):
-            if get_rabit_rank() == 0:
-                report_dict = self._get_report_dict(evals_log)
-                put_queue(lambda: tune.report(**report_dict))
-
-    class _TuneCheckpointCallback(_OrigTuneCheckpointCallback):
-        def after_iteration(self, model, epoch: int, evals_log: Dict):
-            if get_rabit_rank() == 0:
-                put_queue(
-                    lambda: self._create_checkpoint(
-                        model, epoch, self._filename, self._frequency
+    if not hasattr(train, "report"):
+
+        # New style callbacks.
+        class TuneReportCallback(OrigTuneReportCallback):
+            def after_iteration(self, model, epoch: int, evals_log: Dict):
+                if get_rabit_rank() == 0:
+                    report_dict = self._get_report_dict(evals_log)
+                    put_queue(lambda: tune.report(**report_dict))
+
+        class _TuneCheckpointCallback(_OrigTuneCheckpointCallback):
+            def after_iteration(self, model, epoch: int, evals_log: Dict):
+                if get_rabit_rank() == 0:
+                    put_queue(
+                        lambda: self._create_checkpoint(
+                            model, epoch, self._filename, self._frequency
+                        )
                     )
-                )
 
-    class TuneReportCheckpointCallback(OrigTuneReportCheckpointCallback):
-        _checkpoint_callback_cls = _TuneCheckpointCallback
-        _report_callbacks_cls = TuneReportCallback
+        class TuneReportCheckpointCallback(OrigTuneReportCheckpointCallback):
+            _checkpoint_callback_cls = _TuneCheckpointCallback
+            _report_callbacks_cls = TuneReportCallback
+
+    else:
+
+        class TuneReportCheckpointCallback(OrigTuneReportCheckpointCallback):
+            def after_iteration(self, model, epoch: int, evals_log: Dict):
+                if get_rabit_rank() == 0:
+                    put_queue(
+                        lambda: super(
+                            TuneReportCheckpointCallback, self
+                        ).after_iteration(model=model, epoch=epoch, evals_log=evals_log)
+                    )
+
+        class TuneReportCallback(OrigTuneReportCallback):
+            def after_iteration(self, model, epoch: int, evals_log: Dict):
+                if get_rabit_rank() == 0:
+                    put_queue(
+                        lambda: super(TuneReportCallback, self).after_iteration(
+                            model=model, epoch=epoch, evals_log=evals_log
+                        )
+                    )
 
 
 def _try_add_tune_callback(kwargs: Dict):
-    if TUNE_INSTALLED and is_session_enabled():
+    if TUNE_INSTALLED and (is_session_enabled() or get_session()):
         callbacks = kwargs.get("callbacks", []) or []
         new_callbacks = []
         has_tune_callback = False
@@ -88,10 +112,19 @@ def _try_add_tune_callback(kwargs: Dict):
                 )
                 has_tune_callback = True
             elif isinstance(cb, OrigTuneReportCheckpointCallback):
+                if getattr(cb, "_report", None):
+                    orig_metrics = cb._report._metrics
+                    orig_filename = cb._checkpoint._filename
+                    orig_frequency = cb._checkpoint._frequency
+                else:
+                    orig_metrics = cb._metrics
+                    orig_filename = cb._filename
+                    orig_frequency = cb._frequency
+
                 replace_cb = TuneReportCheckpointCallback(
-                    metrics=cb._report._metrics,
-                    filename=cb._checkpoint._filename,
-                    frequency=cb._checkpoint._frequency,
+                    metrics=orig_metrics,
+                    filename=orig_filename,
+                    frequency=orig_frequency,
                 )
                 new_callbacks.append(replace_cb)
                 logging.warning(