diff --git a/python/ray/tune/ray_trial_executor.py b/python/ray/tune/ray_trial_executor.py
index 0332c18d0..5d6b91c86 100644
--- a/python/ray/tune/ray_trial_executor.py
+++ b/python/ray/tune/ray_trial_executor.py
@@ -456,15 +456,11 @@ class RayTrialExecutor(TrialExecutor):
         trial_item = self._find_item(self._running, trial)
         assert len(trial_item) < 2, trial_item
 
-    def _start_trial(self, trial, checkpoint=None, train=True) -> bool:
+    def _start_trial(self, trial) -> bool:
         """Starts trial and restores last result if trial was paused.
 
         Args:
             trial (Trial): The trial to start.
-            checkpoint (Optional[Checkpoint]): The checkpoint to restore from.
-                If None, and no trial checkpoint exists, the trial is started
-                from the beginning.
-            train (bool): Whether or not to start training.
 
         Returns:
             True if trial was started successfully, False otherwise.
@@ -477,13 +473,13 @@ class RayTrialExecutor(TrialExecutor):
             return False
         trial.set_runner(runner)
         self._notify_trainable_of_new_resources_if_needed(trial)
-        self.restore(trial, checkpoint)
+        self.restore(trial, trial.checkpoint)
         self.set_status(trial, Trial.RUNNING)
 
         if trial in self._staged_trials:
             self._staged_trials.remove(trial)
 
-        if train and not trial.is_restoring:
+        if not trial.is_restoring:
             self._train(trial)
         return True
 
@@ -561,26 +557,20 @@ class RayTrialExecutor(TrialExecutor):
         finally:
             trial.set_runner(None)
 
-    def start_trial(self,
-                    trial: Trial,
-                    checkpoint: Optional[Checkpoint] = None,
-                    train: bool = True) -> bool:
+    def start_trial(self, trial: Trial) -> bool:
         """Starts the trial.
 
         Will not return resources if trial repeatedly fails on start.
 
         Args:
             trial (Trial): Trial to be started.
-            checkpoint (Checkpoint): A Python object or path storing the state
-                of trial.
-            train (bool): Whether or not to start training.
 
         Returns:
             True if the remote runner has been started. False if trial was
                 not started (e.g. because of lacking resources/pending PG).
         """
         try:
-            return self._start_trial(trial, checkpoint, train=train)
+            return self._start_trial(trial)
         except AbortTrialExecution:
             logger.exception("Trial %s: Error starting runner, aborting!",
                              trial)
diff --git a/python/ray/tune/tests/test_ray_trial_executor.py b/python/ray/tune/tests/test_ray_trial_executor.py
index a1ef76b22..760347466 100644
--- a/python/ray/tune/tests/test_ray_trial_executor.py
+++ b/python/ray/tune/tests/test_ray_trial_executor.py
@@ -177,9 +177,9 @@ class RayTrialExecutorTest(unittest.TestCase):
         self.trial_executor.start_trial(trial)
         self.assertEqual(Trial.RUNNING, trial.status)
         self.trial_executor.fetch_result(trial)
-        checkpoint = self.trial_executor.pause_trial(trial)
+        self.trial_executor.pause_trial(trial)
         self.assertEqual(Trial.PAUSED, trial.status)
-        self.trial_executor.start_trial(trial, checkpoint)
+        self.trial_executor.start_trial(trial)
         self.assertEqual(Trial.RUNNING, trial.status)
         self.trial_executor.stop_trial(trial)
         self.assertEqual(Trial.TERMINATED, trial.status)
diff --git a/python/ray/tune/trial_executor.py b/python/ray/tune/trial_executor.py
index 77c12ad21..4c6cc999b 100644
--- a/python/ray/tune/trial_executor.py
+++ b/python/ray/tune/trial_executor.py
@@ -169,17 +169,11 @@ class TrialExecutor(metaclass=_WarnOnDirectInheritanceMeta):
         pass
 
     @abstractmethod
-    def start_trial(self,
-                    trial: Trial,
-                    checkpoint: Optional[Checkpoint] = None,
-                    train: bool = True) -> bool:
+    def start_trial(self, trial: Trial) -> bool:
         """Starts the trial restoring from checkpoint if checkpoint is provided.
 
         Args:
             trial (Trial): Trial to be started.
-            checkpoint (Checkpoint): A Python object or path storing the state
-            of trial.
-            train (bool): Whether or not to start training.
 
         Returns:
             True if trial started successfully, False otherwise.