[rllib] Better document which methods are abstract and which ones are overrides (#3480)

python/ray/rllib/optimizers/sync_samples_optimizer.py

@@ -6,6 +6,7 @@ import ray
 import logging
 from ray.rllib.optimizers.policy_optimizer import PolicyOptimizer
 from ray.rllib.evaluation.sample_batch import SampleBatch
+from ray.rllib.utils.annotations import override
 from ray.rllib.utils.filter import RunningStat
 from ray.rllib.utils.timer import TimerStat
 
@@ -20,6 +21,7 @@ class SyncSamplesOptimizer(PolicyOptimizer):
     model weights are then broadcast to all remote evaluators.
     """
 
+    @override(PolicyOptimizer)
     def _init(self, num_sgd_iter=1, train_batch_size=1):
         self.update_weights_timer = TimerStat()
         self.sample_timer = TimerStat()
@@ -29,6 +31,7 @@ class SyncSamplesOptimizer(PolicyOptimizer):
         self.train_batch_size = train_batch_size
         self.learner_stats = {}
 
+    @override(PolicyOptimizer)
     def step(self):
         with self.update_weights_timer:
             if self.remote_evaluators:
@@ -62,6 +65,7 @@ class SyncSamplesOptimizer(PolicyOptimizer):
         self.num_steps_trained += samples.count
         return fetches
 
+    @override(PolicyOptimizer)
     def stats(self):
         return dict(
             PolicyOptimizer.stats(self), **{