[tune] Document trainable attributes and enable user-checkpoint… (#4868)

python/ray/rllib/agents/mock.py

@@ -6,6 +6,7 @@ import os
 import pickle
 import numpy as np
 
+from ray.tune import result as tune_result
 from ray.rllib.agents.trainer import Trainer, with_common_config
 
 
@@ -18,6 +19,7 @@ class _MockTrainer(Trainer):
         "persistent_error": False,
         "test_variable": 1,
         "num_workers": 0,
+        "user_checkpoint_freq": 0,
     })
 
     @classmethod
@@ -32,11 +34,15 @@ class _MockTrainer(Trainer):
         if self.config["mock_error"] and self.iteration == 1 \
                 and (self.config["persistent_error"] or not self.restored):
             raise Exception("mock error")
-        return dict(
+        result = dict(
             episode_reward_mean=10,
             episode_len_mean=10,
             timesteps_this_iter=10,
             info={})
+        if self.config["user_checkpoint_freq"] > 0 and self.iteration > 0:
+            if self.iteration % self.config["user_checkpoint_freq"] == 0:
+                result.update({tune_result.SHOULD_CHECKPOINT: True})
+        return result
 
     def _save(self, checkpoint_dir):
         path = os.path.join(checkpoint_dir, "mock_agent.pkl")

python/ray/rllib/agents/trainer.py

@@ -579,12 +579,6 @@ class Trainer(Trainable):
         else:
             return res[0]  # backwards compatibility
 
-    @property
-    def iteration(self):
-        """Current training iter, auto-incremented with each train() call."""
-
-        return self._iteration
-
     @property
     def _name(self):
         """Subclasses should override this to declare their name."""