[rllib] Export tensorflow model of policy graph (#3585)

* Export tensorflow model of policy graph

* Add tests,examples,pydocs and infer extra signatures from existing methods

* Add example usage in export_policy_model comment

* Fix lint error

* Fix lint error

* Fix lint error

python/ray/rllib/agents/agent.py

@@ -16,6 +16,7 @@ import ray
 from ray.rllib.offline import NoopOutput, JsonReader, MixedInput, JsonWriter
 from ray.rllib.models import MODEL_DEFAULTS
 from ray.rllib.evaluation.policy_evaluator import PolicyEvaluator
+from ray.rllib.evaluation.sample_batch import DEFAULT_POLICY_ID
 from ray.rllib.optimizers.policy_optimizer import PolicyOptimizer
 from ray.rllib.utils.annotations import override
 from ray.rllib.utils import FilterManager, deep_update, merge_dicts
@@ -427,6 +428,21 @@ class Agent(Trainable):
                                  self.config) for i in range(count)
         ]
 
+    def export_policy_model(self, export_dir, policy_id=DEFAULT_POLICY_ID):
+        """Export policy model with given policy_id to local directory.
+
+        Arguments:
+            export_dir (string): Writable local directory.
+            policy_id (string): Optional policy id to export.
+
+        Example:
+            >>> agent = MyAgent()
+            >>> for _ in range(10):
+            >>>     agent.train()
+            >>> agent.export_policy_model("/tmp/export_dir")
+        """
+        self.local_evaluator.export_policy_model(export_dir, policy_id)
+
     @classmethod
     def resource_help(cls, config):
         return ("\n\nYou can adjust the resource requests of RLlib agents by "