[rllib] [minor] Rename agent_id to experiment_tag (#1143)

* tagstr

* doc

* rename

* fix test

python/ray/rllib/agent.py

@@ -42,7 +42,7 @@ class Agent(object):
 
     def __init__(
             self, env_creator, config, local_dir='/tmp/ray',
-            upload_dir=None, agent_id=None):
+            upload_dir=None, experiment_tag=None):
         """Initialize an RLLib agent.
 
         Args:
@@ -53,8 +53,10 @@ class Agent(object):
                 be placed.
             upload_dir (str): Optional remote URI like s3://bucketname/ where
                 results will be uploaded.
-            agent_id (str): Optional unique identifier for this agent, used
-                to determine where to store results in the local dir.
+            experiment_tag (str): Optional string containing extra metadata
+                about the experiment, e.g. a summary of parameters. This string
+                will be included in the logdir path and when displaying agent
+                progress.
         """
         self._initialize_ok = False
         self._experiment_id = uuid.uuid4().hex
@@ -63,7 +65,10 @@ class Agent(object):
             env_name = env_creator
             self.env_creator = lambda: gym.make(env_name)
         else:
-            env_name = "custom"
+            if hasattr(env_creator, "env_name"):
+                env_name = env_creator.env_name
+            else:
+                env_name = "custom"
             self.env_creator = env_creator
 
         self.config = self._default_config.copy()
@@ -75,7 +80,7 @@ class Agent(object):
                         "all agent configs: {}".format(k, self.config.keys()))
         self.config.update(config)
         self.config.update({
-            "agent_id": agent_id,
+            "experiment_tag": experiment_tag,
             "alg": self._agent_name,
             "env_name": env_name,
             "experiment_id": self._experiment_id,
@@ -84,7 +89,7 @@ class Agent(object):
         logdir_suffix = "{}_{}_{}".format(
             env_name,
             self._agent_name,
-            agent_id or datetime.today().strftime("%Y-%m-%d_%H-%M-%S"))
+            experiment_tag or datetime.today().strftime("%Y-%m-%d_%H-%M-%S"))
 
         if not os.path.exists(local_dir):
             os.makedirs(local_dir)

python/ray/tune/config_parser.py

@@ -93,13 +93,13 @@ def parse_to_trials(config):
             next_cfg, resolved_vars = grid_search.next()
             resolved, resolved_vars = resolve(next_cfg, resolved_vars, i)
             if resolved_vars:
-                agent_id = "{}_{}".format(
+                experiment_tag = "{}_{}".format(
                     i, param_str(resolved, resolved_vars))
             else:
-                agent_id = str(i)
+                experiment_tag = str(i)
             trials.append(Trial(
                 args.env, args.alg, resolved,
-                os.path.join(args.local_dir, experiment_name), agent_id,
+                os.path.join(args.local_dir, experiment_name), experiment_tag,
                 args.resources, args.stop, args.checkpoint_freq, None,
                 args.upload_dir))
 

python/ray/tune/examples/tune_mnist_ray.py

@@ -214,7 +214,7 @@ if __name__ == '__main__':
                     'script_min_iter_time_s': 1,
                     'activation': act,
                 },
-                agent_id='act={}'.format(act)))
+                experiment_tag='act={}'.format(act)))
 
     ray.init()
 

python/ray/tune/trial.py

@@ -31,7 +31,7 @@ class Trial(object):
 
     def __init__(
             self, env_creator, alg, config={}, local_dir='/tmp/ray',
-            agent_id=None, resources=Resources(cpu=1, gpu=0),
+            experiment_tag=None, resources=Resources(cpu=1, gpu=0),
             stopping_criterion={}, checkpoint_freq=None,
             restore_path=None, upload_dir=None):
         """Initialize a new trial.
@@ -45,11 +45,14 @@ class Trial(object):
         if type(env_creator) is str:
             self.env_name = env_creator
         else:
-            self.env_name = "custom"
+            if hasattr(env_creator, "env_name"):
+                self.env_name = env_creator.env_name
+            else:
+                self.env_name = "custom"
         self.alg = alg
         self.config = config
         self.local_dir = local_dir
-        self.agent_id = agent_id
+        self.experiment_tag = experiment_tag
         self.resources = resources
         self.stopping_criterion = stopping_criterion
         self.checkpoint_freq = checkpoint_freq
@@ -77,7 +80,7 @@ class Trial(object):
                 agent_cls)
         self.agent = cls.remote(
             self.env_creator, self.config, self.local_dir, self.upload_dir,
-            agent_id=self.agent_id)
+            experiment_tag=self.experiment_tag)
         if self.restore_path:
             ray.get(self.agent.restore.remote(self.restore_path))
 
@@ -178,8 +181,8 @@ class Trial(object):
 
     def __str__(self):
         identifier = '{}_{}'.format(self.alg, self.env_name)
-        if self.agent_id:
-            identifier += '_' + self.agent_id
+        if self.experiment_tag:
+            identifier += '_' + self.experiment_tag
         return identifier
 
     def __eq__(self, other):