rename save_checkpoint_secs -> checkpoint_save_secs

rl_coach/architectures/tensorflow_components/distributed_tf_utils.py

@@ -75,13 +75,13 @@ def create_worker_server_and_device(cluster_spec: tf.train.ClusterSpec, task_ind
 
 
 def create_monitored_session(target: tf.train.Server, task_index: int,
-                             checkpoint_dir: str, save_checkpoint_secs: int, config: tf.ConfigProto=None) -> tf.Session:
+                             checkpoint_dir: str, checkpoint_save_secs: int, config: tf.ConfigProto=None) -> tf.Session:
     """
     Create a monitored session for the worker
     :param target: the target string for the tf.Session
     :param task_index: the task index of the worker
     :param checkpoint_dir: a directory path where the checkpoints will be stored
-    :param save_checkpoint_secs: number of seconds between checkpoints storing
+    :param checkpoint_save_secs: number of seconds between checkpoints storing
     :param config: the tensorflow configuration (optional)
     :return: the session to use for the run
     """
@@ -94,7 +94,7 @@ def create_monitored_session(target: tf.train.Server, task_index: int,
         is_chief=is_chief,
         hooks=[],
         checkpoint_dir=checkpoint_dir,
-        save_checkpoint_secs=save_checkpoint_secs,
+        checkpoint_save_secs=checkpoint_save_secs,
         config=config
     )
 

rl_coach/coach.py

@@ -176,7 +176,7 @@ def parse_arguments(parser: argparse.ArgumentParser) -> argparse.Namespace:
     args.framework = Frameworks[args.framework.lower()]
 
     # checkpoints
-    args.checkpoint_save_dir = os.path.join(args.experiment_path, 'checkpoint') if args.save_checkpoint_secs is not None else None
+    args.checkpoint_save_dir = os.path.join(args.experiment_path, 'checkpoint') if args.checkpoint_save_secs is not None else None
 
     return args
 
@@ -257,7 +257,7 @@ def main():
                         help="(flag) TensorFlow verbosity level",
                         default=3,
                         type=int)
-    parser.add_argument('-s', '--save_checkpoint_secs',
+    parser.add_argument('-s', '--checkpoint_save_secs',
                         help="(int) Time in seconds between saving checkpoints of the model.",
                         default=None,
                         type=int)

rl_coach/graph_managers/graph_manager.py

@@ -208,7 +208,7 @@ class GraphManager(object):
             self.sess = create_monitored_session(target=task_parameters.worker_target,
                                                  task_index=task_parameters.task_index,
                                                  checkpoint_dir=checkpoint_dir,
-                                                 save_checkpoint_secs=task_parameters.save_checkpoint_secs,
+                                                 checkpoint_save_secs=task_parameters.checkpoint_save_secs,
                                                  config=config)
             # set the session for all the modules
             self.set_session(self.sess)
@@ -490,8 +490,8 @@ class GraphManager(object):
 
     def occasionally_save_checkpoint(self):
         # only the chief process saves checkpoints
-        if self.task_parameters.save_checkpoint_secs \
-                and time.time() - self.last_checkpoint_saving_time >= self.task_parameters.save_checkpoint_secs \
+        if self.task_parameters.checkpoint_save_secs \
+                and time.time() - self.last_checkpoint_saving_time >= self.task_parameters.checkpoint_save_secs \
                 and (self.task_parameters.task_index == 0  # distributed
                      or self.task_parameters.task_index is None  # single-worker
                      ):

tutorials/1. Implementing an Algorithm.ipynb

@@ -367,7 +367,7 @@
     "                                evaluate_only=False,\n",
     "                                experiment_path=log_path)\n",
     "\n",
-    "task_parameters.__dict__['save_checkpoint_secs'] = None\n",
+    "task_parameters.__dict__['checkpoint_save_secs'] = None\n",
     "\n",
     "graph_manager.create_graph(task_parameters)\n",
     "\n",

tutorials/2. Adding an Environment.ipynb

@@ -345,7 +345,7 @@
     "                                evaluate_only=False,\n",
     "                                experiment_path=log_path)\n",
     "\n",
-    "task_parameters.__dict__['save_checkpoint_secs'] = None\n",
+    "task_parameters.__dict__['checkpoint_save_secs'] = None\n",
     "\n",
     "\n",
     "graph_manager.create_graph(task_parameters)\n",

tutorials/3. Implementing a Hierarchical RL Graph.ipynb

@@ -372,7 +372,7 @@
     "                                evaluate_only=False,\n",
     "                                experiment_path=log_path)\n",
     "\n",
-    "task_parameters.__dict__['save_checkpoint_secs'] = None\n",
+    "task_parameters.__dict__['checkpoint_save_secs'] = None\n",
     "task_parameters.__dict__['verbosity'] = 'low'\n",
     "\n",
     "graph_manager.create_graph(task_parameters)\n",