fix Unity-Technologies/ml-agents#1041 (#1102)

python/learn.py

 from unitytrainers.trainer_controller import TrainerController
 from unitytrainers.exception import TrainerError
 
+def run_training(sub_id, use_seed, options):
+    # Docker Parameters
+    if options['--docker-target-name'] == 'Empty':
+        docker_target_name = ''
+    else:
+        docker_target_name = options['--docker-target-name']
+
+    # General parameters
+    run_id = options['--run-id']
+    num_runs = int(options['--num-runs'])
+    seed = int(options['--seed'])
+    load_model = options['--load']
+    train_model = options['--train']
+    save_freq = int(options['--save-freq'])
+    env_path = options['<env>']
+    keep_checkpoints = int(options['--keep-checkpoints'])
+    worker_id = int(options['--worker-id'])
+    curriculum_file = str(options['--curriculum'])
+    if curriculum_file == "None":
+        curriculum_file = None
+    lesson = int(options['--lesson'])
+    fast_simulation = not bool(options['--slow'])
+    no_graphics = options['--no-graphics']
+
+    # Constants
+    # Assumption that this yaml is present in same dir as this file
+    base_path = os.path.dirname(__file__)
+    TRAINER_CONFIG_PATH = os.path.abspath(os.path.join(base_path, "trainer_config.yaml"))
+
+
+
+
+    if env_path is None and num_runs > 1:
+        raise TrainerError("It is not possible to launch more than one concurrent training session "
+                           "when training from the editor")
+
+    tc = TrainerController(env_path, run_id + "-" + str(sub_id), save_freq, curriculum_file, fast_simulation,
+                            load_model, train_model, worker_id + sub_id, keep_checkpoints, lesson, use_seed,
+                            docker_target_name, TRAINER_CONFIG_PATH, no_graphics)
+    tc.start_learning()
+
 if __name__ == '__main__':
     print('''
     
 
     options = docopt(_USAGE)
     logger.info(options)
-    # Docker Parameters
-    if options['--docker-target-name'] == 'Empty':
-        docker_target_name = ''
-    else:
-        docker_target_name = options['--docker-target-name']
-
-    # General parameters
-    run_id = options['--run-id']
-    load_model = options['--load']
-    train_model = options['--train']
-    save_freq = int(options['--save-freq'])
-    env_path = options['<env>']
-    keep_checkpoints = int(options['--keep-checkpoints'])
-    worker_id = int(options['--worker-id'])
-    curriculum_file = str(options['--curriculum'])
-    if curriculum_file == "None":
-        curriculum_file = None
-    lesson = int(options['--lesson'])
-    fast_simulation = not bool(options['--slow'])
-    no_graphics = options['--no-graphics']
-    # Constants
-    # Assumption that this yaml is present in same dir as this file
-    base_path = os.path.dirname(__file__)
-    TRAINER_CONFIG_PATH = os.path.abspath(os.path.join(base_path, "trainer_config.yaml"))
-
-
-    def run_training(sub_id, use_seed):
-        tc = TrainerController(env_path, run_id + "-" + str(sub_id), save_freq, curriculum_file, fast_simulation,
-                               load_model, train_model, worker_id + sub_id, keep_checkpoints, lesson, use_seed,
-                               docker_target_name, TRAINER_CONFIG_PATH, no_graphics)
-        tc.start_learning()
-
-
-    if env_path is None and num_runs > 1:
-        raise TrainerError("It is not possible to launch more than one concurrent training session "
-                           "when training from the editor")
 
     jobs = []
     for i in range(num_runs):
             use_seed = seed
-        p = multiprocessing.Process(target=run_training, args=(i, use_seed))
+        p = multiprocessing.Process(target=run_training, args=(i, use_seed, options))
-        p.start()
+        p.start()