Replace Ray with multiprocess

python/learn.py

 import logging
 
 import os
-import ray
+import multiprocessing
 from docopt import docopt
 
 from unitytrainers.trainer_controller import TrainerController
     base_path = os.path.dirname(__file__)
     TRAINER_CONFIG_PATH = os.path.abspath(os.path.join(base_path, "trainer_config.yaml"))
 
-    @ray.remote
     def run_training(sub_id):
         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, seed,
-    ray.init()
-    ray.get([run_training.remote(i) for i in range(num_runs)])
+    jobs = []
+    for i in range(num_runs):
+        p = multiprocessing.Process(target=run_training, args=(i,))
+        jobs.append(p)
+        p.start()