unified ray init that is version agnostic

Author: vonHartz

mdp_playground/config_processor/config_processor.py

@@ -17,6 +17,29 @@
 ModelCatalog.register_custom_preprocessor("ohe", OneHotPreprocessor)
 
 
+# def init_ray(log_level=None, tmp_dir=None, include_webui=None,
+#              object_store_memory=int(2e9),
+#              redis_max_memory=int(1e9), local_mode=False):
+def init_ray(**kwargs):
+    import ray
+    if ray.__version__[0] == '1':  # new version 1.0 API
+        if "redis_max_memory" in kwargs:
+            value = kwargs["redis_max_memory"]
+            del kwargs["redis_max_memory"]
+            kwargs["_redis_max_memory"] = value
+        if "tmp_dir" in kwargs:
+            value = kwargs["tmp_dir"]
+            del kwargs["tmp_dir"]
+            kwargs["_temp_dir"] = value
+
+    if "log_level" in kwargs:
+        value = kwargs["log_level"]
+        del kwargs["log_level"]
+        kwargs["logging_level"] = value
+
+    ray.init(**kwargs)
+
+
 def process_configs(config_file, stats_file_prefix, config_num, log_level,
                     framework='ray', framework_dir='/tmp/ray'):
     config_file_path = os.path.abspath('/'.join(config_file.split('/')[:-1]))
@@ -129,30 +152,34 @@ def process_configs(config_file, stats_file_prefix, config_num, log_level,
 
 
 def setup_ray(config, config_num, log_level, framework_dir):
-    import ray
     tmp_dir = framework_dir + '/tmp_' + str(config_num)
+    # import ray
     if config.algorithm == 'DQN': #hack
-        ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9),
-                 temp_dir=tmp_dir,
-                 logging_level=log_level,
-                 # local_mode=True,
-                 # webui_host='0.0.0.0'); logging_level=logging.INFO,
-                 )
+        init_ray(log_level=log_level, tmp_dir=tmp_dir)
+        # ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9),
+        #          temp_dir=tmp_dir,
+        #          logging_level=log_level,
+        #          # local_mode=True,
+        #          # webui_host='0.0.0.0'); logging_level=logging.INFO,
+        #          )
         # ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9), local_mode=True, plasma_directory='/tmp') #, memory=int(8e9), local_mode=True # local_mode (bool): If true, the code will be executed serially. This is useful for debugging. # when true on_train_result and on_episode_end operate in the same current directory as the script. A3C is crashing in local mode, so didn't use it and had to work around by giving full path + filename in stats_file_name.; also has argument driver_object_store_memory=, plasma_directory='/tmp'
     elif config.algorithm == 'A3C': #hack
-        ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9),
-                 temp_dir=tmp_dir,
-                 logging_level=log_level,
-                 # local_mode=True,
-                 # webui_host='0.0.0.0'); logging_level=logging.INFO,
-                 )        # ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9), local_mode=True, plasma_directory='/tmp')
+        init_ray(log_level=log_level, tmp_dir=tmp_dir)
+        # ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9),
+        #          temp_dir=tmp_dir,
+        #          logging_level=log_level,
+        #          # local_mode=True,
+        #          # webui_host='0.0.0.0'); logging_level=logging.INFO,
+        #          )        # ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9), local_mode=True, plasma_directory='/tmp')
     else:
-        ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9),
-                 temp_dir=tmp_dir,
-                 logging_level=log_level,
-                 local_mode=True,
-                 # webui_host='0.0.0.0'); logging_level=logging.INFO,
-                 )
+        init_ray(log_level=log_level, tmp_dir=tmp_dir, local_mode=True)
+
+        # ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9),
+        #          temp_dir=tmp_dir,
+        #          logging_level=log_level,
+        #          local_mode=True,
+        #          # webui_host='0.0.0.0'); logging_level=logging.INFO,
+        #          )
 
 def init_stats_file(stats_file_name, columns_to_write):
     fout = open(stats_file_name, 'a') #hardcoded

mdp_playground/scripts/run_experiments_ray.py

@@ -13,6 +13,7 @@
 #from ray.rllib.utils.seed import seed as rllib_seed
 import mdp_playground
 from mdp_playground.envs import RLToyEnv
+from mdp_playground.config_processor import init_ray
 from ray.tune.registry import register_env
 register_env("RLToy-v0", lambda config: RLToyEnv(**config))
 import sys, os
@@ -97,13 +98,16 @@ def create_gym_env_wrapper_frame_stack_atari(config): #hack ###TODO remove?
     ModelCatalog.register_custom_preprocessor("ohe", OneHotPreprocessor)
 
     if config.algorithm == 'DQN':
-        ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9), include_webui=False) #webui_host='0.0.0.0')
+        init_ray(include_webui=False)
+        # ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9), include_webui=False) #webui_host='0.0.0.0')
         # ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9), local_mode=True, plasma_directory='/tmp') #, memory=int(8e9), local_mode=True # when true on_train_result and on_episode_end operate in the same current directory as the script. A3C is crashing in local mode, so didn't use it and had to work around by giving full path + filename in stats_file_name.; also has argument driver_object_store_memory=, plasma_directory='/tmp'
     elif config.algorithm == 'A3C': #hack
-        ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9), include_webui=False)
+        init_ray(include_webui=False)
+        # ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9), include_webui=False)
         # ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9), local_mode=True, plasma_directory='/tmp')
     else:
-        ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9), local_mode=True, temp_dir='/tmp/ray' + str(args.config_num), include_webui=False)
+        init_ray(local_mode=True, temp_dir='/tmp/ray' + str(args.config_num), include_webui=False)
+        # ray.init(object_store_memory=int(2e9), redis_max_memory=int(1e9), local_mode=True, temp_dir='/tmp/ray' + str(args.config_num), include_webui=False)
 
 
     var_configs_deepcopy = copy.deepcopy(config.var_configs) #hack because this needs to be read in on_train_result and trying to read config there raises an error because it's been imported from a Python module and I think they try to reload it there.
@@ -468,4 +472,4 @@ def create_gym_env_wrapper_mujoco_wrapper(config, wrapped_mujoco_env):
 
 if __name__ == '__main__':
     args = parse_args()
-    main(args)
+    main(args)

pyproject.toml

@@ -57,11 +57,14 @@ scipy = { version = "1.3.0", optional = true }
 pillow = { version = "6.1.0", optional = true }
 tensorflow-probability = { version = "0.9.0", optional = true }
 mujoco-py = { version = "2.0.2.13", optional = true }
+tensorflow = { version = "2.2.0", optional = true }
+ray = { version = "1.3.0", optional = true }
 dill = "^0.3.3"
 colorama = "^0.4.4"
 
 [tool.poetry.extras]
-extras_disc = ["pandas", "requests", "configspace", "scipy", "pillow", "pillow"]
+extras = ["pandas", "requests", "configspace", "scipy", "pillow", "tensorflow", "ray"]
+extras_disc = ["pandas", "requests", "configspace", "scipy", "pillow"]
 extras_cont = ["pandas", "requests", "configspace", "scipy", "tensorflow-probability", "mujoco-py"]
 
 [tool.poetry.dev-dependencies]

setup.py

@@ -12,7 +12,7 @@
 {'': ['*']}
 
 extras_require = [
-    'ray[rllib,debug]==0.7.3',
+    'ray[rllib,debug]==1.3.0',
     'tensorflow==2.2.0',
     'pillow==6.1.0',
     'pandas==0.25.0',
@@ -88,7 +88,8 @@
     python_requires=">=3.6",
     install_requires=['gym<=0.14', 'dill'],
     extras_require={
-      'extras_disc': extras_require,
+      'extras': extras_require,
+      'extras_disc': extras_require_disc,
       'extras_cont': extras_require_cont,
     },