Modify mlagents for removing server build

jorldy/core/env/ml_agent.py

@@ -10,10 +10,7 @@
 
 def match_build():
     os = platform.system()
-    if os == "Linux":
-        return "Server" if subprocess.getoutput("which Xorg") == "" else "Linux"
-    else:
-        return {"Windows": "Windows", "Darwin": "Mac"}[os]
+    return {"Windows": "Windows", "Darwin": "Mac", "Linux": "Linux"}[os]
 
 
 class _MLAgent(BaseEnv):
@@ -22,21 +19,26 @@ class _MLAgent(BaseEnv):
     Args:
         env_name (str): name of environment in ML-Agents.
         train_mode (bool): parameter that determine whether to use low-resource training rendering mode.
+        render (bool): parameter that determine whether to render.
     """
 
-    def __init__(self, env_name, train_mode=True, id=None, **kwargs):
+    def __init__(self, env_name, train_mode=True, render=False, id=None, **kwargs):
         env_path = f"./core/env/mlagents/{env_name}/{match_build()}/{env_name}"
         id = (
             np.random.randint(65534 - UnityEnvironment.BASE_ENVIRONMENT_PORT)
             if id is None
             else id
         )
 
+        graphic_available = False if subprocess.getoutput("which Xorg") == "" else True
+        no_graphics = not (render and graphic_available)
+
         engine_configuration_channel = EngineConfigurationChannel()
         self.env = UnityEnvironment(
             file_name=env_path,
             side_channels=[engine_configuration_channel],
             worker_id=id,
+            no_graphics=no_graphics,
         )
 
         self.env.reset()

jorldy/core/env/mlagents/DroneDelivery/Linux/DroneDelivery_Data/ML-Agents/Timers/TrainScene_timers.json

@@ -0,0 +1 @@
+{"count":1,"self":26.936591999999997,"total":118.449636,"children":{"InitializeActuators":{"count":2,"self":0.001787,"total":0.001787,"children":null},"InitializeSensors":{"count":2,"self":0.008045,"total":0.008045,"children":null},"AgentSendState":{"count":64469,"self":0.078348,"total":7.660735,"children":{"CollectObservations":{"count":12960,"self":0.982823,"total":0.982823,"children":null},"WriteActionMask":{"count":12960,"self":0.006781,"total":0.006781,"children":null},"RequestDecision":{"count":12960,"self":0.021561,"total":6.592783,"children":{"AgentInfo.ToProto":{"count":12960,"self":0.03957,"total":6.571222,"children":{"GenerateSensorData":{"count":12960,"self":0.882423,"total":6.5316519999999993,"children":{"RenderTextureSensor.GetCompressedObservation":{"count":64800,"self":5.6492287999999995,"total":5.649229,"children":null}}}}}}}}},"DecideAction":{"count":64469,"self":83.570432,"total":83.57042899999999,"children":null},"AgentAct":{"count":64469,"self":0.19736199999999998,"total":0.218889,"children":{"AgentInfo.ToProto":{"count":40,"self":0.00010899999999999999,"total":0.021526999999999998,"children":{"GenerateSensorData":{"count":40,"self":0.004854,"total":0.021418,"children":{"RenderTextureSensor.GetCompressedObservation":{"count":200,"self":0.016564,"total":0.016564,"children":null}}}}}}},"AgentInfo.ToProto":{"count":104,"self":0.000329,"total":0.051813,"children":{"GenerateSensorData":{"count":104,"self":0.008588,"total":0.051483999999999995,"children":{"RenderTextureSensor.GetCompressedObservation":{"count":520,"self":0.042896,"total":0.042896,"children":null}}}}}},"gauges":{"My Behavior.CumulativeReward":{"count":144,"max":8.68783951,"min":-2.13500714,"runningAverage":-0.7490371,"value":-0.8841691,"weightedAverage":-0.534805238}},"metadata":{"timer_format_version":"0.1.0","start_time_seconds":"1637553147","unity_version":"2021.1.6f1","command_line_arguments":"\/data\/private\/JORLDY\/jorldy\/.\/core\/env\/mlagents\/DroneDelivery\/Linux\/DroneDelivery.x86_64 -nographics -batchmode --mlagents-port 5009","communication_protocol_version":"1.5.0","com.unity.ml-agents_version":"2.1.0-exp.1","scene_name":"TrainScene","end_time_seconds":"1637553266"}}.1.0-exp.1","scene_name":"TrainScene","end_time_seconds":"1637553266"}}