# Limitations and Common Issues 

## Unity SDK
### Headless Mode
If you enable Headless mode, you will not be able to collect visual 
observations from your agents.

### Rendering Speed and Synchronization
Currently the speed of the game physics can only be increased to 100x 
real-time. The Academy also moves in time with FixedUpdate() rather than 
Update(), so game behavior tied to frame updates may be out of sync. 

## Python API

### Python version
As of version 0.3, we no longer support Python 2. 

### Environment Permission Error

If you directly import your Unity environment without building it in the 
editor, you might need to give it additional permissions to execute it. 

If you receive such a permission error on macOS, run:

`chmod -R 755 *.app` 

or on Linux:

`chmod -R 755 *.x86_64` 

On Windows, you can find instructions 
[here](https://technet.microsoft.com/en-us/library/cc754344(v=ws.11).aspx).

### Environment Connection Timeout

If you are able to launch the environment from `UnityEnvironment` but 
then receive a timeout error, there may be a number of possible causes.
 * _Cause_: There may be no Brains in your environment which are set 
 to `External`.  In this case, the environment will not attempt to 
 communicate with python. _Solution_: Set the Brains(s) you wish to 
 externally control through the Python API to `External` from the 
 Unity Editor, and rebuild the environment.
 * _Cause_: On OSX, the firewall may be preventing communication with 
 the environment. _Solution_: Add the built environment binary to the 
 list of exceptions on the firewall by following instructions 
 [here](https://support.apple.com/en-us/HT201642). 
 * _Cause_: An error happened in the Unity Environment preventing 
 communication. _Solution_: Look into the 
 [log files](https://docs.unity3d.com/Manual/LogFiles.html) 
 generated by the Unity Environment to figure what error happened. 

### Communication port {} still in use

If you receive an exception `"Couldn't launch new environment because 
communication port {} is still in use. "`, you can change the worker 
number in the Python script when calling 

`UnityEnvironment(file_name=filename, worker_id=X)`

### Mean reward : nan

If you receive a message `Mean reward : nan` when attempting to train a 
model using PPO, this is due to the episodes of the learning environment 
not terminating. In order to address this, set `Max Steps` for either 
the Academy or Agents within the Scene Inspector to a value greater 
than 0. Alternatively, it is possible to manually set `done` conditions 
for episodes from within scripts for custom episode-terminating events.