Currently headless mode is disabled. We hope to address these in a future version of Unity.
If you enable Headless mode, you will not be able to collect visual
observations from your agents.
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.
### macOS Metal Support
When running a Unity Environment on macOS using Metal rendering, the application can crash when the lock-screen is open. The solution is to set rendering to OpenGL. This can be done by navigating: `Edit -> Project Settings -> Player`. Clicking on `Other Settings`. Unchecking `Auto Graphics API for Mac`. Setting `OpenGL Core` to be above `Metal` in the priority list.
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 version
As of version 0.3, we no longer support Python 2.
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 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 *.x86_64`
On Windows, you can find instructions [here](https://technet.microsoft.com/en-us/library/cc754344(v=ws.11).aspx).
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 train 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).
### Filename not found
If you receive a file-not-found error while attempting to launch an environment, ensure that the environment files are in the root repository directory. For example, if there is a sub-folder containing the environment files, those files should be removed from the sub-folder and moved to the root.
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
generated by the Unity Environment to figure what error happened.
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
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
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.
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.
GitHub
7 年前