What happened + What you expected to happen

When initializing a Ray Trainer, we provide a logdir argument, and the __init__ method of the Trainer stores it as a logdir class variable.

Then, when creating a Trainable with Trainer.to_tune_trainable(), it in-turn calls _create_tune_trainable(), which does not use self.logdir. So when tune_function is defined inside `_create_tu

Trying to --appimage-extract-and-run a x86_64 Linux AppImage on FreeBSD 12.1-RELEASE-p8 with the Linux compatibility layer:

user@FreeBSD$  /home/user/Downloads/Akira-26-x86_64.AppImage --appimage-extract-and-run
mkdir_p error: Permission denied
Failed to extract AppImage

but

user@FreeBSD$  /home/user/Downloads/Akira-26-x86_64.AppImage --appimage-extract

hi there,

Just installed latest versions of shipit packages and here's something new:

Running 'deploy:fetch' task...
Create workspace...
Workspace created: "/var/folders/s0/scv46d414cd28hyzsd5_pcrw0000gn/T/tmp-72206PXTF2WKB77Ro"
Initialize local repository in "/var/folders/s0/scv46d414cd28hyzsd5_pcrw0000gn/T/tmp-72206PXTF2WKB77Ro"
Running "git init" on local.
@ Initialized empty Gi

SUMMARY

While using the action runner type "local-shell-script", the action always try to set execute permission for the action script before the execution.

For example, action runner logs for the core.sendmail action

2022-03-09 07:02:06,866 INFO [-] Executing action via LocalRunner: dcc6c28d-5674-4cc2-9174-ca6c1e7b23a3
2022-03-09 07:02:06,866 INFO [-] [Action info] name: sendm

We are using font-awesome V4 and should migrate to font-awesome V5 which comes with its own vue.js module: https://github.com/FortAwesome/vue-fontawesome

Migration includes removing old font-awesome V4 module and changing all existing icons to new vue.js tag.

This is blocked until #114 is merged which comes with first initial integration.

The documentation for creating complex inference graphs should include what components can be connected to what, and how the overall graph should behave.

For example, all inference graphs need to end with a single node, whether its a combiner combining multiple inputs, or a transformer, or a model--the graph can't split and then never rejoin, etc.

Describe the solution you'd like
Add types to Python codebase

What does your solution aim to solve?
Make it more explicit what arguments functions take and therefore make it easier to extend consume or refactor code.

Documentation for "cobbler image" missing

There is not really any documentation on cobbler image: https://cobbler.readthedocs.io/en/latest/cobbler.html#cobbler-image

There used to be examples on the Wiki on how to use it (for instance with memtest86+: https://github.com/cobbler/cobbler/wiki/Memtest/c908bb268589ef61ec08502d021718f69fb48cb6). That page has been removed from the Wiki in 2

(suggested by Berndinox in #205; been bugging me for a while too)

Currently, the Docker image exposes port 80. We should change this so that running Meli doesn't require root access.

We'll need to update the deployment docs.