Done

I mean if I continue and build on the example in the docs, what will happen if the training task is completed, and then I get it and log to it? Will it be defined as running again?

the level of configurability in this thing is one of the best I've seen

So what's our next move FriendlySquid61 ? O_O

Thanks a lot, that clarifies things

Oh... from the docs I understood that I don't have to run the script, that I can either configure it in the UI, or with the sscript (wizard) so I ignored it up until now

As a part of a repo

I mean the code in whatever form it is - I'm working with git specifically, but if i have diffs I'd like to see the code with the diffs applied

eventually i think it should display the contents of the script executed in the most straightforward manner regardless of version control

That's a fix, but I think it is a basic feature and very usefull to see the actual code in the UI

the explicity of the variable queue makes it feels like it runs somewhere else

For example I have a DATA_DIR environment variable which points to the directory where disk-data is stored

I'm not, just want to be very precise an consice about them when I do ask... but bear with me, its coming 🙂

it is the location of the repo

:face_palm: 🤔 :man-tipping-hand:

Thx DangerousDragonfly8 💪

Thanks Martin, code runs as expected

192.168.1.71?

the worst part of debugging this is waiting for the docker to install tensorflow each time over and over again 😞

Well done to you!

It's working! 😄

I'm using ip address show

okay lets go

Why is that an issue?

So could you re-explain assuming my piepline object is created by pipeline = PipelineController(...) ?

Nope

a third one?

this is the full one TimelyPenguin76

I've read that

💪