So copy train.conf from elsewhere to ~/train.conf?

yes that will work 🙂

yes.
Obviously when you import the offline session, you will need to set it to point to your server with the correct credentials

Just to clarify, where do I run the second command?

Anywhere just open a python console and import the offline task:
from trains import TaskTask.import_offline_session('./my_task_aaa.zip')

Related, how to I specify in my code the cache_dir where the zip is saved?

This is the Trains cache folder, you can set it in the trains.conf file:
https://github.com/allegroai/trains/blob/10ec4d56fb4a1f933128b35d68c727189310aae8/docs/trains.conf#L24

Hi ImpressionableRaven99
Yes, it is 🙂
Call this one before task.init, and it will run offline (at the end of the execution, you will get a link to the local zip file of the execution)
Task.set_offline(True)Then later you can import it to the system with:
Task.import_offline_session('./my_task_aaa.zip')

Because all my config will be in one place (my training script). I'd like the zipped runs to be at a specific place on the shared disk. Otherwise I'll have to manually copy/paste them so they are visible from the other node (the one running the server)

not really 😞
Why would you want to set it up manually ? makes sense to have it in the cache folder, no?

Is there a way to automatically deduplicate? I'm guessing tasks have some unique id in the zip (maybe even the file name)

BTW: you can quite easily add an option to set the offline folder, check here:
https://github.com/allegroai/trains/blob/10ec4d56fb4a1f933128b35d68c727189310aae8/trains/config/init.py#L31
PRs are always appreciated :)

Thanks. let me try it...

Related, how to I specify in my code the cache_dir where the zip is saved?

Just to clarify, where do I run the second command?

I see that to create a trains.conf file I need to run trains-init which requires a browser. What if I can't open a browser on that machine?

The import process actually creates a new Task every import, that said if you take a look here:
https://github.com/allegroai/trains/blob/10ec4d56fb4a1f933128b35d68c727189310aae8/trains/task.py#L1733
you can pass a pre-existing Task ID to "import_task" https://github.com/allegroai/trains/blob/10ec4d56fb4a1f933128b35d68c727189310aae8/trains/task.py#L1653

E.g. this one https://github.com/allegroai/trains/blob/master/docs/trains.conf

Thanks. On the second one, can I specify it my code? (I'd prefer to avoid a separate trains.conf file if possible)

But this will require some code changes...

Seems to work. Although if I import the same run at two different stages (because I want to see how it's doing while training, not only at the end). it doesn't recognise it's the same task/run just with more iterations. It just creates a new task...

Thanks, Martin.

copy paste the trains.conf from any machine, it just need the definition of the trains-server address.
Specifically if you run in offline mode, there is no need for the trains.conf and you can just copy the one on GitHub

I see.
You can get the offline folder programmatically then copy the folder content (it's the same as the zip, and you can also pass a folder instead of zip to the import function)
task.get_offline_mode_folder()You can also have a soft link of the offline folder (if you are working on a linux machine:
ln -s myoffline_folder ~/.trains/cache/offline

Yes, it will always create a new Task.