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16 × Eureka!conda has 3.11.6 installed in the base env,
and the base shell appears to not have python installed at all
And the task seems to not be installing from requirements.txt, because one package ends up missing
the problem seems to come and go … really not sure if anything I am changing is resolving it,
e.g. restarting the daemon,
changing to bash shell as the default login for osx
And the clearml-agent
is installed in the “base” conda env
@<1523701087100473344:profile|SuccessfulKoala55> well, afaik, the base Xcode python 3.9.6 is installed with the Xcode tools, in /usr/bin
, and then anaconda installed as the user running the clearml-agent
,
conda init is in both the .bashrc
and .bash_profile
🤔 does a job/experiment always reproduce from git + commit hash + specific file?
(again, haven’t read through all the docs yet, a lot to take in)
🤔 could one create empty draft experiment placeholders, finalize all their code, commit it, and then and manually connect the impl as it exists in a file in a commit in a repo to that draft, once I’ve decided that all development is done?
but I’ll try out what you said - parameterize it all, and run a short version locally, then scale up in the UI
huh, ok … the need to run stuff locally first is a little odd, ngl… just have to get a sense of what the workflow here is
but it looks like execute_remotely
is indeed what I want, and I should just standardize on using that,
either in-situ, or in an outer runner script that just calls that first, then calls down to my actual implementation
@<1523701087100473344:profile|SuccessfulKoala55> any insight on this? still blocked
local development is fine, but local-running-first I am just unsure about
I suspect that this is something to do with system python vs conda python … but, very opaque
@<1523701087100473344:profile|SuccessfulKoala55> any insight on this? still blocked
the agent is running on the separate worker machine running OSX,
being launched byclearml-agent daemon --detached
I am running the job by:
- making a git commit
- running my jupyter notebook locally to create the “base” task
- cloning that and changing ‘configuration’
- enqueueing