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Hi All, Looking For Some Help When Executing Pipelines With Custom Docker Images. I Have A Component Defined And I Expect Its Python Runtime Environment To Be Managed By A Custom Docker Image (


What’s interesting to me (as a ClearML newbie) is it’s clearly compiling that wheel using my host machine (MacOS).

Hmm kind of, and kind of not.
If you take a look at the Tasks created (regardless on how they are created,. pipeline, manually, etc.), you have a list of python packages required by the code, as they are detected at runtime (i.e. when the code was first executed, on the development machine). When creating a Pipeline controller (runner), the pipeline Tasks are just lists, and package version are listed based on the Machine running the initial pipeline (in your case Mac), the reason is so at least we have a version pf the packages (if exist) that will be working for you Yes you are correct, there should not be a connection between the runner machine and the remote machine, that said we do want to be able to specify the required packages and usually python packages are available on most OS distro. If we were not auto-detecting them, then you would have had to specify them manually, which you can also do and it will override the packages it detected. Does that make sense ?

Just threw a new file into the gist above

Not sure what I'm seeing there, but it definitely does not include the error.
If it helps you can DM me the full log (btw: all pass/secrets are automatically masked from the log, but I would double chech just in case 😉 )

  
  
Posted 2 years ago
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