Merely define preferred backend for joblib instead of hard-coding it #476
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Reason: According to [1] hard-coding `backend` is discouraged: It is not recommended to hard-code the backend name in a call to Parallel in a library. Instead it is recommended to set soft hints (prefer) or hard constraints (require) so as to make it possible for library users to change the backend from the outside using the parallel_backend context manager. [1] https://joblib.readthedocs.io/en/latest/generated/joblib.Parallel.html
heiderich
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Feb 14, 2022
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Thanks @heiderich for the contribution! It seems that prefer is indeed the right way to specify the backend in joblib instead of backend.
Could you share in which environment (e.g. OS, Python version, joblib version, etc.) you ran into the issue as a reference? Thanks!
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@jeongyoonlee I already mentioned some of the relevant versions in #475. I just added the |
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Proposed changes
This fixes #475 by merely indicating a preference for the backend instead of hardcoding it. This way users can specify the backend using
joblib.parallel_backend(see https://joblib.readthedocs.io/en/latest/parallel.html#parallel) according to their circumstances.Types of changes
What types of changes does your code introduce to CausalML?
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xin the boxes that apply. You can also fill these out after creating the PR. If you're unsure about any of them, don't hesitate to ask. We're here to help! This is simply a reminder of what we are going to look for before merging your code.Further comments
Related: #468