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Support MLFlowLogger
with only the mlflow-skinny
dependency installed
#16486
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Sounds good to me. You will probably need separate variables for each check in case some features are not supported with the skinny version |
Co-authored-by: Carlos Mocholí <[email protected]> Fixes #16486
Why was this merged on 2.0 if it was broken on 1.9? |
@adeandrade We only include bug-fixes in the 1.9.x releases. And this wasn't considered one because it's adding support for this alternative MLFlow package. Does our Logger not work with |
@carmocca pytorch-lightning was working with mlflow-skinny on 1.8 and it broke on 1.9 but I guess mlflow-skinny was not considered before. It's OK. I'll stick to 1.8 until 2.0 is released. |
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Bug description
Sorry not sure to label this as a "feature" or a "bug":
mlflow-skinny
is a variant of themlflow
library that installs the bare-minimum required for tracking: https://pypi.org/project/mlflow-skinny/As far as I can tell, this meets the requirements for using the
MLFlowLogger
, but currently it doesn't work because:https://github.com/Lightning-AI/lightning/blob/4a802e00a843264afd5aea023d8475d4f1b4d360/src/pytorch_lightning/loggers/mlflow.py#L40
checks that precisely the
mlflow
library is installed. If this line were replaced with:It seems to work fine.
Should I make a PR for this? Would we want to add separate tests for
mlflow
andmlflow-skinny
environments?How to reproduce the bug
No response
Error messages and logs
No response
Environment
No response
More info
No response
cc @Borda
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