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Add Callbacks for logging and/or performing custom operations after every generation #678

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weixuanfu opened this issue Mar 26, 2018 · 4 comments

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@weixuanfu
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weixuanfu commented Mar 26, 2018

Similar to Keras's “callbacks”— we need add a class that can access the training state after every training iteration for better logging and/or performing custom operations after every generation during TPOT optimization. This class is related to a few features in current version (0.9.2) of TPOT (e.g. early stopping and verbosity in general).

Related issue #667

@rhiever
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rhiever commented Mar 28, 2018

Looking forward to this in TPOT. I think it will clean up the interface quite a bit.

@MarkusShepherd
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This would be a great feature, e.g., for MLflow to track metrics across generations. What would be required to implement this?

@agi1512
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agi1512 commented Mar 27, 2021

Still looking forward for this feature to be implemented.

@kenimou
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kenimou commented Apr 14, 2021

This will be great to have. Would like to integrate with mlflow if possible so that we have more visibility into what has been done, etc.

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