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This repository has been archived by the owner on Sep 29, 2023. It is now read-only.
Currently the training loop is in ehr_ml/blob/master/ehr_ml/clmbr/__init__.py. Training should be external to the specific model choice to better support other architecture choices and hook into existing training/tunining frameworks like Ray Tune, pytorch lightning
The text was updated successfully, but these errors were encountered:
I moved the training loop to ehr_ml/clmbr/featurizer inside a .fit method. Not exactly external to the model (actually kind of built-in to the featurizer class now) but in the featurizer class does build the model based on the config, so in that sense this kind of accomplishes the goal of model-agnostic training code?
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Currently the training loop is in
ehr_ml/blob/master/ehr_ml/clmbr/__init__.py
. Training should be external to the specific model choice to better support other architecture choices and hook into existing training/tunining frameworks like Ray Tune, pytorch lightningThe text was updated successfully, but these errors were encountered: