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It would be nice to enable saving and loading models checkpoints, this could help to control training the model in different sessions in case is a large model, as well as keeping a copy of the model in case of some error during the training time
I open this issue for contributors
This Issue requests the following features:
Describe the solution you'd expect
Enable saving model checkpoints as a callback named ModelCheckpoint that takes as an argument the location to save the model
The checkpoints should save the training status and the logbook object, you can make use of the already implemented class LogbookSaver
Implement save and load methods in GASearchCV and GAFeatureSelectionCV
When calling the fit method, it should resume the training where it was left by default
Enable an option to start the training again (from generation 0) but with starting point (i.e hyperparameters or features) the best ones found so far in the saved model
Additional context
You can check TensorFlow save and load weights methods as an inspiration
The text was updated successfully, but these errors were encountered:
@rodrigo-arenas I have some questions about the last two bullet points:
When calling the fit method, it should resume the training where it was left by default
Enable an option to start the training again (from generation 0) but with starting point (i.e hyperparameters or features) the best ones found so far in the saved model
Should there be an option provided to the fit method to start training again? Or should the functionality described above be implemented within the ModelCheckpoint callback?
Do you mean that I should be able to use the load method to load from the checkpoint path, similar to what is described in TensorFlow's ModelCheckpoint?
It would be nice to enable saving and loading models checkpoints, this could help to control training the model in different sessions in case is a large model, as well as keeping a copy of the model in case of some error during the training time
I open this issue for contributors
This Issue requests the following features:
Describe the solution you'd expect
ModelCheckpoint
that takes as an argument the location to save the modelLogbookSaver
GASearchCV
andGAFeatureSelectionCV
Additional context
You can check TensorFlow save and load weights methods as an inspiration
The text was updated successfully, but these errors were encountered: