Closed sarahmish closed 2 years ago
In keras adapter, we build the model within the fit function, this entails that with every fit call we will rebuild the model and thus we cannot "continue" the process of training (i.e. call fit twice to train the same model).
keras
fit
https://github.com/MLBazaar/MLPrimitives/blob/19f00492cf8a73eb6f89f3146ec442257babfc6c/mlprimitives/adapters/keras.py#L101-L104
Is this the expected behavior? Or should there be a flag to indicate if this is the first call to fit, then build the model, otherwise continue
if not self._fitted: self._augment_hyperparameters(X, 'input', kwargs) self._augment_hyperparameters(y, 'target', kwargs) self.model = self._build_model(**kwargs)
Description
In
kerasadapter, we build the model within thefitfunction, this entails that with everyfitcall we will rebuild the model and thus we cannot "continue" the process of training (i.e. callfittwice to train the same model).https://github.com/MLBazaar/MLPrimitives/blob/19f00492cf8a73eb6f89f3146ec442257babfc6c/mlprimitives/adapters/keras.py#L101-L104
Is this the expected behavior? Or should there be a flag to indicate if this is the first call to
fit, then build the model, otherwise continue