drugforge.ml.early_stopping.ProgressQuotientEarlyStopping

class drugforge.ml.early_stopping.ProgressQuotientEarlyStopping(alpha, k, burnin=0)

Bases: object

Class for stopping based on quotient of generalization loss and training progress. PQ_alpha in the book. This criterion is calculated after every k epochs, and interstitial epochs will automatically not be stopped at.

__init__(alpha, k, burnin=0)

Parameters:

• alpha (float) – Quotient threshold

• k (int) – Length of training strip to evaluate at the end of

• burnin (int, default = 0) – If given, ensure that at least this many epochs of training have been done before we stop

Methods

__init__(alpha, k[, burnin])
check(epoch, loss, wts_dict, train_loss)	Check if training should be stopped.

check(epoch, loss, wts_dict, train_loss)

Check if training should be stopped. Return True to stop, False to keep going.

Parameters:

• loss (float) – Model loss from the current epoch of training

• wts_dict (dict) – Weights dict from Pytorch for keeping track of the best model

Returns:

Whether to stop training

Return type:

bool