prevision_quantum_nn.models.utilities.early_stopper¶
early stopper module
Module Contents¶
Classes¶
EarlyStopper |
Class EarlyStopper. |
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class
prevision_quantum_nn.models.utilities.early_stopper.EarlyStopper(window=10)¶ Class EarlyStopper.
Used to early stop the convergence of the quantum neural network
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window¶ early stopper window or patience
Type: int
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val_losses¶ list of validation losses to be kept in memory
Type: list
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best_var¶ the best set of weights that yielded the minimum loss in the window
Type: list
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best_val_loss¶ best validation loss so far in the window
Type: float
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buffer¶ keeps the weights of the models until early stopper criterion is met
Type: queue
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add_validation_loss(self, loss)¶ Adds validation loss to loss buffer.
Also stores the best loss reached so far.
Parameters: loss (float) – loss of the current iteration
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get_stopping_criterion(self)¶ Stopping_criterions.
Returns: - bool
- True is algorithm should stop False if algorithm should continue
Return type: stopping_criterion
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update(self, val_loss, var)¶ Updates the early stopper at a given iteration.
Parameters: - val_loss (float) – validation loss to be stored
- var – (list):list of weights that yielded this loss
Returns: - bool
if True, the calculatino will stop
Return type: stopping_criterion
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get_best_var(self)¶ Returns best weights.
Returns: - list
- list of best weights
Return type: best_var
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