Source code for catalyst.dl.callbacks.metrics.auc

from typing import List

from catalyst.dl.callbacks import MeterMetricsCallback
from catalyst.utils import meters

[docs]class AUCCallback(MeterMetricsCallback): """Calculates the AUC per class for each loader. .. note:: Currently, supports binary and multi-label cases. """
[docs] def __init__( self, input_key: str = "targets", output_key: str = "logits", prefix: str = "auc", class_names: List[str] = None, num_classes: int = 2, activation: str = "Sigmoid", ): """ Args: input_key (str): input key to use for auc calculation specifies our ``y_true`` output_key (str): output key to use for auc calculation; specifies our ``y_pred`` prefix (str): name to display for auc when printing class_names (List[str]): class names to display in the logs. If None, defaults to indices for each class, starting from 0 num_classes (int): Number of classes; must be > 1 activation (str): An torch.nn activation applied to the outputs. Must be one of ``'none'``, ``'Sigmoid'``, or ``'Softmax2d'`` """ num_classes = num_classes if class_names is None else len(class_names) meter_list = [meters.AUCMeter() for _ in range(num_classes)] super().__init__( metric_names=[prefix], meter_list=meter_list, input_key=input_key, output_key=output_key, class_names=class_names, num_classes=num_classes, activation=activation, )
__all__ = ["AUCCallback"]