c78c065b44a97ee3afe2172d2213479622a29562,poutyne/framework/metrics/epoch_metrics/fscores.py,FBeta,forward,#FBeta#Any#Any#,138

Before Change

            self._pred_sum = torch.zeros(num_classes, device=y_pred.device)
            self._total_sum = torch.zeros(num_classes, device=y_pred.device)

        if mask is None:
            mask = torch.ones_like(y_true)
        mask = mask.to(dtype=torch.bool)
        y_true = y_true.float()

        argmax_y_pred = y_pred.max(dim=1)[1].float()

After Change

            y_true, mask = y_true
            mask |= mask.bool()

        if self.ignore_index is not None:
            mask |= y_true != self.ignore_index

        // Calculate true_positive_sum, true_negative_sum, pred_sum, true_sum
        num_classes = y_pred.size(1)
        if (y_true >= num_classes).any():
            raise ValueError("A gold label passed to FBetaMeasure contains "
                             "an id >= {}, the number of classes.".format(num_classes))

Instances