pass n_classes arg to metric.compute_metric

    for metric in metrics:

      if per_task_metrics:

        multitask_scores[metric.name], computed_metrics = metric.compute_metric(

            y, y_pred, w, per_task_metrics=True)

            y, y_pred, w, per_task_metrics=True, n_classes = self.n_classes)

        all_task_scores[metric.name] = computed_metrics

      else:

        multitask_scores[metric.name] = metric.compute_metric(

            y, y_pred, w, per_task_metrics=False)

            y, y_pred, w, per_task_metrics=False, n_classes = self.n_classes)

    if not per_task_metrics:

      return multitask_scores