def remove_unseen_classes_from_training(train_mask, labels, removed_class):
    """Remove the unseen classes (the first three classes by default) to get the zero-shot (i.e., completely imbalanced) label setting
    Input: train_mask, labels, removed_class
    Output: train_mask_zs: the bool list only containing seen classes
    """
    train_mask_zs = train_mask.clone()
    for i in range(train_mask_zs.numel()):
        if train_mask_zs[i] == 1 and (labels[i].item() in removed_class):
            train_mask_zs[i] = 0
    return train_mask_zs
Remove the unseen classes (the first three classes by default) to get the zero-shot (i.e., completely imbalanced) label setting
    Input: train_mask, labels, removed_class
    Output: train_mask_zs: the bool list only containing seen classes
    
examples/pytorch/rect/label_utils.py