import torch


def proba_to_label(probas):
    """
    Converts predicted probabilities from extended binary format
    to integer class labels
    Parameters
    ----------
    probas : torch.tensor, shape(n_examples, n_labels)
        Torch tensor consisting of probabilities returned by CORAL model.
    Examples
    ----------
    >>> # 3 training examples, 6 classes
    >>> probas = torch.tensor([[0.934, 0.861, 0.323, 0.492, 0.295],
    ...                        [0.496, 0.485, 0.267, 0.124, 0.058],
    ...                        [0.985, 0.967, 0.920, 0.819, 0.506]])
    >>> proba_to_label(probas)
    tensor([2, 0, 5])
    """
    predict_levels = probas > 0.5
    predicted_labels = torch.sum(predict_levels, dim=1)
    return predicted_labels