target_mapping = {'like': 1, 'view': 0.5, 'skip': -0.5, 'dislike': -1}
reverse_mapping = {y: x for x, y in target_mapping.items()}
label_weight = {'like': 0.5, 'view': 0.1, 'skip': -0.1, 'dislike': -10}
if len(target_mapping) != len(reverse_mapping):
    raise ValueError("Invalid mapping")

class CustomCbLoss:

    def calc_ders_range(self, approxes, targets, weights):
        assert len(approxes) == len(targets)
        if weights is not None:
            assert len(weights) == len(approxes)
        results = []
        for t, p in zip(targets, approxes):
            results.append((label_weight[reverse_mapping[t]], 0))
        return results


def vc_metric(y_label, y_pred, weights=None):
    return sum(label_weight[reverse_mapping[l]] * p * (weights[i] if weights is not None else 1)
               for i, (l, p) in enumerate(zip(y_label, y_pred)))

class VCCBMetric:

    def get_final_error(self, error, weight):
        return error / (weight + 1e-38)

    def is_max_optimal(self):
        return True

    def evaluate(self, approxes, targets, weights):
        return vc_metric(targets, approxes[0], weights), sum(weights) if weights is not None else len(approxes)