def test_multilabel_metrics_without_num_classes(
    outputs: torch.Tensor,
    targets: torch.Tensor,
    zero_division: int,
    true_values: Dict[str, float],
) -> None:
    """
    Test multilabel metric

    Args:
        outputs: tensor of predictions
        targets: tensor of targets
        zero_division: zero division policy flag
        true_values: true values of metrics
    """
    metric = MultilabelPrecisionRecallF1SupportMetric(zero_division=zero_division)
    metric.update(outputs=outputs, targets=targets)
    metrics = metric.compute_key_value()
    for key in true_values:
        assert key in metrics
        assert abs(metrics[key] - true_values[key]) < EPS

    Test multilabel metric

    Args:
        outputs: tensor of predictions
        targets: tensor of targets
        zero_division: zero division policy flag
        true_values: true values of metrics
    
tests/catalyst/metrics/test_classification.py