f4beaac559e00a3676d942dc7e8fea69efc01cfe,catalyst/metrics/mrr.py,,mrr,#,8

Before Change

        result (torch.Tensor):
            The mrr score for each user.
    
    k = min(outputs.size(1), k)
    _, indices_for_sort = outputs.sort(descending=True, dim=-1)
    true_sorted_by_preds = torch.gather(
        targets, dim=-1, index=indices_for_sort
    )

After Change

        mrr_score (torch.Tensor):
            The mrr score for each batch.
    
    results = []
    for k in topk:
        results.append(torch.mean(reciprocal_rank(outputs, targets, k)))

    return results


__all__ = ["reciprocal_rank", "mrr"]

Instances