f4beaac559e00a3676d942dc7e8fea69efc01cfe,catalyst/metrics/avg_precision.py,,mean_avg_precision,#Any#Any#Any#,74

Before Change

            The map score for every k.
            size: [len(top_k), 1]
    
    map_k_tuple = tuple(
        torch.mean(avg_precision(outputs, targets, k)).item() for k in top_k
    )
    return map_k_tuple


__all__ = ["mean_avg_precision", "avg_precision"]

After Change

    results = []
    for k in topk:
        k = min(outputs.size(1), k)
        results.append(torch.mean(avg_precision(outputs, targets)[:k]))

    return results

Instances