# src.evaluation_metric.matching_recall¶

src.evaluation_metric.matching_recall(pmat_pred: torch.Tensor, pmat_gt: torch.Tensor, ns: torch.Tensor) torch.Tensor[source]

Matching Recall between predicted permutation matrix and ground truth permutation matrix.

$\text{matching recall} = \frac{tr(\mathbf{X}\cdot {\mathbf{X}^{gt}}^\top)}{\sum \mathbf{X}^{gt}}$
Parameters
• pmat_pred$$(b\times n_1 \times n_2)$$ predicted permutation matrix $$(\mathbf{X})$$

• pmat_gt$$(b\times n_1 \times n_2)$$ ground truth permutation matrix $$(\mathbf{X}^{gt})$$

• ns$$(b)$$ number of exact pairs. We support batched instances with different number of nodes, and ns is required to specify the exact number of nodes of each instance in the batch.

Returns

$$(b)$$ matching recall

Note

This function is equivalent to “matching accuracy” if the matching problem has no outliers.