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author | Jordan Gong <jordan.gong@protonmail.com> | 2021-03-01 11:20:34 +0800 |
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committer | Jordan Gong <jordan.gong@protonmail.com> | 2021-03-01 11:20:34 +0800 |
commit | 4bdc37bbd86a83647bbbda7bd1367c08e6c6f6d4 (patch) | |
tree | 88840ce856b023b97138958f4b2cb7e2875bdd0e | |
parent | fed5e6a9b35fda8306147e9ce772dfbf3142a061 (diff) |
Remove identical sample in Batch All case
-rw-r--r-- | utils/triplet_loss.py | 5 |
1 files changed, 4 insertions, 1 deletions
diff --git a/utils/triplet_loss.py b/utils/triplet_loss.py index db0cf0f..6822cf6 100644 --- a/utils/triplet_loss.py +++ b/utils/triplet_loss.py @@ -68,7 +68,10 @@ class BatchTripletLoss(nn.Module): @staticmethod def _all_distance(dist, y, p, n): - positive_mask = y.unsqueeze(1) == y.unsqueeze(2) + # Unmask identical samples + positive_mask = torch.eye( + n, dtype=torch.bool, device=y.device + ) ^ (y.unsqueeze(1) == y.unsqueeze(2)) negative_mask = y.unsqueeze(1) != y.unsqueeze(2) all_positive = dist[positive_mask].view(p, n, -1, 1) all_negative = dist[negative_mask].view(p, n, 1, -1) |