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| author | Jordan Gong <jordan.gong@protonmail.com> | 2021-02-08 18:11:25 +0800 |
|---|---|---|
| committer | Jordan Gong <jordan.gong@protonmail.com> | 2021-02-08 18:25:42 +0800 |
| commit | 99ddd7c142a4ec97cb8bd14b204651790b3cf4ee (patch) | |
| tree | a4ccbd08a7155e90df63aba60eb93ab2b7969c9b /utils/triplet_loss.py | |
| parent | 507e1d163aaa6ea4be23e7f08ff6ce0ef58c830b (diff) | |
Code refactoring, modifications and new features
1. Decode features outside of auto-encoder
2. Turn off HPM 1x1 conv by default
3. Change canonical feature map size from `feature_channels * 8 x 4 x 2` to `feature_channels * 2 x 16 x 8`
4. Use mean of canonical embeddings instead of mean of static features
5. Calculate static and dynamic loss separately
6. Calculate mean of parts in triplet loss instead of sum of parts
7. Add switch to log disentangled images
8. Change default configuration
Diffstat (limited to 'utils/triplet_loss.py')
| -rw-r--r-- | utils/triplet_loss.py | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/utils/triplet_loss.py b/utils/triplet_loss.py index 8c143d6..d573ef4 100644 --- a/utils/triplet_loss.py +++ b/utils/triplet_loss.py @@ -34,5 +34,5 @@ class BatchAllTripletLoss(nn.Module): parted_loss_mean = all_loss.sum(1) / non_zero_counts parted_loss_mean[non_zero_counts == 0] = 0 - loss = parted_loss_mean.sum() + loss = parted_loss_mean.mean() return loss |