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authorJordan Gong <jordan.gong@protonmail.com>2021-01-07 18:37:43 +0800
committerJordan Gong <jordan.gong@protonmail.com>2021-01-07 18:37:43 +0800
commit4a284084c253b9114fc02e1782962556ff113761 (patch)
treed6ceff8da68b224186d84772ee6153353675bcfe /utils
parenta27af5dfd58e7b48cf3bd063fa2b4b51ed1e0277 (diff)
Add typical training script and some bug fixes
1. Resolve deprecated scheduler stepping issue 2. Make losses in the same scale(replace mean with sum in separate triplet loss, enlarge pose similarity loss 10x) 3. Add ReLU when compute distance in triplet loss 4. Remove classes except Model from `models` package init
Diffstat (limited to 'utils')
-rw-r--r--utils/triplet_loss.py6
1 files changed, 4 insertions, 2 deletions
diff --git a/utils/triplet_loss.py b/utils/triplet_loss.py
index 242be45..1d63a0e 100644
--- a/utils/triplet_loss.py
+++ b/utils/triplet_loss.py
@@ -18,7 +18,9 @@ class BatchAllTripletLoss(nn.Module):
x1_squared_sum = x_squared_sum.unsqueeze(1)
x2_squared_sum = x_squared_sum.unsqueeze(2)
x1_times_x2_sum = x @ x.transpose(1, 2)
- dist = torch.sqrt(x1_squared_sum - 2 * x1_times_x2_sum + x2_squared_sum)
+ dist = torch.sqrt(
+ F.relu(x1_squared_sum - 2 * x1_times_x2_sum + x2_squared_sum)
+ )
hard_positive_mask = y.unsqueeze(1) == y.unsqueeze(2)
hard_negative_mask = y.unsqueeze(1) != y.unsqueeze(2)
@@ -31,5 +33,5 @@ class BatchAllTripletLoss(nn.Module):
parted_loss_mean = all_loss.sum(1) / (all_loss != 0).sum(1)
parted_loss_mean[parted_loss_mean == float('Inf')] = 0
- loss = parted_loss_mean.mean()
+ loss = parted_loss_mean.sum()
return loss