success

losses/gf_loss.py

@@ -0,0 +1,11 @@
+import torch
+
+
+def compute_loss(output, data):
+    estimated_score = output['estimated_score']
+    target_score = output['target_score']
+    std = output['std']
+    bs = estimated_score.shape[0]
+    loss_weighting = std ** 2
+    loss = torch.mean(torch.sum((loss_weighting * (estimated_score - target_score) ** 2).view(bs, -1), dim=-1))
+    return loss