update loss

core/loss.py

@@ -0,0 +1,16 @@
+import torch
+import PytorchBoot.stereotype as stereotype
+
+@stereotype.loss_function("gf_loss")
+class GFLoss:
+    def __init__(self, config):
+        pass
+
+    def compute(self, output, _):
+        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

losses/gf_loss.py

@@ -1,12 +0,0 @@
-import torch
-import PytorchBoot.stereotype as stereotype
-
-@stereotype.loss_function("gf_loss")
-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