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

losses/loss_function_factory.py

@@ -0,0 +1,18 @@
+import losses.gf_loss
+
+
+class LossFunctionFactory:
+    @staticmethod
+    def create(function_name):
+        if function_name == "gf_loss":
+            return losses.gf_loss.compute_loss
+        else:
+            raise ValueError("Unknown loss function {}".format(function_name))
+
+
+''' ------------ Debug ------------ '''
+if __name__ == "__main__":
+    from configs.config import ConfigManager
+
+    ConfigManager.load_config_with('../configs/local_train_config.yaml')
+    ConfigManager.print_config()