update basic model

models/basic_model.py

@@ -131,21 +131,19 @@ class BasicModel():
         
         model.train()
 
-        loss_value = 0
-        for _, data in enumerate(data_loader):
-            X = data[0].to(device)
-            Y = data[1].to(device)
-            pred_Y = model(X)
-
-            loss = criterion(pred_Y, Y)
+        total_loss, total_num = 0.0, 0
+        for data, target in data_loader:
+            data, target = data.to(device), target.to(device)
+            out = model(data)
+            loss = criterion(out, target)
 
             optimizer.zero_grad()
             loss.backward()
             optimizer.step()
 
-            loss_value += loss.item()
+            total_loss += loss.item() * data.size(0)
 
-        return loss_value
+        return total_loss / total_num
 
     def _predict(self, data_loader):
         model = self.model
@@ -155,9 +153,9 @@ class BasicModel():
 
         with torch.no_grad():
             results = []
-            for _, data in enumerate(data_loader):
-                X = data[0].to(device)
-                pred_Y = model(X)
+            for data, _ in data_loader:
+                data = data.to(device)
+                pred_Y = model(data)
                 results.append(pred_Y)
     
         return torch.cat(results, axis=0)