Update core/train_eval.py

core/train_eval.py

@@ -167,7 +167,7 @@ def train_and_evaluate(df, features, target, model_cls, horizon=1, hidden=64, la
             train_loss = 0.0
             for batch_X, batch_y in train_loader:
                 optimizer.zero_grad()
-                outputs = model(batch_X)
+                outputs = model(batch_X)  # Ensure only batch_X is passed to model
                 loss = criterion(outputs, batch_y)
                 loss.backward()
                 optimizer.step()
@@ -179,7 +179,7 @@ def train_and_evaluate(df, features, target, model_cls, horizon=1, hidden=64, la
             val_loss = 0.0
             with torch.no_grad():
                 for batch_X, batch_y in test_loader:
-                    outputs = model(batch_X)
+                    outputs = model(batch_X)  # Ensure only batch_X is passed to model
                     loss = criterion(outputs, batch_y)
                     val_loss += loss.item() * batch_X.size(0)
                 val_loss /= len(test_loader.dataset)