ESMValGroup · rogerkuou · Jul 15, 2026 · Jul 15, 2026 · Jul 16, 2026 · Jul 16, 2026
diff --git a/climanet/predict.py b/climanet/predict.py
@@ -95,6 +95,10 @@ def predict_monthly_var(
     model.to(device)
     model.eval()
 
+    # Length of the dataset should >=1
+    if len(dataset) < 1:
+        raise ValueError("The dataset is empty. Please provide a non-empty dataset.")
+
     use_cuda = device == "cuda"
     dataloader = DataLoader(
         dataset,
@@ -116,7 +120,7 @@ def predict_monthly_var(
 
     with torch.inference_mode():
         idx = 0
-        average_loss = 0.0
+        average_loss = torch.tensor(0.0, device=device)
         for i, batch in enumerate(dataloader):
             # Move batch to the appropriate device
             batch = {k: v.to(device, non_blocking=use_cuda) for k, v in batch.items()}

diff --git a/notebooks/data_vis.ipynb → notebooks/data_vis_sst.ipynb b/notebooks/data_vis.ipynb → notebooks/data_vis_sst.ipynb
diff --git a/notebooks/example_daily.ipynb → notebooks/example_daily_sst.ipynb b/notebooks/example_daily.ipynb → notebooks/example_daily_sst.ipynb
diff --git a/notebooks/example_hourly.ipynb → notebooks/example_hourly_sst.ipynb b/notebooks/example_hourly.ipynb → notebooks/example_hourly_sst.ipynb