Fix black

exps/synthetic/baseline.py

@@ -73,7 +73,7 @@ def main(save_dir):
 
     additional_xaxis = np.arange(-6, 6, 0.2)
     models = dict()
-    
+
     for idx, (timestamp, dataset) in enumerate(tqdm(dynamic_env, ncols=50)):
         xaxis_all = dataset[:, 0].numpy()
         # xaxis_all = np.concatenate((additional_xaxis, xaxis_all))
@@ -84,15 +84,19 @@ def main(save_dir):
         # split the dataset
         indexes = list(range(xaxis_all.shape[0]))
         random.shuffle(indexes)
-        train_indexes = indexes[:len(indexes)//2]
-        valid_indexes = indexes[len(indexes)//2:]
+        train_indexes = indexes[: len(indexes) // 2]
+        valid_indexes = indexes[len(indexes) // 2 :]
         train_xs, train_ys = xaxis_all[train_indexes], yaxis_all[train_indexes]
         valid_xs, valid_ys = xaxis_all[valid_indexes], yaxis_all[valid_indexes]
-        
+
         model, loss_fn, train_loss = optimize_fn(train_xs, train_ys)
         # model, loss_fn, train_loss = optimize_fn(xaxis_all, yaxis_all)
         pred_valid_ys, valid_loss = evaluate_fn(model, valid_xs, valid_ys, loss_fn)
-        print("[{:03d}] T-{:03d}, train-loss={:.5f}, valid-loss={:.5f}".format(idx, timestamp, train_loss, valid_loss))
+        print(
+            "[{:03d}] T-{:03d}, train-loss={:.5f}, valid-loss={:.5f}".format(
+                idx, timestamp, train_loss, valid_loss
+            )
+        )
 
         # the first plot
         scatter_list = []
@@ -114,10 +118,10 @@ def main(save_dir):
                 "color": "r",
                 "s": 10,
                 "alpha": 0.5,
-                "label": "MLP at now"
+                "label": "MLP at now",
             }
         )
-        
+
         draw_fig(save_dir, timestamp, scatter_list)
     print("Save all figures into {:}".format(save_dir))
     save_dir = save_dir.resolve()

lib/xlayers/super_module.py

@@ -49,8 +49,8 @@ class SuperModule(abc.ABC, nn.Module):
     def add_module(self, name: str, module: Optional[torch.nn.Module]) -> None:
         if not isinstance(module, SuperModule):
             warnings.warn(
-                "Add {:} module, which is not SuperModule, into {:}".format(
-                    name, self.__class__.__name__
+                "Add {:}:{:} module, which is not SuperModule, into {:}".format(
+                    name, module.__class__.__name__, self.__class__.__name__
                 )
                 + "\n"
                 + "It may cause some functions invalid."