try swin

main.py

@@ -716,17 +716,19 @@ if __name__ == "__main__":
         model.load_model(save_path)
         model.evaluate('test')
     else:
-        while True:
-            try:
-                model = Main(args, logger)
-                model.fit()
-            except Exception as e:
-                print(e)
-                traceback.print_exc()
-                try:
-                    del model
-                except Exception:
-                    pass
-                time.sleep(30)
-                continue
-            break
+        model = Main(args, logger)
+        model.fit()
+        # while True:
+        #     try:
+        #         model = Main(args, logger)
+        #         model.fit()
+        #     except Exception as e:
+        #         print(e)
+        #         traceback.print_exc()
+        #         try:
+        #             del model
+        #         except Exception:
+        #             pass
+        #         time.sleep(30)
+        #         continue
+        #     break

models.py

@@ -862,7 +862,7 @@ class PoolFormerBlock(nn.Module):
         self.norm1 = norm_layer(dim)
         #self.token_mixer = Pooling(pool_size=pool_size)
         # self.token_mixer = FNetBlock()
-        self.token_mixer = WindowAttention(dim=dim, window_size=to_2tuple(7), num_heads=3, pretrained_window_size=[5,5])
+        self.token_mixer = WindowAttention(dim=dim, window_size=to_2tuple(7), num_heads=1, pretrained_window_size=[5,5])
         self.norm2 = norm_layer(dim)
         mlp_hidden_dim = int(dim * mlp_ratio)
         self.mlp = Mlp(in_features=dim, hidden_features=mlp_hidden_dim,