--- a
+++ b/experiments/train_normal_pipeline.py
@@ -0,0 +1,25 @@
+import sys
+from collect_generalizability_metrics import get_generalizability_gap
+from training.vanilla_trainer import VanillaTrainer
+
+if __name__ == '__main__':
+    config = {"model": "DeepLab",
+              "device": "cuda",
+              "lr": 0.00001,
+              "batch_size": 8,
+              "epochs": 250}
+    trainer = VanillaTrainer(sys.argv[1], config)
+    trainer.train()
+
+    # for i in ["TriUnet", "DeepLab", "FPN", "Unet"]:
+    #     config["model"] = i
+    #     trainer = VanillaTrainer(sys.argv[1], config)
+    #     trainer.train()
+    # for i in range(13, 100):
+    #     trainer = VanillaTrainer("DeepLab", i, config)
+    #     trainer.train()
+    # i = 4
+    # while True:
+    #     config = {"epochs": 200, "id": i, "lr": 0.00001, "pretrain": False}
+    #     training.vanilla_trainer.train_vanilla_predictor(config)
+    #     i += 1