optim start

src/models/param_scan.py

@@ -358,47 +358,51 @@ def main():
     with open("configs/train_config.yaml", "r") as f:
         config = yaml.load(f, Loader=yaml.FullLoader)
 
-    models = ["cnn", "rnn", "transformer"]
+    # models = ["cnn", "rnn", "transformer"]
     targets = ["regression", "classification", "multi_classification"]
 
-    for current_model in models:
-        model_type = current_model
-        for target_type in targets:
-            target = target_type
-    # model_type = "rnn"
-    # target = "classification"
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--model_type", type=str, default="cnn", help="Type of model to train."
+    )
+    args = parser.parse_args()
+    model_type = args.model_type
+    print("model_type:", model_type)
+
+    for target_type in targets:
+        target = target_type
 
-            data_path = config["data_path"]
-            data_mean = config["data_mean"]
-            data_std = config["data_std"]
-            n_train = config["n_train"]
-            n_val = config["n_val"]
-            n_test = config["n_test"]
-            batch_size = config["batch_size"]
-            buffer_size = config["buffer_size"]
-            epochs = config["epochs"]
-            optimizer = config["optimizer"]
-            loss = config["loss"]
-            learning_rate = config["learning_rate"]
-            model_config = config["model_config"]
-
-            train(
-                data_path,
-                data_mean,
-                data_std,
-                n_train,
-                n_val,
-                n_test,
-                batch_size,
-                buffer_size,
-                epochs,
-                optimizer,
-                loss,
-                learning_rate,
-                model_config,
-                model_type,
-                target,
-            )
+        data_path = config["data_path"]
+        data_mean = config["data_mean"]
+        data_std = config["data_std"]
+        n_train = config["n_train"]
+        n_val = config["n_val"]
+        n_test = config["n_test"]
+        batch_size = config["batch_size"]
+        buffer_size = config["buffer_size"]
+        epochs = config["epochs"]
+        optimizer = config["optimizer"]
+        loss = config["loss"]
+        learning_rate = config["learning_rate"]
+        model_config = config["model_config"]
+
+        train(
+            data_path,
+            data_mean,
+            data_std,
+            n_train,
+            n_val,
+            n_test,
+            batch_size,
+            buffer_size,
+            epochs,
+            optimizer,
+            loss,
+            learning_rate,
+            model_config,
+            model_type,
+            target,
+        )
 
 
 if __name__ == "__main__":