diff --git a/rdagent/scenarios/kaggle/experiment/meta_tpl/fea_share_preprocess.py b/rdagent/scenarios/kaggle/experiment/meta_tpl/fea_share_preprocess.py
index b1121f73..787e1698 100644
--- a/rdagent/scenarios/kaggle/experiment/meta_tpl/fea_share_preprocess.py
+++ b/rdagent/scenarios/kaggle/experiment/meta_tpl/fea_share_preprocess.py
@@ -6,15 +6,12 @@ from sklearn.pipeline import Pipeline
 from sklearn.preprocessing import LabelEncoder, OneHotEncoder
 
 
-def prepreprocess(debug_mode=False):
+def prepreprocess():
     """
     This method loads the data, drops the unnecessary columns, and splits it into train and validation sets.
     """
     # Load and preprocess the data
     data_df = pd.read_csv("/kaggle/input/train.csv")
-    if debug_mode:
-        data_df = data_df.sample(frac=0.1, random_state=42)
-    data_df = data_df
     data_df = data_df.drop(["id"], axis=1)
 
     X = data_df.drop(["class"], axis=1)
@@ -81,11 +78,11 @@ def preprocess_transform(X: pd.DataFrame, preprocessor):
     return X_transformed
 
 
-def preprocess_script(debug_mode=False):
+def preprocess_script():
     """
     This method applies the preprocessing steps to the training, validation, and test datasets.
     """
-    X_train, X_valid, y_train, y_valid = prepreprocess(debug_mode=debug_mode)
+    X_train, X_valid, y_train, y_valid = prepreprocess()
 
     # Fit the preprocessor on the training data
     preprocessor = preprocess_fit(X_train)
@@ -96,8 +93,6 @@ def preprocess_script(debug_mode=False):
 
     # Load and preprocess the test data
     submission_df = pd.read_csv("/kaggle/input/test.csv")
-    if debug_mode:
-        data_df = data_df.sample(frac=0.1, random_state=42)
     passenger_ids = submission_df["id"]
     submission_df = submission_df.drop(["id"], axis=1)
     X_test = preprocess_transform(submission_df, preprocessor)
diff --git a/rdagent/scenarios/kaggle/experiment/workspace.py b/rdagent/scenarios/kaggle/experiment/workspace.py
index 64faa6dc..42388785 100644
--- a/rdagent/scenarios/kaggle/experiment/workspace.py
+++ b/rdagent/scenarios/kaggle/experiment/workspace.py
@@ -13,7 +13,7 @@ KG_FEATURE_PREPROCESS_SCRIPT = """import pickle
 
 from fea_share_preprocess import preprocess_script
 
-X_train, X_valid, y_train, y_valid, X_test, passenger_ids = preprocess_script(debug_mode=True)
+X_train, X_valid, y_train, y_valid, X_test, passenger_ids = preprocess_script()
 
 pickle.dump(X_train, open("X_train.pkl", "wb"))
 pickle.dump(X_valid, open("X_valid.pkl", "wb"))