fix

app.py

@@ -2,28 +2,25 @@ import gradio as gr
 import torch
 from torch import tensor
 from torch.nn import functional as F
-from sklearn.preprocessing import LabelEncoder
 import pandas as pd
 
-label_encoder = LabelEncoder()
-
 model = torch.load('model.pkl')
 
 def calc(X_test):
     # return model.predict(X_test)
     return X_test
 
-def main(inputs):
-    df = pd.DataFrame(columns=inputs[1:])
-    df.loc[0] = inputs[1:]
+# def main(inputs):
+#     df = pd.DataFrame(columns=inputs[1:])
+#     df.loc[0] = inputs[1:]
 
-    for column in df.columns:
-        df[column] = label_encoder.fit_transform(df[column])
+#     for column in df.columns:
+#         df[column] = label_encoder.fit_transform(df[column])
 
-    t_indep = tensor(df[indep_cols].values, dtype=torch.float)
-    vals,indices = t_indep.max(dim=0)
-    t_indep = t_indep / vals
-    return calc_preds(coeffs, t_indep)
+#     t_indep = tensor(df[indep_cols].values, dtype=torch.float)
+#     vals,indices = t_indep.max(dim=0)
+#     t_indep = t_indep / vals
+#     return calc_preds(coeffs, t_indep)
 
 iface = gr.Interface(
     fn=calc,