Update app.py

app.py

@@ -9,18 +9,10 @@ from official.nlp.data import classifier_data_lib
 from official.nlp.bert import tokenization
 from official.nlp import optimization
 tf.get_logger().setLevel('ERROR')
-
 import math
 from datetime import datetime
-
 import gradio as gr
 
-import socket
-hostname = socket.gethostname()
-ip_address = socket.gethostbyname(hostname)
-print(f"Hostname: {hostname}")
-print(f"IP Address: {ip_address}")
-
 
 config = tf.compat.v1.ConfigProto(
         device_count = {'cpu': 0}
@@ -38,16 +30,12 @@ optimizer = optimization.create_optimizer(init_lr=init_lr,
 checkpoint_filepath=r'./Checkpoint'
 model = tf.keras.models.load_model(checkpoint_filepath, custom_objects={'KerasLayer':hub.KerasLayer , 'AdamWeightDecay': optimizer})
 
-
-
 df_report = pd.read_csv('./CTH_Description.csv')
 df_report['CTH Code'] = df_report['CTH Code'].astype(str).str.zfill(8)
 
 df_report_DUTY = pd.read_csv('./CTH_WISE_DUTY_RATE.csv')
 df_report_DUTY['CTH'] = df_report_DUTY['CTH'].astype(str).str.zfill(8)
 
-#print(df_report_DUTY)
-
 df = pd.read_csv("./CTH_CODE_MAP.csv")
 df['CTH'] = df['CTH'].astype(str).str.zfill(8)
 df = df[['CTH', 'code']]