change train.py

eda/esmm/Model_pipline/train.py

@@ -470,7 +470,7 @@ if __name__ == "__main__":
             result = main(te_files)
             df = df_sort(result,queue_name)
             # df2 = df.drop("time",1)
-            df.to_csv(FLAGS.local_dir + "nearby_queue.csv", header=True, index=False)
+            df.to_csv(FLAGS.local_dir + "/nearby_queue.csv", header=True, index=False)
             # df.to_sql('esmm_device_diary_queue_nearby', con=engine, if_exists='replace', index=False, chunksize=8000)
         if queue_name == "native_queue":
             print(queue_name + " task")
@@ -479,7 +479,7 @@ if __name__ == "__main__":
             # nearby_sql = "select device_id,city_id,nearby_queue from esmm_device_diary_queue_nearby"
             # cur.execute(nearby_sql)
             # df_nearby = cur.fetchall()
-            df_nearby = pd.read_csv(FLAGS.local_dir + "nearby_queue.csv")
+            df_nearby = pd.read_csv(FLAGS.local_dir + "/nearby_queue.csv")
             #merge
             df_merge = pd.merge(df_native,df_nearby, on=['device_id', 'city_id'], how='outer').fillna("")
             df_merge['device_id'] = df_merge['device_id'].astype(str)