use python ffm_encoder

eda/esmm/Feature_pipline/get_tfrecord.py

-#!/usr/bin/env python
 #coding=utf-8
 
 from __future__ import absolute_import

eda/esmm/Model_pipline/DeepCvrMTL.py

-#!/usr/bin/env python
 #coding=utf-8
 
 #from __future__ import absolute_import

eda/esmm/Model_pipline/send_mail.py

-# -*- coding: utf-8 -*-
+#coding=utf-8
 
 import smtplib
 from email.mime.text import MIMEText

eda/esmm/Model_pipline/sort_and_2sql.py

+#coding=utf-8
+
 from sqlalchemy import create_engine
 import pandas as pd
 import pymysql

eda/esmm/Model_pipline/submit.sh

@@ -15,11 +15,8 @@ rm ${DATA_PATH}/va/*
 rm ${DATA_PATH}/native/*
 rm ${DATA_PATH}/nearby/*
 
-echo "mysql to csv"
-mysql -u root -p3SYz54LS9#^9sBvC -h 10.66.157.22 -P 4000 -D jerry_test -e "select number,data from esmm_data2ffm_train" > ${DATA_PATH}/tr.csv
-mysql -u root -p3SYz54LS9#^9sBvC -h 10.66.157.22 -P 4000 -D jerry_test -e "select number,data from esmm_data2ffm_cv" > ${DATA_PATH}/va.csv
-mysql -u root -p3SYz54LS9#^9sBvC -h 10.66.157.22 -P 4000 -D jerry_test -e "select number,data from esmm_data2ffm_infer_native" > ${DATA_PATH}/native.csv
-mysql -u root -p3SYz54LS9#^9sBvC -h 10.66.157.22 -P 4000 -D jerry_test -e "select number,data from esmm_data2ffm_infer_nearby" > ${DATA_PATH}/nearby.csv
+echo "data2ffm"
+${PYTHON_PATH} ${MODEL_PATH}/Feature_pipline/data2ffm.py
 
 echo "split data"
 split -l $((`wc -l < ${DATA_PATH}/tr.csv`/15)) ${DATA_PATH}/tr.csv -d -a 4 ${DATA_PATH}/tr/tr_ --additional-suffix=.csv