rov-offline/ad_model_run.sh

#!/bin/bash
source ~/.bash_profile
conda activate rov-offline-py38
cd /data/rov-offline
now_date=`date +"%Y%m%d"`
echo "now_date: $now_date"

# 1. 下载训练所用特征数据并做处理
echo "ad_feature_process start..."
python ad_feature_process.py
if [ $? -ne 0 ];
then
  msg = "[ERROR] ad_feature_process.py"
  echo $msg
  exit -1
fi
echo "ad_feature_process end!"

# 2. 对样本进行采样
echo "ad_feature_data_sample start..."
python ad_feature_data_sample.py
if [ $? -ne 0 ];
then
  msg = "[ERROR] ad_feature_data_sample.py"
  echo $msg
  exit -1
fi
echo "ad_feature_data_sample end!"

# 3. 训练集和测试集生成
echo "ad_generate_train_test start..."
python ad_generate_train_test.py
if [ $? -ne 0 ];
then
  msg = "[ERROR] ad_generate_train_test.py"
  echo $msg
  exit -1
fi
echo "ad_generate_train_test end!"

# 4. 模型训练
echo "ad_xgboost_train start..."
python ad_xgboost_train.py
if [ $? -ne 0 ];
then
  msg = "[ERROR] ad_xgboost_train.py"
  echo $msg
  exit -1
fi
echo "ad_xgboost_train end!"

## 5. 离线预测数据处理
#echo "ad_predict_video_data_process start..."
#python ad_predict_video_data_process.py
#if [ $? -ne 0 ];
#then
#  msg = "[ERROR] ad_predict_video_data_process.py"
#  echo $msg
#  exit -1
#fi
#echo "ad_predict_video_data_process end!"
#
#echo "ad_predict_user_data_process start..."
#python ad_predict_user_data_process.py
#if [ $? -ne 0 ];
#then
#  msg = "[ERROR] ad_predict_user_data_process.py"
#  echo $msg
#  exit -1
#fi
#echo "ad_predict_user_data_process end!"
#
#echo "ad_xgboost_predict_data_generate start..."
#python ad_xgboost_predict_data_generate.py
#if [ $? -ne 0 ];
#then
#  msg = "[ERROR] ad_xgboost_predict_data_generate.py"
#  echo $msg
#  exit -1
#fi
#echo "ad_xgboost_predict_data_generate end!"

## 6. 离线预测
#echo "ad_xgboost_predict start..."
#python ad_xgboost_predict.py
#if [ $? -ne 0 ];
#then
#  msg = "[ERROR] ad_xgboost_predict.py"
#  echo $msg
#  exit -1
#fi
#echo "ad_xgboost_predict end!"