删除运行脚本时在本地生成日志

eda/esmm/Model_pipline/submit.sh

@@ -36,9 +36,9 @@ ${PYTHON_PATH} ${MODEL_PATH}/train.py --ctr_task_wgt=0.5 --learning_rate=0.0001
 
 
 echo "infer native..."
-${PYTHON_PATH} ${MODEL_PATH}/train.py --ctr_task_wgt=0.5 --learning_rate=0.0001 --deep_layers=512,256,128,64,32 --dropout=0.3,0.3,0.3,0.3,0.3 --optimizer=Adam --num_epochs=1 --embedding_size=16 --batch_size=2000 --field_size=15 --feature_size=300000 --l2_reg=0.005 --log_steps=100 --num_threads=36 --model_dir=${DATA_PATH}/model_ckpt/DeepCvrMTL/ --data_dir=${DATA_PATH}/native --task_type=infer > ${DATA_PATH}/native_infer.log
+${PYTHON_PATH} ${MODEL_PATH}/train.py --ctr_task_wgt=0.5 --learning_rate=0.0001 --deep_layers=512,256,128,64,32 --dropout=0.3,0.3,0.3,0.3,0.3 --optimizer=Adam --num_epochs=1 --embedding_size=16 --batch_size=2000 --field_size=15 --feature_size=300000 --l2_reg=0.005 --log_steps=100 --num_threads=36 --model_dir=${DATA_PATH}/model_ckpt/DeepCvrMTL/ --data_dir=${DATA_PATH}/native --task_type=infer
 
 
 echo "infer nearby..."
-${PYTHON_PATH} ${MODEL_PATH}/train.py --ctr_task_wgt=0.5 --learning_rate=0.0001 --deep_layers=512,256,128,64,32 --dropout=0.3,0.3,0.3,0.3,0.3 --optimizer=Adam --num_epochs=1 --embedding_size=16 --batch_size=2000 --field_size=15 --feature_size=300000 --l2_reg=0.005 --log_steps=100 --num_threads=36 --model_dir=${DATA_PATH}/model_ckpt/DeepCvrMTL/ --data_dir=${DATA_PATH}/nearby --task_type=infer > ${DATA_PATH}/nearby_infer.log
+${PYTHON_PATH} ${MODEL_PATH}/train.py --ctr_task_wgt=0.5 --learning_rate=0.0001 --deep_layers=512,256,128,64,32 --dropout=0.3,0.3,0.3,0.3,0.3 --optimizer=Adam --num_epochs=1 --embedding_size=16 --batch_size=2000 --field_size=15 --feature_size=300000 --l2_reg=0.005 --log_steps=100 --num_threads=36 --model_dir=${DATA_PATH}/model_ckpt/DeepCvrMTL/ --data_dir=${DATA_PATH}/nearby --task_type=infer
 

eda/esmm/Model_pipline/to_database.py

@@ -92,11 +92,11 @@ def main():
             con.close()
         engine = create_engine(str(r"mysql+pymysql://%s:" + '%s' + "@%s:%s/%s") % (user, password, host, port, db))
         df_all.to_sql('esmm_device_diary_queue',con=engine,if_exists='append',index=False,chunksize=8000)
+        print("insert done")
+
     except Exception as e:
         print(e)
 
-    print("done")
-
 
 if __name__ == '__main__':
     path = "/home/gmuser/esmm"

eda/esmm/Model_pipline/write_data.sh

@@ -5,4 +5,4 @@ MODEL_PATH=/srv/apps/ffm-baseline/eda/esmm/Model_pipline
 DATA_PATH=/home/gmuser/esmm
 
 echo "sort and 2sql"
-${PYTHON_PATH} ${MODEL_PATH}/to_database.py > ${DATA_PATH}/insert_database.log
+${PYTHON_PATH} ${MODEL_PATH}/to_database.py