特征工程优化

shell/models_upload.sh

@@ -2,4 +2,4 @@ cd /srv/apps/tensorServing_models/
 #文件打包
 tar -czvf model_service.tar.gz service
 #上传至coding
-curl -T model_service.tar.gz -u guoyu@igengmei.com:Gengmei123! "https://gengmei-generic.pkg.coding.net/tob/mode/service"
+curl -T model_service.tar.gz -u guoyu@igengmei.com:Gengmei123! "https://gengmei-generic.pkg.coding.net/tob/mode/service"
\ No newline at end of file

train/train_service.py

@@ -185,7 +185,7 @@ if __name__ == '__main__':
     print("读取数据...")
     timestmp1 = int(round(time.time()))
     df_train = loadData(data_path_train)
-    df_test = loadData(data_path_test)
+    # df_test = loadData(data_path_test)
     timestmp2 = int(round(time.time()))
     print("读取数据耗时s:{}".format(timestmp2 - timestmp1))
 
@@ -198,20 +198,20 @@ if __name__ == '__main__':
     print(datasColumns)
 
     df_train = df_train[datasColumns + ["label"]]
-    df_test = df_test[datasColumns + ["label"]]
+    # df_test = df_test[datasColumns + ["label"]]
 
     trainSize = df_train["label"].count()
     print("trainSize:{}".format(trainSize))
-    testSize = df_test["label"].count()
-    print("trainSize:{},testSize{}".format(trainSize,testSize))
+    # testSize = df_test["label"].count()
+    # print("trainSize:{},testSize{}".format(trainSize,testSize))
 
     # 数据类型转换
     df_train = csvTypeConvert(datasColumns,df_train,data_vocab)
-    df_test = csvTypeConvert(datasColumns,df_test,data_vocab)
+    # df_test = csvTypeConvert(datasColumns,df_test,data_vocab)
 
     # 获取训练数据
     train_data = getDataSet(df_train,shuffleSize=trainSize,)
-    test_data = getDataSet(df_test,shuffleSize=testSize)
+    # test_data = getDataSet(df_test,shuffleSize=testSize)
 
 
     print("train start...")