AI开发平台MODELARTS-模型推理代码编写说明:XGBoost的推理脚本示例

时间：2024-09-05 08:29:59

AI开发平台MODELARTS

XGBoost的推理脚本示例

更多机器学习引擎的推理代码请参考Pyspark、Scikit Learn。

# coding:utf-8
import collections
import json
import xgboost as xgb
from model_service.python_model_service import XgSklServingBaseService


class UserService(XgSklServingBaseService):

    # request data preprocess
    def _preprocess(self, data):
        list_data = []
        json_data = json.loads(data, object_pairs_hook=collections.OrderedDict)
        for element in json_data["data"]["req_data"]:
            array = []
            for each in element:
                array.append(element[each])
                list_data.append(array)
        return list_data

    #   predict
    def _inference(self, data):
        xg_model = xgb.Booster(model_file=self.model_path)
        pre_data = xgb.DMatrix(data)
        pre_result = xg_model.predict(pre_data)
        pre_result = pre_result.tolist()
        return pre_result

    # predict result process
    def _postprocess(self, data):
        resp_data = []
        for element in data:
            resp_data.append({"predict_result": element})
        return resp_data

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