Project-AutoML/predictor.py (21 lines of code) (raw):

# Licensed to Apache Software Foundation (ASF) under one or more contributor # license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright # ownership. Apache Software Foundation (ASF) licenses this file to you under # the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. from mlflow.pyfunc import PythonModel class PredictorWrapper(PythonModel): def load_context(self, context): model_path = context.artifacts["model_path"] if "autosklearn" in model_path: self.predictor = self.load_autosklearn_predictor(model_path) elif "flaml" in model_path: self.predictor = self.load_flaml_predictor(model_path) else: assert f"cant not load model from path {model_path}" def predict(self, context, model_input): results = self.predictor.predict(model_input) return {"results": results} def load_autosklearn_predictor(self, path): from automl.mod.mod_autosklearn import Predictor predictor = Predictor(path) return predictor def load_flaml_predictor(self, path): from automl.mod.mod_flaml import Predictor predictor = Predictor(path) return predictor