""" Copyright (C) Microsoft Corporation. All rights reserved.​ ​ Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, royalty-free right to use, copy, and modify the software code provided by us ("Software Code"). You may not sublicense the Software Code or any use of it (except to your affiliates and to vendors to perform work on your behalf) through distribution, network access, service agreement, lease, rental, or otherwise. This license does not purport to express any claim of ownership over data you may have shared with Microsoft in the creation of the Software Code. Unless applicable law gives you more rights, Microsoft reserves all other rights not expressly granted herein, whether by implication, estoppel or otherwise. ​ ​ THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ import json import numpy from azureml.core.model import Model import joblib def init(): global model # load the model from file into a global object model_path = Model.get_model_path( model_name="sklearn_regression_model.pkl") model = joblib.load(model_path) def run(raw_data): try: data = json.loads(raw_data)["data"] data = numpy.array(data) result = model.predict(data) return json.dumps({"result": result.tolist()}) except Exception as e: result = str(e) return json.dumps({"error": result}) if __name__ == "__main__": # Test scoring init() test_row = '{"data":[[1,2,3,4,5,6,7,8,9,10],[10,9,8,7,6,5,4,3,2,1]]}' prediction = run(test_row) print("Test result: ", prediction)