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@korkridake
Created June 5, 2020 07:08
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MLOps Ep.4 Productionizing Scoring Script
%%writefile score.py
import json
import numpy as np
import os
import pickle
import joblib
def init():
global model
##################################################################################################
# AZUREML_MODEL_DIR is an environment variable created during deployment.
# It is the path to the model folder (./azureml-models/$MODEL_NAME/$VERSION)
# For multiple models, it points to the folder containing all deployed models (./azureml-models)
##################################################################################################
model_path = os.path.join(os.getenv('AZUREML_MODEL_DIR'), 'sklearn_regression_model.pkl')
model = joblib.load(model_path)
def run(raw_data):
data = np.array(json.loads(raw_data)['data'])
# make prediction
y_hat = model.predict(data)
# you can return any data type as long as it is JSON-serializable
return y_hat.tolist()
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