update samples from Release-144 as a part of 1.0.60 SDK release

how-to-use-azureml/deployment/deploy-to-local/score.py

@@ -0,0 +1,34 @@
+import pickle
+import json
+import numpy as np
+from sklearn.externals import joblib
+from sklearn.linear_model import Ridge
+from azureml.core.model import Model
+
+from inference_schema.schema_decorators import input_schema, output_schema
+from inference_schema.parameter_types.numpy_parameter_type import NumpyParameterType
+
+
+def init():
+    global model
+    # note here "sklearn_regression_model.pkl" is the name of the model registered under
+    # this is a different behavior than before when the code is run locally, even though the code is the same.
+    model_path = Model.get_model_path('sklearn_regression_model.pkl')
+    # deserialize the model file back into a sklearn model
+    model = joblib.load(model_path)
+
+
+input_sample = np.array([[10, 9, 8, 7, 6, 5, 4, 3, 2, 1]])
+output_sample = np.array([3726.995])
+
+
+@input_schema('data', NumpyParameterType(input_sample))
+@output_schema(NumpyParameterType(output_sample))
+def run(data):
+    try:
+        result = model.predict(data)
+        # you can return any datatype as long as it is JSON-serializable
+        return result.tolist()
+    except Exception as e:
+        error = str(e)
+        return error