try camelCase
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@@ -7,10 +7,10 @@ print('SDK version' + azureml.core.VERSION)
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# PREREQ: load workspace info
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# import azureml.core
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# <load>
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# <loadWorkspace>
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from azureml.core import Workspace
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ws = Workspace.from_config()
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# </load>
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# </loadWorkspace>
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scorepy_content = "import json\nimport numpy as np\nimport os\nimport pickle\nfrom sklearn.externals import joblib\nfrom sklearn.linear_model import LogisticRegression\n\nfrom azureml.core.model import Model\n\ndef init():\n global model\n # retreive the path to the model file using the model name\n model_path = Model.get_model_path('sklearn_mnist')\n model = joblib.load(model_path)\n\ndef run(raw_data):\n data = np.array(json.loads(raw_data)['data'])\n # make prediction\n y_hat = model.predict(data)\n return json.dumps(y_hat.tolist())"
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print(scorepy_content)
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