2021-06-08 18:32:35 +02:00
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import json
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import mlflow
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import pandas as pd
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from pprint import pprint
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from mlflow.tracking import MlflowClient
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model_name = "s430705"
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model_version = 50
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mlflow.set_tracking_uri("http://172.17.0.1:5000")
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model = mlflow.keras.pyfunc.load_model(
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model_uri=f"models:/{model_name}/{model_version}",
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)
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2021-06-10 14:45:52 +02:00
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client = MlflowClient()
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2021-06-10 14:58:09 +02:00
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with open(client.get_model_version(model_name, model_version).source + '/input_example.json', 'r') as input_file:
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data = json.load(input_file)
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example_input = data["inputs"]
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input_dictionary = {i: x for i, x in enumerate(example_input)}
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input_ex = pd.DataFrame(input_dictionary, index=[0])
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2021-06-10 14:59:48 +02:00
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print("RESULT: ", model.predict(input_ex))
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