predict data teest
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@ -14,4 +14,11 @@ model = mlflow.keras.pyfunc.load_model(
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)
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client = MlflowClient()
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print("XD: ", client.get_model_version(model_name, model_version).source)
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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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print(model.predict(input_ex))
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