14 lines
438 B
Python
14 lines
438 B
Python
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import mlflow
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import numpy as np
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import json
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logged_model = 'mlrunsArtifact/1/6b2323cf51794581bf1e2f6d060d50f6/artifacts/model'
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loaded_model = mlflow.pyfunc.load_model(logged_model)
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with open(f'{logged_model}/input_example.json') as f:
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input_example_data = json.load(f)
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input_example = np.array(input_example_data['inputs']).reshape(-1,)
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print(f'Input: {input_example}')
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print(f'Prediction: {loaded_model.predict(input_example)}')
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