15 lines
384 B
Python
15 lines
384 B
Python
import json
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import mlflow
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import numpy as np
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logged_model = 'mlruns/1/4b83e774512444188fb587288818c298/artifacts/model'
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loaded_model = mlflow.pyfunc.load_model(logged_model)
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with open('input_example.json') as f:
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data = json.load(f)
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input_example = np.array([data['inputs'][0]], dtype=np.float64).reshape(-1, 2)
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print(f'Prediction: {loaded_model.predict(input_example)}')
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