2022-05-11 18:51:12 +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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2022-05-11 19:10:13 +02:00
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logged_model = 'mlruns/1/fa3e620f03e64d888c364827907fb6f5/artifacts/s444409'
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2022-05-11 19:20:06 +02:00
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logged_model2 = 'mlruns/1/fa3e620f03e64d888c364827907fb6f5/artifacts/s444409/data/model.pth'
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loaded_model = mlflow.pyfunc.load_model(logged_model2)
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2022-05-11 18:51:12 +02:00
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with open(f'{logged_model}/input_example.json') as f:
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data = json.load(f)
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input_example = pd.DataFrame(data['inputs'][0])
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loaded_model.predict(input_example)
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