2021-05-23 18:50:55 +02:00
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import json
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import mlflow as mlf
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2021-05-28 21:48:35 +02:00
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from mlflow.tracking import MlflowClient
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2021-05-23 18:50:55 +02:00
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import pandas as pd
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2021-05-23 18:58:52 +02:00
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model_name = "s430705"
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2021-05-28 21:48:35 +02:00
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model_version = 30
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2021-05-23 19:07:22 +02:00
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mlf.set_tracking_uri("http://172.17.0.1:5000")
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2021-05-23 19:51:26 +02:00
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model = mlf.pyfunc.load_model(
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2021-05-23 18:50:55 +02:00
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model_uri=f"models:/{model_name}/{model_version}"
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)
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2021-05-28 21:48:35 +02:00
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client = MlflowClient()
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models_version = client.search_model_versions("name='s430705'")
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input_path = models_version[-1].source
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with open(f'{input_path}/input_example.json', 'r') as datafile:
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2021-05-23 18:50:55 +02:00
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data = json.load(datafile)['inputs']
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input_dictionary = {idx:x for idx, x in enumerate(data)}
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input_ex = pd.DataFrame([input_dictionary])
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print(model.predict(input_ex))
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