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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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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2021-05-23 19:48:38 +02:00
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model_version = 8
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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 19:48:38 +02:00
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mlf.keras.log_model("runs:/dd2657243e2c4176a2ec2e3340c3ff13/run-relative/path/to/model", registered_model_name="s430705")
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model = mlf.keras.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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2021-05-23 19:48:38 +02:00
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with open('movies_imdb2/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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