mlflow--mlflow
wehub-resource-sync
34 行
841 B
Python
34 行
841 B
Python
from pprint import pprint
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import numpy as np
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from sklearn.linear_model import LinearRegression
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from sklearn.pipeline import Pipeline
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from sklearn.preprocessing import StandardScaler
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from utils import fetch_logged_data
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import mlflow
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def main():
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# enable autologging
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mlflow.sklearn.autolog()
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# prepare training data
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X = np.array([[1, 1], [1, 2], [2, 2], [2, 3]])
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y = np.dot(X, np.array([1, 2])) + 3
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# train a model
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pipe = Pipeline([("scaler", StandardScaler()), ("lr", LinearRegression())])
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pipe.fit(X, y)
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run_id = mlflow.last_active_run().info.run_id
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print(f"Logged data and model in run: {run_id}")
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# show logged data
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for key, data in fetch_logged_data(run_id).items():
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print(f"\n---------- logged {key} ----------")
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pprint(data)
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if __name__ == "__main__":
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main()
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