mlflow--mlflow
wehub-resource-sync
16 行
519 B
Python
16 行
519 B
Python
from sklearn.datasets import load_iris
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from sklearn.linear_model import LogisticRegression
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import mlflow
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from mlflow.models import infer_signature
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X, y = load_iris(return_X_y=True, as_frame=True)
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model = LogisticRegression().fit(X, y)
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signature = infer_signature(X, model.predict(X))
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with mlflow.start_run() as run:
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mlflow.sklearn.log_model(model, name="model", signature=signature)
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runs_uri = f"runs:/{run.info.run_id}/model"
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model = mlflow.sklearn.load_model(runs_uri)
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print(model.predict(X)[:10])
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