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64 lines
1.6 KiB
YAML
64 lines
1.6 KiB
YAML
tracking:
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enabled: true
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auth:
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enabled: true
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username: vib-user
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password: "ComplicatedPassword123!4"
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extraOverrides:
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default_permission: WRITE
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containerPorts:
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http: 8100
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service:
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type: LoadBalancer
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ports:
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http: 80
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serviceAccount:
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create: true
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automountServiceAccountToken: true
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containerSecurityContext:
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enabled: true
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runAsUser: 1002
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runAsGroup: 1002
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runAsNonRoot: true
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readOnlyRootFilesystem: true
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allowPrivilegeEscalation: false
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capabilities:
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drop: ["ALL"]
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podSecurityContext:
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enabled: true
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fsGroup: 1002
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seccompProfile:
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type: RuntimeDefault
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persistence:
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enabled: true
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mountPath: /vib-mlflow/test
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metrics:
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enabled: true
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run:
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enabled: true
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useJob: true
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resourcesPreset: "medium"
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source:
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launchCommand: "python vib_test.py"
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configMap:
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# Example taken from the MLFlow UI (https://mlflow.org/docs/latest/ml/tracking/tutorials/local-database#step-3-start-logging)
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vib_test.py: |
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import mlflow
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from sklearn.model_selection import train_test_split
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from sklearn.datasets import load_diabetes
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from sklearn.ensemble import RandomForestRegressor
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mlflow.sklearn.autolog()
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db = load_diabetes()
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X_train, X_test, y_train, y_test = train_test_split(db.data, db.target)
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# Create and train models.
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rf = RandomForestRegressor(n_estimators=100, max_depth=6, max_features=3)
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rf.fit(X_train, y_train)
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# Use the model to make predictions on the test dataset.
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predictions = rf.predict(X_test)
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