machine learning / yml

.gitlab-ci.yml

+image: python:3.9
+
+stages:
+  - build
+  - test
+  - export
+
+# Build stage
+build:
+  stage: build
+  script:
+    - python machine_learning.py
+
+# Test stage
+test:
+  stage: test
+  script:
+    - pytest test_prediction.py
+
+# Export stage
+export:
+  stage: export
+  script:
+    - mv digits_model.joblib artifacts/
\ No newline at end of file

machine_learning.py

+from joblib import dump
+from sklearn import svm
+from sklearn import datasets
+
+
+def train_model():
+    model = svm.SVC()
+    X, y = datasets.load_digits(return_X_y=True)
+    model.fit(X, y)
+    return model
+
+def export_model(model):
+    dump(model, './digits_model.joblib')
+
+def start():
+    model = train_model()
+    export_model(model)
+    print('Model successfully exported.')
+
+if __name__ == '__main__':
+    start()

test_prediction.py

+import numpy as np
+import matplotlib.pyplot as plt
+from sklearn import datasets
+from machine_learning import train_model
+
+
+def test_inference_sample():
+    model = train_model()
+    X, _ = datasets.load_digits(return_X_y=True)
+    prediction = model.predict(X[0:1])[0]
+    assert prediction == 0
+
+def test_inference_batch():
+    model = train_model()
+    X, _ = datasets.load_digits(return_X_y=True)
+    predictions = model.predict(X[0:100])
+    assert np.all(predictions < 10)
\ No newline at end of file