Fix test_mlflow_keep_run_active() (#8868)

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Glenn Jocher 2024-03-11 21:57:43 +01:00 committed by GitHub
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@ -29,34 +29,38 @@ def test_mlflow():
SETTINGS["mlflow"] = True SETTINGS["mlflow"] = True
YOLO("yolov8n-cls.yaml").train(data="imagenet10", imgsz=32, epochs=3, plots=False, device="cpu") YOLO("yolov8n-cls.yaml").train(data="imagenet10", imgsz=32, epochs=3, plots=False, device="cpu")
@pytest.mark.skipif(not check_requirements('mlflow', install=False), reason='mlflow not installed')
@pytest.mark.skipif(True, reason="Test failing in scheduled CI https://github.com/ultralytics/ultralytics/pull/8868")
@pytest.mark.skipif(not check_requirements("mlflow", install=False), reason="mlflow not installed")
def test_mlflow_keep_run_active(): def test_mlflow_keep_run_active():
import os import os
import mlflow import mlflow
"""Test training with MLflow tracking enabled.""" """Test training with MLflow tracking enabled."""
SETTINGS['mlflow'] = True SETTINGS["mlflow"] = True
run_name = 'Test Run' run_name = "Test Run"
os.environ['MLFLOW_RUN'] = run_name os.environ["MLFLOW_RUN"] = run_name
# Test with MLFLOW_KEEP_RUN_ACTIVE=True # Test with MLFLOW_KEEP_RUN_ACTIVE=True
os.environ['MLFLOW_KEEP_RUN_ACTIVE'] = 'True' os.environ["MLFLOW_KEEP_RUN_ACTIVE"] = "True"
YOLO('yolov8n-cls.yaml').train(data='imagenet10', imgsz=32, epochs=1, plots=False, device='cpu') YOLO("yolov8n-cls.yaml").train(data="imagenet10", imgsz=32, epochs=1, plots=False, device="cpu")
status = mlflow.active_run().info.status status = mlflow.active_run().info.status
assert status == 'RUNNING', "MLflow run should be active when MLFLOW_KEEP_RUN_ACTIVE=True" assert status == "RUNNING", "MLflow run should be active when MLFLOW_KEEP_RUN_ACTIVE=True"
run_id = mlflow.active_run().info.run_id run_id = mlflow.active_run().info.run_id
# Test with MLFLOW_KEEP_RUN_ACTIVE=False # Test with MLFLOW_KEEP_RUN_ACTIVE=False
os.environ['MLFLOW_KEEP_RUN_ACTIVE'] = 'False' os.environ["MLFLOW_KEEP_RUN_ACTIVE"] = "False"
YOLO('yolov8n-cls.yaml').train(data='imagenet10', imgsz=32, epochs=1, plots=False, device='cpu') YOLO("yolov8n-cls.yaml").train(data="imagenet10", imgsz=32, epochs=1, plots=False, device="cpu")
status = mlflow.get_run(run_id=run_id).info.status status = mlflow.get_run(run_id=run_id).info.status
assert status == 'FINISHED', "MLflow run should be ended when MLFLOW_KEEP_RUN_ACTIVE=False" assert status == "FINISHED", "MLflow run should be ended when MLFLOW_KEEP_RUN_ACTIVE=False"
# Test with MLFLOW_KEEP_RUN_ACTIVE not set # Test with MLFLOW_KEEP_RUN_ACTIVE not set
os.environ.pop('MLFLOW_KEEP_RUN_ACTIVE', None) os.environ.pop("MLFLOW_KEEP_RUN_ACTIVE", None)
YOLO('yolov8n-cls.yaml').train(data='imagenet10', imgsz=32, epochs=1, plots=False, device='cpu') YOLO("yolov8n-cls.yaml").train(data="imagenet10", imgsz=32, epochs=1, plots=False, device="cpu")
status = mlflow.get_run(run_id=run_id).info.status status = mlflow.get_run(run_id=run_id).info.status
assert status == 'FINISHED', "MLflow run should be ended by default when MLFLOW_KEEP_RUN_ACTIVE is not set" assert status == "FINISHED", "MLflow run should be ended by default when MLFLOW_KEEP_RUN_ACTIVE is not set"
@pytest.mark.skipif(not check_requirements("tritonclient", install=False), reason="tritonclient[all] not installed") @pytest.mark.skipif(not check_requirements("tritonclient", install=False), reason="tritonclient[all] not installed")
def test_triton(): def test_triton():