def test_mlflow_metrics_dataset_exists(tmp_path, tracking_uri, metrics3):
"""Check if MlflowMetricsDataSet is well identified as
existing if it has already been saved.
"""
prefix = "test_metric"
mlflow.set_tracking_uri(tracking_uri.as_uri())
mlflow_metrics_dataset = MlflowMetricsDataSet(prefix=prefix)
# a mlflow run_id is automatically created
mlflow_metrics_dataset.save(metrics3)
assert mlflow_metrics_dataset.exists()
def test_mlflow_metrics_dataset_does_not_exist(tmp_path, tracking_uri,
metrics3):
"""Check if MlflowMetricsDataSet is well identified as
not existingif it has never been saved.
"""
mlflow.set_tracking_uri(tracking_uri.as_uri())
mlflow.start_run(
) # starts a run toenable mlflow_metrics_dataset to know where to seacrh
run_id = mlflow.active_run().info.run_id
mlflow.end_run()
mlflow_metrics_dataset = MlflowMetricsDataSet(prefix="test_metric",
run_id=run_id)
# a mlflow run_id is automatically created
assert not mlflow_metrics_dataset.exists()