Automate your ML model retraining with Kubeflow

store_metrics_component.py

def store_training_job_metrics_op(project_id: str, metrics_file_path: str, model_name: str, model_folder: str):
    return dsl.ContainerOp(
        name='store-training-job-metrics',
        image='gcr.io/{}/taxi-fare-utils:1.0'.format(project_id),
        command=['python3', '-m', 'metrics_writer'],
        arguments=[
            '--metrics_file_path', metrics_file_path,
            '--model_name', model_name,
            '--model_folder', model_folder
        ]
    )
store_training_job_metrics_task = store_training_job_metrics_op(
        project_id,
        dsl.InputArgumentPath(download_blob_task.output),
        MODEL_NAME,
        model_folder)