def run(mlcube: str, platform: str, task: str):
mlcube: mlcube_metadata.MLCube = mlcube_metadata.MLCube(path=mlcube)
mlcube.platform = gcp_metadata.Platform(path=platform)
mlcube.invoke = mlcube_metadata.MLCubeInvoke(task)
mlcube.task = mlcube_metadata.MLCubeTask(os.path.join(mlcube.tasks_path, f'{mlcube.invoke.task_name}.yaml'))
print(mlcube)
runner = GCPRun(mlcube)
runner.run(task_file=task)
def run(mlcube: str, platform: str, task: str):
mlcube: mlcube_metadata.MLCube = mlcube_metadata.MLCube(path=mlcube)
mlcube.platform = objects.load_object_from_file(
file_path=platform, obj_class=platform_config.PlatformConfig)
mlcube.invoke = mlcube_metadata.MLCubeInvoke(task)
mlcube.task = mlcube_metadata.MLCubeTask(
os.path.join(mlcube.tasks_path, f'{mlcube.invoke.task_name}.yaml'))
print(mlcube)
runner = DockerRun(mlcube)
runner.run()
def setUp(self):
self.path_to_mlcube = os.path.join(os.path.dirname(__file__),
"test_data/test_cube")
self.path_to_platform = os.path.join(self.path_to_mlcube,
"platforms/docker.yaml")
self.path_to_task = os.path.join(self.path_to_mlcube,
"run/kubernetes.yaml")
self.mlcube = mlcube_metadata.MLCube(path=self.path_to_mlcube)
self.mlcube.platform = objects.load_object_from_file(
file_path=self.path_to_platform,
obj_class=platform_config.PlatformConfig)
self.mlcube.invoke = mlcube_metadata.MLCubeInvoke(self.path_to_task)
self.mlcube_k8s_runner = KubernetesRun(mlcube=self.mlcube,
loglevel="INFO")