def test_model_name_is_set(test_output_dirs: OutputFolderForTests) -> None:
container = DummyContainerWithModel()
container.local_dataset = test_output_dirs.root_dir
runner = MLRunner(model_config=None, container=container)
runner.setup()
expected_name = "DummyContainerWithModel"
assert runner.container._model_name == expected_name
assert expected_name in str(runner.container.outputs_folder)
def _create_container(
extra_local_dataset_paths: List[Path] = [],
extra_azure_dataset_ids: List[str] = []) -> LightningContainer:
container = DummyContainerWithModel()
container.local_dataset = test_output_dirs.root_dir
container.extra_local_dataset_paths = extra_local_dataset_paths # type: ignore
container.extra_azure_dataset_ids = extra_azure_dataset_ids
runner = MLRunner(model_config=None, container=container)
runner.setup()
return runner.container
def test_regression_test(test_output_dirs: OutputFolderForTests) -> None:
"""
Test that the file comparison for regression tests is actually called in the workflow.
"""
container = DummyContainerWithModel()
container.local_dataset = test_output_dirs.root_dir
container.regression_test_folder = Path(str(uuid.uuid4().hex))
runner = MLRunner(container=container)
runner.setup()
with pytest.raises(ValueError) as ex:
runner.run()
assert "Folder with expected files does not exist" in str(ex)
def test_optim_params2(test_output_dirs: OutputFolderForTests) -> None:
"""
Test if the optimizer parameters are read correctly for containers.
"""
container = DummyContainerWithModel()
container.local_dataset = test_output_dirs.root_dir
runner = MLRunner(model_config=None, container=container)
runner.setup()
lightning_model = runner.container.model
optim, _ = lightning_model.configure_optimizers()
expected_lr = 1e-1
assert container.l_rate == expected_lr
assert optim[0].param_groups[0]["lr"] == expected_lr