def test_save_file(value: Any, expected: Any) -> None:
file = full_ml_test_data_path("test.txt")
io_util.save_lines_to_file(Path(file), value)
assert_file_contents(file, expected)
os.remove(str(file))
def store_run_information(results_folder: Path, dataset_id: Optional[str],
ground_truth_ids: List[str],
image_channels: List[str]) -> None:
"""
Store dataset id and ground truth ids into files in the results folder.
:param image_channels: The names of the image channels that the model consumes.
:param results_folder: The folder where the files should be stored.
:param dataset_id: The dataset id
:param ground_truth_ids: The list of ground truth ids
"""
# Recovery runs will download the previous job's output folder, it could contain these files.
# Save these files for each epoch to keep the folders self-contained
# Save the dataset id to a file
save_lines_to_file(results_folder / DATASET_ID_FILE, [dataset_id or ""])
# Save ground truth ids in a file
save_lines_to_file(results_folder / GROUND_TRUTH_IDS_FILE,
ground_truth_ids)
# Save channel ids in a file
save_lines_to_file(results_folder / IMAGE_CHANNEL_IDS_FILE, image_channels)