Spaces:
Sleeping
Sleeping
| # import json | |
| # import unittest | |
| # from src.data.config import NORMALIZATION_DICT_FILENAME | |
| # from src.data.dataset import Normalizer | |
| # from src.galileo import Encoder | |
| # from src.utils import check_config, config_dir, load_check_config | |
| # class TestConfigs(unittest.TestCase): | |
| # @staticmethod | |
| # def check_models_can_be_loaded(config): | |
| # _ = Encoder(**config["model"]["encoder"]) | |
| # def test_configs(self): | |
| # configs = list((config_dir / "mae").glob("*.json")) | |
| # for config_path in configs: | |
| # try: | |
| # loaded_config = load_check_config(config_path.name) | |
| # self.check_models_can_be_loaded(loaded_config) | |
| # except Exception as e: | |
| # print(f"Failed for {config_path} with {e}") | |
| # raise e | |
| # def test_normalization_dict(self): | |
| # if (config_dir / NORMALIZATION_DICT_FILENAME).exists(): | |
| # with (config_dir / NORMALIZATION_DICT_FILENAME).open("r") as f: | |
| # norm_dict = json.load(f) | |
| # output_dict = {} | |
| # for key, val in norm_dict.items(): | |
| # if "n" not in key: | |
| # output_dict[int(key)] = val | |
| # else: | |
| # output_dict[key] = val | |
| # normalizer = Normalizer(std=True, normalizing_dicts=output_dict) | |
| # for key, val in normalizer.shift_div_dict.items(): | |
| # divs = val["div"] | |
| # for d in divs: | |
| # self.assertNotEqual(d, 0, f"0 in {key}") | |