def test_upgrade_to_latest(self): for p in glob.iglob( os.path.join(os.path.dirname(__file__), "json_config/*.json")): with open(p) as f: test_data = json.load(f) for test_case in test_data: json_config = upgrade_to_latest(test_case["original"]) config_from_json(PyTextConfig, json_config)
def load(load_path: str): """ Load task, will construct the task using the saved config then load metadata and model state. """ if not (load_path and os.path.isfile(load_path)): raise ValueError(f"Invalid snapshot path{load_path}") print(f"Loading model from {load_path}...") state = torch.load(load_path, map_location=lambda storage, loc: storage) config = config_from_json(PyTextConfig, state[CONFIG_JSON]) task = create_task(config.task, metadata=state[DATA_STATE], model_state=state[MODEL_STATE]) return task, config
def _get_config(self, cls, config_str): params_json = json.loads(config_str) config = config_from_json(cls, params_json) return config