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