class SetupModel(object): model = classification_model() labels = get_labels(os.environ['LABELS_PATH']) def __init__(self, f): self.f = f file_path = f'/tmp/{STATE_DICT_NAME}' download_file(BUCKET_NAME, STATE_DICT_NAME, file_path) state_dict = torch.load(file_path, map_location=lambda storage, loc: storage) self.model.load_state_dict(state_dict), self.model.eval() os.remove(file_path) def __call__(self, *args, **kwargs): return self.f(*args, **kwargs)
class SetupModel(object): model = classification_model() labels = list(label_dict.values()) tfms = tfms_from_stats(STATS, SZ)[-1] def __init__(self, f): self.f = f file_path = f'/tmp/{STATE_DICT_NAME}' download_file(BUCKET_NAME, STATE_DICT_NAME, file_path) state_dict = torch.load(file_path, map_location=lambda storage, loc: storage) self.model.load_state_dict(state_dict) self.model.eval() os.remove(file_path) def __call__(self, *args, **kwargs): return self.f(*args, **kwargs)