def load(model_path, cuda=False): decoder_params = torch.load(model_path, map_location=lambda storage, loc: storage) decoder_params['args'].cuda = cuda # update saved args saved_args = decoder_params['args'] update_args(saved_args, init_arg_parser()) model = ParaphraseIdentificationModel( saved_args, decoder_params['vocab'], decoder_params['transition_system']) model.load_state_dict(decoder_params['state_dict']) if cuda: model = model.cuda() model.eval() return model
def load(cls, model_path, cuda=False): params = torch.load(model_path, map_location=lambda storage, loc: storage) vocab = params['vocab'] transition_system = params['transition_system'] saved_args = params['args'] # update saved args update_args(saved_args, init_arg_parser()) saved_state = params['state_dict'] saved_args.cuda = cuda parser = cls(saved_args, vocab, transition_system) parser.load_state_dict(saved_state) if cuda: parser = parser.cuda() parser.eval() return parser