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