def test_jigsaw(args, device_id, pt, step):
device = "cpu" if args.visible_gpus == '-1' else "cuda"
if (pt != ''):
test_from = pt
else:
test_from = args.test_from
logger.info('Loading checkpoint from %s' % test_from)
checkpoint = torch.load(test_from,
map_location=lambda storage, loc: storage)
opt = vars(checkpoint['opt'])
for k in opt.keys():
if (k in model_flags):
setattr(args, k, opt[k])
print(args)
jigsaw = args.jigsaw if 'jigsaw' in args else 'jigsaw_lab'
if jigsaw == 'jigsaw_dec':
model = SentenceTransformer(args, device, checkpoint, sum_or_jigsaw=1)
else:
model = Jigsaw(args, device, checkpoint)
model.eval()
test_iter = jigsaw_data_loader.Dataloader(args,
jigsaw_data_loader.load_dataset(
args, 'test', shuffle=False),
args.test_batch_size,
device,
shuffle=False,
is_test=True)
trainer = build_trainer(args, device_id, model, None)
trainer.test(test_iter, step)
def train_iter_fct():
return jigsaw_data_loader.Dataloader(args,
jigsaw_data_loader.load_dataset(
args, 'train', shuffle=True),
args.batch_size,
device,
shuffle=True,
is_test=False)