diff --git "a/implementation/lits/segmamba_lits/train_segmamba_lits_20251228-212200.log" "b/implementation/lits/segmamba_lits/train_segmamba_lits_20251228-212200.log"
new file mode 100644--- /dev/null
+++ "b/implementation/lits/segmamba_lits/train_segmamba_lits_20251228-212200.log"
@@ -0,0 +1,1279 @@
+[21:22:00.610] Namespace(data='lits', save_dir='./implementation/lits/segmamba_lits', data_dir='/teamspace/studios/this_studio/lits', num_workers=2, split='train', use_small_dataset=False, model_type='segmamba', lr=4e-05, lr_scheduler='linear', warm_up=False, device='cuda:0', max_epoch=20, image_size=128, batch_size=2, checkpoint='best', checkpoint_sam='./checkpoint_sam/sam_vit_b_01ec64.pth', num_classes=2, tolerance=5, boundary_kernel_size=5, use_pretrain=False, pretrain_path='', resume=False, resume_best=False, ddp=False, gpu_ids=[0, 1], accumulation_steps=20, iter_nums=11, num_clicks=50, num_clicks_validation=10, use_box=True, dynamic_box=False, use_scribble=True, num_multiple_outputs=3, multiple_outputs=True, refine=True, no_detach=False, refine_test=False, dynamic=True, efficient_scribble=True, use_sam3d_turbo=False, save_predictions=False, save_csv=False, save_test_dir='./', save_name='segmamba_lits')
+[21:22:50.638] epoch: 0/20, iter: 0/42: loss:7.7643: rank:-1
+[21:23:12.007] epoch: 0/20, iter: 1/42: loss:7.6816: rank:-1
+[21:23:28.390] epoch: 0/20, iter: 2/42: loss:7.8668: rank:-1
+[21:23:53.464] epoch: 0/20, iter: 3/42: loss:7.2042: rank:-1
+[21:24:10.595] epoch: 0/20, iter: 4/42: loss:7.3394: rank:-1
+[21:24:23.173] epoch: 0/20, iter: 5/42: loss:7.031: rank:-1
+[21:24:43.030] epoch: 0/20, iter: 6/42: loss:6.1888: rank:-1
+[21:25:00.700] epoch: 0/20, iter: 7/42: loss:6.3632: rank:-1
+[21:25:18.184] epoch: 0/20, iter: 8/42: loss:6.112: rank:-1
+[21:25:42.628] epoch: 0/20, iter: 9/42: loss:4.7389: rank:-1
+[21:25:52.590] epoch: 0/20, iter: 10/42: loss:6.2234: rank:-1
+[21:26:13.378] epoch: 0/20, iter: 11/42: loss:4.9788: rank:-1
+[21:26:34.633] epoch: 0/20, iter: 12/42: loss:4.7268: rank:-1
+[21:26:46.208] epoch: 0/20, iter: 13/42: loss:5.7346: rank:-1
+[21:26:58.717] epoch: 0/20, iter: 14/42: loss:5.0716: rank:-1
+[21:27:11.747] epoch: 0/20, iter: 15/42: loss:5.0755: rank:-1
+[21:27:20.210] epoch: 0/20, iter: 16/42: loss:5.651: rank:-1
+[21:27:34.132] epoch: 0/20, iter: 17/42: loss:4.9922: rank:-1
+[21:27:56.642] epoch: 0/20, iter: 18/42: loss:4.3757: rank:-1
+[21:28:06.599] epoch: 0/20, iter: 19/42: loss:4.6099: rank:-1
+[21:28:17.337] epoch: 0/20, iter: 20/42: loss:5.1981: rank:-1
+[21:28:27.542] epoch: 0/20, iter: 21/42: loss:4.4029: rank:-1
+[21:28:43.183] epoch: 0/20, iter: 22/42: loss:4.8197: rank:-1
+[21:28:55.749] epoch: 0/20, iter: 23/42: loss:4.6227: rank:-1
+[21:29:16.619] epoch: 0/20, iter: 24/42: loss:5.8971: rank:-1
+[21:29:30.665] epoch: 0/20, iter: 25/42: loss:4.6182: rank:-1
+[21:29:43.851] epoch: 0/20, iter: 26/42: loss:6.1467: rank:-1
+[21:29:55.073] epoch: 0/20, iter: 27/42: loss:5.0781: rank:-1
+[21:30:09.642] epoch: 0/20, iter: 28/42: loss:4.4742: rank:-1
+[21:30:25.838] epoch: 0/20, iter: 29/42: loss:3.9636: rank:-1
+[21:30:45.929] epoch: 0/20, iter: 30/42: loss:4.2852: rank:-1
+[21:30:55.183] epoch: 0/20, iter: 31/42: loss:4.735: rank:-1
+[21:31:04.985] epoch: 0/20, iter: 32/42: loss:4.3038: rank:-1
+[21:31:17.986] epoch: 0/20, iter: 33/42: loss:4.6351: rank:-1
+[21:31:39.623] epoch: 0/20, iter: 34/42: loss:3.0373: rank:-1
+[21:31:55.949] epoch: 0/20, iter: 35/42: loss:4.745: rank:-1
+[21:32:06.577] epoch: 0/20, iter: 36/42: loss:4.023: rank:-1
+[21:32:17.858] epoch: 0/20, iter: 37/42: loss:4.4147: rank:-1
+[21:32:39.968] epoch: 0/20, iter: 38/42: loss:2.9668: rank:-1
+[21:32:55.926] epoch: 0/20, iter: 39/42: loss:3.9367: rank:-1
+[21:33:17.948] epoch: 0/20, iter: 40/42: loss:4.0132: rank:-1
+[21:33:25.484] epoch: 0/20, iter: 41/42: loss:3.8788: rank:-1
+[21:33:25.485] - Train metrics: 5.188704
+[21:33:29.455] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(195, device='cuda:0')
+[21:33:34.015] dice before refine 0.0 and after 0.0, label 0: tensor(9, device='cuda:0'), label 1: tensor(177, device='cuda:0')
+[21:33:34.470] dice before refine 0.0 and after 0.00048426148714497685, label 0: tensor(0, device='cuda:0'), label 1: tensor(382, device='cuda:0')
+[21:33:41.447] dice before refine 0.0 and after 0.011266163550317287, label 0: tensor(62, device='cuda:0'), label 1: tensor(439, device='cuda:0')
+[21:33:41.814] dice before refine 0.006399999838322401 and after 0.003657938214018941, label 0: tensor(0, device='cuda:0'), label 1: tensor(39, device='cuda:0')
+[21:33:45.176] dice before refine 0.007054673507809639 and after 0.009987261146306992, label 0: tensor(18, device='cuda:0'), label 1: tensor(60, device='cuda:0')
+[21:33:45.588] dice before refine 0.0 and after 0.00017222078167833388, label 0: tensor(0, device='cuda:0'), label 1: tensor(182, device='cuda:0')
+[21:33:54.471] dice before refine 0.0 and after 0.005602696910500526, label 0: tensor(510, device='cuda:0'), label 1: tensor(380, device='cuda:0')
+[21:33:54.889] dice before refine 0.0 and after 0.001317749498412013, label 0: tensor(0, device='cuda:0'), label 1: tensor(260, device='cuda:0')
+[21:34:01.527] dice before refine 0.0 and after 0.008733624592423439, label 0: tensor(53, device='cuda:0'), label 1: tensor(355, device='cuda:0')
+[21:34:02.077] epoch: 0/20, iter: 0/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-120/image.nii.gz',) mean dice over clicks:0.0013567869464168325 stich left and right side (total size): 1
+[21:34:02.596] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(90, device='cuda:0')
+[21:34:07.256] dice before refine 0.0 and after 0.0, label 0: tensor(77, device='cuda:0'), label 1: tensor(115, device='cuda:0')
+[21:34:07.626] dice before refine 0.0033370412420481443 and after 0.015297775156795979, label 0: tensor(0, device='cuda:0'), label 1: tensor(87, device='cuda:0')
+[21:34:15.022] dice before refine 0.002934272401034832 and after 0.05618207901716232, label 0: tensor(355, device='cuda:0'), label 1: tensor(291, device='cuda:0')
+[21:34:15.412] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(85, device='cuda:0')
+[21:34:19.957] dice before refine 0.0 and after 0.0006927606300450861, label 0: tensor(80, device='cuda:0'), label 1: tensor(95, device='cuda:0')
+[21:34:20.331] dice before refine 0.004847832024097443 and after 0.01776573248207569, label 0: tensor(0, device='cuda:0'), label 1: tensor(97, device='cuda:0')
+[21:34:28.233] dice before refine 0.004127358552068472 and after 0.07265148311853409, label 0: tensor(445, device='cuda:0'), label 1: tensor(275, device='cuda:0')
+[21:34:29.441] epoch: 0/20, iter: 1/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-55/image.nii.gz',) mean dice over clicks:0.0363835563713854 stich left and right side (total size): 1
+[21:34:29.956] dice before refine 0.00042682146886363626 and after 0.0014713996788486838, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:34:36.814] dice before refine 0.0003415592072997242 and after 0.05418814346194267, label 0: tensor(3, device='cuda:0'), label 1: tensor(507, device='cuda:0')
+[21:34:37.376] dice before refine 0.0038961186073720455 and after 0.3163600265979767, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:34:44.881] dice before refine 0.003805597312748432 and after 0.3643198013305664, label 0: tensor(7, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:34:45.555] dice before refine 0.0003809300542343408 and after 0.06998071074485779, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:34:56.130] dice before refine 0.00023444482940249145 and after 0.07545099407434464, label 0: tensor(157, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:34:56.965] dice before refine 0.0012250742875039577 and after 0.040976352989673615, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:35:07.108] dice before refine 0.0013515222817659378 and after 0.06268169730901718, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:35:07.559] dice before refine 0.0008709077374078333 and after 0.02366194874048233, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:35:14.900] dice before refine 0.0007929271087050438 and after 0.10599236190319061, label 0: tensor(51, device='cuda:0'), label 1: tensor(504, device='cuda:0')
+[21:35:15.482] dice before refine 0.0020348343532532454 and after 0.1640280783176422, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:35:24.808] dice before refine 0.0022041103802621365 and after 0.24722982943058014, label 0: tensor(135, device='cuda:0'), label 1: tensor(509, device='cuda:0')
+[21:35:25.602] dice before refine 0.00161983713041991 and after 0.1751549243927002, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:35:35.752] dice before refine 0.0016068993136286736 and after 0.19048093259334564, label 0: tensor(61, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:35:36.614] dice before refine 0.001275671529583633 and after 0.03225815296173096, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:35:46.975] dice before refine 0.0013093675952404737 and after 0.04452347382903099, label 0: tensor(19, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:35:47.653] epoch: 0/20, iter: 2/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-100/image.nii.gz',) mean dice over clicks:0.08414647118611769 stich left and right side (total size): 1
+[21:35:48.167] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[21:35:51.049] dice before refine 0.0 and after 0.0, label 0: tensor(10, device='cuda:0'), label 1: tensor(0, device='cuda:0')
+[21:35:51.429] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[21:35:54.274] dice before refine 0.0 and after 0.0, label 0: tensor(10, device='cuda:0'), label 1: tensor(0, device='cuda:0')
+[21:35:54.719] epoch: 0/20, iter: 3/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-83/image.nii.gz',) mean dice over clicks:0.0 stich left and right side (total size): 1
+[21:35:55.186] dice before refine 0.0 and after 0.026678141206502914, label 0: tensor(0, device='cuda:0'), label 1: tensor(168, device='cuda:0')
+[21:35:59.697] dice before refine 0.0 and after 0.20212766528129578, label 0: tensor(3, device='cuda:0'), label 1: tensor(207, device='cuda:0')
+[21:36:00.117] dice before refine 0.00045320644858293235 and after 0.19218826293945312, label 0: tensor(0, device='cuda:0'), label 1: tensor(497, device='cuda:0')
+[21:36:06.726] dice before refine 0.0004534119216259569 and after 0.42451760172843933, label 0: tensor(35, device='cuda:0'), label 1: tensor(508, device='cuda:0')
+[21:36:07.100] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(179, device='cuda:0')
+[21:36:11.217] dice before refine 0.0 and after 0.24053724110126495, label 0: tensor(0, device='cuda:0'), label 1: tensor(180, device='cuda:0')
+[21:36:11.633] dice before refine 0.0017929179593920708 and after 0.24622531235218048, label 0: tensor(0, device='cuda:0'), label 1: tensor(522, device='cuda:0')
+[21:36:18.066] dice before refine 0.0013428827514871955 and after 0.4330326020717621, label 0: tensor(32, device='cuda:0'), label 1: tensor(376, device='cuda:0')
+[21:36:18.446] dice before refine 0.0015461924485862255 and after 0.04390612989664078, label 0: tensor(0, device='cuda:0'), label 1: tensor(235, device='cuda:0')
+[21:36:23.430] dice before refine 0.0015461924485862255 and after 0.3457106351852417, label 0: tensor(0, device='cuda:0'), label 1: tensor(264, device='cuda:0')
+[21:36:23.857] dice before refine 0.003975213505327702 and after 0.3840511441230774, label 0: tensor(0, device='cuda:0'), label 1: tensor(526, device='cuda:0')
+[21:36:30.475] dice before refine 0.003976142965257168 and after 0.5473897457122803, label 0: tensor(17, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:36:30.857] dice before refine 0.0007733951788395643 and after 0.05251313000917435, label 0: tensor(0, device='cuda:0'), label 1: tensor(202, device='cuda:0')
+[21:36:36.035] dice before refine 0.0007733951788395643 and after 0.3332263231277466, label 0: tensor(0, device='cuda:0'), label 1: tensor(388, device='cuda:0')
+[21:36:36.460] dice before refine 0.0030352557078003883 and after 0.3505442440509796, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:36:42.942] dice before refine 0.0030356100760400295 and after 0.5535772442817688, label 0: tensor(6, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:36:43.673] epoch: 0/20, iter: 4/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-2/image.nii.gz',) mean dice over clicks:0.42724333026192407 stich left and right side (total size): 1
+[21:36:44.172] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(158, device='cuda:0')
+[21:36:48.139] dice before refine 0.0 and after 0.0, label 0: tensor(11, device='cuda:0'), label 1: tensor(107, device='cuda:0')
+[21:36:48.564] dice before refine 0.0 and after 0.04056854173541069, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:36:58.916] dice before refine 0.0 and after 0.0423901341855526, label 0: tensor(506, device='cuda:0'), label 1: tensor(504, device='cuda:0')
+[21:36:59.359] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(158, device='cuda:0')
+[21:37:03.033] dice before refine 0.0 and after 0.0, label 0: tensor(5, device='cuda:0'), label 1: tensor(185, device='cuda:0')
+[21:37:03.513] dice before refine 0.006486621219664812 and after 0.369735985994339, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:37:13.387] dice before refine 0.005431898403912783 and after 0.4143142104148865, label 0: tensor(327, device='cuda:0'), label 1: tensor(508, device='cuda:0')
+[21:37:14.284] epoch: 0/20, iter: 5/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-52/image.nii.gz',) mean dice over clicks:0.3024583784016696 stich left and right side (total size): 1
+[21:37:14.713] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(44, device='cuda:0')
+[21:37:18.480] dice before refine 0.0 and after 0.0, label 0: tensor(58, device='cuda:0'), label 1: tensor(36, device='cuda:0')
+[21:37:18.845] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(43, device='cuda:0')
+[21:37:22.584] dice before refine 0.0 and after 0.0, label 0: tensor(57, device='cuda:0'), label 1: tensor(34, device='cuda:0')
+[21:37:22.956] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(126, device='cuda:0')
+[21:37:28.349] dice before refine 0.0 and after 0.0, label 0: tensor(94, device='cuda:0'), label 1: tensor(153, device='cuda:0')
+[21:37:28.721] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(113, device='cuda:0')
+[21:37:34.971] dice before refine 0.0 and after 0.0, label 0: tensor(160, device='cuda:0'), label 1: tensor(132, device='cuda:0')
+[21:37:35.344] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(168, device='cuda:0')
+[21:37:39.444] dice before refine 0.0 and after 0.0, label 0: tensor(47, device='cuda:0'), label 1: tensor(100, device='cuda:0')
+[21:37:39.821] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(155, device='cuda:0')
+[21:37:44.129] dice before refine 0.0 and after 0.0, label 0: tensor(32, device='cuda:0'), label 1: tensor(160, device='cuda:0')
+[21:37:44.504] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(94, device='cuda:0')
+[21:37:51.038] dice before refine 0.0 and after 0.0, label 0: tensor(312, device='cuda:0'), label 1: tensor(104, device='cuda:0')
+[21:37:51.420] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(152, device='cuda:0')
+[21:37:58.007] dice before refine 0.0 and after 0.0, label 0: tensor(222, device='cuda:0'), label 1: tensor(102, device='cuda:0')
+[21:37:58.686] epoch: 0/20, iter: 6/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-121/image.nii.gz',) mean dice over clicks:0.0 stich left and right side (total size): 1
+[21:37:59.176] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(482, device='cuda:0')
+[21:38:07.459] dice before refine 0.0 and after 0.01078427117317915, label 0: tensor(157, device='cuda:0'), label 1: tensor(503, device='cuda:0')
+[21:38:07.903] dice before refine 0.0 and after 0.020714227110147476, label 0: tensor(0, device='cuda:0'), label 1: tensor(458, device='cuda:0')
+[21:38:16.913] dice before refine 0.0 and after 0.10523897409439087, label 0: tensor(278, device='cuda:0'), label 1: tensor(505, device='cuda:0')
+[21:38:17.334] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(336, device='cuda:0')
+[21:38:24.716] dice before refine 0.0 and after 0.07778224349021912, label 0: tensor(102, device='cuda:0'), label 1: tensor(506, device='cuda:0')
+[21:38:25.140] dice before refine 0.0008363535162061453 and after 0.19942976534366608, label 0: tensor(0, device='cuda:0'), label 1: tensor(423, device='cuda:0')
+[21:38:33.205] dice before refine 0.0005593623500317335 and after 0.3474556505680084, label 0: tensor(171, device='cuda:0'), label 1: tensor(506, device='cuda:0')
+[21:38:33.749] dice before refine 0.0002693675342015922 and after 0.047121383249759674, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:38:44.638] dice before refine 5.3998595831217244e-05 and after 0.07831805944442749, label 0: tensor(335, device='cuda:0'), label 1: tensor(508, device='cuda:0')
+[21:38:45.174] dice before refine 5.681818220182322e-05 and after 0.01607510820031166, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:38:56.046] dice before refine 5.6882821809267625e-05 and after 0.03483671694993973, label 0: tensor(333, device='cuda:0'), label 1: tensor(508, device='cuda:0')
+[21:38:56.575] dice before refine 7.419223402393982e-05 and after 0.008586850017309189, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:39:07.976] dice before refine 0.0 and after 0.02824566885828972, label 0: tensor(447, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:39:08.504] dice before refine 0.0 and after 0.014310820959508419, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:39:20.206] dice before refine 0.0 and after 0.044880203902721405, label 0: tensor(550, device='cuda:0'), label 1: tensor(509, device='cuda:0')
+[21:39:20.797] epoch: 0/20, iter: 7/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-113/image.nii.gz',) mean dice over clicks:0.028557270595973187 stich left and right side (total size): 1
+[21:39:21.315] dice before refine 0.0018885741010308266 and after 0.00035631569335237145, label 0: tensor(0, device='cuda:0'), label 1: tensor(113, device='cuda:0')
+[21:39:26.217] dice before refine 0.0012618296314030886 and after 0.21877044439315796, label 0: tensor(6, device='cuda:0'), label 1: tensor(397, device='cuda:0')
+[21:39:26.599] dice before refine 0.013174404390156269 and after 0.2222222238779068, label 0: tensor(0, device='cuda:0'), label 1: tensor(139, device='cuda:0')
+[21:39:31.908] dice before refine 0.013182674534618855 and after 0.4482811689376831, label 0: tensor(8, device='cuda:0'), label 1: tensor(319, device='cuda:0')
+[21:39:32.290] dice before refine 0.002541295951232314 and after 0.058986175805330276, label 0: tensor(0, device='cuda:0'), label 1: tensor(174, device='cuda:0')
+[21:39:37.518] dice before refine 0.0031746032182127237 and after 0.4885386824607849, label 0: tensor(1, device='cuda:0'), label 1: tensor(281, device='cuda:0')
+[21:39:37.900] dice before refine 0.008199306204915047 and after 0.22797131538391113, label 0: tensor(0, device='cuda:0'), label 1: tensor(127, device='cuda:0')
+[21:39:43.484] dice before refine 0.008824456483125687 and after 0.5757325887680054, label 0: tensor(0, device='cuda:0'), label 1: tensor(307, device='cuda:0')
+[21:39:43.937] epoch: 0/20, iter: 8/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-81/image.nii.gz',) mean dice over clicks:0.2919971617785367 stich left and right side (total size): 1
+[21:39:44.481] dice before refine 0.000302236556308344 and after 0.028667518869042397, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:39:53.350] dice before refine 0.00030295379110611975 and after 0.07540111988782883, label 0: tensor(228, device='cuda:0'), label 1: tensor(504, device='cuda:0')
+[21:39:53.851] dice before refine 0.00032601962448097765 and after 0.04785635322332382, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:40:03.182] dice before refine 0.0002611733216326684 and after 0.08644517511129379, label 0: tensor(263, device='cuda:0'), label 1: tensor(509, device='cuda:0')
+[21:40:03.643] dice before refine 0.015483114868402481 and after 0.48169299960136414, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:40:13.892] dice before refine 0.005254682619124651 and after 0.5739263296127319, label 0: tensor(505, device='cuda:0'), label 1: tensor(505, device='cuda:0')
+[21:40:14.368] dice before refine 0.02493993751704693 and after 0.5771890878677368, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:40:24.847] dice before refine 0.012753534130752087 and after 0.671230673789978, label 0: tensor(474, device='cuda:0'), label 1: tensor(507, device='cuda:0')
+[21:40:25.427] dice before refine 0.0010375387500971556 and after 0.06997781991958618, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:40:37.786] dice before refine 0.0006924608605913818 and after 0.11106137931346893, label 0: tensor(502, device='cuda:0'), label 1: tensor(508, device='cuda:0')
+[21:40:38.396] dice before refine 0.0014959349064156413 and after 0.11465582251548767, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:40:49.982] dice before refine 0.0009327650186605752 and after 0.1443548947572708, label 0: tensor(342, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:40:50.431] dice before refine 0.0009462528396397829 and after 0.08038022369146347, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:41:00.726] dice before refine 0.00019056693417951465 and after 0.1852818727493286, label 0: tensor(419, device='cuda:0'), label 1: tensor(506, device='cuda:0')
+[21:41:01.181] dice before refine 0.0033195021096616983 and after 0.14563831686973572, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:41:08.395] dice before refine 0.0029069767333567142 and after 0.21290284395217896, label 0: tensor(82, device='cuda:0'), label 1: tensor(504, device='cuda:0')
+[21:41:08.950] epoch: 0/20, iter: 9/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-90/image.nii.gz',) mean dice over clicks:0.22139538011767648 stich left and right side (total size): 1
+[21:41:09.470] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(20, device='cuda:0')
+[21:41:12.470] dice before refine 0.0 and after 0.0, label 0: tensor(10, device='cuda:0'), label 1: tensor(25, device='cuda:0')
+[21:41:12.823] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(28, device='cuda:0')
+[21:41:15.771] dice before refine 0.0 and after 0.0, label 0: tensor(9, device='cuda:0'), label 1: tensor(22, device='cuda:0')
+[21:41:16.385] epoch: 0/20, iter: 10/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-127/image.nii.gz',) mean dice over clicks:0.0 stich left and right side (total size): 1
+[21:41:16.386] - Val metrics mean dice: 0.12668530324179092
+[21:41:17.015] - Val metrics best mean dice: 0.12668530324179092 at epoch 0 
+[21:41:40.236] epoch: 1/20, iter: 0/42: loss:3.7377: rank:-1
+[21:41:50.081] epoch: 1/20, iter: 1/42: loss:4.1152: rank:-1
+[21:42:02.097] epoch: 1/20, iter: 2/42: loss:4.3866: rank:-1
+[21:42:21.174] epoch: 1/20, iter: 3/42: loss:3.2495: rank:-1
+[21:42:37.133] epoch: 1/20, iter: 4/42: loss:3.5876: rank:-1
+[21:42:56.360] epoch: 1/20, iter: 5/42: loss:4.1841: rank:-1
+[21:43:07.596] epoch: 1/20, iter: 6/42: loss:3.3689: rank:-1
+[21:43:18.101] epoch: 1/20, iter: 7/42: loss:3.5175: rank:-1
+[21:43:40.401] epoch: 1/20, iter: 8/42: loss:2.8581: rank:-1
+[21:44:04.699] epoch: 1/20, iter: 9/42: loss:2.4715: rank:-1
+[21:44:16.939] epoch: 1/20, iter: 10/42: loss:3.4599: rank:-1
+[21:44:25.642] epoch: 1/20, iter: 11/42: loss:4.4791: rank:-1
+[21:44:36.714] epoch: 1/20, iter: 12/42: loss:4.3862: rank:-1
+[21:44:55.985] epoch: 1/20, iter: 13/42: loss:4.0136: rank:-1
+[21:45:19.876] epoch: 1/20, iter: 14/42: loss:4.4249: rank:-1
+[21:45:37.501] epoch: 1/20, iter: 15/42: loss:3.9379: rank:-1
+[21:45:55.269] epoch: 1/20, iter: 16/42: loss:4.0784: rank:-1
+[21:46:16.145] epoch: 1/20, iter: 17/42: loss:3.5738: rank:-1
+[21:46:43.897] epoch: 1/20, iter: 18/42: loss:4.1122: rank:-1
+[21:46:53.840] epoch: 1/20, iter: 19/42: loss:3.7243: rank:-1
+[21:47:09.752] epoch: 1/20, iter: 20/42: loss:3.5075: rank:-1
+[21:47:24.907] epoch: 1/20, iter: 21/42: loss:2.7696: rank:-1
+[21:47:41.074] epoch: 1/20, iter: 22/42: loss:3.0569: rank:-1
+[21:47:58.127] epoch: 1/20, iter: 23/42: loss:4.734: rank:-1
+[21:48:13.789] epoch: 1/20, iter: 24/42: loss:3.8168: rank:-1
+[21:48:39.553] epoch: 1/20, iter: 25/42: loss:2.2866: rank:-1
+[21:48:50.613] epoch: 1/20, iter: 26/42: loss:4.2865: rank:-1
+[21:49:02.678] epoch: 1/20, iter: 27/42: loss:3.64: rank:-1
+[21:49:24.081] epoch: 1/20, iter: 28/42: loss:3.2795: rank:-1
+[21:49:36.549] epoch: 1/20, iter: 29/42: loss:3.3827: rank:-1
+[21:49:58.116] epoch: 1/20, iter: 30/42: loss:2.693: rank:-1
+[21:50:18.337] epoch: 1/20, iter: 31/42: loss:3.1584: rank:-1
+[21:50:28.146] epoch: 1/20, iter: 32/42: loss:4.1169: rank:-1
+[21:50:56.548] epoch: 1/20, iter: 33/42: loss:5.9586: rank:-1
+[21:51:15.396] epoch: 1/20, iter: 34/42: loss:3.4004: rank:-1
+[21:51:40.451] epoch: 1/20, iter: 35/42: loss:2.0897: rank:-1
+[21:51:59.536] epoch: 1/20, iter: 36/42: loss:2.3034: rank:-1
+[21:52:20.837] epoch: 1/20, iter: 37/42: loss:2.8798: rank:-1
+[21:52:36.082] epoch: 1/20, iter: 38/42: loss:4.0638: rank:-1
+[21:52:55.971] epoch: 1/20, iter: 39/42: loss:3.4877: rank:-1
+[21:53:10.333] epoch: 1/20, iter: 40/42: loss:2.874: rank:-1
+[21:53:20.556] epoch: 1/20, iter: 41/42: loss:2.6461: rank:-1
+[21:53:20.557] - Train metrics: 3.5737934
+[21:53:24.272] dice before refine 0.003340480849146843 and after 0.015238719061017036, label 0: tensor(0, device='cuda:0'), label 1: tensor(190, device='cuda:0')
+[21:53:29.815] dice before refine 0.0018803725251927972 and after 0.0546722449362278, label 0: tensor(109, device='cuda:0'), label 1: tensor(164, device='cuda:0')
+[21:53:30.268] dice before refine 0.000777076231315732 and after 0.05481570586562157, label 0: tensor(0, device='cuda:0'), label 1: tensor(384, device='cuda:0')
+[21:53:38.774] dice before refine 0.0005091811763122678 and after 0.1332227885723114, label 0: tensor(312, device='cuda:0'), label 1: tensor(382, device='cuda:0')
+[21:53:39.135] dice before refine 0.026561731472611427 and after 0.023694733157753944, label 0: tensor(0, device='cuda:0'), label 1: tensor(36, device='cuda:0')
+[21:53:43.306] dice before refine 0.02675613760948181 and after 0.023605462163686752, label 0: tensor(158, device='cuda:0'), label 1: tensor(12, device='cuda:0')
+[21:53:43.726] dice before refine 0.01709246262907982 and after 0.030085531994700432, label 0: tensor(0, device='cuda:0'), label 1: tensor(253, device='cuda:0')
+[21:53:52.439] dice before refine 0.01608228124678135 and after 0.07126905769109726, label 0: tensor(509, device='cuda:0'), label 1: tensor(153, device='cuda:0')
+[21:53:52.860] dice before refine 0.0 and after 0.06913086771965027, label 0: tensor(0, device='cuda:0'), label 1: tensor(287, device='cuda:0')
+[21:53:59.419] dice before refine 0.0 and after 0.5300309658050537, label 0: tensor(73, device='cuda:0'), label 1: tensor(366, device='cuda:0')
+[21:53:59.933] epoch: 1/20, iter: 0/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-120/image.nii.gz',) mean dice over clicks:0.04953528822145679 stich left and right side (total size): 1
+[21:54:00.468] dice before refine 0.0005402219831012189 and after 0.00018795226060319692, label 0: tensor(0, device='cuda:0'), label 1: tensor(108, device='cuda:0')
+[21:54:07.602] dice before refine 0.00045618126750923693 and after 0.005249076522886753, label 0: tensor(510, device='cuda:0'), label 1: tensor(107, device='cuda:0')
+[21:54:07.972] dice before refine 0.039232052862644196 and after 0.04670967161655426, label 0: tensor(0, device='cuda:0'), label 1: tensor(99, device='cuda:0')
+[21:54:15.565] dice before refine 0.03959696739912033 and after 0.07602180540561676, label 0: tensor(510, device='cuda:0'), label 1: tensor(179, device='cuda:0')
+[21:54:15.974] dice before refine 0.001134816207922995 and after 0.0007874015718698502, label 0: tensor(0, device='cuda:0'), label 1: tensor(155, device='cuda:0')
+[21:54:22.079] dice before refine 0.0007910188869573176 and after 0.016381919384002686, label 0: tensor(294, device='cuda:0'), label 1: tensor(192, device='cuda:0')
+[21:54:22.453] dice before refine 0.034989919513463974 and after 0.04875690117478371, label 0: tensor(0, device='cuda:0'), label 1: tensor(121, device='cuda:0')
+[21:54:30.206] dice before refine 0.03728582710027695 and after 0.11566172540187836, label 0: tensor(509, device='cuda:0'), label 1: tensor(201, device='cuda:0')
+[21:54:31.530] epoch: 1/20, iter: 1/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-55/image.nii.gz',) mean dice over clicks:0.06609219448132948 stich left and right side (total size): 1
+[21:54:32.052] dice before refine 0.1727641075849533 and after 0.22971299290657043, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:54:39.199] dice before refine 0.2290586233139038 and after 0.5419644117355347, label 0: tensor(55, device='cuda:0'), label 1: tensor(504, device='cuda:0')
+[21:54:39.765] dice before refine 0.6828361749649048 and after 0.7100183963775635, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:54:49.607] dice before refine 0.7210025787353516 and after 0.812035083770752, label 0: tensor(346, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:54:50.287] dice before refine 0.43470498919487 and after 0.443069726228714, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:54:58.651] dice before refine 0.45325762033462524 and after 0.49985530972480774, label 0: tensor(31, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:54:59.489] dice before refine 0.3868134319782257 and after 0.43968045711517334, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:55:10.330] dice before refine 0.42541539669036865 and after 0.5145308375358582, label 0: tensor(97, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:55:10.785] dice before refine 0.13374046981334686 and after 0.12191975116729736, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:55:19.371] dice before refine 0.13193561136722565 and after 0.33539244532585144, label 0: tensor(161, device='cuda:0'), label 1: tensor(507, device='cuda:0')
+[21:55:19.946] dice before refine 0.09640924632549286 and after 0.07208490371704102, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:55:28.424] dice before refine 0.10521295666694641 and after 0.18768863379955292, label 0: tensor(73, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:55:29.201] dice before refine 0.4189198613166809 and after 0.44261839985847473, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:55:38.695] dice before refine 0.44351834058761597 and after 0.485770583152771, label 0: tensor(47, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:55:39.525] dice before refine 0.22443927824497223 and after 0.23095321655273438, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:55:51.994] dice before refine 0.23984569311141968 and after 0.26615944504737854, label 0: tensor(233, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:55:52.671] epoch: 1/20, iter: 2/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-100/image.nii.gz',) mean dice over clicks:0.4145325070077723 stich left and right side (total size): 1
+[21:55:53.187] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[21:55:56.031] dice before refine 0.0 and after 0.0, label 0: tensor(3, device='cuda:0'), label 1: tensor(7, device='cuda:0')
+[21:55:56.407] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[21:55:59.260] dice before refine 0.0 and after 0.0, label 0: tensor(2, device='cuda:0'), label 1: tensor(8, device='cuda:0')
+[21:55:59.638] epoch: 1/20, iter: 3/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-83/image.nii.gz',) mean dice over clicks:0.0 stich left and right side (total size): 1
+[21:56:00.100] dice before refine 0.0 and after 0.010077178478240967, label 0: tensor(0, device='cuda:0'), label 1: tensor(155, device='cuda:0')
+[21:56:04.527] dice before refine 0.0 and after 0.06718818098306656, label 0: tensor(39, device='cuda:0'), label 1: tensor(75, device='cuda:0')
+[21:56:04.944] dice before refine 0.040945131331682205 and after 0.12534186244010925, label 0: tensor(0, device='cuda:0'), label 1: tensor(506, device='cuda:0')
+[21:56:10.814] dice before refine 0.041124165058135986 and after 0.27250775694847107, label 0: tensor(63, device='cuda:0'), label 1: tensor(229, device='cuda:0')
+[21:56:11.203] dice before refine 0.011595971882343292 and after 0.15169847011566162, label 0: tensor(0, device='cuda:0'), label 1: tensor(172, device='cuda:0')
+[21:56:15.287] dice before refine 0.011560693383216858 and after 0.6383712887763977, label 0: tensor(32, device='cuda:0'), label 1: tensor(132, device='cuda:0')
+[21:56:15.702] dice before refine 0.06213347613811493 and after 0.1426905393600464, label 0: tensor(0, device='cuda:0'), label 1: tensor(503, device='cuda:0')
+[21:56:21.989] dice before refine 0.060316428542137146 and after 0.2924569249153137, label 0: tensor(88, device='cuda:0'), label 1: tensor(254, device='cuda:0')
+[21:56:22.378] dice before refine 0.0025343953166157007 and after 0.02253587916493416, label 0: tensor(0, device='cuda:0'), label 1: tensor(367, device='cuda:0')
+[21:56:27.922] dice before refine 0.0021678106859326363 and after 0.08523908257484436, label 0: tensor(63, device='cuda:0'), label 1: tensor(184, device='cuda:0')
+[21:56:28.352] dice before refine 0.25951817631721497 and after 0.45987674593925476, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:56:35.179] dice before refine 0.2636151909828186 and after 0.7392035722732544, label 0: tensor(115, device='cuda:0'), label 1: tensor(339, device='cuda:0')
+[21:56:35.561] dice before refine 0.035682689398527145 and after 0.0994846522808075, label 0: tensor(0, device='cuda:0'), label 1: tensor(241, device='cuda:0')
+[21:56:40.080] dice before refine 0.03980099409818649 and after 0.6023444533348083, label 0: tensor(39, device='cuda:0'), label 1: tensor(155, device='cuda:0')
+[21:56:40.504] dice before refine 0.2674132287502289 and after 0.28182780742645264, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:56:47.423] dice before refine 0.2776637077331543 and after 0.5020270943641663, label 0: tensor(105, device='cuda:0'), label 1: tensor(320, device='cuda:0')
+[21:56:48.124] epoch: 1/20, iter: 4/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-2/image.nii.gz',) mean dice over clicks:0.2821330468763005 stich left and right side (total size): 1
+[21:56:48.633] dice before refine 0.0 and after 5.2893261454300955e-05, label 0: tensor(0, device='cuda:0'), label 1: tensor(103, device='cuda:0')
+[21:56:52.973] dice before refine 0.0 and after 0.014423954300582409, label 0: tensor(59, device='cuda:0'), label 1: tensor(84, device='cuda:0')
+[21:56:53.388] dice before refine 0.13637873530387878 and after 0.21381323039531708, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:57:01.163] dice before refine 0.14006111025810242 and after 0.5794454216957092, label 0: tensor(143, device='cuda:0'), label 1: tensor(430, device='cuda:0')
+[21:57:01.610] dice before refine 0.0 and after 0.002095150528475642, label 0: tensor(0, device='cuda:0'), label 1: tensor(94, device='cuda:0')
+[21:57:05.707] dice before refine 0.0 and after 0.02576112374663353, label 0: tensor(56, device='cuda:0'), label 1: tensor(98, device='cuda:0')
+[21:57:06.204] dice before refine 0.5483456254005432 and after 0.5501400828361511, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:57:16.506] dice before refine 0.5774121880531311 and after 0.7540242671966553, label 0: tensor(514, device='cuda:0'), label 1: tensor(504, device='cuda:0')
+[21:57:17.473] epoch: 1/20, iter: 5/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-52/image.nii.gz',) mean dice over clicks:0.2878344424746253 stich left and right side (total size): 1
+[21:57:17.895] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(44, device='cuda:0')
+[21:57:21.673] dice before refine 0.0 and after 0.0, label 0: tensor(106, device='cuda:0'), label 1: tensor(32, device='cuda:0')
+[21:57:22.033] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(45, device='cuda:0')
+[21:57:25.300] dice before refine 0.0 and after 0.0, label 0: tensor(25, device='cuda:0'), label 1: tensor(33, device='cuda:0')
+[21:57:25.672] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(135, device='cuda:0')
+[21:57:32.994] dice before refine 0.0 and after 0.06005706265568733, label 0: tensor(509, device='cuda:0'), label 1: tensor(104, device='cuda:0')
+[21:57:33.365] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(96, device='cuda:0')
+[21:57:37.439] dice before refine 0.0 and after 0.00808135885745287, label 0: tensor(38, device='cuda:0'), label 1: tensor(132, device='cuda:0')
+[21:57:37.811] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(122, device='cuda:0')
+[21:57:41.685] dice before refine 0.0 and after 0.01133907400071621, label 0: tensor(25, device='cuda:0'), label 1: tensor(118, device='cuda:0')
+[21:57:42.061] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(135, device='cuda:0')
+[21:57:46.259] dice before refine 0.0 and after 0.017273690551519394, label 0: tensor(30, device='cuda:0'), label 1: tensor(123, device='cuda:0')
+[21:57:46.633] dice before refine 0.0004007012175861746 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(129, device='cuda:0')
+[21:57:54.069] dice before refine 0.0003573342983145267 and after 0.20065905153751373, label 0: tensor(510, device='cuda:0'), label 1: tensor(81, device='cuda:0')
+[21:57:54.450] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(121, device='cuda:0')
+[21:58:01.142] dice before refine 0.0 and after 0.1853710561990738, label 0: tensor(140, device='cuda:0'), label 1: tensor(207, device='cuda:0')
+[21:58:01.895] epoch: 1/20, iter: 6/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-121/image.nii.gz',) mean dice over clicks:0.016184079206802628 stich left and right side (total size): 1
+[21:58:02.388] dice before refine 0.13980938494205475 and after 0.17563876509666443, label 0: tensor(0, device='cuda:0'), label 1: tensor(529, device='cuda:0')
+[21:58:11.097] dice before refine 0.1509052962064743 and after 0.26588866114616394, label 0: tensor(557, device='cuda:0'), label 1: tensor(246, device='cuda:0')
+[21:58:11.532] dice before refine 0.17059260606765747 and after 0.18398119509220123, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:58:20.431] dice before refine 0.18075956404209137 and after 0.275420218706131, label 0: tensor(510, device='cuda:0'), label 1: tensor(187, device='cuda:0')
+[21:58:20.855] dice before refine 0.08281469345092773 and after 0.19250275194644928, label 0: tensor(0, device='cuda:0'), label 1: tensor(480, device='cuda:0')
+[21:58:29.703] dice before refine 0.08583156019449234 and after 0.493971049785614, label 0: tensor(328, device='cuda:0'), label 1: tensor(317, device='cuda:0')
+[21:58:30.124] dice before refine 0.05358508229255676 and after 0.10520032048225403, label 0: tensor(0, device='cuda:0'), label 1: tensor(385, device='cuda:0')
+[21:58:40.146] dice before refine 0.05447370931506157 and after 0.33316150307655334, label 0: tensor(509, device='cuda:0'), label 1: tensor(425, device='cuda:0')
+[21:58:40.685] dice before refine 0.4587603807449341 and after 0.46844449639320374, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:58:52.322] dice before refine 0.45758816599845886 and after 0.6479492783546448, label 0: tensor(503, device='cuda:0'), label 1: tensor(507, device='cuda:0')
+[21:58:52.860] dice before refine 0.45574504137039185 and after 0.45912596583366394, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:59:04.026] dice before refine 0.45428794622421265 and after 0.6576166749000549, label 0: tensor(502, device='cuda:0'), label 1: tensor(508, device='cuda:0')
+[21:59:04.553] dice before refine 0.32414883375167847 and after 0.3593980669975281, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:59:15.734] dice before refine 0.33066532015800476 and after 0.5967575311660767, label 0: tensor(504, device='cuda:0'), label 1: tensor(506, device='cuda:0')
+[21:59:16.281] dice before refine 0.34057918190956116 and after 0.3618077337741852, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[21:59:27.362] dice before refine 0.341221421957016 and after 0.6098010540008545, label 0: tensor(543, device='cuda:0'), label 1: tensor(506, device='cuda:0')
+[21:59:27.866] epoch: 1/20, iter: 7/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-113/image.nii.gz',) mean dice over clicks:0.3736454112963243 stich left and right side (total size): 1
+[21:59:28.368] dice before refine 0.2791828215122223 and after 0.2549408972263336, label 0: tensor(0, device='cuda:0'), label 1: tensor(102, device='cuda:0')
+[21:59:33.393] dice before refine 0.3240678012371063 and after 0.3245672583580017, label 0: tensor(272, device='cuda:0'), label 1: tensor(70, device='cuda:0')
+[21:59:33.769] dice before refine 0.5171263813972473 and after 0.5345258116722107, label 0: tensor(0, device='cuda:0'), label 1: tensor(149, device='cuda:0')
+[21:59:38.301] dice before refine 0.4808308184146881 and after 0.6292572021484375, label 0: tensor(182, device='cuda:0'), label 1: tensor(79, device='cuda:0')
+[21:59:38.680] dice before refine 0.5753604173660278 and after 0.5632568001747131, label 0: tensor(0, device='cuda:0'), label 1: tensor(188, device='cuda:0')
+[21:59:43.481] dice before refine 0.593384325504303 and after 0.6970019936561584, label 0: tensor(142, device='cuda:0'), label 1: tensor(108, device='cuda:0')
+[21:59:43.858] dice before refine 0.5646978616714478 and after 0.6109082102775574, label 0: tensor(0, device='cuda:0'), label 1: tensor(164, device='cuda:0')
+[21:59:48.572] dice before refine 0.5773726105690002 and after 0.737730085849762, label 0: tensor(173, device='cuda:0'), label 1: tensor(76, device='cuda:0')
+[21:59:49.004] epoch: 1/20, iter: 8/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-81/image.nii.gz',) mean dice over clicks:0.6285893808711659 stich left and right side (total size): 1
+[21:59:49.534] dice before refine 0.03501142933964729 and after 0.03513247147202492, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:00:00.296] dice before refine 0.037149377167224884 and after 0.06667641550302505, label 0: tensor(509, device='cuda:0'), label 1: tensor(501, device='cuda:0')
+[22:00:00.796] dice before refine 0.03947385773062706 and after 0.03859706595540047, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:00:12.058] dice before refine 0.04207717999815941 and after 0.07039148360490799, label 0: tensor(507, device='cuda:0'), label 1: tensor(503, device='cuda:0')
+[22:00:12.521] dice before refine 0.46548664569854736 and after 0.48316338658332825, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:00:22.890] dice before refine 0.4956962764263153 and after 0.6622840166091919, label 0: tensor(505, device='cuda:0'), label 1: tensor(505, device='cuda:0')
+[22:00:23.362] dice before refine 0.4767422378063202 and after 0.48062893748283386, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:00:34.192] dice before refine 0.49934789538383484 and after 0.6445888876914978, label 0: tensor(504, device='cuda:0'), label 1: tensor(506, device='cuda:0')
+[22:00:34.773] dice before refine 0.476798415184021 and after 0.46645140647888184, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:00:46.377] dice before refine 0.47586119174957275 and after 0.5562226176261902, label 0: tensor(503, device='cuda:0'), label 1: tensor(507, device='cuda:0')
+[22:00:46.996] dice before refine 0.4385472536087036 and after 0.4328904151916504, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:00:58.836] dice before refine 0.4384496510028839 and after 0.510100245475769, label 0: tensor(502, device='cuda:0'), label 1: tensor(508, device='cuda:0')
+[22:00:59.280] dice before refine 0.24861639738082886 and after 0.2808257043361664, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:01:08.470] dice before refine 0.26225438714027405 and after 0.6151355504989624, label 0: tensor(347, device='cuda:0'), label 1: tensor(505, device='cuda:0')
+[22:01:08.897] dice before refine 0.254607617855072 and after 0.26440247893333435, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:01:16.109] dice before refine 0.26055312156677246 and after 0.6527829170227051, label 0: tensor(93, device='cuda:0'), label 1: tensor(507, device='cuda:0')
+[22:01:16.656] epoch: 1/20, iter: 9/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-90/image.nii.gz',) mean dice over clicks:0.4188787476582961 stich left and right side (total size): 1
+[22:01:17.173] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(26, device='cuda:0')
+[22:01:20.125] dice before refine 0.0 and after 0.0045074052177369595, label 0: tensor(15, device='cuda:0'), label 1: tensor(12, device='cuda:0')
+[22:01:20.479] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(17, device='cuda:0')
+[22:01:23.479] dice before refine 0.0 and after 0.02812499925494194, label 0: tensor(14, device='cuda:0'), label 1: tensor(33, device='cuda:0')
+[22:01:24.060] epoch: 1/20, iter: 10/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-127/image.nii.gz',) mean dice over clicks:0.02419630311090838 stich left and right side (total size): 1
+[22:01:24.060] - Val metrics mean dice: 0.23287467283681648
+[22:01:24.915] - Val metrics best mean dice: 0.23287467283681648 at epoch 1 
+[22:01:53.717] epoch: 2/20, iter: 0/42: loss:3.3353: rank:-1
+[22:02:04.324] epoch: 2/20, iter: 1/42: loss:4.0682: rank:-1
+[22:02:16.697] epoch: 2/20, iter: 2/42: loss:3.1733: rank:-1
+[22:02:37.342] epoch: 2/20, iter: 3/42: loss:2.1544: rank:-1
+[22:02:54.529] epoch: 2/20, iter: 4/42: loss:3.344: rank:-1
+[22:03:07.179] epoch: 2/20, iter: 5/42: loss:3.0277: rank:-1
+[22:03:25.607] epoch: 2/20, iter: 6/42: loss:1.9549: rank:-1
+[22:03:45.844] epoch: 2/20, iter: 7/42: loss:1.7372: rank:-1
+[22:04:02.445] epoch: 2/20, iter: 8/42: loss:2.9768: rank:-1
+[22:04:23.143] epoch: 2/20, iter: 9/42: loss:3.9566: rank:-1
+[22:04:35.113] epoch: 2/20, iter: 10/42: loss:4.0184: rank:-1
+[22:04:46.897] epoch: 2/20, iter: 11/42: loss:3.3748: rank:-1
+[22:05:06.786] epoch: 2/20, iter: 12/42: loss:1.911: rank:-1
+[22:05:19.871] epoch: 2/20, iter: 13/42: loss:4.0467: rank:-1
+[22:05:31.704] epoch: 2/20, iter: 14/42: loss:3.971: rank:-1
+[22:05:56.109] epoch: 2/20, iter: 15/42: loss:3.827: rank:-1
+[22:06:05.363] epoch: 2/20, iter: 16/42: loss:4.246: rank:-1
+[22:06:26.801] epoch: 2/20, iter: 17/42: loss:3.6012: rank:-1
+[22:06:46.807] epoch: 2/20, iter: 18/42: loss:2.7122: rank:-1
+[22:06:59.101] epoch: 2/20, iter: 19/42: loss:4.0997: rank:-1
+[22:07:19.004] epoch: 2/20, iter: 20/42: loss:2.898: rank:-1
+[22:07:37.172] epoch: 2/20, iter: 21/42: loss:2.7943: rank:-1
+[22:08:00.393] epoch: 2/20, iter: 22/42: loss:4.4599: rank:-1
+[22:08:14.678] epoch: 2/20, iter: 23/42: loss:2.5199: rank:-1
+[22:08:28.006] epoch: 2/20, iter: 24/42: loss:3.1098: rank:-1
+[22:08:42.067] epoch: 2/20, iter: 25/42: loss:3.2056: rank:-1
+[22:09:00.618] epoch: 2/20, iter: 26/42: loss:2.5794: rank:-1
+[22:09:21.467] epoch: 2/20, iter: 27/42: loss:3.3894: rank:-1
+[22:09:31.165] epoch: 2/20, iter: 28/42: loss:3.3814: rank:-1
+[22:09:40.620] epoch: 2/20, iter: 29/42: loss:3.792: rank:-1
+[22:09:59.028] epoch: 2/20, iter: 30/42: loss:2.4286: rank:-1
+[22:10:17.427] epoch: 2/20, iter: 31/42: loss:2.0008: rank:-1
+[22:10:35.262] epoch: 2/20, iter: 32/42: loss:4.6954: rank:-1
+[22:10:50.315] epoch: 2/20, iter: 33/42: loss:1.6506: rank:-1
+[22:11:03.858] epoch: 2/20, iter: 34/42: loss:2.199: rank:-1
+[22:11:21.148] epoch: 2/20, iter: 35/42: loss:6.9445: rank:-1
+[22:11:32.928] epoch: 2/20, iter: 36/42: loss:3.4903: rank:-1
+[22:11:57.220] epoch: 2/20, iter: 37/42: loss:2.9281: rank:-1
+[22:12:17.701] epoch: 2/20, iter: 38/42: loss:3.001: rank:-1
+[22:12:43.073] epoch: 2/20, iter: 39/42: loss:4.3429: rank:-1
+[22:12:56.317] epoch: 2/20, iter: 40/42: loss:3.5807: rank:-1
+[22:13:09.124] epoch: 2/20, iter: 41/42: loss:2.6444: rank:-1
+[22:13:09.126] - Train metrics: 3.2755368
+[22:13:12.890] dice before refine 3.1503008358413354e-05 and after 0.033841270953416824, label 0: tensor(0, device='cuda:0'), label 1: tensor(216, device='cuda:0')
+[22:13:17.892] dice before refine 0.0 and after 0.0484347902238369, label 0: tensor(155, device='cuda:0'), label 1: tensor(91, device='cuda:0')
+[22:13:18.359] dice before refine 0.0001923949021147564 and after 0.043740276247262955, label 0: tensor(0, device='cuda:0'), label 1: tensor(359, device='cuda:0')
+[22:13:26.807] dice before refine 0.0 and after 0.07508502900600433, label 0: tensor(298, device='cuda:0'), label 1: tensor(220, device='cuda:0')
+[22:13:27.173] dice before refine 0.009334280155599117 and after 0.009146423079073429, label 0: tensor(0, device='cuda:0'), label 1: tensor(35, device='cuda:0')
+[22:13:32.115] dice before refine 0.0058022961020469666 and after 0.006972453556954861, label 0: tensor(190, device='cuda:0'), label 1: tensor(14, device='cuda:0')
+[22:13:32.536] dice before refine 0.007414613850414753 and after 0.02040254883468151, label 0: tensor(0, device='cuda:0'), label 1: tensor(172, device='cuda:0')
+[22:13:40.866] dice before refine 0.0037759034894406796 and after 0.03914916515350342, label 0: tensor(510, device='cuda:0'), label 1: tensor(75, device='cuda:0')
+[22:13:41.297] dice before refine 0.0 and after 0.0630694255232811, label 0: tensor(0, device='cuda:0'), label 1: tensor(344, device='cuda:0')
+[22:13:47.515] dice before refine 0.0 and after 0.0992925614118576, label 0: tensor(259, device='cuda:0'), label 1: tensor(135, device='cuda:0')
+[22:13:48.043] epoch: 2/20, iter: 0/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-120/image.nii.gz',) mean dice over clicks:0.026679503816095265 stich left and right side (total size): 1
+[22:13:48.564] dice before refine 0.010390070267021656 and after 0.02236800454556942, label 0: tensor(0, device='cuda:0'), label 1: tensor(111, device='cuda:0')
+[22:13:56.186] dice before refine 0.015523969195783138 and after 0.06659604609012604, label 0: tensor(510, device='cuda:0'), label 1: tensor(117, device='cuda:0')
+[22:13:56.562] dice before refine 0.04248129948973656 and after 0.04528103396296501, label 0: tensor(0, device='cuda:0'), label 1: tensor(101, device='cuda:0')
+[22:14:03.832] dice before refine 0.0374932587146759 and after 0.056546323001384735, label 0: tensor(510, device='cuda:0'), label 1: tensor(137, device='cuda:0')
+[22:14:04.227] dice before refine 0.013032879680395126 and after 0.025484157726168633, label 0: tensor(0, device='cuda:0'), label 1: tensor(143, device='cuda:0')
+[22:14:11.587] dice before refine 0.01541608665138483 and after 0.05123034119606018, label 0: tensor(510, device='cuda:0'), label 1: tensor(97, device='cuda:0')
+[22:14:11.955] dice before refine 0.04868682101368904 and after 0.052019309252500534, label 0: tensor(0, device='cuda:0'), label 1: tensor(91, device='cuda:0')
+[22:14:19.032] dice before refine 0.049322132021188736 and after 0.06306429207324982, label 0: tensor(510, device='cuda:0'), label 1: tensor(48, device='cuda:0')
+[22:14:20.291] epoch: 2/20, iter: 1/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-55/image.nii.gz',) mean dice over clicks:0.037154667248780075 stich left and right side (total size): 1
+[22:14:20.816] dice before refine 0.010122091509401798 and after 0.06382181495428085, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:14:28.197] dice before refine 0.20453490316867828 and after 0.44698676466941833, label 0: tensor(268, device='cuda:0'), label 1: tensor(394, device='cuda:0')
+[22:14:28.760] dice before refine 0.6321223974227905 and after 0.6787323355674744, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:14:39.745] dice before refine 0.8369540572166443 and after 0.9489872455596924, label 0: tensor(503, device='cuda:0'), label 1: tensor(507, device='cuda:0')
+[22:14:40.419] dice before refine 0.46217644214630127 and after 0.4662023186683655, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:14:48.756] dice before refine 0.5720407366752625 and after 0.6551771759986877, label 0: tensor(73, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:14:49.594] dice before refine 0.5319765210151672 and after 0.5732249021530151, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:14:59.897] dice before refine 0.6202824115753174 and after 0.7049665451049805, label 0: tensor(105, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:15:00.352] dice before refine 0.11988867819309235 and after 0.1778898537158966, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:15:08.310] dice before refine 0.25622090697288513 and after 0.5411666631698608, label 0: tensor(235, device='cuda:0'), label 1: tensor(446, device='cuda:0')
+[22:15:08.888] dice before refine 0.2321084439754486 and after 0.3102399706840515, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:15:19.890] dice before refine 0.7753812074661255 and after 0.9174346923828125, label 0: tensor(535, device='cuda:0'), label 1: tensor(509, device='cuda:0')
+[22:15:20.664] dice before refine 0.5771431922912598 and after 0.5841461420059204, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:15:30.290] dice before refine 0.6050511598587036 and after 0.6811520457267761, label 0: tensor(132, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:15:31.138] dice before refine 0.4952365756034851 and after 0.5178167819976807, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:15:43.256] dice before refine 0.5588208436965942 and after 0.6268035173416138, label 0: tensor(312, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:15:43.928] epoch: 2/20, iter: 2/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-100/image.nii.gz',) mean dice over clicks:0.6380511576479132 stich left and right side (total size): 1
+[22:15:44.449] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[22:15:47.301] dice before refine 0.0 and after 0.0, label 0: tensor(10, device='cuda:0'), label 1: tensor(0, device='cuda:0')
+[22:15:47.676] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[22:15:50.485] dice before refine 0.0 and after 0.0, label 0: tensor(10, device='cuda:0'), label 1: tensor(0, device='cuda:0')
+[22:15:50.870] epoch: 2/20, iter: 3/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-83/image.nii.gz',) mean dice over clicks:0.0 stich left and right side (total size): 1
+[22:15:51.339] dice before refine 0.0 and after 0.024796759709715843, label 0: tensor(0, device='cuda:0'), label 1: tensor(220, device='cuda:0')
+[22:15:55.262] dice before refine 0.0 and after 0.05369800701737404, label 0: tensor(60, device='cuda:0'), label 1: tensor(53, device='cuda:0')
+[22:15:55.682] dice before refine 0.0005747952382080257 and after 0.11613383144140244, label 0: tensor(0, device='cuda:0'), label 1: tensor(455, device='cuda:0')
+[22:16:01.000] dice before refine 0.018534192815423012 and after 0.1804484874010086, label 0: tensor(144, device='cuda:0'), label 1: tensor(94, device='cuda:0')
+[22:16:01.393] dice before refine 0.0015665212413296103 and after 0.26394644379615784, label 0: tensor(0, device='cuda:0'), label 1: tensor(238, device='cuda:0')
+[22:16:05.231] dice before refine 0.007303218822926283 and after 0.39993584156036377, label 0: tensor(81, device='cuda:0'), label 1: tensor(32, device='cuda:0')
+[22:16:05.644] dice before refine 0.01080042403191328 and after 0.15765823423862457, label 0: tensor(0, device='cuda:0'), label 1: tensor(482, device='cuda:0')
+[22:16:11.397] dice before refine 0.05738084390759468 and after 0.22590190172195435, label 0: tensor(232, device='cuda:0'), label 1: tensor(68, device='cuda:0')
+[22:16:11.779] dice before refine 0.0 and after 0.09258478879928589, label 0: tensor(0, device='cuda:0'), label 1: tensor(302, device='cuda:0')
+[22:16:16.295] dice before refine 0.0007716049440205097 and after 0.06527947634458542, label 0: tensor(119, device='cuda:0'), label 1: tensor(60, device='cuda:0')
+[22:16:16.722] dice before refine 0.4560388922691345 and after 0.7167572975158691, label 0: tensor(0, device='cuda:0'), label 1: tensor(532, device='cuda:0')
+[22:16:23.814] dice before refine 0.7811495065689087 and after 0.8837652802467346, label 0: tensor(298, device='cuda:0'), label 1: tensor(87, device='cuda:0')
+[22:16:24.195] dice before refine 0.01868230104446411 and after 0.2284727841615677, label 0: tensor(0, device='cuda:0'), label 1: tensor(244, device='cuda:0')
+[22:16:28.530] dice before refine 0.09650831669569016 and after 0.3231370449066162, label 0: tensor(33, device='cuda:0'), label 1: tensor(32, device='cuda:0')
+[22:16:28.954] dice before refine 0.4252600371837616 and after 0.510728120803833, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:16:36.023] dice before refine 0.27908843755722046 and after 0.2996385395526886, label 0: tensor(291, device='cuda:0'), label 1: tensor(110, device='cuda:0')
+[22:16:36.765] epoch: 2/20, iter: 4/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-2/image.nii.gz',) mean dice over clicks:0.205108950083906 stich left and right side (total size): 1
+[22:16:37.270] dice before refine 0.0 and after 0.00927018653601408, label 0: tensor(0, device='cuda:0'), label 1: tensor(219, device='cuda:0')
+[22:16:41.348] dice before refine 0.0 and after 0.018768956884741783, label 0: tensor(120, device='cuda:0'), label 1: tensor(12, device='cuda:0')
+[22:16:41.764] dice before refine 0.06095890328288078 and after 0.2043064534664154, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:16:49.492] dice before refine 0.18295033276081085 and after 0.2912733256816864, label 0: tensor(510, device='cuda:0'), label 1: tensor(35, device='cuda:0')
+[22:16:49.933] dice before refine 0.0 and after 0.005453653633594513, label 0: tensor(0, device='cuda:0'), label 1: tensor(124, device='cuda:0')
+[22:16:53.666] dice before refine 0.0 and after 0.03466379642486572, label 0: tensor(39, device='cuda:0'), label 1: tensor(51, device='cuda:0')
+[22:16:54.141] dice before refine 0.4558165669441223 and after 0.4696090519428253, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:17:03.543] dice before refine 0.5175058841705322 and after 0.5961238145828247, label 0: tensor(510, device='cuda:0'), label 1: tensor(84, device='cuda:0')
+[22:17:04.426] epoch: 2/20, iter: 5/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-52/image.nii.gz',) mean dice over clicks:0.23588638278571042 stich left and right side (total size): 1
+[22:17:04.851] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(52, device='cuda:0')
+[22:17:08.247] dice before refine 0.0 and after 0.016617730259895325, label 0: tensor(39, device='cuda:0'), label 1: tensor(16, device='cuda:0')
+[22:17:08.611] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(37, device='cuda:0')
+[22:17:11.893] dice before refine 0.0 and after 0.012837143614888191, label 0: tensor(38, device='cuda:0'), label 1: tensor(20, device='cuda:0')
+[22:17:12.261] dice before refine 6.225486868061125e-05 and after 0.0073328446596860886, label 0: tensor(0, device='cuda:0'), label 1: tensor(95, device='cuda:0')
+[22:17:19.334] dice before refine 5.42578891327139e-05 and after 0.05436542630195618, label 0: tensor(510, device='cuda:0'), label 1: tensor(15, device='cuda:0')
+[22:17:19.703] dice before refine 0.0 and after 0.0014380132779479027, label 0: tensor(0, device='cuda:0'), label 1: tensor(116, device='cuda:0')
+[22:17:24.611] dice before refine 0.0 and after 0.03527260944247246, label 0: tensor(92, device='cuda:0'), label 1: tensor(34, device='cuda:0')
+[22:17:24.978] dice before refine 0.0 and after 0.03368375822901726, label 0: tensor(0, device='cuda:0'), label 1: tensor(133, device='cuda:0')
+[22:17:28.805] dice before refine 0.0 and after 0.026054704561829567, label 0: tensor(75, device='cuda:0'), label 1: tensor(30, device='cuda:0')
+[22:17:29.182] dice before refine 0.0 and after 0.02026386372745037, label 0: tensor(0, device='cuda:0'), label 1: tensor(180, device='cuda:0')
+[22:17:33.533] dice before refine 0.0 and after 0.03106505796313286, label 0: tensor(76, device='cuda:0'), label 1: tensor(43, device='cuda:0')
+[22:17:33.907] dice before refine 0.0009629062260501087 and after 0.026749778538942337, label 0: tensor(0, device='cuda:0'), label 1: tensor(104, device='cuda:0')
+[22:17:40.667] dice before refine 0.002359693869948387 and after 0.12393325567245483, label 0: tensor(510, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[22:17:41.067] dice before refine 0.0 and after 0.007800539489835501, label 0: tensor(0, device='cuda:0'), label 1: tensor(107, device='cuda:0')
+[22:17:48.413] dice before refine 0.0 and after 0.14352178573608398, label 0: tensor(510, device='cuda:0'), label 1: tensor(25, device='cuda:0')
+[22:17:49.065] epoch: 2/20, iter: 6/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-121/image.nii.gz',) mean dice over clicks:0.0370010509875349 stich left and right side (total size): 1
+[22:17:49.545] dice before refine 0.060813892632722855 and after 0.14110177755355835, label 0: tensor(0, device='cuda:0'), label 1: tensor(514, device='cuda:0')
+[22:17:57.543] dice before refine 0.10431903600692749 and after 0.22657513618469238, label 0: tensor(509, device='cuda:0'), label 1: tensor(61, device='cuda:0')
+[22:17:57.971] dice before refine 0.07748982310295105 and after 0.14767178893089294, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:18:06.011] dice before refine 0.0924883782863617 and after 0.1775587648153305, label 0: tensor(510, device='cuda:0'), label 1: tensor(55, device='cuda:0')
+[22:18:06.436] dice before refine 0.014969874173402786 and after 0.1621638834476471, label 0: tensor(0, device='cuda:0'), label 1: tensor(403, device='cuda:0')
+[22:18:14.549] dice before refine 0.1214369609951973 and after 0.38033515214920044, label 0: tensor(510, device='cuda:0'), label 1: tensor(90, device='cuda:0')
+[22:18:14.968] dice before refine 0.013700034469366074 and after 0.03921642154455185, label 0: tensor(0, device='cuda:0'), label 1: tensor(342, device='cuda:0')
+[22:18:23.693] dice before refine 0.062162257730960846 and after 0.2373483031988144, label 0: tensor(510, device='cuda:0'), label 1: tensor(91, device='cuda:0')
+[22:18:24.229] dice before refine 0.5551888346672058 and after 0.5351864695549011, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:18:35.707] dice before refine 0.6054762601852417 and after 0.7407770156860352, label 0: tensor(509, device='cuda:0'), label 1: tensor(360, device='cuda:0')
+[22:18:36.255] dice before refine 0.5081302523612976 and after 0.5360738039016724, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:18:47.355] dice before refine 0.5581827759742737 and after 0.7424253821372986, label 0: tensor(509, device='cuda:0'), label 1: tensor(318, device='cuda:0')
+[22:18:47.877] dice before refine 0.27989888191223145 and after 0.30860063433647156, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:18:59.129] dice before refine 0.37595173716545105 and after 0.5316106081008911, label 0: tensor(509, device='cuda:0'), label 1: tensor(219, device='cuda:0')
+[22:18:59.651] dice before refine 0.25804123282432556 and after 0.29298144578933716, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:19:11.027] dice before refine 0.3635171353816986 and after 0.5601929426193237, label 0: tensor(510, device='cuda:0'), label 1: tensor(296, device='cuda:0')
+[22:19:11.599] epoch: 2/20, iter: 7/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-113/image.nii.gz',) mean dice over clicks:0.31358903781934216 stich left and right side (total size): 1
+[22:19:12.104] dice before refine 0.3741581439971924 and after 0.45207956433296204, label 0: tensor(0, device='cuda:0'), label 1: tensor(136, device='cuda:0')
+[22:19:17.242] dice before refine 0.4802331030368805 and after 0.630713939666748, label 0: tensor(223, device='cuda:0'), label 1: tensor(28, device='cuda:0')
+[22:19:17.621] dice before refine 0.47467106580734253 and after 0.48531100153923035, label 0: tensor(0, device='cuda:0'), label 1: tensor(118, device='cuda:0')
+[22:19:22.674] dice before refine 0.170624241232872 and after 0.18253658711910248, label 0: tensor(158, device='cuda:0'), label 1: tensor(45, device='cuda:0')
+[22:19:23.053] dice before refine 0.36868003010749817 and after 0.4274022877216339, label 0: tensor(0, device='cuda:0'), label 1: tensor(144, device='cuda:0')
+[22:19:28.610] dice before refine 0.2939428687095642 and after 0.3569355905056, label 0: tensor(180, device='cuda:0'), label 1: tensor(27, device='cuda:0')
+[22:19:28.993] dice before refine 0.4227124750614166 and after 0.4929131269454956, label 0: tensor(0, device='cuda:0'), label 1: tensor(153, device='cuda:0')
+[22:19:34.098] dice before refine 0.4992290437221527 and after 0.7246479988098145, label 0: tensor(183, device='cuda:0'), label 1: tensor(36, device='cuda:0')
+[22:19:34.529] epoch: 2/20, iter: 8/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-81/image.nii.gz',) mean dice over clicks:0.3178921775384383 stich left and right side (total size): 1
+[22:19:35.064] dice before refine 6.114711868576705e-05 and after 0.0036419543903321028, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:19:45.799] dice before refine 0.014792140573263168 and after 0.21832682192325592, label 0: tensor(509, device='cuda:0'), label 1: tensor(501, device='cuda:0')
+[22:19:46.326] dice before refine 0.01810012385249138 and after 0.01916050724685192, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:19:57.234] dice before refine 0.07785524427890778 and after 0.300552099943161, label 0: tensor(518, device='cuda:0'), label 1: tensor(500, device='cuda:0')
+[22:19:57.698] dice before refine 0.47483202815055847 and after 0.48237866163253784, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:20:06.647] dice before refine 0.5920822620391846 and after 0.6959254145622253, label 0: tensor(510, device='cuda:0'), label 1: tensor(97, device='cuda:0')
+[22:20:07.125] dice before refine 0.5487136840820312 and after 0.5578064322471619, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:20:16.474] dice before refine 0.656020998954773 and after 0.7434359788894653, label 0: tensor(510, device='cuda:0'), label 1: tensor(103, device='cuda:0')
+[22:20:17.057] dice before refine 0.571658730506897 and after 0.5567623972892761, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:20:28.749] dice before refine 0.6457977890968323 and after 0.7575938701629639, label 0: tensor(507, device='cuda:0'), label 1: tensor(503, device='cuda:0')
+[22:20:29.363] dice before refine 0.6933335065841675 and after 0.6794242262840271, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:20:41.014] dice before refine 0.7493940591812134 and after 0.8276007771492004, label 0: tensor(506, device='cuda:0'), label 1: tensor(504, device='cuda:0')
+[22:20:41.464] dice before refine 0.10201063752174377 and after 0.15295027196407318, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:20:50.655] dice before refine 0.1308002918958664 and after 0.25553661584854126, label 0: tensor(510, device='cuda:0'), label 1: tensor(111, device='cuda:0')
+[22:20:51.109] dice before refine 0.09723774343729019 and after 0.24833081662654877, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:20:59.477] dice before refine 0.326241135597229 and after 0.569000780582428, label 0: tensor(510, device='cuda:0'), label 1: tensor(79, device='cuda:0')
+[22:21:00.019] epoch: 2/20, iter: 9/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-90/image.nii.gz',) mean dice over clicks:0.5186592557213523 stich left and right side (total size): 1
+[22:21:00.558] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(19, device='cuda:0')
+[22:21:03.611] dice before refine 0.0 and after 0.004777379799634218, label 0: tensor(18, device='cuda:0'), label 1: tensor(22, device='cuda:0')
+[22:21:03.966] dice before refine 9.883864549919963e-05 and after 0.003683241317048669, label 0: tensor(0, device='cuda:0'), label 1: tensor(21, device='cuda:0')
+[22:21:07.090] dice before refine 0.0 and after 0.005615519359707832, label 0: tensor(22, device='cuda:0'), label 1: tensor(4, device='cuda:0')
+[22:21:07.587] epoch: 2/20, iter: 10/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-127/image.nii.gz',) mean dice over clicks:0.005455594636838545 stich left and right side (total size): 1
+[22:21:07.588] - Val metrics mean dice: 0.21231616166235553
+[22:21:08.206] - Val metrics best mean dice: 0.23287467283681648 at epoch 1 
+[22:21:38.469] epoch: 3/20, iter: 0/42: loss:2.7549: rank:-1
+[22:21:50.601] epoch: 3/20, iter: 1/42: loss:3.4059: rank:-1
+[22:22:14.046] epoch: 3/20, iter: 2/42: loss:2.1957: rank:-1
+[22:22:29.704] epoch: 3/20, iter: 3/42: loss:4.1521: rank:-1
+[22:22:52.663] epoch: 3/20, iter: 4/42: loss:2.2941: rank:-1
+[22:23:10.912] epoch: 3/20, iter: 5/42: loss:2.0127: rank:-1
+[22:23:25.004] epoch: 3/20, iter: 6/42: loss:3.797: rank:-1
+[22:23:46.448] epoch: 3/20, iter: 7/42: loss:3.6349: rank:-1
+[22:23:55.793] epoch: 3/20, iter: 8/42: loss:4.2641: rank:-1
+[22:24:10.757] epoch: 3/20, iter: 9/42: loss:4.0026: rank:-1
+[22:24:25.000] epoch: 3/20, iter: 10/42: loss:2.3595: rank:-1
+[22:24:36.282] epoch: 3/20, iter: 11/42: loss:3.114: rank:-1
+[22:24:52.466] epoch: 3/20, iter: 12/42: loss:4.9899: rank:-1
+[22:25:07.549] epoch: 3/20, iter: 13/42: loss:2.7491: rank:-1
+[22:25:26.843] epoch: 3/20, iter: 14/42: loss:2.4329: rank:-1
+[22:25:37.868] epoch: 3/20, iter: 15/42: loss:3.7472: rank:-1
+[22:25:57.319] epoch: 3/20, iter: 16/42: loss:3.96: rank:-1
+[22:26:18.640] epoch: 3/20, iter: 17/42: loss:3.657: rank:-1
+[22:26:30.695] epoch: 3/20, iter: 18/42: loss:3.999: rank:-1
+[22:26:46.342] epoch: 3/20, iter: 19/42: loss:1.2334: rank:-1
+[22:26:57.844] epoch: 3/20, iter: 20/42: loss:2.5019: rank:-1
+[22:27:17.934] epoch: 3/20, iter: 21/42: loss:4.5845: rank:-1
+[22:27:35.537] epoch: 3/20, iter: 22/42: loss:2.4453: rank:-1
+[22:28:02.240] epoch: 3/20, iter: 23/42: loss:4.8464: rank:-1
+[22:28:19.756] epoch: 3/20, iter: 24/42: loss:3.8888: rank:-1
+[22:28:35.325] epoch: 3/20, iter: 25/42: loss:1.9328: rank:-1
+[22:28:45.019] epoch: 3/20, iter: 26/42: loss:3.1812: rank:-1
+[22:28:57.066] epoch: 3/20, iter: 27/42: loss:3.2415: rank:-1
+[22:29:18.581] epoch: 3/20, iter: 28/42: loss:2.4812: rank:-1
+[22:29:30.861] epoch: 3/20, iter: 29/42: loss:3.7755: rank:-1
+[22:29:46.163] epoch: 3/20, iter: 30/42: loss:2.0269: rank:-1
+[22:30:04.172] epoch: 3/20, iter: 31/42: loss:3.2159: rank:-1
+[22:30:24.451] epoch: 3/20, iter: 32/42: loss:1.554: rank:-1
+[22:30:42.013] epoch: 3/20, iter: 33/42: loss:1.8738: rank:-1
+[22:30:52.615] epoch: 3/20, iter: 34/42: loss:3.1986: rank:-1
+[22:31:13.568] epoch: 3/20, iter: 35/42: loss:2.5829: rank:-1
+[22:31:34.950] epoch: 3/20, iter: 36/42: loss:1.6166: rank:-1
+[22:31:50.063] epoch: 3/20, iter: 37/42: loss:3.0735: rank:-1
+[22:32:11.650] epoch: 3/20, iter: 38/42: loss:1.7064: rank:-1
+[22:32:28.552] epoch: 3/20, iter: 39/42: loss:3.5061: rank:-1
+[22:32:37.756] epoch: 3/20, iter: 40/42: loss:4.5375: rank:-1
+[22:32:46.666] epoch: 3/20, iter: 41/42: loss:0.9648: rank:-1
+[22:32:46.667] - Train metrics: 3.0355256
+[22:32:50.411] dice before refine 0.05067344754934311 and after 0.1578492373228073, label 0: tensor(0, device='cuda:0'), label 1: tensor(190, device='cuda:0')
+[22:32:55.900] dice before refine 0.03471052274107933 and after 0.16276031732559204, label 0: tensor(195, device='cuda:0'), label 1: tensor(67, device='cuda:0')
+[22:32:56.367] dice before refine 0.010606758296489716 and after 0.16615717113018036, label 0: tensor(0, device='cuda:0'), label 1: tensor(381, device='cuda:0')
+[22:33:04.442] dice before refine 0.0012828964972868562 and after 0.1539975255727768, label 0: tensor(328, device='cuda:0'), label 1: tensor(177, device='cuda:0')
+[22:33:04.806] dice before refine 0.012280667200684547 and after 0.01500516664236784, label 0: tensor(0, device='cuda:0'), label 1: tensor(29, device='cuda:0')
+[22:33:08.206] dice before refine 0.008061837404966354 and after 0.015686459839344025, label 0: tensor(48, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[22:33:08.625] dice before refine 0.03355717286467552 and after 0.07158195972442627, label 0: tensor(0, device='cuda:0'), label 1: tensor(167, device='cuda:0')
+[22:33:16.452] dice before refine 0.04201629385352135 and after 0.14619684219360352, label 0: tensor(510, device='cuda:0'), label 1: tensor(44, device='cuda:0')
+[22:33:16.872] dice before refine 0.0006339412066154182 and after 0.14574766159057617, label 0: tensor(0, device='cuda:0'), label 1: tensor(297, device='cuda:0')
+[22:33:23.804] dice before refine 0.004437049385160208 and after 0.1395905464887619, label 0: tensor(294, device='cuda:0'), label 1: tensor(122, device='cuda:0')
+[22:33:24.360] epoch: 3/20, iter: 0/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-120/image.nii.gz',) mean dice over clicks:0.05311215499585325 stich left and right side (total size): 1
+[22:33:24.884] dice before refine 0.007550977170467377 and after 0.021138180047273636, label 0: tensor(0, device='cuda:0'), label 1: tensor(126, device='cuda:0')
+[22:33:32.511] dice before refine 0.010173802264034748 and after 0.09325601160526276, label 0: tensor(510, device='cuda:0'), label 1: tensor(54, device='cuda:0')
+[22:33:32.880] dice before refine 0.056770388036966324 and after 0.08104941993951797, label 0: tensor(0, device='cuda:0'), label 1: tensor(111, device='cuda:0')
+[22:33:40.031] dice before refine 0.06306946277618408 and after 0.1191680058836937, label 0: tensor(510, device='cuda:0'), label 1: tensor(141, device='cuda:0')
+[22:33:40.429] dice before refine 0.007791868876665831 and after 0.018578780815005302, label 0: tensor(0, device='cuda:0'), label 1: tensor(126, device='cuda:0')
+[22:33:47.598] dice before refine 0.002867857925593853 and after 0.08650657534599304, label 0: tensor(381, device='cuda:0'), label 1: tensor(69, device='cuda:0')
+[22:33:47.968] dice before refine 0.053174883127212524 and after 0.07968337833881378, label 0: tensor(0, device='cuda:0'), label 1: tensor(80, device='cuda:0')
+[22:33:54.233] dice before refine 0.06565967202186584 and after 0.1750132143497467, label 0: tensor(456, device='cuda:0'), label 1: tensor(34, device='cuda:0')
+[22:33:55.491] epoch: 3/20, iter: 1/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-55/image.nii.gz',) mean dice over clicks:0.07645987346768379 stich left and right side (total size): 1
+[22:33:56.033] dice before refine 0.06064842641353607 and after 0.28620871901512146, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:34:03.604] dice before refine 0.7546601295471191 and after 0.949373722076416, label 0: tensor(353, device='cuda:0'), label 1: tensor(149, device='cuda:0')
+[22:34:04.166] dice before refine 0.5276724100112915 and after 0.5466203093528748, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:34:14.404] dice before refine 0.8562904596328735 and after 0.9476257562637329, label 0: tensor(503, device='cuda:0'), label 1: tensor(507, device='cuda:0')
+[22:34:15.086] dice before refine 0.29165345430374146 and after 0.25839507579803467, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:34:24.136] dice before refine 0.5351606011390686 and after 0.645961344242096, label 0: tensor(118, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:34:24.979] dice before refine 0.30341649055480957 and after 0.2730471193790436, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:34:35.731] dice before refine 0.567703127861023 and after 0.6045031547546387, label 0: tensor(87, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:34:36.210] dice before refine 0.1818697303533554 and after 0.347842812538147, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:34:44.881] dice before refine 0.7808141112327576 and after 0.9307876825332642, label 0: tensor(499, device='cuda:0'), label 1: tensor(158, device='cuda:0')
+[22:34:45.459] dice before refine 0.4796810448169708 and after 0.4833226799964905, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:34:55.910] dice before refine 0.8678694367408752 and after 0.9593498706817627, label 0: tensor(506, device='cuda:0'), label 1: tensor(421, device='cuda:0')
+[22:34:56.696] dice before refine 0.5164575576782227 and after 0.4660623371601105, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:35:06.738] dice before refine 0.6203778982162476 and after 0.679337203502655, label 0: tensor(99, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:35:07.565] dice before refine 0.43143802881240845 and after 0.39428919553756714, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:35:19.014] dice before refine 0.5126146078109741 and after 0.5690013766288757, label 0: tensor(239, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:35:19.714] epoch: 3/20, iter: 2/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-100/image.nii.gz',) mean dice over clicks:0.5905080410567197 stich left and right side (total size): 1
+[22:35:20.228] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[22:35:23.083] dice before refine 0.0 and after 0.0, label 0: tensor(10, device='cuda:0'), label 1: tensor(0, device='cuda:0')
+[22:35:23.457] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[22:35:26.329] dice before refine 0.0 and after 0.0, label 0: tensor(10, device='cuda:0'), label 1: tensor(0, device='cuda:0')
+[22:35:26.698] epoch: 3/20, iter: 3/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-83/image.nii.gz',) mean dice over clicks:0.0 stich left and right side (total size): 1
+[22:35:27.151] dice before refine 0.0 and after 0.15507134795188904, label 0: tensor(0, device='cuda:0'), label 1: tensor(132, device='cuda:0')
+[22:35:30.925] dice before refine 0.0 and after 0.09495414793491364, label 0: tensor(83, device='cuda:0'), label 1: tensor(43, device='cuda:0')
+[22:35:31.345] dice before refine 0.012006120756268501 and after 0.3941138982772827, label 0: tensor(0, device='cuda:0'), label 1: tensor(505, device='cuda:0')
+[22:35:37.313] dice before refine 0.11014401167631149 and after 0.3102310299873352, label 0: tensor(184, device='cuda:0'), label 1: tensor(85, device='cuda:0')
+[22:35:37.686] dice before refine 0.0010143702384084463 and after 0.7421820759773254, label 0: tensor(0, device='cuda:0'), label 1: tensor(184, device='cuda:0')
+[22:35:41.441] dice before refine 0.03514480963349342 and after 0.8435592651367188, label 0: tensor(37, device='cuda:0'), label 1: tensor(26, device='cuda:0')
+[22:35:41.853] dice before refine 0.03402352333068848 and after 0.5477310419082642, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:35:47.600] dice before refine 0.5789695978164673 and after 0.874961256980896, label 0: tensor(214, device='cuda:0'), label 1: tensor(70, device='cuda:0')
+[22:35:47.982] dice before refine 0.11451397836208344 and after 0.6995773911476135, label 0: tensor(0, device='cuda:0'), label 1: tensor(312, device='cuda:0')
+[22:35:52.640] dice before refine 0.674291729927063 and after 0.8716672658920288, label 0: tensor(94, device='cuda:0'), label 1: tensor(58, device='cuda:0')
+[22:35:53.062] dice before refine 0.7278613448143005 and after 0.7951739430427551, label 0: tensor(0, device='cuda:0'), label 1: tensor(532, device='cuda:0')
+[22:36:00.191] dice before refine 0.6618964076042175 and after 0.792155385017395, label 0: tensor(521, device='cuda:0'), label 1: tensor(61, device='cuda:0')
+[22:36:00.575] dice before refine 0.05287254601716995 and after 0.43263712525367737, label 0: tensor(0, device='cuda:0'), label 1: tensor(316, device='cuda:0')
+[22:36:04.883] dice before refine 0.5507907867431641 and after 0.8413372039794922, label 0: tensor(68, device='cuda:0'), label 1: tensor(40, device='cuda:0')
+[22:36:05.307] dice before refine 0.4052061140537262 and after 0.6327241659164429, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:36:12.433] dice before refine 0.6937722563743591 and after 0.8121968507766724, label 0: tensor(510, device='cuda:0'), label 1: tensor(63, device='cuda:0')
+[22:36:13.160] epoch: 3/20, iter: 4/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-2/image.nii.gz',) mean dice over clicks:0.4319716448133642 stich left and right side (total size): 1
+[22:36:13.663] dice before refine 0.0 and after 0.017307378351688385, label 0: tensor(0, device='cuda:0'), label 1: tensor(118, device='cuda:0')
+[22:36:17.705] dice before refine 0.0 and after 0.046133484691381454, label 0: tensor(55, device='cuda:0'), label 1: tensor(8, device='cuda:0')
+[22:36:18.121] dice before refine 0.02652907557785511 and after 0.19433479011058807, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:36:25.868] dice before refine 0.14439664781093597 and after 0.2907826602458954, label 0: tensor(510, device='cuda:0'), label 1: tensor(23, device='cuda:0')
+[22:36:26.330] dice before refine 0.0 and after 0.07886864244937897, label 0: tensor(0, device='cuda:0'), label 1: tensor(136, device='cuda:0')
+[22:36:31.034] dice before refine 0.0 and after 0.08464384824037552, label 0: tensor(88, device='cuda:0'), label 1: tensor(28, device='cuda:0')
+[22:36:31.513] dice before refine 0.469851553440094 and after 0.545438289642334, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:36:40.702] dice before refine 0.6842795014381409 and after 0.8032083511352539, label 0: tensor(510, device='cuda:0'), label 1: tensor(48, device='cuda:0')
+[22:36:41.675] epoch: 3/20, iter: 5/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-52/image.nii.gz',) mean dice over clicks:0.3818644041364843 stich left and right side (total size): 1
+[22:36:42.101] dice before refine 0.0 and after 0.009668323211371899, label 0: tensor(0, device='cuda:0'), label 1: tensor(47, device='cuda:0')
+[22:36:48.112] dice before refine 0.0 and after 0.04008389636874199, label 0: tensor(510, device='cuda:0'), label 1: tensor(6, device='cuda:0')
+[22:36:48.475] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(39, device='cuda:0')
+[22:36:52.226] dice before refine 0.0 and after 0.0729752779006958, label 0: tensor(118, device='cuda:0'), label 1: tensor(14, device='cuda:0')
+[22:36:52.608] dice before refine 0.0 and after 0.045530952513217926, label 0: tensor(0, device='cuda:0'), label 1: tensor(149, device='cuda:0')
+[22:36:59.562] dice before refine 4.1281375160906464e-05 and after 0.04712151363492012, label 0: tensor(510, device='cuda:0'), label 1: tensor(7, device='cuda:0')
+[22:36:59.936] dice before refine 0.0012894906103610992 and after 0.1329449713230133, label 0: tensor(0, device='cuda:0'), label 1: tensor(139, device='cuda:0')
+[22:37:04.382] dice before refine 0.0 and after 0.2162705957889557, label 0: tensor(167, device='cuda:0'), label 1: tensor(27, device='cuda:0')
+[22:37:04.765] dice before refine 0.0 and after 0.36143916845321655, label 0: tensor(0, device='cuda:0'), label 1: tensor(167, device='cuda:0')
+[22:37:10.956] dice before refine 0.007362274918705225 and after 0.27139317989349365, label 0: tensor(380, device='cuda:0'), label 1: tensor(25, device='cuda:0')
+[22:37:11.342] dice before refine 0.0 and after 0.20826952159404755, label 0: tensor(0, device='cuda:0'), label 1: tensor(164, device='cuda:0')
+[22:37:15.991] dice before refine 0.0 and after 0.7484720349311829, label 0: tensor(98, device='cuda:0'), label 1: tensor(39, device='cuda:0')
+[22:37:16.377] dice before refine 0.0030933632515370846 and after 0.09329446405172348, label 0: tensor(0, device='cuda:0'), label 1: tensor(151, device='cuda:0')
+[22:37:23.000] dice before refine 0.0021450319327414036 and after 0.15668052434921265, label 0: tensor(510, device='cuda:0'), label 1: tensor(13, device='cuda:0')
+[22:37:23.382] dice before refine 0.0 and after 0.11327097564935684, label 0: tensor(0, device='cuda:0'), label 1: tensor(116, device='cuda:0')
+[22:37:30.077] dice before refine 0.009234828874468803 and after 0.20686741173267365, label 0: tensor(510, device='cuda:0'), label 1: tensor(41, device='cuda:0')
+[22:37:30.748] epoch: 3/20, iter: 6/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-121/image.nii.gz',) mean dice over clicks:0.12484844062816013 stich left and right side (total size): 1
+[22:37:31.234] dice before refine 0.00021965349151287228 and after 0.2957631051540375, label 0: tensor(0, device='cuda:0'), label 1: tensor(539, device='cuda:0')
+[22:37:39.199] dice before refine 0.099249467253685 and after 0.3992084562778473, label 0: tensor(510, device='cuda:0'), label 1: tensor(87, device='cuda:0')
+[22:37:39.631] dice before refine 0.0031411016825586557 and after 0.30521830916404724, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:37:47.630] dice before refine 0.12099141627550125 and after 0.404572457075119, label 0: tensor(510, device='cuda:0'), label 1: tensor(84, device='cuda:0')
+[22:37:48.057] dice before refine 0.0006071310490369797 and after 0.33018946647644043, label 0: tensor(0, device='cuda:0'), label 1: tensor(505, device='cuda:0')
+[22:37:56.186] dice before refine 0.034861642867326736 and after 0.4235052466392517, label 0: tensor(510, device='cuda:0'), label 1: tensor(112, device='cuda:0')
+[22:37:56.610] dice before refine 0.0017184590687975287 and after 0.24407850205898285, label 0: tensor(0, device='cuda:0'), label 1: tensor(390, device='cuda:0')
+[22:38:04.507] dice before refine 0.12240096926689148 and after 0.4508543312549591, label 0: tensor(352, device='cuda:0'), label 1: tensor(102, device='cuda:0')
+[22:38:05.044] dice before refine 0.6085328459739685 and after 0.6174039840698242, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:38:16.077] dice before refine 0.6309638619422913 and after 0.7618075013160706, label 0: tensor(510, device='cuda:0'), label 1: tensor(240, device='cuda:0')
+[22:38:16.617] dice before refine 0.5142660140991211 and after 0.5647352337837219, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:38:27.409] dice before refine 0.5863524079322815 and after 0.7465102672576904, label 0: tensor(510, device='cuda:0'), label 1: tensor(180, device='cuda:0')
+[22:38:27.934] dice before refine 0.2742357552051544 and after 0.33648601174354553, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:38:38.850] dice before refine 0.49474629759788513 and after 0.6253957748413086, label 0: tensor(510, device='cuda:0'), label 1: tensor(221, device='cuda:0')
+[22:38:39.388] dice before refine 0.19367653131484985 and after 0.32162392139434814, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:38:50.465] dice before refine 0.4881821572780609 and after 0.6586000323295593, label 0: tensor(510, device='cuda:0'), label 1: tensor(175, device='cuda:0')
+[22:38:51.060] epoch: 3/20, iter: 7/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-113/image.nii.gz',) mean dice over clicks:0.4854405874555761 stich left and right side (total size): 1
+[22:38:51.571] dice before refine 0.29820552468299866 and after 0.4072113037109375, label 0: tensor(0, device='cuda:0'), label 1: tensor(157, device='cuda:0')
+[22:38:57.294] dice before refine 0.2232292890548706 and after 0.3488451838493347, label 0: tensor(310, device='cuda:0'), label 1: tensor(32, device='cuda:0')
+[22:38:57.679] dice before refine 0.44119641184806824 and after 0.5747800469398499, label 0: tensor(0, device='cuda:0'), label 1: tensor(153, device='cuda:0')
+[22:39:03.109] dice before refine 0.30782267451286316 and after 0.4179980754852295, label 0: tensor(237, device='cuda:0'), label 1: tensor(37, device='cuda:0')
+[22:39:03.491] dice before refine 0.23904633522033691 and after 0.29859352111816406, label 0: tensor(0, device='cuda:0'), label 1: tensor(109, device='cuda:0')
+[22:39:08.629] dice before refine 0.1971784383058548 and after 0.25416338443756104, label 0: tensor(155, device='cuda:0'), label 1: tensor(33, device='cuda:0')
+[22:39:09.012] dice before refine 0.35686251521110535 and after 0.46320033073425293, label 0: tensor(0, device='cuda:0'), label 1: tensor(136, device='cuda:0')
+[22:39:14.263] dice before refine 0.22485756874084473 and after 0.27781063318252563, label 0: tensor(181, device='cuda:0'), label 1: tensor(54, device='cuda:0')
+[22:39:14.783] epoch: 3/20, iter: 8/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-81/image.nii.gz',) mean dice over clicks:0.3022784373976968 stich left and right side (total size): 1
+[22:39:15.327] dice before refine 0.0 and after 0.051679693162441254, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:39:24.822] dice before refine 0.17740842700004578 and after 0.465680867433548, label 0: tensor(405, device='cuda:0'), label 1: tensor(345, device='cuda:0')
+[22:39:25.326] dice before refine 0.00301856710575521 and after 0.01001514308154583, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:39:34.729] dice before refine 0.2976057827472687 and after 0.5744630098342896, label 0: tensor(544, device='cuda:0'), label 1: tensor(501, device='cuda:0')
+[22:39:35.192] dice before refine 0.42739197611808777 and after 0.5047689080238342, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:39:43.639] dice before refine 0.7603546977043152 and after 0.888037383556366, label 0: tensor(509, device='cuda:0'), label 1: tensor(83, device='cuda:0')
+[22:39:44.120] dice before refine 0.5498350262641907 and after 0.6204542517662048, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:39:52.589] dice before refine 0.7553741931915283 and after 0.8602385520935059, label 0: tensor(510, device='cuda:0'), label 1: tensor(76, device='cuda:0')
+[22:39:53.167] dice before refine 0.6370977759361267 and after 0.6455574631690979, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:40:04.640] dice before refine 0.7788124680519104 and after 0.8585094213485718, label 0: tensor(507, device='cuda:0'), label 1: tensor(503, device='cuda:0')
+[22:40:05.254] dice before refine 0.7221536040306091 and after 0.707622766494751, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:40:16.723] dice before refine 0.8178098201751709 and after 0.8921011090278625, label 0: tensor(503, device='cuda:0'), label 1: tensor(507, device='cuda:0')
+[22:40:17.172] dice before refine 0.0660233199596405 and after 0.18686363101005554, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:40:25.972] dice before refine 0.17120730876922607 and after 0.32533812522888184, label 0: tensor(510, device='cuda:0'), label 1: tensor(80, device='cuda:0')
+[22:40:26.405] dice before refine 0.04764118790626526 and after 0.23840652406215668, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:40:34.240] dice before refine 0.2615794539451599 and after 0.47250130772590637, label 0: tensor(510, device='cuda:0'), label 1: tensor(87, device='cuda:0')
+[22:40:34.748] epoch: 3/20, iter: 9/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-90/image.nii.gz',) mean dice over clicks:0.6150377880443226 stich left and right side (total size): 1
+[22:40:35.277] dice before refine 0.0 and after 0.0049549550749361515, label 0: tensor(0, device='cuda:0'), label 1: tensor(33, device='cuda:0')
+[22:40:38.317] dice before refine 0.0 and after 0.006134393159300089, label 0: tensor(57, device='cuda:0'), label 1: tensor(11, device='cuda:0')
+[22:40:38.675] dice before refine 0.0 and after 0.00658209016546607, label 0: tensor(0, device='cuda:0'), label 1: tensor(26, device='cuda:0')
+[22:40:41.803] dice before refine 0.0 and after 0.006317073944956064, label 0: tensor(27, device='cuda:0'), label 1: tensor(7, device='cuda:0')
+[22:40:42.311] epoch: 3/20, iter: 10/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-127/image.nii.gz',) mean dice over clicks:0.005890298486602577 stich left and right side (total size): 1
+[22:40:42.312] - Val metrics mean dice: 0.2788556064074967
+[22:40:43.083] - Val metrics best mean dice: 0.2788556064074967 at epoch 3 
+[22:41:04.292] epoch: 4/20, iter: 0/42: loss:3.1608: rank:-1
+[22:41:21.118] epoch: 4/20, iter: 1/42: loss:3.4804: rank:-1
+[22:41:33.908] epoch: 4/20, iter: 2/42: loss:3.3103: rank:-1
+[22:41:44.713] epoch: 4/20, iter: 3/42: loss:3.1117: rank:-1
+[22:42:05.697] epoch: 4/20, iter: 4/42: loss:2.2315: rank:-1
+[22:42:25.713] epoch: 4/20, iter: 5/42: loss:2.1745: rank:-1
+[22:42:35.074] epoch: 4/20, iter: 6/42: loss:4.3796: rank:-1
+[22:42:46.419] epoch: 4/20, iter: 7/42: loss:1.758: rank:-1
+[22:43:07.865] epoch: 4/20, iter: 8/42: loss:1.9747: rank:-1
+[22:43:30.451] epoch: 4/20, iter: 9/42: loss:4.1588: rank:-1
+[22:43:53.249] epoch: 4/20, iter: 10/42: loss:5.689: rank:-1
+[22:44:03.799] epoch: 4/20, iter: 11/42: loss:2.4941: rank:-1
+[22:44:23.797] epoch: 4/20, iter: 12/42: loss:4.0873: rank:-1
+[22:44:46.900] epoch: 4/20, iter: 13/42: loss:3.2689: rank:-1
+[22:45:07.842] epoch: 4/20, iter: 14/42: loss:1.5618: rank:-1
+[22:45:18.241] epoch: 4/20, iter: 15/42: loss:2.3385: rank:-1
+[22:45:30.068] epoch: 4/20, iter: 16/42: loss:2.4282: rank:-1
+[22:45:49.574] epoch: 4/20, iter: 17/42: loss:1.6863: rank:-1
+[22:46:03.494] epoch: 4/20, iter: 18/42: loss:3.0849: rank:-1
+[22:46:14.322] epoch: 4/20, iter: 19/42: loss:2.6994: rank:-1
+[22:46:33.860] epoch: 4/20, iter: 20/42: loss:1.787: rank:-1
+[22:46:55.725] epoch: 4/20, iter: 21/42: loss:1.8188: rank:-1
+[22:47:19.956] epoch: 4/20, iter: 22/42: loss:4.5704: rank:-1
+[22:47:33.396] epoch: 4/20, iter: 23/42: loss:3.5471: rank:-1
+[22:47:57.076] epoch: 4/20, iter: 24/42: loss:4.2757: rank:-1
+[22:48:09.715] epoch: 4/20, iter: 25/42: loss:2.2935: rank:-1
+[22:48:21.314] epoch: 4/20, iter: 26/42: loss:2.2628: rank:-1
+[22:48:44.244] epoch: 4/20, iter: 27/42: loss:2.1958: rank:-1
+[22:49:05.893] epoch: 4/20, iter: 28/42: loss:1.8897: rank:-1
+[22:49:22.971] epoch: 4/20, iter: 29/42: loss:1.5163: rank:-1
+[22:49:32.707] epoch: 4/20, iter: 30/42: loss:2.4607: rank:-1
+[22:49:44.625] epoch: 4/20, iter: 31/42: loss:2.5995: rank:-1
+[22:49:58.992] epoch: 4/20, iter: 32/42: loss:2.7958: rank:-1
+[22:50:09.748] epoch: 4/20, iter: 33/42: loss:1.7693: rank:-1
+[22:50:32.269] epoch: 4/20, iter: 34/42: loss:2.9598: rank:-1
+[22:50:41.823] epoch: 4/20, iter: 35/42: loss:2.4863: rank:-1
+[22:50:54.200] epoch: 4/20, iter: 36/42: loss:2.4962: rank:-1
+[22:51:14.068] epoch: 4/20, iter: 37/42: loss:1.5843: rank:-1
+[22:51:29.812] epoch: 4/20, iter: 38/42: loss:1.9649: rank:-1
+[22:51:43.918] epoch: 4/20, iter: 39/42: loss:1.2162: rank:-1
+[22:51:52.883] epoch: 4/20, iter: 40/42: loss:2.4444: rank:-1
+[22:52:01.445] epoch: 4/20, iter: 41/42: loss:0.887: rank:-1
+[22:52:01.446] - Train metrics: 2.6404898
+[22:52:05.163] dice before refine 0.02011275291442871 and after 0.6841498613357544, label 0: tensor(0, device='cuda:0'), label 1: tensor(183, device='cuda:0')
+[22:52:10.083] dice before refine 0.3841243386268616 and after 0.8783695101737976, label 0: tensor(179, device='cuda:0'), label 1: tensor(50, device='cuda:0')
+[22:52:10.543] dice before refine 0.0 and after 0.6138349771499634, label 0: tensor(0, device='cuda:0'), label 1: tensor(378, device='cuda:0')
+[22:52:17.944] dice before refine 0.4942072629928589 and after 0.8513262271881104, label 0: tensor(271, device='cuda:0'), label 1: tensor(153, device='cuda:0')
+[22:52:18.320] dice before refine 0.06178956478834152 and after 0.16038751602172852, label 0: tensor(0, device='cuda:0'), label 1: tensor(36, device='cuda:0')
+[22:52:21.620] dice before refine 0.3257790505886078 and after 0.8537858724594116, label 0: tensor(33, device='cuda:0'), label 1: tensor(16, device='cuda:0')
+[22:52:22.037] dice before refine 0.05861889198422432 and after 0.2967887222766876, label 0: tensor(0, device='cuda:0'), label 1: tensor(196, device='cuda:0')
+[22:52:28.419] dice before refine 0.07521367818117142 and after 0.31856539845466614, label 0: tensor(315, device='cuda:0'), label 1: tensor(84, device='cuda:0')
+[22:52:28.837] dice before refine 0.0 and after 0.3089236319065094, label 0: tensor(0, device='cuda:0'), label 1: tensor(311, device='cuda:0')
+[22:52:34.937] dice before refine 0.03714587911963463 and after 0.3763965964317322, label 0: tensor(256, device='cuda:0'), label 1: tensor(104, device='cuda:0')
+[22:52:35.565] epoch: 4/20, iter: 0/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-120/image.nii.gz',) mean dice over clicks:0.2867402664639733 stich left and right side (total size): 1
+[22:52:36.086] dice before refine 0.0 and after 0.07209694385528564, label 0: tensor(0, device='cuda:0'), label 1: tensor(129, device='cuda:0')
+[22:52:40.777] dice before refine 0.0 and after 0.293170690536499, label 0: tensor(80, device='cuda:0'), label 1: tensor(60, device='cuda:0')
+[22:52:41.147] dice before refine 0.0007887057145126164 and after 0.2629859447479248, label 0: tensor(0, device='cuda:0'), label 1: tensor(106, device='cuda:0')
+[22:52:45.751] dice before refine 0.0 and after 0.9253455996513367, label 0: tensor(134, device='cuda:0'), label 1: tensor(54, device='cuda:0')
+[22:52:46.140] dice before refine 0.0 and after 0.025723472237586975, label 0: tensor(0, device='cuda:0'), label 1: tensor(66, device='cuda:0')
+[22:52:50.780] dice before refine 0.0 and after 0.8640961647033691, label 0: tensor(67, device='cuda:0'), label 1: tensor(49, device='cuda:0')
+[22:52:51.151] dice before refine 0.0 and after 0.22909259796142578, label 0: tensor(0, device='cuda:0'), label 1: tensor(93, device='cuda:0')
+[22:52:55.994] dice before refine 0.0 and after 0.8768942356109619, label 0: tensor(98, device='cuda:0'), label 1: tensor(66, device='cuda:0')
+[22:52:57.264] epoch: 4/20, iter: 1/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-55/image.nii.gz',) mean dice over clicks:0.6609117497097362 stich left and right side (total size): 1
+[22:52:57.785] dice before refine 0.0 and after 0.21133707463741302, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:53:05.188] dice before refine 0.6951028108596802 and after 0.9424244165420532, label 0: tensor(175, device='cuda:0'), label 1: tensor(287, device='cuda:0')
+[22:53:05.751] dice before refine 0.001680122222751379 and after 0.07193803787231445, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:53:14.185] dice before refine 0.7740659713745117 and after 0.8327724933624268, label 0: tensor(257, device='cuda:0'), label 1: tensor(509, device='cuda:0')
+[22:53:14.866] dice before refine 0.1111111119389534 and after 0.025948498398065567, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:53:24.086] dice before refine 0.4016650319099426 and after 0.35107529163360596, label 0: tensor(103, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:53:24.934] dice before refine 0.08516115695238113 and after 0.01939445734024048, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:53:34.928] dice before refine 0.3619495928287506 and after 0.31639525294303894, label 0: tensor(10, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:53:35.387] dice before refine 0.07380441576242447 and after 0.2164468616247177, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:53:43.409] dice before refine 0.7370404601097107 and after 0.9338266849517822, label 0: tensor(534, device='cuda:0'), label 1: tensor(361, device='cuda:0')
+[22:53:43.990] dice before refine 0.006092475261539221 and after 0.10479024797677994, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:53:52.995] dice before refine 0.7940438985824585 and after 0.8588095307350159, label 0: tensor(308, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:53:53.774] dice before refine 0.11996674537658691 and after 0.04748385027050972, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:54:03.295] dice before refine 0.36536267399787903 and after 0.35501617193222046, label 0: tensor(19, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:54:04.125] dice before refine 0.10527966916561127 and after 0.030985524877905846, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:54:14.250] dice before refine 0.3915891945362091 and after 0.3294200599193573, label 0: tensor(71, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:54:14.923] epoch: 4/20, iter: 2/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-100/image.nii.gz',) mean dice over clicks:0.2258683443069458 stich left and right side (total size): 1
+[22:54:15.475] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[22:54:18.310] dice before refine 0.0 and after 0.1111111119389534, label 0: tensor(1, device='cuda:0'), label 1: tensor(9, device='cuda:0')
+[22:54:18.685] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[22:54:21.504] dice before refine 0.0 and after 0.0784313753247261, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[22:54:21.880] epoch: 4/20, iter: 3/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-83/image.nii.gz',) mean dice over clicks:0.007130125029520555 stich left and right side (total size): 1
+[22:54:22.335] dice before refine 0.0 and after 0.6277503371238708, label 0: tensor(0, device='cuda:0'), label 1: tensor(177, device='cuda:0')
+[22:54:26.216] dice before refine 0.1705128252506256 and after 0.8693877458572388, label 0: tensor(67, device='cuda:0'), label 1: tensor(36, device='cuda:0')
+[22:54:26.633] dice before refine 0.0 and after 0.7798290252685547, label 0: tensor(0, device='cuda:0'), label 1: tensor(502, device='cuda:0')
+[22:54:32.240] dice before refine 0.4467446208000183 and after 0.8481451272964478, label 0: tensor(235, device='cuda:0'), label 1: tensor(92, device='cuda:0')
+[22:54:32.614] dice before refine 0.0 and after 0.684909462928772, label 0: tensor(0, device='cuda:0'), label 1: tensor(178, device='cuda:0')
+[22:54:36.258] dice before refine 0.26015302538871765 and after 0.8793399930000305, label 0: tensor(75, device='cuda:0'), label 1: tensor(47, device='cuda:0')
+[22:54:36.668] dice before refine 0.0 and after 0.7540153861045837, label 0: tensor(0, device='cuda:0'), label 1: tensor(476, device='cuda:0')
+[22:54:42.105] dice before refine 0.4836013913154602 and after 0.8998375535011292, label 0: tensor(211, device='cuda:0'), label 1: tensor(77, device='cuda:0')
+[22:54:42.486] dice before refine 0.0 and after 0.6457809209823608, label 0: tensor(0, device='cuda:0'), label 1: tensor(266, device='cuda:0')
+[22:54:46.692] dice before refine 0.6634894609451294 and after 0.8712453842163086, label 0: tensor(138, device='cuda:0'), label 1: tensor(109, device='cuda:0')
+[22:54:47.109] dice before refine 0.3911530673503876 and after 0.6976935863494873, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:54:53.927] dice before refine 0.6806754469871521 and after 0.8918081521987915, label 0: tensor(300, device='cuda:0'), label 1: tensor(71, device='cuda:0')
+[22:54:54.311] dice before refine 0.0 and after 0.7618853449821472, label 0: tensor(0, device='cuda:0'), label 1: tensor(327, device='cuda:0')
+[22:54:58.443] dice before refine 0.5774737596511841 and after 0.8746867179870605, label 0: tensor(109, device='cuda:0'), label 1: tensor(55, device='cuda:0')
+[22:54:58.867] dice before refine 0.607514500617981 and after 0.7058295607566833, label 0: tensor(0, device='cuda:0'), label 1: tensor(556, device='cuda:0')
+[22:55:05.356] dice before refine 0.7349423766136169 and after 0.9074587821960449, label 0: tensor(237, device='cuda:0'), label 1: tensor(81, device='cuda:0')
+[22:55:06.084] epoch: 4/20, iter: 4/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-2/image.nii.gz',) mean dice over clicks:0.8742133324796503 stich left and right side (total size): 1
+[22:55:06.580] dice before refine 0.0 and after 0.20410703122615814, label 0: tensor(0, device='cuda:0'), label 1: tensor(108, device='cuda:0')
+[22:55:10.237] dice before refine 0.0 and after 0.8226442337036133, label 0: tensor(25, device='cuda:0'), label 1: tensor(51, device='cuda:0')
+[22:55:10.654] dice before refine 0.0 and after 0.5216124057769775, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:55:17.415] dice before refine 0.499296098947525 and after 0.8674495220184326, label 0: tensor(263, device='cuda:0'), label 1: tensor(96, device='cuda:0')
+[22:55:17.847] dice before refine 0.0 and after 0.5207509994506836, label 0: tensor(0, device='cuda:0'), label 1: tensor(149, device='cuda:0')
+[22:55:21.524] dice before refine 0.0 and after 0.8306836485862732, label 0: tensor(83, device='cuda:0'), label 1: tensor(34, device='cuda:0')
+[22:55:21.994] dice before refine 0.48421624302864075 and after 0.43971335887908936, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:55:30.720] dice before refine 0.7930055856704712 and after 0.9243650436401367, label 0: tensor(510, device='cuda:0'), label 1: tensor(151, device='cuda:0')
+[22:55:31.642] epoch: 4/20, iter: 5/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-52/image.nii.gz',) mean dice over clicks:0.8217205865816637 stich left and right side (total size): 1
+[22:55:32.073] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(34, device='cuda:0')
+[22:55:35.336] dice before refine 0.0 and after 0.8316429853439331, label 0: tensor(46, device='cuda:0'), label 1: tensor(25, device='cuda:0')
+[22:55:35.692] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(42, device='cuda:0')
+[22:55:38.916] dice before refine 0.0 and after 0.837067186832428, label 0: tensor(43, device='cuda:0'), label 1: tensor(19, device='cuda:0')
+[22:55:39.282] dice before refine 0.0 and after 0.21684867143630981, label 0: tensor(0, device='cuda:0'), label 1: tensor(116, device='cuda:0')
+[22:55:43.050] dice before refine 0.0 and after 0.8438605070114136, label 0: tensor(73, device='cuda:0'), label 1: tensor(35, device='cuda:0')
+[22:55:43.420] dice before refine 0.0 and after 0.4719424545764923, label 0: tensor(0, device='cuda:0'), label 1: tensor(114, device='cuda:0')
+[22:55:47.203] dice before refine 0.0 and after 0.8213755488395691, label 0: tensor(91, device='cuda:0'), label 1: tensor(25, device='cuda:0')
+[22:55:47.573] dice before refine 0.0 and after 0.4815724790096283, label 0: tensor(0, device='cuda:0'), label 1: tensor(111, device='cuda:0')
+[22:55:51.316] dice before refine 0.0 and after 0.8636884093284607, label 0: tensor(83, device='cuda:0'), label 1: tensor(22, device='cuda:0')
+[22:55:51.691] dice before refine 0.0 and after 0.5496277809143066, label 0: tensor(0, device='cuda:0'), label 1: tensor(154, device='cuda:0')
+[22:55:55.765] dice before refine 0.003331482410430908 and after 0.8161764740943909, label 0: tensor(123, device='cuda:0'), label 1: tensor(36, device='cuda:0')
+[22:55:56.137] dice before refine 0.0 and after 0.3059028685092926, label 0: tensor(0, device='cuda:0'), label 1: tensor(129, device='cuda:0')
+[22:56:00.751] dice before refine 0.03162699565291405 and after 0.803320586681366, label 0: tensor(167, device='cuda:0'), label 1: tensor(35, device='cuda:0')
+[22:56:01.124] dice before refine 0.0 and after 0.06040892377495766, label 0: tensor(0, device='cuda:0'), label 1: tensor(116, device='cuda:0')
+[22:56:05.606] dice before refine 0.024193547666072845 and after 0.8218657374382019, label 0: tensor(127, device='cuda:0'), label 1: tensor(45, device='cuda:0')
+[22:56:06.331] epoch: 4/20, iter: 6/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-121/image.nii.gz',) mean dice over clicks:0.6476714282550595 stich left and right side (total size): 1
+[22:56:06.818] dice before refine 0.0 and after 0.5369511842727661, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:56:14.238] dice before refine 0.33596035838127136 and after 0.783513605594635, label 0: tensor(390, device='cuda:0'), label 1: tensor(104, device='cuda:0')
+[22:56:14.663] dice before refine 0.0 and after 0.5939612984657288, label 0: tensor(0, device='cuda:0'), label 1: tensor(520, device='cuda:0')
+[22:56:22.295] dice before refine 0.4250224232673645 and after 0.8333021402359009, label 0: tensor(382, device='cuda:0'), label 1: tensor(97, device='cuda:0')
+[22:56:22.715] dice before refine 0.0 and after 0.5320120453834534, label 0: tensor(0, device='cuda:0'), label 1: tensor(454, device='cuda:0')
+[22:56:29.299] dice before refine 0.4247649013996124 and after 0.8598540425300598, label 0: tensor(260, device='cuda:0'), label 1: tensor(135, device='cuda:0')
+[22:56:29.723] dice before refine 0.0 and after 0.3861614465713501, label 0: tensor(0, device='cuda:0'), label 1: tensor(309, device='cuda:0')
+[22:56:36.470] dice before refine 0.38904252648353577 and after 0.8672316670417786, label 0: tensor(295, device='cuda:0'), label 1: tensor(104, device='cuda:0')
+[22:56:36.998] dice before refine 0.33800214529037476 and after 0.26974108815193176, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:56:47.767] dice before refine 0.6696392297744751 and after 0.8661708831787109, label 0: tensor(507, device='cuda:0'), label 1: tensor(503, device='cuda:0')
+[22:56:48.295] dice before refine 0.32791271805763245 and after 0.2257792353630066, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:56:58.656] dice before refine 0.6369342803955078 and after 0.8630456924438477, label 0: tensor(502, device='cuda:0'), label 1: tensor(508, device='cuda:0')
+[22:56:59.173] dice before refine 0.21478211879730225 and after 0.2852247953414917, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:57:09.570] dice before refine 0.6127193570137024 and after 0.8518475294113159, label 0: tensor(507, device='cuda:0'), label 1: tensor(306, device='cuda:0')
+[22:57:10.082] dice before refine 0.18416762351989746 and after 0.3183121383190155, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:57:20.269] dice before refine 0.6241878867149353 and after 0.8599547147750854, label 0: tensor(509, device='cuda:0'), label 1: tensor(263, device='cuda:0')
+[22:57:20.860] epoch: 4/20, iter: 7/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-113/image.nii.gz',) mean dice over clicks:0.6494757289236243 stich left and right side (total size): 1
+[22:57:21.372] dice before refine 0.5949477553367615 and after 0.7597402334213257, label 0: tensor(0, device='cuda:0'), label 1: tensor(141, device='cuda:0')
+[22:57:25.747] dice before refine 0.7637022733688354 and after 0.9106982350349426, label 0: tensor(156, device='cuda:0'), label 1: tensor(59, device='cuda:0')
+[22:57:26.133] dice before refine 0.5957018136978149 and after 0.8067050576210022, label 0: tensor(0, device='cuda:0'), label 1: tensor(224, device='cuda:0')
+[22:57:30.639] dice before refine 0.7714200019836426 and after 0.9075907468795776, label 0: tensor(111, device='cuda:0'), label 1: tensor(39, device='cuda:0')
+[22:57:31.016] dice before refine 0.6996756196022034 and after 0.7322344183921814, label 0: tensor(0, device='cuda:0'), label 1: tensor(133, device='cuda:0')
+[22:57:35.630] dice before refine 0.7958613038063049 and after 0.9105302691459656, label 0: tensor(143, device='cuda:0'), label 1: tensor(38, device='cuda:0')
+[22:57:36.013] dice before refine 0.5188981294631958 and after 0.810960590839386, label 0: tensor(0, device='cuda:0'), label 1: tensor(228, device='cuda:0')
+[22:57:40.494] dice before refine 0.6098792552947998 and after 0.912972092628479, label 0: tensor(167, device='cuda:0'), label 1: tensor(70, device='cuda:0')
+[22:57:40.933] epoch: 4/20, iter: 8/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-81/image.nii.gz',) mean dice over clicks:0.8874555067582564 stich left and right side (total size): 1
+[22:57:41.478] dice before refine 0.0 and after 0.17650863528251648, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:57:50.486] dice before refine 0.5667110085487366 and after 0.8720231652259827, label 0: tensor(506, device='cuda:0'), label 1: tensor(283, device='cuda:0')
+[22:57:50.995] dice before refine 0.0 and after 0.028122998774051666, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:58:00.188] dice before refine 0.6330263018608093 and after 0.9021450281143188, label 0: tensor(506, device='cuda:0'), label 1: tensor(314, device='cuda:0')
+[22:58:00.657] dice before refine 0.4095904231071472 and after 0.5125540494918823, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:58:09.317] dice before refine 0.768978476524353 and after 0.9109960198402405, label 0: tensor(510, device='cuda:0'), label 1: tensor(178, device='cuda:0')
+[22:58:09.801] dice before refine 0.5086715817451477 and after 0.4915134608745575, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:58:18.878] dice before refine 0.7824868559837341 and after 0.9159559607505798, label 0: tensor(510, device='cuda:0'), label 1: tensor(160, device='cuda:0')
+[22:58:19.466] dice before refine 0.4122371971607208 and after 0.2682875096797943, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:58:29.949] dice before refine 0.7609255909919739 and after 0.8354547023773193, label 0: tensor(501, device='cuda:0'), label 1: tensor(509, device='cuda:0')
+[22:58:30.567] dice before refine 0.45796865224838257 and after 0.28754353523254395, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:58:40.532] dice before refine 0.7029172778129578 and after 0.804485023021698, label 0: tensor(506, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:58:40.982] dice before refine 0.21511627733707428 and after 0.3991531729698181, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:58:49.780] dice before refine 0.6223257780075073 and after 0.892562747001648, label 0: tensor(390, device='cuda:0'), label 1: tensor(132, device='cuda:0')
+[22:58:50.212] dice before refine 0.0 and after 0.43666890263557434, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[22:58:57.860] dice before refine 0.6525707840919495 and after 0.8954315781593323, label 0: tensor(302, device='cuda:0'), label 1: tensor(99, device='cuda:0')
+[22:58:58.392] epoch: 4/20, iter: 9/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-90/image.nii.gz',) mean dice over clicks:0.7215645773844286 stich left and right side (total size): 1
+[22:58:58.903] dice before refine 0.0 and after 0.060453400015830994, label 0: tensor(0, device='cuda:0'), label 1: tensor(37, device='cuda:0')
+[22:59:01.986] dice before refine 0.0 and after 0.5905511975288391, label 0: tensor(51, device='cuda:0'), label 1: tensor(5, device='cuda:0')
+[22:59:02.345] dice before refine 0.003484320593997836 and after 0.056338027119636536, label 0: tensor(0, device='cuda:0'), label 1: tensor(21, device='cuda:0')
+[22:59:05.494] dice before refine 0.0 and after 0.450549453496933, label 0: tensor(30, device='cuda:0'), label 1: tensor(7, device='cuda:0')
+[22:59:06.018] epoch: 4/20, iter: 10/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-127/image.nii.gz',) mean dice over clicks:0.4345551255074414 stich left and right side (total size): 1
+[22:59:06.018] - Val metrics mean dice: 0.5652097064909364
+[22:59:06.867] - Val metrics best mean dice: 0.5652097064909364 at epoch 4 
+[22:59:26.809] epoch: 5/20, iter: 0/42: loss:2.393: rank:-1
+[22:59:37.915] epoch: 5/20, iter: 1/42: loss:2.2428: rank:-1
+[22:59:56.162] epoch: 5/20, iter: 2/42: loss:4.9151: rank:-1
+[23:00:16.253] epoch: 5/20, iter: 3/42: loss:1.925: rank:-1
+[23:00:26.641] epoch: 5/20, iter: 4/42: loss:3.1122: rank:-1
+[23:00:43.309] epoch: 5/20, iter: 5/42: loss:1.9817: rank:-1
+[23:01:04.066] epoch: 5/20, iter: 6/42: loss:3.1871: rank:-1
+[23:01:15.907] epoch: 5/20, iter: 7/42: loss:3.8375: rank:-1
+[23:01:35.490] epoch: 5/20, iter: 8/42: loss:1.7075: rank:-1
+[23:01:50.418] epoch: 5/20, iter: 9/42: loss:2.6663: rank:-1
+[23:02:05.985] epoch: 5/20, iter: 10/42: loss:1.8081: rank:-1
+[23:02:24.178] epoch: 5/20, iter: 11/42: loss:2.4053: rank:-1
+[23:02:39.338] epoch: 5/20, iter: 12/42: loss:2.601: rank:-1
+[23:02:58.677] epoch: 5/20, iter: 13/42: loss:1.6089: rank:-1
+[23:03:16.154] epoch: 5/20, iter: 14/42: loss:3.0675: rank:-1
+[23:03:32.309] epoch: 5/20, iter: 15/42: loss:2.0401: rank:-1
+[23:03:44.568] epoch: 5/20, iter: 16/42: loss:1.4565: rank:-1
+[23:03:55.818] epoch: 5/20, iter: 17/42: loss:3.9935: rank:-1
+[23:04:15.447] epoch: 5/20, iter: 18/42: loss:3.0909: rank:-1
+[23:04:25.420] epoch: 5/20, iter: 19/42: loss:3.5931: rank:-1
+[23:04:47.645] epoch: 5/20, iter: 20/42: loss:2.3811: rank:-1
+[23:05:08.174] epoch: 5/20, iter: 21/42: loss:1.4681: rank:-1
+[23:05:22.150] epoch: 5/20, iter: 22/42: loss:2.344: rank:-1
+[23:05:31.764] epoch: 5/20, iter: 23/42: loss:4.3031: rank:-1
+[23:05:48.139] epoch: 5/20, iter: 24/42: loss:1.8479: rank:-1
+[23:06:01.512] epoch: 5/20, iter: 25/42: loss:1.3053: rank:-1
+[23:06:17.692] epoch: 5/20, iter: 26/42: loss:3.5517: rank:-1
+[23:06:29.222] epoch: 5/20, iter: 27/42: loss:3.0525: rank:-1
+[23:06:49.816] epoch: 5/20, iter: 28/42: loss:2.6725: rank:-1
+[23:07:00.690] epoch: 5/20, iter: 29/42: loss:2.7767: rank:-1
+[23:07:10.616] epoch: 5/20, iter: 30/42: loss:2.527: rank:-1
+[23:07:19.662] epoch: 5/20, iter: 31/42: loss:2.2503: rank:-1
+[23:07:36.152] epoch: 5/20, iter: 32/42: loss:1.3422: rank:-1
+[23:07:58.437] epoch: 5/20, iter: 33/42: loss:3.2799: rank:-1
+[23:08:17.042] epoch: 5/20, iter: 34/42: loss:2.0241: rank:-1
+[23:08:37.452] epoch: 5/20, iter: 35/42: loss:4.1082: rank:-1
+[23:08:55.770] epoch: 5/20, iter: 36/42: loss:1.6889: rank:-1
+[23:09:07.893] epoch: 5/20, iter: 37/42: loss:1.8006: rank:-1
+[23:09:22.182] epoch: 5/20, iter: 38/42: loss:2.6796: rank:-1
+[23:09:38.409] epoch: 5/20, iter: 39/42: loss:3.7335: rank:-1
+[23:09:58.868] epoch: 5/20, iter: 40/42: loss:2.6827: rank:-1
+[23:10:10.912] epoch: 5/20, iter: 41/42: loss:1.4579: rank:-1
+[23:10:10.913] - Train metrics: 2.5931175
+[23:10:14.577] dice before refine 0.00019492227875161916 and after 0.5012001991271973, label 0: tensor(0, device='cuda:0'), label 1: tensor(162, device='cuda:0')
+[23:10:19.644] dice before refine 0.3154827058315277 and after 0.8735632300376892, label 0: tensor(212, device='cuda:0'), label 1: tensor(81, device='cuda:0')
+[23:10:20.105] dice before refine 0.006712254136800766 and after 0.36816471815109253, label 0: tensor(0, device='cuda:0'), label 1: tensor(413, device='cuda:0')
+[23:10:28.043] dice before refine 0.2800639271736145 and after 0.6238974928855896, label 0: tensor(426, device='cuda:0'), label 1: tensor(162, device='cuda:0')
+[23:10:28.421] dice before refine 0.014538357965648174 and after 0.03994328901171684, label 0: tensor(0, device='cuda:0'), label 1: tensor(46, device='cuda:0')
+[23:10:31.787] dice before refine 0.11360239237546921 and after 0.335201233625412, label 0: tensor(41, device='cuda:0'), label 1: tensor(9, device='cuda:0')
+[23:10:32.207] dice before refine 0.014351334422826767 and after 0.12210559099912643, label 0: tensor(0, device='cuda:0'), label 1: tensor(218, device='cuda:0')
+[23:10:38.156] dice before refine 0.4607190489768982 and after 0.8460918664932251, label 0: tensor(159, device='cuda:0'), label 1: tensor(68, device='cuda:0')
+[23:10:38.582] dice before refine 0.001035241293720901 and after 0.24728693068027496, label 0: tensor(0, device='cuda:0'), label 1: tensor(337, device='cuda:0')
+[23:10:45.781] dice before refine 0.31890955567359924 and after 0.7894070148468018, label 0: tensor(282, device='cuda:0'), label 1: tensor(123, device='cuda:0')
+[23:10:46.411] epoch: 5/20, iter: 0/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-120/image.nii.gz',) mean dice over clicks:0.5207929306409576 stich left and right side (total size): 1
+[23:10:46.948] dice before refine 0.012387851253151894 and after 0.10111485421657562, label 0: tensor(0, device='cuda:0'), label 1: tensor(148, device='cuda:0')
+[23:10:54.070] dice before refine 0.12304190546274185 and after 0.3018389940261841, label 0: tensor(510, device='cuda:0'), label 1: tensor(36, device='cuda:0')
+[23:10:54.447] dice before refine 0.07424689084291458 and after 0.18892981112003326, label 0: tensor(0, device='cuda:0'), label 1: tensor(99, device='cuda:0')
+[23:11:01.024] dice before refine 0.32176321744918823 and after 0.7891549468040466, label 0: tensor(104, device='cuda:0'), label 1: tensor(37, device='cuda:0')
+[23:11:01.422] dice before refine 0.010367555543780327 and after 0.07656821608543396, label 0: tensor(0, device='cuda:0'), label 1: tensor(91, device='cuda:0')
+[23:11:08.141] dice before refine 0.22277195751667023 and after 0.5084859728813171, label 0: tensor(540, device='cuda:0'), label 1: tensor(45, device='cuda:0')
+[23:11:08.520] dice before refine 0.07227316498756409 and after 0.2288685292005539, label 0: tensor(0, device='cuda:0'), label 1: tensor(175, device='cuda:0')
+[23:11:14.251] dice before refine 0.5882184505462646 and after 0.8379629850387573, label 0: tensor(149, device='cuda:0'), label 1: tensor(20, device='cuda:0')
+[23:11:15.492] epoch: 5/20, iter: 1/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-55/image.nii.gz',) mean dice over clicks:0.5580316199497743 stich left and right side (total size): 1
+[23:11:16.020] dice before refine 0.0003270244924351573 and after 0.2754277288913727, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:11:23.159] dice before refine 0.7301410436630249 and after 0.944639265537262, label 0: tensor(264, device='cuda:0'), label 1: tensor(137, device='cuda:0')
+[23:11:23.731] dice before refine 0.5345797538757324 and after 0.3861123323440552, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:11:33.087] dice before refine 0.8082624673843384 and after 0.9138917326927185, label 0: tensor(500, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:11:33.784] dice before refine 0.33487507700920105 and after 0.08559856563806534, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:11:42.914] dice before refine 0.5181309580802917 and after 0.45562544465065, label 0: tensor(94, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:11:43.762] dice before refine 0.38770532608032227 and after 0.11950626224279404, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:11:53.474] dice before refine 0.6048130989074707 and after 0.48827627301216125, label 0: tensor(26, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:11:53.933] dice before refine 0.1586432158946991 and after 0.3301394283771515, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:12:01.988] dice before refine 0.7743406295776367 and after 0.9435120224952698, label 0: tensor(357, device='cuda:0'), label 1: tensor(261, device='cuda:0')
+[23:12:02.585] dice before refine 0.24002790451049805 and after 0.2283528745174408, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:12:12.268] dice before refine 0.8325729370117188 and after 0.9422819018363953, label 0: tensor(502, device='cuda:0'), label 1: tensor(508, device='cuda:0')
+[23:12:13.049] dice before refine 0.5113943219184875 and after 0.16282027959823608, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:12:22.358] dice before refine 0.6117667555809021 and after 0.5156648755073547, label 0: tensor(40, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:12:23.192] dice before refine 0.3786715865135193 and after 0.09341904520988464, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:12:33.448] dice before refine 0.530225932598114 and after 0.46147459745407104, label 0: tensor(36, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:12:34.130] epoch: 5/20, iter: 2/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-100/image.nii.gz',) mean dice over clicks:0.3855675702745264 stich left and right side (total size): 1
+[23:12:34.654] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[23:12:37.546] dice before refine 0.0 and after 0.0, label 0: tensor(10, device='cuda:0'), label 1: tensor(0, device='cuda:0')
+[23:12:37.927] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[23:12:40.801] dice before refine 0.0 and after 0.0, label 0: tensor(10, device='cuda:0'), label 1: tensor(0, device='cuda:0')
+[23:12:41.188] epoch: 5/20, iter: 3/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-83/image.nii.gz',) mean dice over clicks:0.0 stich left and right side (total size): 1
+[23:12:41.648] dice before refine 0.0 and after 0.4227820336818695, label 0: tensor(0, device='cuda:0'), label 1: tensor(194, device='cuda:0')
+[23:12:45.509] dice before refine 0.05796118825674057 and after 0.36731231212615967, label 0: tensor(94, device='cuda:0'), label 1: tensor(36, device='cuda:0')
+[23:12:45.931] dice before refine 0.0 and after 0.5527812242507935, label 0: tensor(0, device='cuda:0'), label 1: tensor(498, device='cuda:0')
+[23:12:51.652] dice before refine 0.14597204327583313 and after 0.4777544140815735, label 0: tensor(231, device='cuda:0'), label 1: tensor(71, device='cuda:0')
+[23:12:52.030] dice before refine 0.0 and after 0.8037456274032593, label 0: tensor(0, device='cuda:0'), label 1: tensor(225, device='cuda:0')
+[23:12:55.786] dice before refine 0.4616161584854126 and after 0.8857239484786987, label 0: tensor(66, device='cuda:0'), label 1: tensor(36, device='cuda:0')
+[23:12:56.203] dice before refine 0.0 and after 0.6152201294898987, label 0: tensor(0, device='cuda:0'), label 1: tensor(526, device='cuda:0')
+[23:13:02.159] dice before refine 0.5743051171302795 and after 0.8957602977752686, label 0: tensor(267, device='cuda:0'), label 1: tensor(61, device='cuda:0')
+[23:13:02.544] dice before refine 0.0 and after 0.5444589257240295, label 0: tensor(0, device='cuda:0'), label 1: tensor(179, device='cuda:0')
+[23:13:06.873] dice before refine 0.6828709244728088 and after 0.8856061697006226, label 0: tensor(136, device='cuda:0'), label 1: tensor(48, device='cuda:0')
+[23:13:07.305] dice before refine 0.4969111382961273 and after 0.6570879817008972, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:13:14.531] dice before refine 0.7450127005577087 and after 0.8700193166732788, label 0: tensor(304, device='cuda:0'), label 1: tensor(94, device='cuda:0')
+[23:13:14.916] dice before refine 0.0 and after 0.346850723028183, label 0: tensor(0, device='cuda:0'), label 1: tensor(216, device='cuda:0')
+[23:13:19.132] dice before refine 0.7007364630699158 and after 0.8872647285461426, label 0: tensor(118, device='cuda:0'), label 1: tensor(44, device='cuda:0')
+[23:13:19.556] dice before refine 0.39072147011756897 and after 0.5598410964012146, label 0: tensor(0, device='cuda:0'), label 1: tensor(528, device='cuda:0')
+[23:13:26.096] dice before refine 0.8368059396743774 and after 0.9141128063201904, label 0: tensor(221, device='cuda:0'), label 1: tensor(81, device='cuda:0')
+[23:13:26.781] epoch: 5/20, iter: 4/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-2/image.nii.gz',) mean dice over clicks:0.6085449619726702 stich left and right side (total size): 1
+[23:13:27.286] dice before refine 0.0 and after 0.32078009843826294, label 0: tensor(0, device='cuda:0'), label 1: tensor(143, device='cuda:0')
+[23:13:31.122] dice before refine 0.0856672152876854 and after 0.7974904179573059, label 0: tensor(72, device='cuda:0'), label 1: tensor(31, device='cuda:0')
+[23:13:31.545] dice before refine 0.006312916055321693 and after 0.3888758718967438, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:13:38.887] dice before refine 0.4490358233451843 and after 0.8472574949264526, label 0: tensor(280, device='cuda:0'), label 1: tensor(81, device='cuda:0')
+[23:13:39.347] dice before refine 0.0 and after 0.3701777160167694, label 0: tensor(0, device='cuda:0'), label 1: tensor(140, device='cuda:0')
+[23:13:43.285] dice before refine 0.0038784744683653116 and after 0.8245020508766174, label 0: tensor(50, device='cuda:0'), label 1: tensor(23, device='cuda:0')
+[23:13:43.769] dice before refine 0.6211885213851929 and after 0.48908016085624695, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:13:53.564] dice before refine 0.8066784143447876 and after 0.9048429727554321, label 0: tensor(510, device='cuda:0'), label 1: tensor(162, device='cuda:0')
+[23:13:54.509] epoch: 5/20, iter: 5/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-52/image.nii.gz',) mean dice over clicks:0.8144636262546886 stich left and right side (total size): 1
+[23:13:54.932] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(43, device='cuda:0')
+[23:13:58.199] dice before refine 0.0 and after 0.844878077507019, label 0: tensor(34, device='cuda:0'), label 1: tensor(16, device='cuda:0')
+[23:13:58.562] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(40, device='cuda:0')
+[23:14:01.906] dice before refine 0.0 and after 0.8287606239318848, label 0: tensor(36, device='cuda:0'), label 1: tensor(15, device='cuda:0')
+[23:14:02.290] dice before refine 0.0 and after 0.04274425283074379, label 0: tensor(0, device='cuda:0'), label 1: tensor(118, device='cuda:0')
+[23:14:06.804] dice before refine 0.0 and after 0.04159676283597946, label 0: tensor(99, device='cuda:0'), label 1: tensor(28, device='cuda:0')
+[23:14:07.180] dice before refine 0.0 and after 0.36961451172828674, label 0: tensor(0, device='cuda:0'), label 1: tensor(139, device='cuda:0')
+[23:14:11.341] dice before refine 0.0 and after 0.823699414730072, label 0: tensor(88, device='cuda:0'), label 1: tensor(27, device='cuda:0')
+[23:14:11.712] dice before refine 0.0 and after 0.5927342176437378, label 0: tensor(0, device='cuda:0'), label 1: tensor(148, device='cuda:0')
+[23:14:15.325] dice before refine 0.0 and after 0.8771929740905762, label 0: tensor(59, device='cuda:0'), label 1: tensor(24, device='cuda:0')
+[23:14:15.704] dice before refine 0.0 and after 0.4486458897590637, label 0: tensor(0, device='cuda:0'), label 1: tensor(159, device='cuda:0')
+[23:14:19.553] dice before refine 0.0 and after 0.8338368535041809, label 0: tensor(71, device='cuda:0'), label 1: tensor(30, device='cuda:0')
+[23:14:19.927] dice before refine 0.0003779146645683795 and after 0.005326002836227417, label 0: tensor(0, device='cuda:0'), label 1: tensor(123, device='cuda:0')
+[23:14:25.718] dice before refine 0.03779486566781998 and after 0.7444335222244263, label 0: tensor(275, device='cuda:0'), label 1: tensor(39, device='cuda:0')
+[23:14:26.096] dice before refine 0.0 and after 0.04878048598766327, label 0: tensor(0, device='cuda:0'), label 1: tensor(117, device='cuda:0')
+[23:14:30.545] dice before refine 0.009852216579020023 and after 0.8135955333709717, label 0: tensor(99, device='cuda:0'), label 1: tensor(50, device='cuda:0')
+[23:14:31.226] epoch: 5/20, iter: 6/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-121/image.nii.gz',) mean dice over clicks:0.08842315982011231 stich left and right side (total size): 1
+[23:14:31.715] dice before refine 0.01623014733195305 and after 0.5345309376716614, label 0: tensor(0, device='cuda:0'), label 1: tensor(542, device='cuda:0')
+[23:14:39.381] dice before refine 0.3981047570705414 and after 0.7462735772132874, label 0: tensor(455, device='cuda:0'), label 1: tensor(90, device='cuda:0')
+[23:14:39.807] dice before refine 0.04942942410707474 and after 0.47088518738746643, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:14:47.497] dice before refine 0.44549813866615295 and after 0.8253519535064697, label 0: tensor(479, device='cuda:0'), label 1: tensor(88, device='cuda:0')
+[23:14:47.920] dice before refine 0.005572931375354528 and after 0.5119848251342773, label 0: tensor(0, device='cuda:0'), label 1: tensor(404, device='cuda:0')
+[23:14:54.607] dice before refine 0.47651809453964233 and after 0.8643388152122498, label 0: tensor(364, device='cuda:0'), label 1: tensor(110, device='cuda:0')
+[23:14:55.031] dice before refine 0.007570198271423578 and after 0.5254745483398438, label 0: tensor(0, device='cuda:0'), label 1: tensor(340, device='cuda:0')
+[23:15:02.054] dice before refine 0.42888107895851135 and after 0.8716623783111572, label 0: tensor(326, device='cuda:0'), label 1: tensor(96, device='cuda:0')
+[23:15:02.617] dice before refine 0.5613867044448853 and after 0.4133002758026123, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:15:13.600] dice before refine 0.6643506288528442 and after 0.8499692678451538, label 0: tensor(510, device='cuda:0'), label 1: tensor(314, device='cuda:0')
+[23:15:14.132] dice before refine 0.49194613099098206 and after 0.39112600684165955, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:15:25.215] dice before refine 0.6730049252510071 and after 0.8391973972320557, label 0: tensor(510, device='cuda:0'), label 1: tensor(268, device='cuda:0')
+[23:15:25.737] dice before refine 0.2754332721233368 and after 0.2807283401489258, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:15:36.793] dice before refine 0.5463424324989319 and after 0.7158757448196411, label 0: tensor(510, device='cuda:0'), label 1: tensor(169, device='cuda:0')
+[23:15:37.316] dice before refine 0.21851873397827148 and after 0.29584866762161255, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:15:47.770] dice before refine 0.6691932678222656 and after 0.841548502445221, label 0: tensor(510, device='cuda:0'), label 1: tensor(190, device='cuda:0')
+[23:15:48.348] epoch: 5/20, iter: 7/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-113/image.nii.gz',) mean dice over clicks:0.6981083615259691 stich left and right side (total size): 1
+[23:15:48.857] dice before refine 0.6736818552017212 and after 0.7096238732337952, label 0: tensor(0, device='cuda:0'), label 1: tensor(150, device='cuda:0')
+[23:15:53.336] dice before refine 0.821198046207428 and after 0.9071546196937561, label 0: tensor(110, device='cuda:0'), label 1: tensor(47, device='cuda:0')
+[23:15:53.729] dice before refine 0.8038946986198425 and after 0.8240556716918945, label 0: tensor(0, device='cuda:0'), label 1: tensor(129, device='cuda:0')
+[23:15:58.248] dice before refine 0.7808570861816406 and after 0.898876428604126, label 0: tensor(125, device='cuda:0'), label 1: tensor(48, device='cuda:0')
+[23:15:58.630] dice before refine 0.5379094481468201 and after 0.5280132293701172, label 0: tensor(0, device='cuda:0'), label 1: tensor(159, device='cuda:0')
+[23:16:03.033] dice before refine 0.7912145853042603 and after 0.9032065868377686, label 0: tensor(154, device='cuda:0'), label 1: tensor(49, device='cuda:0')
+[23:16:03.420] dice before refine 0.8060008883476257 and after 0.738231897354126, label 0: tensor(0, device='cuda:0'), label 1: tensor(176, device='cuda:0')
+[23:16:07.894] dice before refine 0.7719529867172241 and after 0.8910630941390991, label 0: tensor(114, device='cuda:0'), label 1: tensor(59, device='cuda:0')
+[23:16:08.324] epoch: 5/20, iter: 8/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-81/image.nii.gz',) mean dice over clicks:0.8666615648703142 stich left and right side (total size): 1
+[23:16:08.857] dice before refine 0.0 and after 0.232162207365036, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:16:18.140] dice before refine 0.538459300994873 and after 0.8746965527534485, label 0: tensor(508, device='cuda:0'), label 1: tensor(129, device='cuda:0')
+[23:16:18.643] dice before refine 0.0 and after 0.12525242567062378, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:16:28.758] dice before refine 0.6115233898162842 and after 0.892443835735321, label 0: tensor(510, device='cuda:0'), label 1: tensor(229, device='cuda:0')
+[23:16:29.220] dice before refine 0.5311179161071777 and after 0.5896535515785217, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:16:37.756] dice before refine 0.7874723076820374 and after 0.9194692373275757, label 0: tensor(510, device='cuda:0'), label 1: tensor(122, device='cuda:0')
+[23:16:38.233] dice before refine 0.6452817320823669 and after 0.6745743751525879, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:16:47.152] dice before refine 0.7817838788032532 and after 0.9085165858268738, label 0: tensor(510, device='cuda:0'), label 1: tensor(96, device='cuda:0')
+[23:16:47.732] dice before refine 0.5402132868766785 and after 0.48014625906944275, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:16:58.676] dice before refine 0.763927161693573 and after 0.8780884146690369, label 0: tensor(502, device='cuda:0'), label 1: tensor(508, device='cuda:0')
+[23:16:59.288] dice before refine 0.541120171546936 and after 0.4507501721382141, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:17:10.332] dice before refine 0.7570347785949707 and after 0.8652467131614685, label 0: tensor(503, device='cuda:0'), label 1: tensor(507, device='cuda:0')
+[23:17:10.778] dice before refine 0.18886753916740417 and after 0.29307833313941956, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:17:19.417] dice before refine 0.39314839243888855 and after 0.5833039879798889, label 0: tensor(510, device='cuda:0'), label 1: tensor(110, device='cuda:0')
+[23:17:19.846] dice before refine 0.1832834780216217 and after 0.3821084797382355, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:17:27.372] dice before refine 0.6499282717704773 and after 0.884669303894043, label 0: tensor(516, device='cuda:0'), label 1: tensor(96, device='cuda:0')
+[23:17:27.859] epoch: 5/20, iter: 9/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-90/image.nii.gz',) mean dice over clicks:0.7472195273095911 stich left and right side (total size): 1
+[23:17:28.378] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(20, device='cuda:0')
+[23:17:31.373] dice before refine 0.0 and after 0.006611062213778496, label 0: tensor(19, device='cuda:0'), label 1: tensor(42, device='cuda:0')
+[23:17:31.722] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(23, device='cuda:0')
+[23:17:34.728] dice before refine 0.0 and after 0.519298255443573, label 0: tensor(43, device='cuda:0'), label 1: tensor(5, device='cuda:0')
+[23:17:35.241] epoch: 5/20, iter: 10/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-127/image.nii.gz',) mean dice over clicks:0.3972210477698933 stich left and right side (total size): 1
+[23:17:35.241] - Val metrics mean dice: 0.5168213063989543
+[23:17:35.833] - Val metrics best mean dice: 0.5652097064909364 at epoch 4 
+[23:18:05.595] epoch: 6/20, iter: 0/42: loss:2.5203: rank:-1
+[23:18:29.963] epoch: 6/20, iter: 1/42: loss:2.2863: rank:-1
+[23:18:50.439] epoch: 6/20, iter: 2/42: loss:4.815: rank:-1
+[23:19:07.737] epoch: 6/20, iter: 3/42: loss:1.4862: rank:-1
+[23:19:26.005] epoch: 6/20, iter: 4/42: loss:2.6548: rank:-1
+[23:19:45.469] epoch: 6/20, iter: 5/42: loss:1.7495: rank:-1
+[23:19:56.950] epoch: 6/20, iter: 6/42: loss:4.1189: rank:-1
+[23:20:11.472] epoch: 6/20, iter: 7/42: loss:2.9261: rank:-1
+[23:20:31.366] epoch: 6/20, iter: 8/42: loss:1.9237: rank:-1
+[23:20:53.967] epoch: 6/20, iter: 9/42: loss:1.7799: rank:-1
+[23:21:16.328] epoch: 6/20, iter: 10/42: loss:2.3469: rank:-1
+[23:21:29.262] epoch: 6/20, iter: 11/42: loss:3.098: rank:-1
+[23:21:48.634] epoch: 6/20, iter: 12/42: loss:2.5778: rank:-1
+[23:21:58.171] epoch: 6/20, iter: 13/42: loss:4.0354: rank:-1
+[23:22:16.187] epoch: 6/20, iter: 14/42: loss:3.0095: rank:-1
+[23:22:40.815] epoch: 6/20, iter: 15/42: loss:2.802: rank:-1
+[23:22:57.010] epoch: 6/20, iter: 16/42: loss:3.0979: rank:-1
+[23:23:11.854] epoch: 6/20, iter: 17/42: loss:1.8857: rank:-1
+[23:23:23.411] epoch: 6/20, iter: 18/42: loss:3.2246: rank:-1
+[23:23:33.974] epoch: 6/20, iter: 19/42: loss:3.2133: rank:-1
+[23:23:47.605] epoch: 6/20, iter: 20/42: loss:1.3166: rank:-1
+[23:24:07.170] epoch: 6/20, iter: 21/42: loss:1.5412: rank:-1
+[23:24:23.091] epoch: 6/20, iter: 22/42: loss:2.872: rank:-1
+[23:24:35.219] epoch: 6/20, iter: 23/42: loss:3.2445: rank:-1
+[23:24:45.244] epoch: 6/20, iter: 24/42: loss:3.2979: rank:-1
+[23:24:57.778] epoch: 6/20, iter: 25/42: loss:2.4248: rank:-1
+[23:25:08.176] epoch: 6/20, iter: 26/42: loss:1.9496: rank:-1
+[23:25:24.861] epoch: 6/20, iter: 27/42: loss:1.701: rank:-1
+[23:25:43.023] epoch: 6/20, iter: 28/42: loss:1.6302: rank:-1
+[23:26:02.917] epoch: 6/20, iter: 29/42: loss:1.3841: rank:-1
+[23:26:17.864] epoch: 6/20, iter: 30/42: loss:4.8785: rank:-1
+[23:26:31.118] epoch: 6/20, iter: 31/42: loss:1.6947: rank:-1
+[23:26:42.065] epoch: 6/20, iter: 32/42: loss:1.9282: rank:-1
+[23:26:53.049] epoch: 6/20, iter: 33/42: loss:2.7476: rank:-1
+[23:27:10.238] epoch: 6/20, iter: 34/42: loss:1.4296: rank:-1
+[23:27:28.987] epoch: 6/20, iter: 35/42: loss:1.6649: rank:-1
+[23:27:49.031] epoch: 6/20, iter: 36/42: loss:1.6567: rank:-1
+[23:28:01.237] epoch: 6/20, iter: 37/42: loss:1.6536: rank:-1
+[23:28:11.382] epoch: 6/20, iter: 38/42: loss:2.6087: rank:-1
+[23:28:31.198] epoch: 6/20, iter: 39/42: loss:1.4839: rank:-1
+[23:28:50.244] epoch: 6/20, iter: 40/42: loss:1.7981: rank:-1
+[23:28:55.489] epoch: 6/20, iter: 41/42: loss:1.4183: rank:-1
+[23:28:55.490] - Train metrics: 2.4256337
+[23:28:59.254] dice before refine 0.0 and after 0.7023195624351501, label 0: tensor(0, device='cuda:0'), label 1: tensor(183, device='cuda:0')
+[23:29:04.598] dice before refine 0.20547401905059814 and after 0.8824971914291382, label 0: tensor(154, device='cuda:0'), label 1: tensor(73, device='cuda:0')
+[23:29:05.044] dice before refine 0.005217164289206266 and after 0.6374923586845398, label 0: tensor(0, device='cuda:0'), label 1: tensor(385, device='cuda:0')
+[23:29:12.679] dice before refine 0.517228901386261 and after 0.8690697550773621, label 0: tensor(251, device='cuda:0'), label 1: tensor(137, device='cuda:0')
+[23:29:13.046] dice before refine 0.03689449280500412 and after 0.26671943068504333, label 0: tensor(0, device='cuda:0'), label 1: tensor(47, device='cuda:0')
+[23:29:16.426] dice before refine 0.7504078149795532 and after 0.8811749219894409, label 0: tensor(63, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[23:29:16.847] dice before refine 0.036761440336704254 and after 0.4323313236236572, label 0: tensor(0, device='cuda:0'), label 1: tensor(217, device='cuda:0')
+[23:29:22.175] dice before refine 0.5683581829071045 and after 0.8559481501579285, label 0: tensor(152, device='cuda:0'), label 1: tensor(81, device='cuda:0')
+[23:29:22.597] dice before refine 0.02557544782757759 and after 0.6538415551185608, label 0: tensor(0, device='cuda:0'), label 1: tensor(301, device='cuda:0')
+[23:29:28.949] dice before refine 0.5311284065246582 and after 0.8664733171463013, label 0: tensor(288, device='cuda:0'), label 1: tensor(135, device='cuda:0')
+[23:29:29.475] epoch: 6/20, iter: 0/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-120/image.nii.gz',) mean dice over clicks:0.8123877752910961 stich left and right side (total size): 1
+[23:29:29.997] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(117, device='cuda:0')
+[23:29:34.630] dice before refine 0.0 and after 0.8952728509902954, label 0: tensor(165, device='cuda:0'), label 1: tensor(56, device='cuda:0')
+[23:29:35.004] dice before refine 0.06981561332941055 and after 0.32457858324050903, label 0: tensor(0, device='cuda:0'), label 1: tensor(133, device='cuda:0')
+[23:29:40.169] dice before refine 0.16776315867900848 and after 0.8920035362243652, label 0: tensor(100, device='cuda:0'), label 1: tensor(38, device='cuda:0')
+[23:29:40.563] dice before refine 0.0 and after 0.05820853263139725, label 0: tensor(0, device='cuda:0'), label 1: tensor(118, device='cuda:0')
+[23:29:45.315] dice before refine 0.0 and after 0.900136411190033, label 0: tensor(136, device='cuda:0'), label 1: tensor(37, device='cuda:0')
+[23:29:45.687] dice before refine 0.05947849154472351 and after 0.28011709451675415, label 0: tensor(0, device='cuda:0'), label 1: tensor(114, device='cuda:0')
+[23:29:50.506] dice before refine 0.3906327784061432 and after 0.9080920815467834, label 0: tensor(114, device='cuda:0'), label 1: tensor(51, device='cuda:0')
+[23:29:51.814] epoch: 6/20, iter: 1/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-55/image.nii.gz',) mean dice over clicks:0.8070553649555553 stich left and right side (total size): 1
+[23:29:52.344] dice before refine 0.0 and after 0.23718713223934174, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:29:59.971] dice before refine 0.6421627998352051 and after 0.9400132894515991, label 0: tensor(194, device='cuda:0'), label 1: tensor(129, device='cuda:0')
+[23:30:00.536] dice before refine 0.39632391929626465 and after 0.2023351788520813, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:30:09.660] dice before refine 0.7374244928359985 and after 0.8597431182861328, label 0: tensor(465, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:30:10.340] dice before refine 0.11468375474214554 and after 0.09175398200750351, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:30:18.669] dice before refine 0.5313097238540649 and after 0.6683768630027771, label 0: tensor(64, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:30:19.514] dice before refine 0.22945158183574677 and after 0.06343633681535721, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:30:29.772] dice before refine 0.4300764501094818 and after 0.41056105494499207, label 0: tensor(107, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:30:30.228] dice before refine 0.10694866627454758 and after 0.2249240130186081, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:30:38.871] dice before refine 0.727120041847229 and after 0.9321016669273376, label 0: tensor(392, device='cuda:0'), label 1: tensor(196, device='cuda:0')
+[23:30:39.452] dice before refine 0.16060085594654083 and after 0.09079024940729141, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:30:48.509] dice before refine 0.8141247034072876 and after 0.8506736159324646, label 0: tensor(406, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:30:49.282] dice before refine 0.3794203996658325 and after 0.1292005181312561, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:30:59.872] dice before refine 0.4205636978149414 and after 0.4297387897968292, label 0: tensor(115, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:31:00.702] dice before refine 0.23272961378097534 and after 0.05012864992022514, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:31:11.582] dice before refine 0.34846240282058716 and after 0.3085865080356598, label 0: tensor(95, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:31:12.293] epoch: 6/20, iter: 2/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-100/image.nii.gz',) mean dice over clicks:0.30866698040203616 stich left and right side (total size): 1
+[23:31:12.811] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[23:31:15.728] dice before refine 0.0 and after 0.0, label 0: tensor(14, device='cuda:0'), label 1: tensor(16, device='cuda:0')
+[23:31:16.108] dice before refine 0.0 and after 0.0, label 0: tensor(0, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[23:31:19.024] dice before refine 0.0 and after 0.37037035822868347, label 0: tensor(3, device='cuda:0'), label 1: tensor(16, device='cuda:0')
+[23:31:19.418] epoch: 6/20, iter: 3/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-83/image.nii.gz',) mean dice over clicks:0.17379571226510135 stich left and right side (total size): 1
+[23:31:19.881] dice before refine 0.0 and after 0.600375235080719, label 0: tensor(0, device='cuda:0'), label 1: tensor(142, device='cuda:0')
+[23:31:23.788] dice before refine 0.2848447859287262 and after 0.8601855039596558, label 0: tensor(92, device='cuda:0'), label 1: tensor(34, device='cuda:0')
+[23:31:24.210] dice before refine 0.0 and after 0.8097983002662659, label 0: tensor(0, device='cuda:0'), label 1: tensor(519, device='cuda:0')
+[23:31:29.708] dice before refine 0.5132450461387634 and after 0.9081069231033325, label 0: tensor(117, device='cuda:0'), label 1: tensor(77, device='cuda:0')
+[23:31:30.082] dice before refine 0.0 and after 0.7585681676864624, label 0: tensor(0, device='cuda:0'), label 1: tensor(173, device='cuda:0')
+[23:31:33.870] dice before refine 0.2769981622695923 and after 0.8741722106933594, label 0: tensor(76, device='cuda:0'), label 1: tensor(43, device='cuda:0')
+[23:31:34.287] dice before refine 0.0 and after 0.7284697890281677, label 0: tensor(0, device='cuda:0'), label 1: tensor(530, device='cuda:0')
+[23:31:39.979] dice before refine 0.5743444561958313 and after 0.8975609540939331, label 0: tensor(219, device='cuda:0'), label 1: tensor(79, device='cuda:0')
+[23:31:40.364] dice before refine 0.0 and after 0.6632105708122253, label 0: tensor(0, device='cuda:0'), label 1: tensor(326, device='cuda:0')
+[23:31:44.907] dice before refine 0.6452915668487549 and after 0.8684993982315063, label 0: tensor(115, device='cuda:0'), label 1: tensor(31, device='cuda:0')
+[23:31:45.339] dice before refine 0.4499092698097229 and after 0.6915497779846191, label 0: tensor(0, device='cuda:0'), label 1: tensor(508, device='cuda:0')
+[23:31:51.800] dice before refine 0.838551938533783 and after 0.9230939745903015, label 0: tensor(263, device='cuda:0'), label 1: tensor(96, device='cuda:0')
+[23:31:52.193] dice before refine 0.0 and after 0.7349497079849243, label 0: tensor(0, device='cuda:0'), label 1: tensor(428, device='cuda:0')
+[23:31:56.590] dice before refine 0.7051137685775757 and after 0.8703573942184448, label 0: tensor(114, device='cuda:0'), label 1: tensor(55, device='cuda:0')
+[23:31:57.015] dice before refine 0.49020469188690186 and after 0.6201410889625549, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:32:03.729] dice before refine 0.8584835529327393 and after 0.9185994863510132, label 0: tensor(274, device='cuda:0'), label 1: tensor(101, device='cuda:0')
+[23:32:04.473] epoch: 6/20, iter: 4/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-2/image.nii.gz',) mean dice over clicks:0.8687470609491522 stich left and right side (total size): 1
+[23:32:04.977] dice before refine 0.0 and after 0.6018783450126648, label 0: tensor(0, device='cuda:0'), label 1: tensor(132, device='cuda:0')
+[23:32:08.591] dice before refine 0.0 and after 0.8489919900894165, label 0: tensor(102, device='cuda:0'), label 1: tensor(19, device='cuda:0')
+[23:32:09.013] dice before refine 0.0 and after 0.714106023311615, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:32:16.091] dice before refine 0.48288974165916443 and after 0.8517851233482361, label 0: tensor(355, device='cuda:0'), label 1: tensor(62, device='cuda:0')
+[23:32:16.539] dice before refine 0.0 and after 0.4883720874786377, label 0: tensor(0, device='cuda:0'), label 1: tensor(100, device='cuda:0')
+[23:32:20.165] dice before refine 0.0 and after 0.8461819291114807, label 0: tensor(59, device='cuda:0'), label 1: tensor(30, device='cuda:0')
+[23:32:20.646] dice before refine 0.6416371464729309 and after 0.6184749007225037, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:32:29.472] dice before refine 0.7603178024291992 and after 0.9116299152374268, label 0: tensor(510, device='cuda:0'), label 1: tensor(130, device='cuda:0')
+[23:32:30.390] epoch: 6/20, iter: 5/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-52/image.nii.gz',) mean dice over clicks:0.8557750907811251 stich left and right side (total size): 1
+[23:32:30.817] dice before refine 0.0 and after 0.44078946113586426, label 0: tensor(0, device='cuda:0'), label 1: tensor(51, device='cuda:0')
+[23:32:34.202] dice before refine 0.0 and after 0.8257426023483276, label 0: tensor(50, device='cuda:0'), label 1: tensor(17, device='cuda:0')
+[23:32:34.571] dice before refine 0.0 and after 0.19708029925823212, label 0: tensor(0, device='cuda:0'), label 1: tensor(40, device='cuda:0')
+[23:32:37.950] dice before refine 0.0 and after 0.821328341960907, label 0: tensor(50, device='cuda:0'), label 1: tensor(15, device='cuda:0')
+[23:32:38.327] dice before refine 0.0 and after 0.6080971956253052, label 0: tensor(0, device='cuda:0'), label 1: tensor(126, device='cuda:0')
+[23:32:42.283] dice before refine 0.0 and after 0.8706004023551941, label 0: tensor(85, device='cuda:0'), label 1: tensor(33, device='cuda:0')
+[23:32:42.660] dice before refine 0.0 and after 0.7435123920440674, label 0: tensor(0, device='cuda:0'), label 1: tensor(112, device='cuda:0')
+[23:32:46.586] dice before refine 0.0 and after 0.8483647108078003, label 0: tensor(117, device='cuda:0'), label 1: tensor(32, device='cuda:0')
+[23:32:46.956] dice before refine 0.0 and after 0.6552147269248962, label 0: tensor(0, device='cuda:0'), label 1: tensor(98, device='cuda:0')
+[23:32:50.743] dice before refine 0.0 and after 0.8619102239608765, label 0: tensor(63, device='cuda:0'), label 1: tensor(36, device='cuda:0')
+[23:32:51.121] dice before refine 0.0 and after 0.7563372850418091, label 0: tensor(0, device='cuda:0'), label 1: tensor(135, device='cuda:0')
+[23:32:55.070] dice before refine 0.0 and after 0.8386433720588684, label 0: tensor(51, device='cuda:0'), label 1: tensor(44, device='cuda:0')
+[23:32:55.448] dice before refine 0.0 and after 0.2758890986442566, label 0: tensor(0, device='cuda:0'), label 1: tensor(121, device='cuda:0')
+[23:33:01.144] dice before refine 0.0030581040773540735 and after 0.8702502250671387, label 0: tensor(123, device='cuda:0'), label 1: tensor(23, device='cuda:0')
+[23:33:01.535] dice before refine 0.0 and after 0.7190375328063965, label 0: tensor(0, device='cuda:0'), label 1: tensor(155, device='cuda:0')
+[23:33:06.102] dice before refine 0.0015781167894601822 and after 0.8685612678527832, label 0: tensor(179, device='cuda:0'), label 1: tensor(32, device='cuda:0')
+[23:33:06.775] epoch: 6/20, iter: 6/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-121/image.nii.gz',) mean dice over clicks:0.6922954348000613 stich left and right side (total size): 1
+[23:33:07.261] dice before refine 0.0 and after 0.6770908236503601, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:33:14.511] dice before refine 0.3676094710826874 and after 0.8743565082550049, label 0: tensor(346, device='cuda:0'), label 1: tensor(106, device='cuda:0')
+[23:33:14.946] dice before refine 0.00016326530021615326 and after 0.6709035038948059, label 0: tensor(0, device='cuda:0'), label 1: tensor(492, device='cuda:0')
+[23:33:22.224] dice before refine 0.43440285325050354 and after 0.8933351039886475, label 0: tensor(339, device='cuda:0'), label 1: tensor(114, device='cuda:0')
+[23:33:22.644] dice before refine 0.0024639645125716925 and after 0.5369448661804199, label 0: tensor(0, device='cuda:0'), label 1: tensor(343, device='cuda:0')
+[23:33:29.560] dice before refine 0.3656862676143646 and after 0.8661448955535889, label 0: tensor(231, device='cuda:0'), label 1: tensor(101, device='cuda:0')
+[23:33:29.988] dice before refine 0.0 and after 0.5547902584075928, label 0: tensor(0, device='cuda:0'), label 1: tensor(453, device='cuda:0')
+[23:33:37.060] dice before refine 0.3817089796066284 and after 0.8697621822357178, label 0: tensor(324, device='cuda:0'), label 1: tensor(117, device='cuda:0')
+[23:33:37.598] dice before refine 0.43121469020843506 and after 0.33703938126564026, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:33:48.555] dice before refine 0.6350753903388977 and after 0.8416408896446228, label 0: tensor(506, device='cuda:0'), label 1: tensor(504, device='cuda:0')
+[23:33:49.087] dice before refine 0.33133476972579956 and after 0.35652831196784973, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:33:59.730] dice before refine 0.6676807999610901 and after 0.8559686541557312, label 0: tensor(508, device='cuda:0'), label 1: tensor(502, device='cuda:0')
+[23:34:00.252] dice before refine 0.16251030564308167 and after 0.3652637004852295, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:34:10.992] dice before refine 0.6492740511894226 and after 0.8656890392303467, label 0: tensor(509, device='cuda:0'), label 1: tensor(273, device='cuda:0')
+[23:34:11.514] dice before refine 0.16161857545375824 and after 0.36286646127700806, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:34:22.100] dice before refine 0.6451520919799805 and after 0.8600566983222961, label 0: tensor(510, device='cuda:0'), label 1: tensor(273, device='cuda:0')
+[23:34:22.706] epoch: 6/20, iter: 7/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-113/image.nii.gz',) mean dice over clicks:0.702048355882818 stich left and right side (total size): 1
+[23:34:23.217] dice before refine 0.8006832003593445 and after 0.7167272567749023, label 0: tensor(0, device='cuda:0'), label 1: tensor(150, device='cuda:0')
+[23:34:27.813] dice before refine 0.8137419819831848 and after 0.9054550528526306, label 0: tensor(139, device='cuda:0'), label 1: tensor(46, device='cuda:0')
+[23:34:28.192] dice before refine 0.8061880469322205 and after 0.7158779501914978, label 0: tensor(0, device='cuda:0'), label 1: tensor(137, device='cuda:0')
+[23:34:32.745] dice before refine 0.807012140750885 and after 0.9050922393798828, label 0: tensor(116, device='cuda:0'), label 1: tensor(50, device='cuda:0')
+[23:34:33.123] dice before refine 0.7235087752342224 and after 0.6280648708343506, label 0: tensor(0, device='cuda:0'), label 1: tensor(142, device='cuda:0')
+[23:34:38.154] dice before refine 0.8319389224052429 and after 0.9046629071235657, label 0: tensor(162, device='cuda:0'), label 1: tensor(59, device='cuda:0')
+[23:34:38.533] dice before refine 0.6922461986541748 and after 0.5520104765892029, label 0: tensor(0, device='cuda:0'), label 1: tensor(110, device='cuda:0')
+[23:34:43.224] dice before refine 0.8273118734359741 and after 0.8765555620193481, label 0: tensor(178, device='cuda:0'), label 1: tensor(39, device='cuda:0')
+[23:34:43.676] epoch: 6/20, iter: 8/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-81/image.nii.gz',) mean dice over clicks:0.8409092426300049 stich left and right side (total size): 1
+[23:34:44.212] dice before refine 0.0 and after 0.0923004224896431, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:34:53.021] dice before refine 0.4529256522655487 and after 0.9097163677215576, label 0: tensor(445, device='cuda:0'), label 1: tensor(287, device='cuda:0')
+[23:34:53.528] dice before refine 0.0 and after 0.04199540987610817, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:35:02.357] dice before refine 0.5211910009384155 and after 0.9046224355697632, label 0: tensor(416, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:35:02.820] dice before refine 0.6953917145729065 and after 0.6130803823471069, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:35:11.735] dice before refine 0.8154881596565247 and after 0.9440842866897583, label 0: tensor(378, device='cuda:0'), label 1: tensor(133, device='cuda:0')
+[23:35:12.214] dice before refine 0.7219282984733582 and after 0.6748161315917969, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:35:21.602] dice before refine 0.7976645827293396 and after 0.9350706934928894, label 0: tensor(506, device='cuda:0'), label 1: tensor(153, device='cuda:0')
+[23:35:22.180] dice before refine 0.43966731429100037 and after 0.3049219846725464, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:35:32.947] dice before refine 0.6723085045814514 and after 0.80076664686203, label 0: tensor(501, device='cuda:0'), label 1: tensor(509, device='cuda:0')
+[23:35:33.570] dice before refine 0.44417765736579895 and after 0.2600666284561157, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:35:44.120] dice before refine 0.6482936143875122 and after 0.741105854511261, label 0: tensor(441, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:35:44.575] dice before refine 0.296221524477005 and after 0.48155179619789124, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:35:52.857] dice before refine 0.6536476016044617 and after 0.8924158811569214, label 0: tensor(555, device='cuda:0'), label 1: tensor(117, device='cuda:0')
+[23:35:53.285] dice before refine 0.07422802597284317 and after 0.4019607901573181, label 0: tensor(0, device='cuda:0'), label 1: tensor(510, device='cuda:0')
+[23:36:01.074] dice before refine 0.6644598245620728 and after 0.8929039835929871, label 0: tensor(444, device='cuda:0'), label 1: tensor(88, device='cuda:0')
+[23:36:01.594] epoch: 6/20, iter: 9/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-90/image.nii.gz',) mean dice over clicks:0.6719500422477722 stich left and right side (total size): 1
+[23:36:02.120] dice before refine 0.0 and after 0.012129860930144787, label 0: tensor(0, device='cuda:0'), label 1: tensor(15, device='cuda:0')
+[23:36:05.182] dice before refine 0.0 and after 0.04652378335595131, label 0: tensor(28, device='cuda:0'), label 1: tensor(4, device='cuda:0')
+[23:36:05.534] dice before refine 0.0 and after 0.1949685513973236, label 0: tensor(0, device='cuda:0'), label 1: tensor(21, device='cuda:0')
+[23:36:08.666] dice before refine 0.0 and after 0.5864661931991577, label 0: tensor(31, device='cuda:0'), label 1: tensor(10, device='cuda:0')
+[23:36:09.165] epoch: 6/20, iter: 10/11 subject: ('/teamspace/studios/this_studio/lits/Task01_LITS17/Training/volume-127/image.nii.gz',) mean dice over clicks:0.4685451496731151 stich left and right side (total size): 1
+[23:36:09.166] - Val metrics mean dice: 0.6547432918070762
+[23:36:10.015] - Val metrics best mean dice: 0.6547432918070762 at epoch 6 
+[23:36:32.107] epoch: 7/20, iter: 0/42: loss:2.8316: rank:-1
+[23:36:51.683] epoch: 7/20, iter: 1/42: loss:4.3542: rank:-1
+[23:37:03.338] epoch: 7/20, iter: 2/42: loss:1.1805: rank:-1
+[23:37:15.794] epoch: 7/20, iter: 3/42: loss:1.8346: rank:-1
+[23:37:30.474] epoch: 7/20, iter: 4/42: loss:4.4902: rank:-1
+[23:37:46.473] epoch: 7/20, iter: 5/42: loss:2.0822: rank:-1
+[23:37:57.149] epoch: 7/20, iter: 6/42: loss:2.8414: rank:-1
+[23:38:09.926] epoch: 7/20, iter: 7/42: loss:2.8429: rank:-1
+[23:38:27.830] epoch: 7/20, iter: 8/42: loss:1.4337: rank:-1
+[23:38:37.086] epoch: 7/20, iter: 9/42: loss:2.4516: rank:-1
+[23:38:46.983] epoch: 7/20, iter: 10/42: loss:2.0565: rank:-1
+[23:39:09.910] epoch: 7/20, iter: 11/42: loss:3.8302: rank:-1
+[23:39:30.406] epoch: 7/20, iter: 12/42: loss:2.6687: rank:-1
+[23:39:49.896] epoch: 7/20, iter: 13/42: loss:1.4811: rank:-1
+[23:40:03.204] epoch: 7/20, iter: 14/42: loss:1.106: rank:-1
+[23:40:20.138] epoch: 7/20, iter: 15/42: loss:1.3464: rank:-1
+[23:40:31.291] epoch: 7/20, iter: 16/42: loss:2.1344: rank:-1
+[23:40:52.395] epoch: 7/20, iter: 17/42: loss:1.4228: rank:-1
+[23:41:03.860] epoch: 7/20, iter: 18/42: loss:4.7278: rank:-1
+[23:41:27.204] epoch: 7/20, iter: 19/42: loss:2.2869: rank:-1
+[23:41:47.445] epoch: 7/20, iter: 20/42: loss:1.5162: rank:-1
+[23:42:04.363] epoch: 7/20, iter: 21/42: loss:1.8119: rank:-1
+[23:42:24.226] epoch: 7/20, iter: 22/42: loss:1.3441: rank:-1
+[23:42:48.859] epoch: 7/20, iter: 23/42: loss:2.516: rank:-1
+[23:43:05.679] epoch: 7/20, iter: 24/42: loss:1.7301: rank:-1
+[23:43:21.387] epoch: 7/20, iter: 25/42: loss:1.1302: rank:-1
+[23:43:31.541] epoch: 7/20, iter: 26/42: loss:3.0731: rank:-1
+[23:43:49.996] epoch: 7/20, iter: 27/42: loss:2.2905: rank:-1
+[23:44:04.160] epoch: 7/20, iter: 28/42: loss:1.568: rank:-1
+[23:44:29.016] epoch: 7/20, iter: 29/42: loss:3.4348: rank:-1
+[23:44:43.256] epoch: 7/20, iter: 30/42: loss:1.5196: rank:-1
+[23:44:53.407] epoch: 7/20, iter: 31/42: loss:3.7365: rank:-1