diff --git "a/ABLATION_0225_randomSelect/wandb/run-20260225_103955-n76tgbfj/files/output.log" "b/ABLATION_0225_randomSelect/wandb/run-20260225_103955-n76tgbfj/files/output.log"
new file mode 100644--- /dev/null
+++ "b/ABLATION_0225_randomSelect/wandb/run-20260225_103955-n76tgbfj/files/output.log"
@@ -0,0 +1,708 @@
+LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2,3,4,5,6,7]
+
+  | Name                   | Type                 | Params | Mode
+------------------------------------------------------------------------
+0 | encoder                | OurSplat             | 888 M  | train
+1 | density_control_module | DensityControlModule | 2.6 M  | train
+2 | decoder                | DecoderSplattingCUDA | 0      | train
+3 | render_losses          | ModuleList           | 0      | train
+4 | density_control_losses | ModuleList           | 0      | train
+5 | direct_losses          | ModuleList           | 0      | train
+------------------------------------------------------------------------
+891 M     Trainable params
+0         Non-trainable params
+891 M     Total params
+3,564.326 Total estimated model params size (MB)
+1226      Modules in train mode
+522       Modules in eval mode
+Sanity Checking: |                                                                                           | 0/? [00:00<?, ?it/s][2026-02-25 10:39:59,700][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:425: The 'val_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=31` in the `DataLoader` to improve performance.
+
+[2026-02-25 10:39:59,701][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user.
+  warnings.warn(  # warn only once
+
+Validation epoch start on rank 0
+Sanity Checking DataLoader 0:   0%|                                                                          | 0/1 [00:00<?, ?it/s]validation step 0; scene = ['306e2b7785657539'];
+target intrinsic:  tensor(0.8595, device='cuda:0') tensor(0.8597, device='cuda:0')
+pred intrinsic:  tensor(0.8779, device='cuda:0') tensor(0.8773, device='cuda:0')
+[rank0]:W0225 10:40:02.204000 145562 site-packages/torch/utils/cpp_extension.py:2425] TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation.
+[rank0]:W0225 10:40:02.204000 145562 site-packages/torch/utils/cpp_extension.py:2425] If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'] to specific architectures.
+[2026-02-25 10:40:02,283][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+[2026-02-25 10:40:02,292][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/utilities/data.py:79: Trying to infer the `batch_size` from an ambiguous collection. The batch size we found is 1. To avoid any miscalculations, use `self.log(..., batch_size=batch_size)`.
+
+Setting up [LPIPS] perceptual loss: trunk [vgg], v[0.1], spatial [off]
+[2026-02-25 10:40:02,292][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 10:40:02,293][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
+  warnings.warn(msg)
+
+Loading model from: /venv/main/lib/python3.12/site-packages/lpips/weights/v0.1/vgg.pth
+[2026-02-25 10:40:03,984][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/functional.py:554: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /pytorch/aten/src/ATen/native/TensorShape.cpp:4322.)
+  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
+
+Sanity Checking DataLoader 0: 100%|██████████████████████████████████████████████████████████████████| 1/1 [00:03<00:00,  0.26it/s][2026-02-25 10:40:04,284][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('val/psnr', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+[2026-02-25 10:40:04,285][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('val/lpips', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+[2026-02-25 10:40:04,286][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('val/ssim', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+[2026-02-25 10:40:04,286][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('val/gaussian_num_ratio', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+[2026-02-25 10:40:04,286][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('info/global_step', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+Epoch 0: |                                                                                                   | 0/? [00:00<?, ?it/s]context = [[34, 36, 50, 53, 54, 60, 63, 70, 76, 78, 79, 80, 81, 88, 92, 94, 102, 110, 112, 114, 122, 125, 126, 131]]target = [[126, 96, 109, 55, 99, 116, 43, 60, 113, 85, 103, 90, 130, 62, 76, 123, 35, 102, 125, 128, 98, 67, 129, 79]]
+[2026-02-25 10:40:13,358][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
+grad.sizes() = [256, 256, 1, 1], strides() = [256, 1, 256, 256]
+bucket_view.sizes() = [256, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
+  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+
+[2026-02-25 10:40:13,429][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                               | 9/? [00:41<00:00,  0.21it/s, v_num=gbfj]train step 10; scene = [['08c26703c4987851']]; loss = 0.828852
+Epoch 0: |                                                                              | 10/? [00:46<00:00,  0.22it/s, v_num=gbfj]context = [[98, 107, 112, 119, 122, 123], [21, 22, 27, 36, 38, 46], [63, 66, 67, 77, 84, 88], [56, 62, 65, 68, 78, 81]]target = [[105, 110, 116, 112, 111, 101], [29, 37, 36, 22, 40, 45], [73, 66, 75, 87, 83, 64], [79, 69, 75, 58, 61, 62]]
+Epoch 0: |                                                                              | 19/? [01:19<00:00,  0.24it/s, v_num=gbfj]train step 20; scene = [['4012c15c8381568b'], ['af08406c5a9a43a0'], ['9f9f9beffb86fad7'], ['fc8d08df6c875cb0']]; loss = 0.247011
+Epoch 0: |                                                                              | 20/? [01:23<00:00,  0.24it/s, v_num=gbfj]context = [[144, 152, 157, 164, 166, 169, 171, 177], [201, 211, 216, 221, 228, 230, 233, 234], [11, 15, 16, 23, 30, 38, 43, 44]]target = [[153, 170, 149, 169, 145, 174, 165, 157], [229, 216, 205, 206, 203, 213, 233, 215], [37, 38, 39, 35, 15, 24, 19, 25]]
+Epoch 0: |                                                                              | 24/? [01:37<00:00,  0.25it/s, v_num=gbfj][2026-02-25 10:41:49,278][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
+  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
+
+Epoch 0: |                                                                              | 29/? [01:57<00:00,  0.25it/s, v_num=gbfj]train step 30; scene = [['00980329a3221f1c'], ['1e7c432d2207b6f2'], ['af2748330e5243d0']]; loss = 0.161471
+Epoch 0: |                                                                              | 30/? [02:00<00:00,  0.25it/s, v_num=gbfj]context = [[2, 7, 10, 15, 20, 24, 25, 29, 30, 32, 33, 37, 40, 44, 49, 60, 64, 74, 76, 81, 89, 91, 95, 99]]target = [[79, 84, 35, 43, 89, 44, 63, 58, 48, 13, 65, 7, 96, 27, 51, 20, 60, 15, 85, 59, 22, 66, 17, 62]]
+Epoch 0: |                                                                              | 39/? [02:34<00:00,  0.25it/s, v_num=gbfj]train step 40; scene = [['79a9385753d426bc'], ['593538382d2dc847'], ['c9c67636b9d521be']]; loss = 0.130091
+Epoch 0: |                                                                              | 40/? [02:38<00:00,  0.25it/s, v_num=gbfj]context = [[200, 208, 223, 225], [6, 8, 12, 31], [104, 107, 111, 129], [69, 80, 86, 95], [11, 15, 18, 37], [52, 60, 70, 78]]target = [[213, 203, 214, 201], [29, 11, 15, 28], [111, 122, 120, 115], [77, 90, 89, 78], [18, 24, 29, 14], [64, 67, 63, 74]]
+Epoch 0: |                                                                              | 49/? [03:11<00:00,  0.26it/s, v_num=gbfj]train step 50; scene = [['579a11551b3315d9'], ['c9dd64b7415e788e'], ['6f3fb517d1798d03']]; loss = 0.134455
+Epoch 0: |                                                                              | 50/? [03:15<00:00,  0.26it/s, v_num=gbfj]context = [[20, 22, 25, 28, 36, 47], [10, 13, 15, 22, 26, 35], [31, 47, 49, 51, 52, 56], [109, 110, 115, 116, 125, 135]]target = [[40, 24, 23, 30, 37, 33], [19, 32, 25, 24, 26, 28], [35, 52, 50, 55, 45, 36], [131, 123, 130, 110, 115, 134]]
+Epoch 0: |                                                                              | 59/? [03:49<00:00,  0.26it/s, v_num=gbfj]train step 60; scene = [['07916b8004a8e336'], ['e51ef9945ae527c4'], ['db84f84b1d775bb8'], ['92ed61f8e16b7e67']]; loss = 0.117451
+Epoch 0: |                                                                              | 60/? [03:52<00:00,  0.26it/s, v_num=gbfj]context = [[96, 97, 101, 102, 105, 106, 107, 114, 124, 134, 138, 145], [76, 78, 82, 83, 96, 98, 100, 111, 112, 118, 119, 125]]target = [[144, 124, 137, 102, 107, 130, 119, 129, 118, 123, 133, 126], [98, 108, 96, 100, 113, 123, 77, 78, 112, 109, 80, 102]]
+Epoch 0: |                                                                              | 69/? [04:27<00:00,  0.26it/s, v_num=gbfj]train step 70; scene = [['c34efa1505a0cfaa'], ['a3d0cca9fb57fd85'], ['43d0e6dce7bb1e95'], ['d8c2f0a3734cb493']]; loss = 0.093367
+Epoch 0: |                                                                              | 70/? [04:30<00:00,  0.26it/s, v_num=gbfj]context = [[204, 208, 211, 218, 232, 234, 237, 239, 240, 241, 247, 253], [6, 7, 10, 12, 35, 36, 37, 38, 40, 45, 48, 55]]target = [[230, 236, 222, 227, 220, 252, 216, 221, 213, 217, 249, 240], [18, 24, 25, 12, 9, 42, 34, 52, 41, 33, 43, 48]]
+Epoch 0: |                                                                              | 79/? [05:04<00:00,  0.26it/s, v_num=gbfj]train step 80; scene = [['24d756c820744e31'], ['cd6c21656a85e9b9'], ['f3b24cf238154fc0']]; loss = 0.097814
+Epoch 0: |                                                                              | 80/? [05:08<00:00,  0.26it/s, v_num=gbfj]context = [[4, 30], [52, 79], [61, 87], [12, 40], [83, 109], [3, 29], [221, 249], [198, 227], [9, 38], [46, 72], [0, 26], [123, 150]]target = [[27, 26], [58, 57], [70, 77], [26, 20], [87, 98], [26, 14], [223, 224], [221, 200], [23, 33], [67, 64], [4, 25], [140, 148]]
+Epoch 0: |                                                                              | 89/? [05:43<00:00,  0.26it/s, v_num=gbfj]train step 90; scene = [['617b4bc98d7e0bb6'], ['666e4a9aba27bb64']]; loss = 0.070999
+Epoch 0: |                                                                              | 90/? [05:47<00:00,  0.26it/s, v_num=gbfj]context = [[134, 135, 138, 146, 147, 151, 156, 161, 162, 164, 166, 167, 168, 169, 187, 189, 197, 210, 215, 224, 225, 228, 230, 231]]target = [[143, 149, 191, 182, 151, 226, 165, 140, 208, 171, 179, 223, 168, 136, 194, 207, 227, 144, 187, 185, 145, 218, 139, 170]]
+Epoch 0: |                                                                              | 99/? [06:21<00:00,  0.26it/s, v_num=gbfj]train step 100; scene = [['12fee7f1978d52f1'], ['c963bb60939e2d81']]; loss = 0.120759
+Epoch 0: |                                                                             | 100/? [06:25<00:00,  0.26it/s, v_num=gbfj]context = [[40, 44, 47, 48, 49, 50, 56, 63, 77, 79, 88, 89], [21, 33, 34, 35, 36, 40, 43, 46, 47, 60, 62, 70]]target = [[58, 81, 76, 64, 68, 72, 51, 87, 77, 65, 88, 45], [31, 47, 25, 35, 55, 22, 48, 65, 29, 40, 63, 67]]
+Epoch 0: |                                                                             | 109/? [06:59<00:00,  0.26it/s, v_num=gbfj]train step 110; scene = [['47396d5a5299873e']]; loss = 0.118578
+Epoch 0: |                                                                             | 110/? [07:03<00:00,  0.26it/s, v_num=gbfj]context = [[20, 22, 29, 30, 31, 34, 37, 45, 47, 51, 56, 69], [18, 22, 24, 27, 31, 37, 44, 48, 49, 60, 61, 67]]target = [[49, 22, 36, 59, 63, 60, 45, 66, 38, 28, 26, 64], [61, 65, 25, 20, 63, 60, 26, 22, 33, 45, 37, 35]]
+Epoch 0: |                                                                             | 119/? [07:37<00:00,  0.26it/s, v_num=gbfj]train step 120; scene = [['9bd7044e7cbf8e60'], ['76e44cf6b5658b26']]; loss = 0.085850
+Epoch 0: |                                                                             | 120/? [07:41<00:00,  0.26it/s, v_num=gbfj]context = [[7, 14, 26, 28, 31, 34, 37, 40], [10, 20, 26, 32, 35, 39, 41, 43], [17, 23, 26, 28, 44, 46, 49, 50]]target = [[14, 26, 10, 22, 30, 13, 31, 11], [24, 31, 36, 14, 40, 34, 41, 13], [24, 44, 34, 48, 46, 36, 26, 38]]
+Epoch 0: |                                                                             | 129/? [08:15<00:00,  0.26it/s, v_num=gbfj]train step 130; scene = [['a8cef6a851fbea3c'], ['b6699f4d039a5b06'], ['55cf2bbe9e017ea4'], ['6b0dd861e1ab1fec'], ['14db202c335af709'], ['8b6ff6c5153a7794'], ['b75f3820760d835c'], ['f7dbc855fd2a7669'], ['cfb20f8971e6a591'], ['95f2be7bb8303f50'], ['ff422469e034ae11'], ['5a2ad43377e9d18d']]; loss = 0.141809
+Epoch 0: |                                                                             | 130/? [08:19<00:00,  0.26it/s, v_num=gbfj]context = [[8, 15, 26, 30, 32, 35, 40, 46, 47, 48, 50, 53, 54, 62, 69, 70, 72, 76, 80, 86, 90, 99, 100, 105]]target = [[26, 12, 49, 100, 89, 24, 10, 81, 37, 63, 52, 17, 39, 70, 16, 56, 40, 55, 43, 34, 72, 28, 48, 45]]
+Epoch 0: |                                                                             | 139/? [08:51<00:00,  0.26it/s, v_num=gbfj]train step 140; scene = [['f62a962df5c26a1a'], ['b076420679a04731']]; loss = 0.094186
+Epoch 0: |                                                                             | 140/? [08:55<00:00,  0.26it/s, v_num=gbfj]context = [[90, 95, 97, 104, 118, 121], [14, 29, 34, 35, 36, 44], [12, 14, 22, 27, 34, 41], [6, 10, 16, 18, 34, 35]]target = [[99, 104, 93, 113, 110, 96], [29, 37, 22, 21, 39, 41], [19, 25, 39, 27, 29, 13], [26, 28, 9, 7, 13, 34]]
+Epoch 0: |                                                                             | 149/? [09:30<00:00,  0.26it/s, v_num=gbfj]train step 150; scene = [['a52d26a78b04aebd']]; loss = 0.080347
+Epoch 0: |                                                                             | 150/? [09:34<00:00,  0.26it/s, v_num=gbfj]context = [[115, 132, 134, 145], [16, 32, 39, 44], [57, 63, 78, 88], [9, 11, 23, 36], [15, 26, 28, 44], [1, 8, 22, 33]]target = [[124, 132, 116, 119], [27, 24, 33, 29], [81, 61, 85, 79], [28, 26, 29, 16], [28, 29, 37, 22], [9, 4, 32, 27]]
+Epoch 0: |                                                                             | 159/? [10:08<00:00,  0.26it/s, v_num=gbfj]train step 160; scene = [['268fbffc6c479d5b']]; loss = 0.061867
+Epoch 0: |                                                                             | 160/? [10:11<00:00,  0.26it/s, v_num=gbfj]context = [[18, 25, 26, 37, 42, 46, 49, 51, 53, 64, 65, 67], [69, 75, 78, 79, 82, 84, 94, 95, 104, 108, 117, 118]]target = [[53, 27, 22, 32, 41, 38, 50, 43, 47, 48, 23, 19], [74, 70, 114, 115, 90, 89, 88, 92, 94, 110, 107, 101]]
+Epoch 0: |                                                                             | 169/? [10:46<00:00,  0.26it/s, v_num=gbfj]train step 170; scene = [['719e2e8912e4eed3'], ['a3e51565a737569f']]; loss = 0.128410
+Epoch 0: |                                                                             | 170/? [10:50<00:00,  0.26it/s, v_num=gbfj]context = [[14, 18, 20, 21, 24, 27, 33, 40, 45, 47, 48, 51, 52, 60, 64, 70, 75, 77, 80, 85, 90, 98, 102, 111]]target = [[29, 93, 32, 39, 81, 108, 72, 107, 51, 35, 16, 36, 70, 18, 34, 92, 94, 47, 23, 74, 50, 77, 19, 37]]
+Epoch 0: |                                                                             | 179/? [11:24<00:00,  0.26it/s, v_num=gbfj]train step 180; scene = [['f44b9aa76a94a0a3']]; loss = 0.076148
+Epoch 0: |                                                                             | 180/? [11:28<00:00,  0.26it/s, v_num=gbfj]context = [[0, 6, 17, 22, 26, 28, 33, 41, 50, 55, 56, 57, 71, 76, 79, 81, 84, 85, 86, 87, 89, 95, 96, 97]]target = [[37, 49, 12, 78, 9, 16, 84, 13, 5, 4, 6, 38, 80, 51, 43, 68, 64, 46, 56, 24, 25, 72, 36, 21]]
+Epoch 0: |                                                                             | 189/? [12:03<00:00,  0.26it/s, v_num=gbfj]train step 190; scene = [['71bb669d936a5718'], ['a47203cfd5e0a478'], ['4b009f82cf5c7098']]; loss = 0.074888
+Epoch 0: |                                                                             | 190/? [12:06<00:00,  0.26it/s, v_num=gbfj]context = [[9, 11, 19, 25, 33, 43, 46, 47, 48, 54, 57, 58, 63, 70, 72, 75, 79, 80, 83, 84, 85, 96, 99, 106]]target = [[30, 53, 82, 31, 55, 12, 20, 72, 104, 70, 24, 52, 21, 32, 102, 71, 35, 11, 46, 10, 15, 74, 33, 26]]
+Epoch 0: |                                                                             | 199/? [12:40<00:00,  0.26it/s, v_num=gbfj]train step 200; scene = [['dd5ec950a01c42a0'], ['6d0db0358f7e051e'], ['983fe650a925ec1b']]; loss = 0.090481
+Epoch 0: |                                                                             | 200/? [12:44<00:00,  0.26it/s, v_num=gbfj]context = [[8, 10, 14, 15, 22, 23, 27, 30, 36, 38, 39, 47, 64, 65, 67, 78, 79, 80, 83, 86, 93, 96, 98, 105]]target = [[73, 63, 10, 27, 89, 35, 44, 58, 97, 71, 17, 24, 66, 87, 50, 12, 23, 11, 31, 45, 69, 96, 98, 94]]
+[2026-02-25 10:52:55,864][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                             | 209/? [13:25<00:00,  0.26it/s, v_num=gbfj]train step 210; scene = [['9be9b273b3c22c61'], ['4b5883872c9b860c']]; loss = 0.065395
+Epoch 0: |                                                                             | 210/? [13:29<00:00,  0.26it/s, v_num=gbfj]context = [[34, 35, 37, 54, 56, 59, 61, 68, 69, 76, 90, 96, 98, 101, 103, 107, 116, 119, 120, 121, 122, 125, 126, 131]]target = [[95, 50, 119, 121, 84, 107, 72, 52, 80, 42, 127, 94, 79, 98, 46, 128, 73, 75, 106, 92, 37, 110, 96, 56]]
+Epoch 0: |                                                                             | 219/? [14:04<00:00,  0.26it/s, v_num=gbfj]train step 220; scene = [['a3b6faa8d238d993'], ['df9ba36fbe753843']]; loss = 0.052379
+Epoch 0: |                                                                             | 220/? [14:08<00:00,  0.26it/s, v_num=gbfj]context = [[39, 71, 74], [21, 41, 51], [28, 55, 59], [2, 31, 37], [15, 25, 48], [57, 64, 93], [76, 87, 105], [31, 53, 64]]target = [[52, 43, 59], [28, 25, 49], [48, 58, 51], [26, 9, 6], [30, 32, 47], [84, 88, 59], [104, 87, 88], [42, 52, 59]]
+Epoch 0: |                                                                             | 229/? [14:42<00:00,  0.26it/s, v_num=gbfj]train step 230; scene = [['ca04de3c55cd1ca0'], ['3d90d586b33daa63'], ['d1772c09b4b6d95f'], ['03d05f69a1cab4f8'], ['60d296908f43a97a'], ['37c400e282bc481e']]; loss = 0.074263
+Epoch 0: |                                                                             | 230/? [14:46<00:00,  0.26it/s, v_num=gbfj]context = [[203, 204, 208, 209, 210, 233], [41, 42, 43, 52, 60, 76], [2, 8, 9, 23, 29, 31], [70, 74, 92, 97, 98, 100]]target = [[226, 223, 210, 217, 228, 222], [46, 70, 71, 75, 43, 56], [24, 23, 29, 25, 3, 21], [95, 81, 74, 73, 98, 92]]
+Epoch 0: |                                                                             | 239/? [15:21<00:00,  0.26it/s, v_num=gbfj]train step 240; scene = [['9794641b7e015578']]; loss = 0.114044
+Epoch 0: |                                                                             | 240/? [15:25<00:00,  0.26it/s, v_num=gbfj]context = [[62, 65, 68, 71, 80, 86, 87, 96, 99, 101, 103, 111], [134, 138, 139, 142, 151, 163, 171, 172, 173, 174, 181, 183]]target = [[87, 89, 96, 93, 103, 71, 65, 77, 63, 98, 102, 105], [165, 177, 159, 147, 138, 152, 171, 141, 181, 146, 161, 176]]
+Epoch 0: |                                                                             | 249/? [15:59<00:00,  0.26it/s, v_num=gbfj]train step 250; scene = [['93dff1b985f2c7f9']]; loss = 0.086482
+Epoch 0: |                                                                             | 250/? [16:03<00:00,  0.26it/s, v_num=gbfj]Validation epoch start on rank 0
+Validation: |                                                                                                | 0/? [00:00<?, ?it/s]validation step 250; scene = ['49b8f80c849dc341'];
+target intrinsic:  tensor(0.8891, device='cuda:0') tensor(0.8894, device='cuda:0')                           | 0/1 [00:00<?, ?it/s]
+pred intrinsic:  tensor(0.8757, device='cuda:0') tensor(0.8759, device='cuda:0')
+[2026-02-25 10:56:11,418][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                             | 250/? [16:04<00:00,  0.26it/s, v_num=gbfj]context = [[113, 115, 120, 131, 135, 137, 144, 152], [16, 20, 23, 28, 32, 35, 39, 52], [14, 18, 25, 26, 28, 29, 51, 53]]target = [[149, 139, 118, 151, 137, 141, 121, 130], [45, 51, 28, 50, 35, 37, 27, 23], [29, 26, 22, 51, 24, 34, 47, 45]]
+Epoch 0: |                                                                             | 259/? [16:37<00:00,  0.26it/s, v_num=gbfj]train step 260; scene = [['b2288bf7003d5d4d']]; loss = 0.095024
+Epoch 0: |                                                                             | 260/? [16:41<00:00,  0.26it/s, v_num=gbfj]context = [[206, 208, 212, 216, 221, 236], [58, 60, 68, 69, 70, 93], [15, 19, 26, 34, 41, 44], [15, 18, 23, 34, 42, 44]]target = [[225, 216, 234, 214, 207, 232], [88, 76, 91, 67, 64, 70], [20, 29, 22, 36, 23, 40], [42, 28, 31, 30, 16, 37]]
+Epoch 0: |                                                                             | 269/? [17:15<00:00,  0.26it/s, v_num=gbfj]train step 270; scene = [['013ec74a4fde6737'], ['78e816776b064fc4'], ['1b778f72bbee1f27'], ['c71549de92ecb2e4'], ['8e16c8644efeec52'], ['35c5fc80e85db7cd'], ['34c8c62d878eca66'], ['203a5fd3a45ac4a7']]; loss = 0.062939
+Epoch 0: |                                                                             | 270/? [17:19<00:00,  0.26it/s, v_num=gbfj]context = [[160, 174, 177, 178, 192, 200], [34, 52, 54, 56, 58, 67], [78, 85, 101, 102, 109, 118], [123, 135, 136, 144, 150, 155]]target = [[169, 195, 175, 174, 194, 189], [55, 53, 57, 48, 40, 66], [90, 108, 110, 84, 109, 83], [131, 130, 127, 124, 139, 133]]
+Epoch 0: |                                                                             | 279/? [17:53<00:00,  0.26it/s, v_num=gbfj]train step 280; scene = [['75335793f866b96d'], ['e9d9dc952f5bbd83']]; loss = 0.044740
+Epoch 0: |                                                                             | 280/? [17:57<00:00,  0.26it/s, v_num=gbfj]context = [[2, 31], [39, 73], [69, 98], [58, 92], [109, 146], [27, 59], [83, 114], [199, 231], [13, 50], [77, 109], [72, 105], [7, 45]]target = [[20, 26], [71, 57], [92, 77], [61, 72], [125, 129], [44, 51], [110, 101], [211, 202], [27, 17], [98, 104], [80, 89], [36, 37]]
+Epoch 0: |                                                                             | 289/? [18:30<00:00,  0.26it/s, v_num=gbfj]train step 290; scene = [['51252022ddf74fb9'], ['8dd73309b133b8bf'], ['9e8db62a9b3cbd5e'], ['d41e59ee023e977b'], ['ce1a9465dc08ef4c'], ['e7887dec76685627']]; loss = 0.062444
+Epoch 0: |                                                                             | 290/? [18:34<00:00,  0.26it/s, v_num=gbfj]context = [[74, 83, 85, 88, 89, 93, 100, 101, 108, 119, 122, 123], [17, 20, 23, 24, 28, 30, 32, 35, 48, 52, 64, 66]]target = [[110, 79, 95, 92, 111, 109, 99, 89, 77, 98, 81, 102], [28, 29, 52, 36, 54, 64, 49, 23, 40, 58, 31, 27]]
+Epoch 0: |                                                                             | 299/? [19:09<00:00,  0.26it/s, v_num=gbfj]train step 300; scene = [['0c5d83212982c0ec'], ['00793a8a3b268d7c'], ['47a9b1e96499a466'], ['a1fb990016d7b3af']]; loss = 0.053361
+Epoch 0: |                                                                             | 300/? [19:13<00:00,  0.26it/s, v_num=gbfj]context = [[83, 88, 89, 91, 92, 100, 102, 104, 107, 111, 113, 115, 129, 132, 134, 135, 140, 142, 145, 150, 154, 173, 175, 180]]target = [[115, 140, 130, 169, 114, 163, 175, 177, 104, 152, 151, 89, 154, 123, 132, 85, 122, 119, 155, 91, 117, 171, 158, 157]]
+Epoch 0: |                                                                             | 309/? [19:46<00:00,  0.26it/s, v_num=gbfj]train step 310; scene = [['9b73ab94b5c43711'], ['8c845b940aa8244c'], ['b2789c1a5c127a02'], ['3db6c0e172d18826']]; loss = 0.069974
+Epoch 0: |                                                                             | 310/? [19:50<00:00,  0.26it/s, v_num=gbfj]context = [[30, 47, 66], [16, 31, 46], [10, 28, 40], [43, 68, 75], [21, 43, 63], [15, 29, 46], [36, 44, 66], [17, 39, 59]]target = [[51, 41, 31], [29, 43, 44], [23, 35, 33], [64, 71, 63], [48, 59, 27], [45, 29, 27], [60, 42, 50], [34, 26, 47]]
+Epoch 0: |                                                                             | 319/? [20:25<00:00,  0.26it/s, v_num=gbfj]train step 320; scene = [['591cd9d079cd7842'], ['3dd7802a2c93a865']]; loss = 0.099855
+Epoch 0: |                                                                             | 320/? [20:29<00:00,  0.26it/s, v_num=gbfj]context = [[4, 22, 28, 31, 34, 37, 45, 46], [26, 28, 38, 41, 46, 55, 57, 59], [129, 139, 145, 150, 151, 158, 167, 169]]target = [[7, 41, 13, 5, 20, 27, 32, 44], [29, 32, 54, 28, 40, 52, 43, 33], [137, 143, 146, 152, 130, 131, 145, 133]]
+Epoch 0: |                                                                             | 329/? [21:04<00:00,  0.26it/s, v_num=gbfj]train step 330; scene = [['30d9f6321281dade'], ['2a08fac923c9e50d']]; loss = 0.057621
+Epoch 0: |                                                                             | 330/? [21:08<00:00,  0.26it/s, v_num=gbfj]context = [[4, 6, 12, 14, 24, 41, 42, 44, 45, 48, 49, 53], [102, 106, 112, 113, 118, 122, 125, 130, 134, 140, 149, 151]]target = [[50, 42, 7, 28, 11, 33, 20, 45, 25, 8, 22, 16], [135, 134, 113, 128, 139, 112, 117, 108, 122, 127, 138, 120]]
+Epoch 0: |                                                                             | 339/? [21:41<00:00,  0.26it/s, v_num=gbfj]train step 340; scene = [['bd9f2096d355b1b8'], ['07d3325178e7a790'], ['8204d757ce43dda8']]; loss = 0.055096
+Epoch 0: |                                                                             | 340/? [21:45<00:00,  0.26it/s, v_num=gbfj]context = [[87, 88, 93, 105, 107, 111, 116, 118, 123, 131, 132, 136], [104, 111, 116, 121, 122, 127, 131, 132, 136, 137, 142, 153]]target = [[114, 108, 107, 130, 95, 129, 118, 104, 116, 96, 109, 99], [127, 106, 145, 129, 114, 109, 143, 150, 111, 133, 146, 122]]
+Epoch 0: |                                                                             | 349/? [22:20<00:00,  0.26it/s, v_num=gbfj]train step 350; scene = [['9d0bfbe5b7f98545'], ['06a16655c8e8ad9c']]; loss = 0.108012
+Epoch 0: |                                                                             | 350/? [22:24<00:00,  0.26it/s, v_num=gbfj]context = [[33, 52, 53, 56, 58, 64, 73, 75], [100, 102, 115, 117, 130, 134, 139, 142], [223, 225, 240, 242, 255, 256, 263, 267]]target = [[41, 60, 53, 63, 72, 38, 37, 73], [122, 141, 116, 138, 110, 119, 118, 135], [260, 237, 261, 264, 238, 255, 243, 253]]
+Epoch 0: |                                                                             | 359/? [22:58<00:00,  0.26it/s, v_num=gbfj]train step 360; scene = [['73b27f4f150327af'], ['169aaaf51ef3849c'], ['068a8406f1a383d8'], ['a9936b77895f33b3']]; loss = 0.075157
+Epoch 0: |                                                                             | 360/? [23:02<00:00,  0.26it/s, v_num=gbfj]context = [[0, 14, 18, 23, 25, 32, 42, 45, 46, 49, 53, 55, 59, 60, 61, 74, 78, 80, 84, 85, 89, 90, 92, 97]]target = [[50, 81, 69, 64, 38, 86, 91, 16, 27, 33, 44, 90, 48, 23, 8, 79, 6, 39, 42, 36, 82, 78, 59, 54]]
+Epoch 0: |                                                                             | 369/? [23:36<00:00,  0.26it/s, v_num=gbfj]train step 370; scene = [['8673faf0a9d48165'], ['99a0790d72e6c2af'], ['6cbbe9075b0d2138']]; loss = 0.056392
+Epoch 0: |                                                                             | 370/? [23:40<00:00,  0.26it/s, v_num=gbfj]context = [[61, 63, 65, 72, 73, 74, 76, 89, 92, 94, 100, 101, 120, 124, 126, 127, 136, 140, 144, 145, 150, 152, 156, 158]]target = [[121, 100, 147, 98, 148, 143, 126, 63, 73, 141, 79, 119, 115, 106, 153, 101, 120, 71, 91, 62, 105, 84, 151, 145]]
+Epoch 0: |                                                                             | 379/? [24:14<00:00,  0.26it/s, v_num=gbfj]train step 380; scene = [['656330f47c5df010'], ['6dfb89a98e14ca66']]; loss = 0.061531
+Epoch 0: |                                                                             | 380/? [24:18<00:00,  0.26it/s, v_num=gbfj]context = [[210, 215, 223, 225, 231, 234, 235, 249], [28, 32, 35, 53, 54, 56, 57, 68], [149, 150, 154, 155, 174, 177, 181, 183]]target = [[241, 236, 218, 230, 223, 228, 239, 227], [55, 46, 44, 49, 30, 33, 60, 45], [157, 160, 161, 164, 170, 181, 168, 166]]
+Epoch 0: |                                                                             | 389/? [24:53<00:00,  0.26it/s, v_num=gbfj]train step 390; scene = [['723f94d150ab09f2'], ['393cdfb7e832d285'], ['14900b71ac66b7bd'], ['452625cd6b071b87'], ['281599bbab3e73dd'], ['0a2b42e240751d33']]; loss = 0.065867
+Epoch 0: |                                                                             | 390/? [24:56<00:00,  0.26it/s, v_num=gbfj]context = [[48, 52, 80], [14, 47, 60], [142, 159, 187], [78, 120, 121], [6, 24, 45], [47, 68, 90], [15, 19, 48], [9, 20, 52]]target = [[51, 50, 70], [45, 15, 56], [172, 148, 157], [120, 98, 109], [20, 33, 11], [83, 84, 73], [45, 30, 32], [16, 36, 45]]
+Epoch 0: |                                                                             | 399/? [25:29<00:00,  0.26it/s, v_num=gbfj]train step 400; scene = [['4303746d8f23f16b'], ['0fe8246bb7e2fe40'], ['b7d77240852d6a52'], ['6e5505414fd63528'], ['44985936f68c3a36'], ['1550f1b4fff1f2a4'], ['cea3d842c3285c65'], ['b34bb5f53856d34f']]; loss = 0.092871
+Epoch 0: |                                                                             | 400/? [25:33<00:00,  0.26it/s, v_num=gbfj]context = [[9, 20, 28, 31, 34, 53], [189, 196, 216, 223, 230, 232], [74, 77, 86, 88, 98, 118], [132, 145, 157, 168, 179, 181]]target = [[51, 32, 14, 50, 45, 34], [212, 226, 201, 205, 215, 222], [93, 113, 107, 94, 83, 79], [161, 139, 177, 151, 156, 172]]
+[2026-02-25 11:05:44,777][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                             | 409/? [26:08<00:00,  0.26it/s, v_num=gbfj]train step 410; scene = [['144e1ec915e46d29'], ['b290b6a0afa1dac7'], ['b3d84dba6581c3d9']]; loss = 0.056830
+Epoch 0: |                                                                             | 410/? [26:12<00:00,  0.26it/s, v_num=gbfj]context = [[26, 40, 41, 50, 55, 58], [159, 174, 179, 192, 198, 201], [2, 3, 5, 7, 24, 40], [187, 204, 205, 208, 217, 221]]target = [[38, 32, 44, 52, 42, 27], [198, 191, 196, 162, 163, 169], [33, 17, 23, 37, 15, 39], [214, 211, 195, 220, 210, 192]]
+Epoch 0: |                                                                             | 419/? [26:46<00:00,  0.26it/s, v_num=gbfj]train step 420; scene = [['a1dff9c50d92dc9c']]; loss = 0.054036
+Epoch 0: |                                                                             | 420/? [26:50<00:00,  0.26it/s, v_num=gbfj]context = [[11, 13, 14, 26, 27, 41, 46, 51], [151, 155, 161, 167, 172, 176, 191, 195], [49, 52, 55, 57, 59, 74, 79, 90]]target = [[25, 44, 17, 33, 37, 24, 38, 40], [193, 191, 194, 162, 158, 176, 163, 171], [87, 85, 67, 58, 86, 68, 83, 78]]
+Epoch 0: |                                                                             | 429/? [27:24<00:00,  0.26it/s, v_num=gbfj]train step 430; scene = [['36664e22fd10a141'], ['0474328f4cefd619']]; loss = 0.044982
+Epoch 0: |                                                                             | 430/? [27:28<00:00,  0.26it/s, v_num=gbfj]context = [[123, 130, 131, 132, 136, 154, 169, 173], [35, 36, 47, 49, 65, 67, 76, 86], [33, 34, 39, 41, 59, 64, 65, 73]]target = [[145, 147, 167, 130, 146, 170, 138, 137], [59, 38, 49, 42, 70, 76, 39, 40], [56, 44, 36, 35, 38, 45, 48, 58]]
+Epoch 0: |                                                                             | 439/? [28:02<00:00,  0.26it/s, v_num=gbfj]train step 440; scene = [['342099a48847f4f6'], ['5ad0327426e3718b'], ['c25b314716aa6b10'], ['c91e2b5399b14430'], ['e1d9ade67e615bd8'], ['46df912c9748215b']]; loss = 0.058583
+Epoch 0: |                                                                             | 440/? [28:06<00:00,  0.26it/s, v_num=gbfj]context = [[0, 33], [10, 57], [36, 82], [46, 79], [62, 99], [33, 79], [11, 52], [1, 34], [0, 37], [26, 62], [18, 67], [96, 138]]target = [[22, 18], [37, 23], [44, 54], [69, 50], [68, 69], [69, 56], [49, 41], [27, 30], [31, 17], [42, 32], [59, 54], [108, 115]]
+Epoch 0: |                                                                             | 449/? [28:41<00:00,  0.26it/s, v_num=gbfj]train step 450; scene = [['e19c6facac1c9624'], ['5244830b7357365b'], ['b80c2522b1070e2f'], ['6ea0ff32c8ea695c'], ['2f311b2bbbeb5940'], ['3f7992e72a096099']]; loss = 0.062199
+Epoch 0: |                                                                             | 450/? [28:45<00:00,  0.26it/s, v_num=gbfj]context = [[41, 42, 44, 49, 57, 66, 68, 73, 75, 76, 83, 91], [4, 5, 15, 24, 32, 35, 37, 38, 45, 47, 49, 56]]target = [[79, 77, 90, 46, 81, 83, 56, 68, 89, 70, 84, 57], [7, 8, 40, 37, 32, 10, 25, 35, 23, 43, 48, 52]]
+Epoch 0: |                                                                             | 459/? [29:19<00:00,  0.26it/s, v_num=gbfj]train step 460; scene = [['46fb6702ed1b9967'], ['bdc3f978b0d3aa8f']]; loss = 0.054696
+Epoch 0: |                                                                             | 460/? [29:23<00:00,  0.26it/s, v_num=gbfj]context = [[65, 66, 69, 78, 84, 85, 90, 91, 99, 103, 112, 116], [39, 40, 52, 63, 64, 68, 72, 73, 83, 87, 90, 92]]target = [[99, 86, 101, 76, 84, 77, 105, 66, 89, 75, 100, 106], [84, 61, 68, 82, 59, 47, 51, 71, 85, 56, 57, 50]]
+Epoch 0: |                                                                             | 469/? [29:56<00:00,  0.26it/s, v_num=gbfj]train step 470; scene = [['2c88995e05a17d17'], ['2b1f47da224557a3'], ['62216d162b71b5b4'], ['61d39a97cb69d99f'], ['42000d5a83b48ee4'], ['cc8480640599f9f3']]; loss = 0.066102
+Epoch 0: |                                                                             | 470/? [30:00<00:00,  0.26it/s, v_num=gbfj]context = [[1, 6, 15, 26, 28, 41, 46, 52], [0, 1, 3, 5, 14, 26, 32, 37], [52, 56, 58, 79, 87, 88, 93, 97]]target = [[24, 22, 32, 14, 42, 21, 12, 37], [14, 10, 11, 25, 12, 34, 7, 32], [62, 60, 80, 87, 63, 55, 78, 88]]
+Epoch 0: |                                                                             | 479/? [30:35<00:00,  0.26it/s, v_num=gbfj]train step 480; scene = [['2e3bb7fb33e1ed30'], ['7460f503eb18fa6a'], ['bde49071d2088850'], ['e80016be3043dfa4']]; loss = 0.075549
+Epoch 0: |                                                                             | 480/? [30:38<00:00,  0.26it/s, v_num=gbfj]context = [[9, 15, 37, 47], [0, 5, 7, 35], [101, 113, 134, 153], [64, 88, 93, 107], [18, 44, 56, 62], [31, 46, 58, 75]]target = [[45, 27, 28, 18], [10, 8, 14, 3], [128, 143, 110, 129], [87, 84, 90, 94], [29, 31, 40, 36], [52, 72, 33, 56]]
+Epoch 0: |                                                                             | 489/? [31:13<00:00,  0.26it/s, v_num=gbfj]train step 490; scene = [['83085493f4bc18d2']]; loss = 0.080811
+Epoch 0: |                                                                             | 490/? [31:17<00:00,  0.26it/s, v_num=gbfj]context = [[0, 3, 7, 12, 38, 40, 45, 48], [25, 28, 57, 62, 69, 70, 76, 78], [25, 34, 37, 39, 41, 53, 65, 67]]target = [[15, 7, 39, 47, 42, 26, 25, 5], [63, 40, 59, 31, 75, 34, 47, 39], [58, 35, 53, 33, 65, 44, 38, 31]]
+Epoch 0: |                                                                             | 499/? [31:51<00:00,  0.26it/s, v_num=gbfj]train step 500; scene = [['1241bcb5732a9502'], ['d33a9e90e1416efb']]; loss = 0.038077
+Epoch 0: |                                                                             | 500/? [31:55<00:00,  0.26it/s, v_num=gbfj]Validation epoch start on rank 0
+Validation: |                                                                                                | 0/? [00:00<?, ?it/s]validation step 500; scene = ['73d6f935f31b3fd4'];
+target intrinsic:  tensor(0.8576, device='cuda:0') tensor(0.8579, device='cuda:0')                           | 0/1 [00:00<?, ?it/s]
+pred intrinsic:  tensor(0.8712, device='cuda:0') tensor(0.8714, device='cuda:0')
+[2026-02-25 11:12:03,856][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                             | 500/? [31:57<00:00,  0.26it/s, v_num=gbfj]context = [[1, 21, 23, 29, 39, 48, 49, 52], [17, 18, 20, 28, 34, 39, 45, 51], [99, 103, 106, 110, 116, 136, 138, 140]]target = [[4, 46, 41, 43, 40, 37, 39, 25], [30, 48, 22, 42, 44, 31, 38, 37], [112, 108, 133, 116, 111, 125, 123, 127]]
+Epoch 0: |                                                                             | 509/? [32:30<00:00,  0.26it/s, v_num=gbfj]train step 510; scene = [['0eed4548041bea8e'], ['277a96ce456580f4']]; loss = 0.051914
+Epoch 0: |                                                                             | 510/? [32:34<00:00,  0.26it/s, v_num=gbfj]context = [[3, 13, 21, 24, 27, 28, 30, 37, 42, 44, 46, 55, 62, 65, 69, 71, 73, 80, 83, 84, 89, 95, 97, 100]]target = [[51, 81, 54, 89, 55, 45, 10, 19, 21, 68, 48, 67, 33, 69, 8, 25, 64, 83, 37, 29, 24, 82, 99, 46]]
+Epoch 0: |                                                                             | 519/? [33:08<00:00,  0.26it/s, v_num=gbfj]train step 520; scene = [['625e3aa0ff734714'], ['395802511d26f32e'], ['39343936591c28de']]; loss = 0.079012
+Epoch 0: |                                                                             | 520/? [33:12<00:00,  0.26it/s, v_num=gbfj]context = [[13, 16, 17, 22, 25, 30, 35, 39, 53, 56, 62, 68, 78, 87, 90, 92, 93, 95, 99, 100, 103, 106, 107, 110]]target = [[39, 96, 58, 28, 16, 59, 44, 17, 26, 83, 103, 31, 57, 35, 107, 51, 27, 77, 46, 30, 100, 91, 93, 97]]
+Epoch 0: |                                                                             | 529/? [33:46<00:00,  0.26it/s, v_num=gbfj]train step 530; scene = [['0c199c575b699444'], ['70d878da47f984e4'], ['15f77c76ea744f99'], ['e54b5eec8cc47776'], ['1969ed97e68d83d9'], ['c7cf9b63dc3e5830'], ['bcef3076b93012b1'], ['ab2680bf91942e23']]; loss = 0.079286
+Epoch 0: |                                                                             | 530/? [33:50<00:00,  0.26it/s, v_num=gbfj]context = [[78, 84, 85, 92, 124, 127], [14, 15, 24, 52, 64, 68], [1, 6, 16, 20, 22, 40], [33, 51, 61, 65, 66, 70]]target = [[104, 103, 94, 96, 88, 82], [15, 53, 58, 47, 56, 60], [31, 10, 18, 26, 23, 24], [37, 69, 62, 65, 49, 64]]
+Epoch 0: |                                                                             | 539/? [34:25<00:00,  0.26it/s, v_num=gbfj]train step 540; scene = [['a071d9276f6a9272']]; loss = 0.068371
+Epoch 0: |                                                                             | 540/? [34:28<00:00,  0.26it/s, v_num=gbfj]context = [[35, 46, 47, 49, 52, 54, 55, 56, 57, 65, 66, 85], [51, 54, 55, 59, 68, 77, 82, 86, 87, 93, 105, 106]]target = [[69, 68, 75, 48, 44, 79, 53, 74, 60, 81, 72, 71], [77, 73, 88, 59, 67, 61, 102, 62, 93, 75, 95, 105]]
+Epoch 0: |                                                                             | 549/? [35:03<00:00,  0.26it/s, v_num=gbfj]train step 550; scene = [['836250796ea45b6c']]; loss = 0.076757
+Epoch 0: |                                                                             | 550/? [35:07<00:00,  0.26it/s, v_num=gbfj]context = [[30, 34, 39, 45, 47, 79, 80, 83], [16, 21, 22, 24, 33, 42, 51, 60], [115, 128, 129, 138, 141, 150, 156, 163]]target = [[79, 51, 62, 77, 46, 54, 33, 49], [27, 59, 20, 41, 21, 48, 58, 30], [133, 125, 124, 159, 122, 129, 155, 119]]
+Epoch 0: |                                                                             | 559/? [35:41<00:00,  0.26it/s, v_num=gbfj]train step 560; scene = [['d70ca840b3c5aec9'], ['65c3f29c43dd1e63'], ['d3917d0a1eda2a1f'], ['5c83dfc8f9ab44fa']]; loss = 0.052628
+Epoch 0: |                                                                             | 560/? [35:45<00:00,  0.26it/s, v_num=gbfj]context = [[62, 66, 67, 68, 71, 87, 88, 92, 100, 108, 110, 122], [153, 160, 165, 168, 171, 177, 178, 181, 183, 185, 200, 205]]target = [[95, 104, 83, 68, 115, 81, 74, 106, 119, 79, 90, 72], [204, 165, 196, 185, 197, 198, 195, 187, 155, 188, 154, 201]]
+Epoch 0: |                                                                             | 569/? [36:20<00:00,  0.26it/s, v_num=gbfj]train step 570; scene = [['9d8ddcdbe1f7ac42'], ['721df0f45094ca34'], ['fdbfe35f5940d3ad']]; loss = 0.041697
+Epoch 0: |                                                                             | 570/? [36:23<00:00,  0.26it/s, v_num=gbfj]context = [[23, 34, 41, 42, 48, 54, 56, 59, 60, 63, 66, 71, 74, 79, 88, 90, 92, 93, 95, 97, 110, 111, 119, 120]]target = [[30, 27, 28, 53, 31, 75, 85, 54, 77, 111, 76, 25, 44, 52, 33, 41, 69, 89, 73, 68, 26, 93, 83, 119]]
+Epoch 0: |                                                                             | 579/? [36:58<00:00,  0.26it/s, v_num=gbfj]train step 580; scene = [['88a0267e41b851f0'], ['df71fbb70b19cbc3'], ['1c713c10ecf5a0c9']]; loss = 0.053067
+Epoch 0: |                                                                             | 580/? [37:01<00:00,  0.26it/s, v_num=gbfj]context = [[9, 22, 36, 39, 43, 68], [70, 85, 95, 98, 116, 121], [10, 28, 45, 47, 50, 57], [132, 144, 154, 158, 168, 188]]target = [[67, 45, 11, 46, 50, 30], [114, 94, 71, 104, 117, 76], [22, 12, 24, 51, 50, 13], [180, 169, 183, 173, 182, 171]]
+Epoch 0: |                                                                             | 589/? [37:36<00:00,  0.26it/s, v_num=gbfj]train step 590; scene = [['3f732b63cdd0729e'], ['9be3165beb073d95'], ['42a6c835ff830674'], ['f928d960cbfae15a'], ['140b10a4f6bb5aa5'], ['cc8e19c8ad1846f4']]; loss = 0.080349
+Epoch 0: |                                                                             | 590/? [37:39<00:00,  0.26it/s, v_num=gbfj]context = [[198, 200, 201, 204, 209, 210, 224, 234], [6, 14, 18, 23, 25, 27, 58, 59], [13, 29, 40, 51, 55, 66, 70, 71]]target = [[203, 208, 227, 217, 222, 223, 200, 211], [11, 46, 45, 19, 20, 18, 47, 7], [16, 51, 40, 15, 55, 44, 23, 61]]
+Epoch 0: |                                                                             | 599/? [38:14<00:00,  0.26it/s, v_num=gbfj]train step 600; scene = [['cb734fdc69e9900e']]; loss = 0.053299
+Epoch 0: |                                                                             | 600/? [38:18<00:00,  0.26it/s, v_num=gbfj]context = [[10, 16, 24, 31, 33, 34, 36, 41, 49, 59, 63, 67], [160, 162, 167, 172, 173, 180, 183, 187, 189, 205, 212, 214]]target = [[32, 54, 42, 14, 39, 60, 66, 33, 62, 22, 47, 49], [182, 199, 163, 179, 203, 200, 174, 209, 164, 172, 194, 167]]
+[2026-02-25 11:18:29,813][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                             | 609/? [38:54<00:00,  0.26it/s, v_num=gbfj]train step 610; scene = [['ed9409fa128e193b'], ['a5c03b0c5fb7203e']]; loss = 0.037882
+Epoch 0: |                                                                             | 610/? [38:57<00:00,  0.26it/s, v_num=gbfj]context = [[36, 37, 39, 50, 51, 52, 57, 59, 72, 73, 86, 94], [45, 46, 54, 57, 66, 75, 77, 81, 83, 89, 97, 101]]target = [[47, 37, 89, 79, 92, 78, 81, 90, 38, 56, 84, 69], [84, 91, 85, 69, 79, 53, 55, 48, 87, 49, 92, 63]]
+Epoch 0: |                                                                             | 619/? [39:32<00:00,  0.26it/s, v_num=gbfj]train step 620; scene = [['7898a828b7203ca4'], ['9c269fce78f0dd27'], ['e1e317857deb7afc'], ['30124191dafb3383'], ['c39f1a9a73797efe'], ['a640a55439a43108']]; loss = 0.046852
+Epoch 0: |                                                                             | 620/? [39:36<00:00,  0.26it/s, v_num=gbfj]context = [[2, 15, 16, 21, 26, 29, 47, 56], [6, 12, 15, 37, 45, 47, 50, 68], [9, 18, 23, 26, 39, 48, 50, 60]]target = [[38, 7, 32, 36, 16, 21, 53, 22], [50, 67, 28, 43, 15, 41, 44, 23], [12, 54, 16, 24, 58, 32, 30, 47]]
+Epoch 0: |                                                                             | 629/? [40:11<00:00,  0.26it/s, v_num=gbfj]train step 630; scene = [['dd3bbf1f7f832e83'], ['0ff7277275e55096'], ['5f45c360d76a3b12']]; loss = 0.043031
+Epoch 0: |                                                                             | 630/? [40:15<00:00,  0.26it/s, v_num=gbfj]context = [[29, 42, 44, 45, 76, 81, 87, 93], [77, 84, 94, 96, 100, 102, 121, 125], [67, 68, 70, 89, 90, 91, 96, 107]]target = [[83, 55, 36, 89, 45, 62, 90, 63], [106, 92, 114, 99, 117, 82, 119, 107], [99, 68, 75, 92, 79, 85, 101, 90]]
+Epoch 0: |                                                                             | 639/? [40:49<00:00,  0.26it/s, v_num=gbfj]train step 640; scene = [['867edbda9bb8ef59'], ['1d83764e77e159d8'], ['e318dafa4071cef9'], ['169f09c33ee35289']]; loss = 0.075569
+Epoch 0: |                                                                             | 640/? [40:53<00:00,  0.26it/s, v_num=gbfj]context = [[52, 57, 67, 75, 77, 80, 85, 86, 99, 105, 112, 117], [6, 11, 22, 23, 32, 39, 42, 47, 48, 53, 63, 64]]target = [[114, 60, 111, 110, 57, 69, 68, 80, 62, 99, 77, 90], [27, 15, 46, 56, 51, 60, 41, 63, 49, 16, 9, 43]]
+Epoch 0: |                                                                             | 649/? [41:27<00:00,  0.26it/s, v_num=gbfj]train step 650; scene = [['23668135f32e0126'], ['daca15248046e480'], ['174ebd189316bd92']]; loss = 0.041372
+Epoch 0: |                                                                             | 650/? [41:31<00:00,  0.26it/s, v_num=gbfj]context = [[6, 23, 25, 26, 28, 32, 37, 38, 39, 40, 50, 57], [0, 2, 3, 11, 17, 19, 24, 25, 38, 40, 45, 53]]target = [[15, 47, 23, 31, 12, 30, 20, 55, 33, 11, 22, 10], [51, 9, 13, 34, 52, 30, 26, 45, 38, 27, 11, 14]]
+Epoch 0: |                                                                             | 659/? [42:05<00:00,  0.26it/s, v_num=gbfj]train step 660; scene = [['60499200285c9abe']]; loss = 0.040887
+Epoch 0: |                                                                             | 660/? [42:09<00:00,  0.26it/s, v_num=gbfj]context = [[57, 65, 76, 86, 93, 99, 100, 122], [31, 34, 42, 47, 60, 80, 81, 83], [13, 16, 19, 30, 33, 49, 50, 55]]target = [[85, 75, 88, 114, 107, 70, 116, 79], [82, 35, 67, 56, 68, 61, 74, 58], [54, 44, 23, 36, 31, 39, 45, 28]]
+Epoch 0: |                                                                             | 669/? [42:42<00:00,  0.26it/s, v_num=gbfj]train step 670; scene = [['7665ff641f430aa5']]; loss = 0.036249
+Epoch 0: |                                                                             | 670/? [42:46<00:00,  0.26it/s, v_num=gbfj]context = [[50, 57, 61, 69, 82, 87, 98, 101], [26, 33, 44, 47, 53, 56, 62, 66], [11, 33, 39, 48, 56, 67, 75, 78]]target = [[67, 96, 71, 75, 73, 57, 55, 89], [65, 39, 63, 59, 60, 47, 55, 41], [18, 56, 21, 64, 32, 59, 33, 25]]
+Epoch 0: |                                                                             | 679/? [43:20<00:00,  0.26it/s, v_num=gbfj]train step 680; scene = [['43c939b11c5fed4a']]; loss = 0.072658
+Epoch 0: |                                                                             | 680/? [43:24<00:00,  0.26it/s, v_num=gbfj]context = [[47, 54, 60, 64, 79, 80, 83, 93], [12, 13, 21, 30, 34, 45, 53, 55], [57, 75, 78, 82, 96, 103, 113, 117]]target = [[80, 62, 75, 54, 57, 92, 53, 58], [38, 32, 15, 44, 42, 51, 27, 39], [81, 87, 106, 94, 99, 103, 73, 79]]
+Epoch 0: |                                                                             | 689/? [43:57<00:00,  0.26it/s, v_num=gbfj]train step 690; scene = [['1848b8b363d0d2b9'], ['afe6b05d0554a880']]; loss = 0.053185
+Epoch 0: |                                                                             | 690/? [44:01<00:00,  0.26it/s, v_num=gbfj]context = [[12, 18, 20, 27, 36, 37, 38, 43, 48, 49, 52, 58, 59, 62, 67, 81, 83, 86, 93, 95, 101, 104, 108, 109]]target = [[34, 24, 43, 31, 87, 30, 51, 54, 52, 94, 86, 21, 44, 97, 61, 95, 38, 60, 49, 73, 41, 19, 65, 67]]
+Epoch 0: |                                                                             | 699/? [44:35<00:00,  0.26it/s, v_num=gbfj]train step 700; scene = [['674ef9fb9cf20f9f'], ['8624ee0839cb6e4c'], ['caed302f388b799f']]; loss = 0.046981
+Epoch 0: |                                                                             | 700/? [44:38<00:00,  0.26it/s, v_num=gbfj]context = [[31, 32, 41, 46, 53, 54, 55, 57, 65, 68, 73, 74, 80, 85, 100, 105, 108, 109, 113, 114, 116, 118, 126, 128]]target = [[117, 52, 85, 57, 37, 45, 78, 100, 125, 35, 113, 66, 105, 103, 61, 83, 88, 40, 116, 60, 79, 32, 102, 107]]
+Epoch 0: |                                                                             | 709/? [45:12<00:00,  0.26it/s, v_num=gbfj]train step 710; scene = [['db6cd90de8fee2ff'], ['7a20ba81fb778529'], ['970350268b239272']]; loss = 0.049116
+Epoch 0: |                                                                             | 710/? [45:16<00:00,  0.26it/s, v_num=gbfj]context = [[3, 12, 16, 31, 41, 45, 49, 53, 54, 55, 67, 69], [208, 211, 217, 221, 222, 227, 230, 231, 239, 247, 252, 267]]target = [[38, 34, 68, 25, 44, 63, 48, 7, 42, 6, 64, 28], [228, 253, 259, 266, 244, 238, 249, 234, 232, 241, 220, 213]]
+Epoch 0: |                                                                             | 719/? [45:51<00:00,  0.26it/s, v_num=gbfj]train step 720; scene = [['f63d2df8871ce70c'], ['0fdeda15097ed4a4']]; loss = 0.041176
+Epoch 0: |                                                                             | 720/? [45:54<00:00,  0.26it/s, v_num=gbfj]context = [[55, 57, 71, 72, 75, 85, 90, 92, 98, 99, 102, 108, 112, 116, 125, 126, 130, 131, 135, 141, 144, 145, 146, 152]]target = [[61, 145, 86, 66, 62, 119, 100, 139, 105, 125, 58, 101, 140, 132, 118, 128, 65, 141, 151, 78, 104, 107, 150, 138]]
+Epoch 0: |                                                                             | 729/? [46:29<00:00,  0.26it/s, v_num=gbfj]train step 730; scene = [['232abb354c423e81'], ['d34926c73ae1277e']]; loss = 0.036067
+Epoch 0: |                                                                             | 730/? [46:33<00:00,  0.26it/s, v_num=gbfj]context = [[45, 50, 54, 58, 66, 70, 72, 78, 85, 88, 94, 105, 109, 110, 111, 117, 120, 122, 126, 127, 128, 133, 135, 142]]target = [[95, 96, 50, 114, 135, 124, 104, 100, 49, 119, 139, 62, 92, 123, 58, 46, 57, 112, 116, 90, 54, 101, 85, 81]]
+Epoch 0: |                                                                             | 739/? [47:07<00:00,  0.26it/s, v_num=gbfj]train step 740; scene = [['19f7966006ad778d'], ['dde0212418df7ca9'], ['ad75e36b74f6b033'], ['ea97e5ae55e56208'], ['9d29b0289133ab4e'], ['282938f90821bdef']]; loss = 0.095494
+Epoch 0: |                                                                             | 740/? [47:11<00:00,  0.26it/s, v_num=gbfj]context = [[8, 13, 19, 22, 30, 31, 36, 45, 46, 48, 54, 57, 58, 59, 60, 61, 65, 73, 77, 83, 86, 88, 93, 105]]target = [[46, 101, 90, 61, 31, 23, 37, 95, 18, 67, 32, 100, 93, 35, 89, 45, 10, 70, 60, 97, 85, 81, 66, 79]]
+Epoch 0: |                                                                             | 749/? [47:45<00:00,  0.26it/s, v_num=gbfj]train step 750; scene = [['f85921f42c5d98d7'], ['a95dacbd3ea3db36']]; loss = 0.038196
+Epoch 0: |                                                                             | 750/? [47:49<00:00,  0.26it/s, v_num=gbfj]Validation epoch start on rank 0
+Validation: |                                                                                                | 0/? [00:00<?, ?it/s]validation step 750; scene = ['91fda69e1cda4602'];
+target intrinsic:  tensor(0.8937, device='cuda:0') tensor(0.8939, device='cuda:0')                           | 0/1 [00:00<?, ?it/s]
+pred intrinsic:  tensor(0.8784, device='cuda:0') tensor(0.8798, device='cuda:0')
+[2026-02-25 11:27:57,672][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                             | 750/? [47:50<00:00,  0.26it/s, v_num=gbfj]context = [[1, 38, 46, 49, 52, 59], [213, 218, 227, 233, 252, 257], [99, 105, 109, 124, 125, 153], [8, 17, 20, 37, 62, 65]]target = [[54, 19, 39, 57, 7, 4], [252, 219, 223, 216, 248, 237], [148, 136, 102, 103, 149, 132], [12, 52, 13, 44, 63, 39]]
+Epoch 0: |                                                                             | 759/? [48:24<00:00,  0.26it/s, v_num=gbfj]train step 760; scene = [['75617c97bff1e873'], ['ff02f88545dfa566']]; loss = 0.032592
+Epoch 0: |                                                                             | 760/? [48:28<00:00,  0.26it/s, v_num=gbfj]context = [[71, 73, 111], [2, 14, 56], [29, 82, 88], [120, 144, 168], [181, 214, 250], [0, 10, 71], [12, 53, 54], [14, 27, 87]]target = [[101, 74, 84], [43, 51, 38], [82, 55, 72], [156, 139, 147], [198, 214, 207], [22, 5, 40], [36, 13, 39], [68, 35, 70]]
+Epoch 0: |                                                                             | 769/? [49:03<00:00,  0.26it/s, v_num=gbfj]train step 770; scene = [['62b0d4ee613af70f'], ['f7926eb1096de201'], ['c63b37ec347f0d0e'], ['b43d9f7c70f5caa0']]; loss = 0.071230
+Epoch 0: |                                                                             | 770/? [49:07<00:00,  0.26it/s, v_num=gbfj]context = [[13, 29, 30, 31, 32, 34, 41, 42, 46, 52, 63, 66], [146, 149, 157, 166, 177, 180, 181, 193, 197, 204, 211, 213]]target = [[35, 55, 52, 59, 24, 51, 63, 18, 42, 44, 33, 61], [183, 158, 171, 175, 163, 196, 177, 181, 210, 167, 187, 174]]
+Epoch 0: |                                                                             | 779/? [49:41<00:00,  0.26it/s, v_num=gbfj]train step 780; scene = [['b41f4db8b8a42a71']]; loss = 0.068812
+Epoch 0: |                                                                             | 780/? [49:45<00:00,  0.26it/s, v_num=gbfj]context = [[43, 50, 53, 55, 57, 58, 59, 60, 68, 81, 94, 96, 102, 106, 108, 110, 112, 121, 125, 126, 130, 131, 136, 140]]target = [[74, 122, 93, 98, 70, 84, 49, 136, 77, 117, 135, 138, 123, 89, 119, 45, 129, 105, 50, 58, 63, 103, 82, 121]]
+Epoch 0: |                                                                             | 789/? [50:19<00:00,  0.26it/s, v_num=gbfj]train step 790; scene = [['d79666d294813d8e']]; loss = 0.161711
+Epoch 0: |                                                                             | 790/? [50:23<00:00,  0.26it/s, v_num=gbfj]context = [[59, 79, 88, 93, 100, 107], [3, 16, 19, 31, 46, 51], [41, 49, 54, 56, 72, 83], [226, 229, 235, 244, 255, 272]]target = [[103, 98, 81, 75, 74, 72], [48, 44, 20, 31, 15, 46], [64, 82, 70, 50, 47, 60], [251, 249, 271, 250, 259, 260]]
+Epoch 0: |                                                                             | 799/? [50:57<00:00,  0.26it/s, v_num=gbfj]train step 800; scene = [['cb797cd30542e55c']]; loss = 0.052498
+Epoch 0: |                                                                             | 800/? [51:01<00:00,  0.26it/s, v_num=gbfj]context = [[10, 19, 20, 39, 42, 55], [1, 6, 11, 20, 30, 42], [0, 3, 4, 19, 42, 45], [21, 35, 52, 82, 85, 88]]target = [[38, 39, 26, 21, 37, 40], [11, 40, 18, 27, 3, 24], [43, 33, 8, 24, 5, 19], [83, 71, 66, 32, 63, 47]]
+[2026-02-25 11:31:13,251][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                             | 809/? [51:36<00:00,  0.26it/s, v_num=gbfj]train step 810; scene = [['9bd08fc9288bef8b']]; loss = 0.057839
+Epoch 0: |                                                                             | 810/? [51:40<00:00,  0.26it/s, v_num=gbfj]context = [[5, 6, 14, 17, 19, 23, 30, 37, 40, 49, 53, 55], [3, 6, 15, 17, 27, 34, 38, 40, 42, 46, 56, 65]]target = [[16, 8, 48, 23, 44, 49, 10, 7, 18, 50, 22, 15], [34, 18, 9, 42, 31, 38, 45, 26, 43, 6, 49, 44]]
+Epoch 0: |                                                                             | 819/? [52:15<00:00,  0.26it/s, v_num=gbfj]train step 820; scene = [['49952f737be91dd2']]; loss = 0.071786
+Epoch 0: |                                                                             | 820/? [52:19<00:00,  0.26it/s, v_num=gbfj]context = [[22, 23, 26, 28, 31, 43, 51, 53, 57, 65, 67, 68, 71, 76, 77, 78, 80, 84, 88, 90, 107, 112, 116, 119]]target = [[35, 45, 31, 72, 24, 71, 89, 54, 25, 61, 44, 97, 56, 47, 82, 87, 50, 110, 108, 75, 103, 67, 86, 117]]
+Epoch 0: |                                                                             | 829/? [52:51<00:00,  0.26it/s, v_num=gbfj]train step 830; scene = [['2f9c9d1b56eb7f75'], ['1c392cc98b3a7642']]; loss = 0.055692
+Epoch 0: |                                                                             | 830/? [52:55<00:00,  0.26it/s, v_num=gbfj]context = [[42, 67, 90, 119], [18, 54, 72, 90], [43, 67, 73, 102], [2, 22, 40, 43], [23, 40, 52, 67], [19, 37, 75, 78]]target = [[86, 112, 87, 94], [59, 40, 20, 47], [58, 97, 66, 77], [34, 19, 32, 17], [62, 37, 35, 54], [54, 22, 31, 50]]
+Epoch 0: |                                                                             | 839/? [53:29<00:00,  0.26it/s, v_num=gbfj]train step 840; scene = [['c51c7bc0c8151abb'], ['a0d16e79ab441c4f']]; loss = 0.094712
+Epoch 0: |                                                                             | 840/? [53:33<00:00,  0.26it/s, v_num=gbfj]context = [[1, 18, 22, 27, 29, 35, 38, 49], [3, 12, 30, 36, 43, 47, 54, 55], [17, 36, 55, 65, 72, 77, 86, 88]]target = [[5, 36, 48, 11, 2, 39, 35, 37], [6, 54, 43, 18, 30, 15, 10, 11], [52, 59, 56, 77, 25, 68, 22, 27]]
+Epoch 0: |                                                                             | 849/? [54:07<00:00,  0.26it/s, v_num=gbfj]train step 850; scene = [['818df63ddd1cf294'], ['3002f9cbe7f00e6c'], ['8ec42c5dfea6823b'], ['64ae75e57c6aa0a4']]; loss = 0.116672
+Epoch 0: |                                                                             | 850/? [54:11<00:00,  0.26it/s, v_num=gbfj]context = [[31, 75, 86], [20, 22, 73], [7, 55, 63], [3, 62, 68], [10, 43, 54], [52, 92, 111], [0, 34, 42], [51, 90, 102]]target = [[40, 57, 36], [39, 67, 34], [12, 9, 52], [29, 12, 39], [49, 13, 17], [106, 93, 85], [39, 20, 9], [79, 60, 53]]
+Epoch 0: |                                                                             | 859/? [54:45<00:00,  0.26it/s, v_num=gbfj]train step 860; scene = [['eb0aa1a4fb58c50c']]; loss = 0.037080
+Epoch 0: |                                                                             | 860/? [54:49<00:00,  0.26it/s, v_num=gbfj]context = [[147, 155, 165, 189, 194, 195], [9, 15, 44, 47, 49, 82], [5, 22, 23, 51, 61, 64], [97, 98, 140, 149, 160, 170]]target = [[194, 192, 155, 151, 174, 158], [22, 27, 54, 18, 81, 31], [25, 27, 29, 23, 6, 59], [137, 162, 98, 111, 152, 164]]
+Epoch 0: |                                                                             | 869/? [55:24<00:00,  0.26it/s, v_num=gbfj]train step 870; scene = [['c357fbd8aca05570']]; loss = 0.047145
+Epoch 0: |                                                                             | 870/? [55:28<00:00,  0.26it/s, v_num=gbfj]context = [[44, 45, 82, 100], [70, 93, 96, 147], [144, 176, 184, 205], [0, 51, 65, 67], [105, 106, 130, 152], [5, 6, 55, 60]]target = [[81, 66, 67, 97], [116, 118, 137, 91], [200, 193, 197, 176], [11, 13, 22, 32], [120, 117, 127, 130], [17, 14, 58, 27]]
+Epoch 0: |                                                                             | 879/? [56:02<00:00,  0.26it/s, v_num=gbfj]train step 880; scene = [['c672fa3960b73528'], ['a60e4127f167ac93'], ['a9739ec3a34012af']]; loss = 0.055690
+Epoch 0: |                                                                             | 880/? [56:06<00:00,  0.26it/s, v_num=gbfj]context = [[15, 85, 91], [0, 68, 74], [73, 85, 121], [4, 53, 80], [15, 36, 63], [42, 81, 92], [0, 45, 49], [65, 97, 132]]target = [[49, 21, 35], [47, 44, 69], [119, 89, 106], [57, 76, 6], [28, 32, 55], [62, 43, 49], [18, 44, 24], [90, 104, 71]]
+Epoch 0: |                                                                             | 889/? [56:39<00:00,  0.26it/s, v_num=gbfj]train step 890; scene = [['40a3f4f9389dd20c'], ['b14ec6f019932d8d'], ['4b9ed7532c875dab'], ['10c36bd5ef5f5a6b'], ['bc9a64096787007d'], ['d58a26d24f2776b2'], ['46f2228076e6f3f7'], ['399668567ff33ad7']]; loss = 0.062283
+Epoch 0: |                                                                             | 890/? [56:43<00:00,  0.26it/s, v_num=gbfj]context = [[32, 34, 35, 37, 39, 44, 52, 59, 73, 84, 87, 93], [20, 21, 22, 34, 43, 47, 52, 57, 64, 69, 72, 96]]target = [[87, 80, 41, 73, 35, 37, 86, 66, 72, 39, 50, 83], [28, 22, 50, 33, 26, 79, 75, 73, 29, 77, 60, 37]]
+Epoch 0: |                                                                             | 899/? [57:17<00:00,  0.26it/s, v_num=gbfj]train step 900; scene = [['711ade236bebd618']]; loss = 0.066008
+Epoch 0: |                                                                             | 900/? [57:21<00:00,  0.26it/s, v_num=gbfj]context = [[6, 7, 14, 15, 17, 19, 39, 43, 44, 45, 47, 48, 49, 53, 57, 61, 67, 69, 72, 73, 78, 90, 92, 103]]target = [[18, 19, 38, 66, 14, 96, 50, 55, 41, 57, 45, 83, 12, 100, 24, 53, 85, 40, 54, 58, 20, 44, 86, 95]]
+Epoch 0: |                                                                             | 909/? [57:55<00:00,  0.26it/s, v_num=gbfj]train step 910; scene = [['6b495ce9634d2fbb']]; loss = 0.076393
+Epoch 0: |                                                                             | 910/? [57:59<00:00,  0.26it/s, v_num=gbfj]context = [[59, 61, 62, 63, 73, 74, 77, 90, 100, 105, 111, 112], [8, 15, 18, 21, 26, 35, 37, 40, 41, 56, 68, 70]]target = [[76, 98, 64, 84, 69, 87, 100, 99, 67, 108, 77, 78], [22, 24, 41, 15, 45, 44, 34, 28, 13, 39, 11, 55]]
+Epoch 0: |                                                                             | 919/? [58:33<00:00,  0.26it/s, v_num=gbfj]train step 920; scene = [['013264a550df794f'], ['4203a06d618eeb97']]; loss = 0.106677
+Epoch 0: |                                                                             | 920/? [58:37<00:00,  0.26it/s, v_num=gbfj]context = [[14, 16, 18, 28, 30, 37, 45, 49, 50, 61, 63, 65], [97, 98, 114, 115, 121, 134, 137, 140, 143, 144, 169, 179]]target = [[38, 62, 50, 58, 42, 55, 57, 46, 43, 49, 56, 40], [158, 178, 130, 108, 145, 120, 168, 164, 156, 177, 125, 111]]
+Epoch 0: |                                                                             | 929/? [59:11<00:00,  0.26it/s, v_num=gbfj]train step 930; scene = [['5747f1d12ad10026'], ['48c9bb29482ddf76'], ['a45bddb856f554a1']]; loss = 0.044541
+Epoch 0: |                                                                             | 930/? [59:15<00:00,  0.26it/s, v_num=gbfj]context = [[0, 2, 12, 23, 26, 31, 35, 37, 41, 42, 44, 49], [164, 174, 179, 182, 184, 187, 189, 201, 202, 205, 207, 216]]target = [[33, 7, 10, 26, 44, 36, 39, 30, 43, 11, 38, 27], [214, 173, 176, 191, 182, 190, 175, 210, 215, 167, 195, 198]]
+Epoch 0: |                                                                             | 939/? [59:49<00:00,  0.26it/s, v_num=gbfj]train step 940; scene = [['db02cd4ba6a027da'], ['8f5e074629cedd06']]; loss = 0.044365
+Epoch 0: |                                                                             | 940/? [59:52<00:00,  0.26it/s, v_num=gbfj]context = [[127, 141, 154, 157, 160, 163, 172, 173, 189, 190, 192, 196], [6, 23, 36, 41, 46, 51, 57, 61, 65, 66, 83, 84]]target = [[157, 179, 153, 148, 161, 137, 194, 177, 128, 162, 166, 174], [38, 41, 32, 28, 8, 37, 36, 9, 77, 18, 80, 26]]
+Epoch 0: |                                                                           | 949/? [1:00:27<00:00,  0.26it/s, v_num=gbfj]train step 950; scene = [['5b98e84e8e7ffef0'], ['d7ca47da5fac7140'], ['eff98653337775a8'], ['ba00608cd351deb0']]; loss = 0.042423
+Epoch 0: |                                                                           | 950/? [1:00:31<00:00,  0.26it/s, v_num=gbfj]context = [[28, 33, 43, 46, 47, 51, 54, 67, 68, 72, 74, 75, 88, 90, 94, 98, 101, 102, 103, 105, 107, 113, 118, 125]]target = [[56, 59, 68, 66, 119, 65, 80, 100, 101, 39, 97, 94, 110, 62, 109, 40, 91, 42, 44, 78, 60, 73, 108, 50]]
+Epoch 0: |                                                                           | 959/? [1:01:06<00:00,  0.26it/s, v_num=gbfj]train step 960; scene = [['f6d65c637ff68de3'], ['9b4d466924c40d8b'], ['b6c9aa729ebc703e']]; loss = 0.076341
+Epoch 0: |                                                                           | 960/? [1:01:09<00:00,  0.26it/s, v_num=gbfj]context = [[2, 10, 11, 14, 19, 21, 23, 33, 39, 45, 49, 52, 53, 55, 58, 61, 71, 74, 80, 83, 84, 90, 94, 99]]target = [[41, 39, 14, 8, 52, 95, 19, 76, 24, 68, 75, 69, 22, 3, 47, 98, 17, 38, 89, 35, 21, 57, 45, 43]]
+Epoch 0: |                                                                           | 969/? [1:01:44<00:00,  0.26it/s, v_num=gbfj]train step 970; scene = [['4b6cbf1f4c87d918']]; loss = 0.033576
+Epoch 0: |                                                                           | 970/? [1:01:48<00:00,  0.26it/s, v_num=gbfj]context = [[20, 23, 30, 51, 53, 56, 60, 70], [145, 151, 184, 191, 192, 195, 215, 219], [36, 61, 63, 93, 106, 109, 111, 114]]target = [[52, 61, 27, 43, 44, 68, 67, 65], [210, 148, 165, 147, 166, 153, 170, 176], [108, 92, 76, 81, 71, 104, 41, 54]]
+Epoch 0: |                                                                           | 979/? [1:02:22<00:00,  0.26it/s, v_num=gbfj]train step 980; scene = [['0492d6125268e9ae']]; loss = 0.036096
+Epoch 0: |                                                                           | 980/? [1:02:26<00:00,  0.26it/s, v_num=gbfj]context = [[2, 4, 66, 70], [30, 96, 104, 105], [2, 13, 43, 65], [6, 42, 79, 91], [48, 85, 95, 96], [43, 62, 80, 101]]target = [[16, 66, 47, 53], [66, 42, 33, 84], [51, 25, 31, 53], [39, 90, 74, 16], [89, 80, 56, 68], [49, 45, 72, 48]]
+Epoch 0: |                                                                           | 989/? [1:03:01<00:00,  0.26it/s, v_num=gbfj]train step 990; scene = [['b0413d361b4e8abb']]; loss = 0.032310
+Epoch 0: |                                                                           | 990/? [1:03:05<00:00,  0.26it/s, v_num=gbfj]context = [[14, 19, 24, 29, 30, 38, 39, 40, 53, 57, 58, 65], [0, 1, 21, 33, 35, 38, 39, 43, 49, 58, 59, 64]]target = [[38, 37, 40, 27, 39, 45, 15, 52, 55, 22, 23, 31], [12, 42, 48, 30, 10, 58, 52, 59, 8, 46, 19, 44]]
+Epoch 0: |                                                                           | 999/? [1:03:38<00:00,  0.26it/s, v_num=gbfj]train step 1000; scene = [['2bf91de5cd028c93'], ['2abe932fd9d76528'], ['8fabc39ad677dece'], ['188398a54205f797']]; loss = 0.049565
+Epoch 0: |                                                                          | 1000/? [1:03:42<00:00,  0.26it/s, v_num=gbfj]Validation epoch start on rank 0
+Validation: |                                                                                                | 0/? [00:00<?, ?it/s]validation step 1000; scene = ['647f2049bf4cb3f3'];
+target intrinsic:  tensor(0.8998, device='cuda:0') tensor(0.9001, device='cuda:0')                           | 0/1 [00:00<?, ?it/s]
+pred intrinsic:  tensor(0.8738, device='cuda:0') tensor(0.8754, device='cuda:0')
+[2026-02-25 11:43:50,712][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                          | 1000/? [1:03:44<00:00,  0.26it/s, v_num=gbfj]context = [[176, 185, 186, 188, 208, 224, 228, 246], [0, 6, 9, 11, 37, 43, 46, 54], [0, 16, 23, 40, 41, 44, 55, 68]]target = [[205, 177, 207, 223, 188, 184, 231, 179], [7, 27, 9, 11, 39, 15, 12, 28], [38, 2, 54, 3, 25, 7, 37, 46]]
+[2026-02-25 11:43:54,528][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                          | 1009/? [1:04:19<00:00,  0.26it/s, v_num=gbfj]train step 1010; scene = [['3b42fa1245f6b00b'], ['c472581eb9a351cb'], ['222255ddcacd20cf'], ['b953af75bafccce8'], ['2c862f06019afc7e'], ['4178cb9ef3e0fd6d'], ['7f9480301fa3e38b'], ['8ccc9f1ead9cad5b']]; loss = 0.057068
+Epoch 0: |                                                                          | 1010/? [1:04:23<00:00,  0.26it/s, v_num=gbfj]context = [[0, 73], [12, 74], [41, 117], [34, 98], [3, 58], [117, 195], [117, 198], [33, 101], [0, 71], [45, 102], [36, 110], [82, 153]]target = [[44, 27], [42, 20], [116, 46], [88, 73], [5, 49], [190, 129], [127, 171], [75, 70], [61, 20], [97, 100], [51, 43], [151, 139]]
+Epoch 0: |                                                                          | 1019/? [1:04:56<00:00,  0.26it/s, v_num=gbfj]train step 1020; scene = [['3a95efa051965ee0']]; loss = 0.086429
+Epoch 0: |                                                                          | 1020/? [1:05:00<00:00,  0.26it/s, v_num=gbfj]context = [[8, 11, 13, 14, 15, 20, 21, 31, 34, 43, 46, 50, 55, 61, 71, 75, 76, 77, 81, 83, 85, 87, 93, 105]]target = [[83, 40, 76, 65, 29, 87, 84, 91, 31, 73, 50, 22, 38, 57, 99, 20, 19, 24, 26, 82, 36, 34, 44, 15]]
+Epoch 0: |                                                                          | 1029/? [1:05:35<00:00,  0.26it/s, v_num=gbfj]train step 1030; scene = [['6bd6d8270eee0b81'], ['2ac1cf1adda42447'], ['a017de2545c81e26'], ['4d5593ce15e317ed'], ['437188c182ae6a10'], ['86440d86f60644b7'], ['27508406fddac6dd'], ['7feae1e0e2c1701b'], ['a86dd7257f21bc73'], ['a025554e94654c2f'], ['20ee785f1bc6340d'], ['db6cd90de8fee2ff']]; loss = 0.097839
+Epoch 0: |                                                                          | 1030/? [1:05:39<00:00,  0.26it/s, v_num=gbfj]context = [[84, 89, 90, 91, 93, 111, 112, 113, 116, 117, 121, 126, 128, 134, 138, 139, 145, 153, 159, 161, 169, 173, 178, 181]]target = [[147, 138, 152, 92, 157, 97, 115, 154, 98, 113, 142, 137, 177, 165, 158, 146, 120, 139, 136, 122, 104, 85, 128, 144]]
+Epoch 0: |                                                                          | 1039/? [1:06:13<00:00,  0.26it/s, v_num=gbfj]train step 1040; scene = [['80fd51689742e978'], ['5eb07ee6a9e4fec2']]; loss = 0.049519
+Epoch 0: |                                                                          | 1040/? [1:06:17<00:00,  0.26it/s, v_num=gbfj]context = [[98, 99, 101, 110, 114, 116, 123, 126, 131, 137, 139, 150, 153, 155, 156, 158, 165, 177, 178, 184, 185, 187, 192, 195]]target = [[134, 141, 100, 117, 190, 107, 162, 158, 179, 192, 121, 151, 157, 139, 118, 175, 156, 183, 127, 167, 103, 172, 154, 116]]
+Epoch 0: |                                                                          | 1049/? [1:06:51<00:00,  0.26it/s, v_num=gbfj]train step 1050; scene = [['77dd1e7595b8f9a1']]; loss = 0.059777
+Epoch 0: |                                                                          | 1050/? [1:06:55<00:00,  0.26it/s, v_num=gbfj]context = [[114, 115, 118, 119, 124, 126, 130, 147, 149, 151, 158, 166, 169, 170, 173, 174, 177, 180, 191, 192, 203, 206, 208, 211]]target = [[209, 128, 160, 132, 164, 207, 201, 145, 117, 163, 120, 202, 151, 119, 124, 162, 189, 133, 184, 198, 153, 116, 188, 193]]
+Epoch 0: |                                                                          | 1059/? [1:07:29<00:00,  0.26it/s, v_num=gbfj]train step 1060; scene = [['51b6e63c903275b4'], ['2a9baa599c00613f'], ['1d7dc2d489714b09'], ['9f92d7e79d4a35bb']]; loss = 0.043058
+Epoch 0: |                                                                          | 1060/? [1:07:33<00:00,  0.26it/s, v_num=gbfj]context = [[15, 17, 24, 33, 36, 40, 69, 74, 77, 82, 83, 84], [1, 5, 9, 16, 25, 29, 32, 33, 44, 47, 49, 51]]target = [[41, 42, 50, 25, 44, 31, 43, 24, 81, 18, 26, 71], [45, 3, 37, 11, 42, 29, 49, 41, 17, 22, 39, 23]]
+Epoch 0: |                                                                          | 1069/? [1:08:08<00:00,  0.26it/s, v_num=gbfj]train step 1070; scene = [['a464ce7c8383dbbb']]; loss = 0.074656
+Epoch 0: |                                                                          | 1070/? [1:08:12<00:00,  0.26it/s, v_num=gbfj]context = [[6, 10, 28, 32, 57, 71, 89, 92], [34, 52, 65, 75, 88, 89, 114, 117], [119, 123, 131, 133, 137, 160, 180, 190]]target = [[90, 59, 62, 24, 52, 29, 47, 35], [72, 39, 106, 85, 58, 74, 77, 40], [188, 149, 156, 166, 161, 120, 125, 158]]
+Epoch 0: |                                                                          | 1079/? [1:08:46<00:00,  0.26it/s, v_num=gbfj]train step 1080; scene = [['b382af5f342061fa'], ['f6a0556897b15d6b']]; loss = 0.037185
+Epoch 0: |                                                                          | 1080/? [1:08:49<00:00,  0.26it/s, v_num=gbfj]context = [[127, 150, 162, 189], [25, 41, 98, 102], [6, 17, 20, 68], [24, 48, 78, 100], [154, 155, 175, 235], [41, 55, 86, 109]]target = [[180, 163, 148, 162], [45, 57, 100, 82], [16, 24, 44, 47], [50, 42, 47, 92], [206, 210, 196, 211], [80, 89, 82, 62]]
+Epoch 0: |                                                                          | 1089/? [1:09:24<00:00,  0.26it/s, v_num=gbfj]train step 1090; scene = [['5beb85aaf29d1242']]; loss = 0.062721
+Epoch 0: |                                                                          | 1090/? [1:09:28<00:00,  0.26it/s, v_num=gbfj]context = [[27, 37, 53, 65, 72, 76, 79, 83, 86, 97, 104, 109], [10, 17, 18, 32, 38, 45, 46, 52, 67, 68, 72, 79]]target = [[103, 63, 65, 74, 40, 85, 44, 107, 57, 58, 53, 29], [18, 61, 49, 74, 69, 21, 73, 59, 30, 67, 11, 43]]
+Epoch 0: |                                                                          | 1099/? [1:10:02<00:00,  0.26it/s, v_num=gbfj]train step 1100; scene = [['db811a2460c4f9b5'], ['7db8c4965bba509a'], ['a7a79393e5bb8108'], ['2d77b1dd90856337']]; loss = 0.070510
+Epoch 0: |                                                                          | 1100/? [1:10:06<00:00,  0.26it/s, v_num=gbfj]context = [[1, 10, 15, 20, 27, 35, 38, 44, 51, 52, 53, 70], [40, 44, 45, 46, 52, 54, 56, 63, 88, 95, 96, 98]]target = [[18, 63, 10, 69, 55, 26, 40, 21, 59, 51, 42, 48], [84, 92, 51, 54, 77, 50, 59, 47, 86, 43, 89, 87]]
+Epoch 0: |                                                                          | 1109/? [1:10:39<00:00,  0.26it/s, v_num=gbfj]train step 1110; scene = [['a815d5a5f2ec9562'], ['3be8c5ae6c95c9b4']]; loss = 0.042599
+Epoch 0: |                                                                          | 1110/? [1:10:43<00:00,  0.26it/s, v_num=gbfj]context = [[0, 2, 11, 15, 25, 28, 29, 32, 33, 35, 40, 44, 47, 49, 55, 56, 66, 72, 74, 84, 86, 88, 96, 97]]target = [[15, 85, 74, 83, 43, 47, 21, 40, 39, 66, 3, 26, 29, 9, 38, 23, 94, 36, 62, 19, 12, 44, 76, 31]]
+Epoch 0: |                                                                          | 1119/? [1:11:18<00:00,  0.26it/s, v_num=gbfj]train step 1120; scene = [['3ab1ce6779776017']]; loss = 0.084081
+Epoch 0: |                                                                          | 1120/? [1:11:22<00:00,  0.26it/s, v_num=gbfj]context = [[9, 16, 17, 21, 23, 30, 31, 43, 55, 57, 59, 61], [11, 25, 51, 66, 72, 76, 82, 87, 91, 94, 97, 99]]target = [[56, 22, 30, 35, 59, 36, 38, 23, 34, 11, 26, 51], [19, 73, 37, 71, 50, 43, 17, 80, 25, 54, 28, 24]]
+Epoch 0: |                                                                          | 1129/? [1:11:55<00:00,  0.26it/s, v_num=gbfj]train step 1130; scene = [['fd0ebd5afbfd1acf'], ['edf6636dfd51ba3c'], ['7b2c118f021e6902'], ['b3356e816a130b87'], ['78cbac3ff58f2e41'], ['94c654bd3e031bcb'], ['b281bf93286a0573'], ['d9dce3382830aea6'], ['070a524bacb9aa38'], ['cae0139a521aa052'], ['5645a008715acf0a'], ['23174a6cd65a0731']]; loss = 0.098991
+Epoch 0: |                                                                          | 1130/? [1:11:59<00:00,  0.26it/s, v_num=gbfj]context = [[8, 50, 81, 84], [2, 42, 44, 54], [25, 26, 79, 87], [25, 30, 88, 92], [45, 100, 129, 135], [17, 68, 77, 83]]target = [[62, 80, 76, 55], [11, 29, 39, 13], [42, 27, 75, 58], [31, 63, 29, 48], [72, 58, 93, 106], [66, 77, 60, 59]]
+Epoch 0: |                                                                          | 1139/? [1:12:33<00:00,  0.26it/s, v_num=gbfj]train step 1140; scene = [['090a038e9d844b4e'], ['d28a2455cc34badb']]; loss = 0.030675
+Epoch 0: |                                                                          | 1140/? [1:12:37<00:00,  0.26it/s, v_num=gbfj]context = [[19, 20, 28, 32, 34, 36, 38, 40, 52, 54, 63, 65, 68, 77, 78, 87, 94, 98, 100, 105, 107, 113, 114, 116]]target = [[32, 23, 97, 28, 51, 21, 114, 76, 46, 84, 74, 31, 98, 108, 77, 82, 72, 49, 103, 47, 80, 39, 59, 70]]
+Epoch 0: |                                                                          | 1149/? [1:13:12<00:00,  0.26it/s, v_num=gbfj]train step 1150; scene = [['82347d56a4a55c27'], ['ee03755cce11b682']]; loss = 0.064203
+Epoch 0: |                                                                          | 1150/? [1:13:16<00:00,  0.26it/s, v_num=gbfj]context = [[13, 16, 50, 52, 55, 62], [55, 56, 79, 89, 111, 117], [35, 43, 73, 74, 82, 85], [30, 56, 58, 80, 102, 108]]target = [[39, 59, 30, 34, 42, 27], [91, 98, 71, 70, 84, 68], [42, 44, 39, 68, 69, 50], [42, 68, 72, 55, 87, 51]]
+Epoch 0: |                                                                          | 1159/? [1:13:50<00:00,  0.26it/s, v_num=gbfj]train step 1160; scene = [['255998558abc7172']]; loss = 0.073919
+Epoch 0: |                                                                          | 1160/? [1:13:54<00:00,  0.26it/s, v_num=gbfj]context = [[13, 16, 18, 19, 21, 25, 28, 29, 36, 38, 43, 47, 49, 50, 53, 56, 67, 68, 69, 71, 72, 93, 108, 110]]target = [[47, 34, 77, 80, 28, 94, 97, 19, 29, 26, 68, 40, 53, 20, 60, 30, 92, 70, 83, 48, 106, 15, 63, 41]]
+Epoch 0: |                                                                          | 1169/? [1:14:28<00:00,  0.26it/s, v_num=gbfj]train step 1170; scene = [['771aa992eae9a574'], ['4f9716bb3dc7feec'], ['fbed2318ae410b31'], ['8e1b4054949b6a46']]; loss = 0.050381
+Epoch 0: |                                                                          | 1170/? [1:14:32<00:00,  0.26it/s, v_num=gbfj]context = [[207, 214, 223, 228, 242, 250, 268, 269], [35, 58, 71, 96, 97, 109, 110, 114], [0, 27, 28, 46, 50, 60, 68, 75]]target = [[216, 210, 265, 253, 237, 223, 241, 234], [105, 106, 100, 96, 73, 51, 109, 93], [2, 54, 60, 70, 28, 22, 51, 62]]
+Epoch 0: |                                                                          | 1179/? [1:15:07<00:00,  0.26it/s, v_num=gbfj]train step 1180; scene = [['18c880b4b5ef683e']]; loss = 0.067251
+Epoch 0: |                                                                          | 1180/? [1:15:11<00:00,  0.26it/s, v_num=gbfj]context = [[48, 60, 70, 80, 90, 109, 110, 114], [3, 8, 11, 23, 28, 34, 62, 82], [14, 17, 19, 24, 30, 34, 59, 67]]target = [[85, 101, 84, 113, 106, 74, 87, 98], [81, 68, 48, 46, 67, 69, 56, 22], [31, 33, 45, 20, 17, 61, 37, 44]]
+Epoch 0: |                                                                          | 1189/? [1:15:45<00:00,  0.26it/s, v_num=gbfj]train step 1190; scene = [['019fdd708d7163bd'], ['7046980b0d3d3c63'], ['f1af5d4039ce3a2c']]; loss = 0.055840
+Epoch 0: |                                                                          | 1190/? [1:15:49<00:00,  0.26it/s, v_num=gbfj]context = [[0, 7, 8, 11, 15, 20, 21, 28, 30, 33, 38, 42, 47, 54, 59, 63, 66, 71, 73, 79, 81, 88, 90, 97]]target = [[83, 9, 22, 57, 21, 76, 37, 10, 7, 13, 43, 47, 19, 6, 51, 71, 95, 78, 24, 92, 30, 28, 55, 84]]
+Epoch 0: |                                                                          | 1199/? [1:16:24<00:00,  0.26it/s, v_num=gbfj]train step 1200; scene = [['5070ea042c65de0d'], ['19f950b6900d6176'], ['02768fad99be3290'], ['ed6c9a5913622c3d'], ['0a4cbe699be68e5c'], ['0892e76375b283ba'], ['efd001b0d5127d61'], ['9adb745c741c85e0'], ['e4774e728791dc20'], ['23710dc8de8b4a49'], ['347d7c1f3516f732'], ['97283dc038203c65']]; loss = 0.184461
+Epoch 0: |                                                                          | 1200/? [1:16:28<00:00,  0.26it/s, v_num=gbfj]context = [[44, 48, 49, 54, 63, 66, 67, 70, 76, 77, 78, 84, 90, 100, 101, 105, 106, 111, 113, 116, 120, 123, 125, 141]]target = [[63, 111, 132, 61, 108, 104, 110, 81, 59, 89, 131, 126, 73, 100, 134, 74, 121, 84, 80, 51, 140, 133, 55, 83]]
+[2026-02-25 11:56:39,754][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                          | 1209/? [1:17:05<00:00,  0.26it/s, v_num=gbfj]train step 1210; scene = [['7ba6259f378c70f8']]; loss = 0.043222
+Epoch 0: |                                                                          | 1210/? [1:17:09<00:00,  0.26it/s, v_num=gbfj]context = [[77, 82, 86, 95, 101, 107, 111, 112, 113, 117, 120, 130], [9, 29, 33, 44, 49, 53, 54, 58, 67, 68, 81, 96]]target = [[99, 107, 90, 119, 117, 113, 92, 120, 121, 123, 86, 94], [32, 87, 79, 70, 51, 71, 33, 67, 53, 82, 41, 56]]
+Epoch 0: |                                                                          | 1219/? [1:17:43<00:00,  0.26it/s, v_num=gbfj]train step 1220; scene = [['0049c83bad21bbdf'], ['a73f4bf6ce8b2a00'], ['f7bef32e09ab061e'], ['175e1611df44964f']]; loss = 0.033200
+Epoch 0: |                                                                          | 1220/? [1:17:47<00:00,  0.26it/s, v_num=gbfj]context = [[44, 47, 55, 57, 65, 80, 85, 87, 88, 94, 112, 116], [25, 37, 49, 59, 61, 70, 82, 84, 86, 94, 97, 100]]target = [[96, 81, 62, 98, 79, 76, 52, 95, 59, 65, 56, 72], [34, 26, 32, 50, 44, 97, 67, 53, 75, 66, 59, 40]]
+Epoch 0: |                                                                          | 1229/? [1:18:22<00:00,  0.26it/s, v_num=gbfj]train step 1230; scene = [['342ff7b7111b53c1'], ['9ebe2434b1d68246'], ['b84cce034b55e1e4']]; loss = 0.042462
+Epoch 0: |                                                                          | 1230/? [1:18:26<00:00,  0.26it/s, v_num=gbfj]context = [[5, 8, 11, 16, 19, 23, 25, 34, 35, 36, 43, 49, 51, 57, 60, 68, 77, 78, 86, 88, 97, 98, 101, 102]]target = [[84, 48, 64, 18, 41, 19, 60, 25, 52, 49, 51, 50, 75, 38, 42, 81, 92, 32, 69, 67, 26, 100, 65, 61]]
+Epoch 0: |                                                                          | 1239/? [1:19:00<00:00,  0.26it/s, v_num=gbfj]train step 1240; scene = [['d7ac888a45c3c904'], ['60d988ddbc2d04f1'], ['617340307747e227'], ['969c91a2507e2d81'], ['af197296b340b564'], ['d488b5f08aadff0c']]; loss = 0.081841
+Epoch 0: |                                                                          | 1240/? [1:19:04<00:00,  0.26it/s, v_num=gbfj]context = [[9, 16, 18, 25, 28, 30, 41, 43, 46, 51, 53, 55, 56, 57, 59, 68, 71, 72, 74, 77, 87, 95, 105, 106]]target = [[72, 53, 26, 17, 11, 65, 42, 97, 60, 75, 93, 10, 45, 15, 102, 38, 101, 54, 23, 98, 13, 68, 16, 46]]
+Epoch 0: |                                                                          | 1249/? [1:19:38<00:00,  0.26it/s, v_num=gbfj]train step 1250; scene = [['d51d569c27d0b2b5'], ['e33b2a9076f25c4d'], ['2f330103819454c6'], ['944e92ff3fea78eb'], ['5a6387d05cd51e02'], ['2f269b68e14e256a'], ['55f1b82ae9c5571f'], ['1490c145692a1899'], ['b1b24b049d5a5da4'], ['834e851000651b8f'], ['4bc6b34a301aac73'], ['97caecafbfa7f1f6']]; loss = 0.104616
+Epoch 0: |                                                                          | 1250/? [1:19:42<00:00,  0.26it/s, v_num=gbfj]Validation epoch start on rank 0
+Validation: |                                                                                                | 0/? [00:00<?, ?it/s]validation step 1250; scene = ['70b0a33083333dc9'];
+target intrinsic:  tensor(0.8872, device='cuda:0') tensor(0.8874, device='cuda:0')                           | 0/1 [00:00<?, ?it/s]
+pred intrinsic:  tensor(0.8993, device='cuda:0') tensor(0.8994, device='cuda:0')
+[2026-02-25 11:59:50,137][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                          | 1250/? [1:19:43<00:00,  0.26it/s, v_num=gbfj]context = [[0, 2, 3, 7, 9, 14, 16, 19, 27, 30, 32, 34, 39, 43, 56, 62, 65, 73, 75, 80, 82, 85, 91, 97]]target = [[7, 68, 16, 60, 94, 67, 34, 41, 53, 11, 1, 12, 30, 6, 61, 76, 22, 32, 25, 81, 88, 33, 9, 45]]
+Epoch 0: |                                                                          | 1259/? [1:20:16<00:00,  0.26it/s, v_num=gbfj]train step 1260; scene = [['1a1f0a618bad5d30'], ['3046f14dad8f19f2'], ['8b4aecd7318912e3']]; loss = 0.048090
+Epoch 0: |                                                                          | 1260/? [1:20:20<00:00,  0.26it/s, v_num=gbfj]context = [[44, 48, 50, 51, 55, 60, 62, 66, 72, 78, 79, 85, 91, 98, 99, 100, 102, 112, 117, 121, 123, 125, 129, 141]]target = [[73, 109, 111, 54, 63, 69, 65, 124, 82, 119, 125, 110, 117, 56, 123, 86, 99, 126, 134, 53, 84, 112, 74, 100]]
+Epoch 0: |                                                                          | 1269/? [1:20:55<00:00,  0.26it/s, v_num=gbfj]train step 1270; scene = [['a0438ace9b7619cf'], ['336b3140d9d8bebd']]; loss = 0.075172
+Epoch 0: |                                                                          | 1270/? [1:20:59<00:00,  0.26it/s, v_num=gbfj]context = [[20, 22, 25, 26, 40, 44, 45, 51, 55, 63, 67, 70, 72, 76, 80, 81, 82, 84, 88, 96, 104, 109, 110, 117]]target = [[84, 115, 116, 28, 110, 27, 111, 85, 100, 39, 61, 63, 68, 56, 101, 113, 108, 94, 73, 62, 67, 98, 47, 55]]
+Epoch 0: |                                                                          | 1279/? [1:21:33<00:00,  0.26it/s, v_num=gbfj]train step 1280; scene = [['118f75d62c9a1f46'], ['3bcbf64a56113736'], ['6ca39802dcef328e'], ['0d754618c77e44f6']]; loss = 0.051803
+Epoch 0: |                                                                          | 1280/? [1:21:37<00:00,  0.26it/s, v_num=gbfj]context = [[5, 19, 21, 22, 26, 37, 47, 50, 53, 75, 85, 87], [4, 19, 23, 26, 29, 36, 37, 63, 69, 72, 75, 80]]target = [[65, 33, 14, 32, 52, 25, 54, 34, 15, 6, 60, 30], [11, 5, 9, 35, 70, 15, 51, 38, 20, 42, 68, 22]]
+Epoch 0: |                                                                          | 1289/? [1:22:10<00:00,  0.26it/s, v_num=gbfj]train step 1290; scene = [['4738c57794aa47f8']]; loss = 0.051556
+Epoch 0: |                                                                          | 1290/? [1:22:14<00:00,  0.26it/s, v_num=gbfj]context = [[1, 4, 14, 17, 27, 30, 32, 37, 44, 52, 64, 80], [0, 8, 12, 14, 24, 28, 29, 37, 49, 54, 56, 67]]target = [[64, 28, 44, 35, 23, 68, 42, 61, 3, 77, 52, 14], [1, 11, 56, 59, 13, 63, 55, 61, 38, 9, 18, 37]]
+Epoch 0: |                                                                          | 1299/? [1:22:49<00:00,  0.26it/s, v_num=gbfj]train step 1300; scene = [['f18e524ab2d288c3'], ['9dff9a317da1d49d'], ['11a87d6d490e024d']]; loss = 0.037604
+Epoch 0: |                                                                          | 1300/? [1:22:52<00:00,  0.26it/s, v_num=gbfj]context = [[5, 6, 8, 12, 30, 45, 58, 64, 65, 75, 79, 85], [22, 26, 27, 28, 39, 45, 47, 55, 56, 57, 66, 72]]target = [[34, 57, 32, 7, 11, 58, 73, 68, 83, 14, 61, 55], [42, 34, 36, 47, 33, 67, 31, 30, 50, 27, 24, 58]]
+Epoch 0: |                                                                          | 1309/? [1:23:26<00:00,  0.26it/s, v_num=gbfj]train step 1310; scene = [['589e362118b32d25'], ['d13522abd38eddfe'], ['f1657c6128d2b332'], ['1cb3ecb30e3e9d0e'], ['827c5f3b3886553d'], ['4d27fb96530fe02b']]; loss = 0.098528
+Epoch 0: |                                                                          | 1310/? [1:23:30<00:00,  0.26it/s, v_num=gbfj]context = [[20, 21, 27, 31, 36, 40, 48, 51, 55, 62, 69, 72, 74, 75, 83, 89, 96, 97, 99, 104, 105, 106, 114, 117]]target = [[57, 113, 99, 80, 42, 30, 24, 74, 34, 52, 63, 59, 100, 101, 76, 36, 105, 66, 55, 27, 84, 22, 79, 86]]
+Epoch 0: |                                                                          | 1319/? [1:24:05<00:00,  0.26it/s, v_num=gbfj]train step 1320; scene = [['c21766bd51fed5bc'], ['47a2a8b326b9f40e'], ['d0c0d78936b6e5ce'], ['e0ee3878561a5fed']]; loss = 0.057211
+Epoch 0: |                                                                          | 1320/? [1:24:08<00:00,  0.26it/s, v_num=gbfj]context = [[194, 242], [34, 99], [51, 136], [156, 207], [36, 100], [0, 48], [10, 99], [22, 79], [18, 99], [2, 74], [39, 128], [201, 272]]target = [[225, 201], [63, 36], [58, 72], [193, 181], [39, 77], [13, 1], [29, 68], [36, 58], [45, 66], [58, 18], [100, 50], [234, 262]]
+Epoch 0: |                                                                          | 1329/? [1:24:42<00:00,  0.26it/s, v_num=gbfj]train step 1330; scene = [['07fdb102ee3677f5']]; loss = 0.047636
+Epoch 0: |                                                                          | 1330/? [1:24:46<00:00,  0.26it/s, v_num=gbfj]context = [[20, 23, 28, 29, 37, 43, 49, 53, 56, 57, 61, 65, 69, 70, 80, 92, 98, 102, 103, 104, 106, 108, 116, 117]]target = [[37, 57, 73, 79, 30, 102, 42, 115, 86, 33, 28, 25, 114, 53, 76, 107, 36, 106, 52, 49, 59, 66, 61, 101]]
+Epoch 0: |                                                                          | 1339/? [1:25:21<00:00,  0.26it/s, v_num=gbfj]train step 1340; scene = [['2ff4f3b2475e0e8c'], ['db062134f9dec5f1']]; loss = 0.033567
+Epoch 0: |                                                                          | 1340/? [1:25:24<00:00,  0.26it/s, v_num=gbfj]context = [[20, 22, 50, 84], [0, 36, 48, 51], [10, 38, 52, 66], [0, 24, 25, 53], [0, 4, 19, 45], [54, 57, 73, 112]]target = [[42, 28, 78, 23], [3, 12, 46, 44], [57, 60, 15, 41], [47, 3, 31, 2], [42, 13, 23, 28], [102, 69, 98, 70]]
+Epoch 0: |                                                                          | 1349/? [1:25:58<00:00,  0.26it/s, v_num=gbfj]train step 1350; scene = [['87e1164e050e9686'], ['3803b2c8fd539a88']]; loss = 0.064285
+Epoch 0: |                                                                          | 1350/? [1:26:02<00:00,  0.26it/s, v_num=gbfj]context = [[52, 53, 55, 63, 64, 66, 74, 75, 77, 79, 85, 89, 90, 99, 121, 122, 123, 126, 133, 134, 135, 136, 147, 149]]target = [[99, 80, 109, 136, 92, 134, 112, 76, 135, 68, 116, 138, 54, 145, 144, 143, 61, 72, 102, 77, 90, 85, 139, 58]]
+Epoch 0: |                                                                          | 1359/? [1:26:37<00:00,  0.26it/s, v_num=gbfj]train step 1360; scene = [['7db4ed902d003a63']]; loss = 0.068900
+Epoch 0: |                                                                          | 1360/? [1:26:41<00:00,  0.26it/s, v_num=gbfj]context = [[13, 26, 58, 83], [117, 127, 165, 171], [12, 45, 50, 66], [21, 23, 67, 101], [26, 34, 95, 97], [42, 73, 81, 98]]target = [[65, 36, 43, 27], [124, 136, 141, 132], [33, 37, 62, 29], [82, 90, 80, 97], [45, 44, 32, 86], [55, 82, 58, 89]]
+Epoch 0: |                                                                          | 1369/? [1:27:15<00:00,  0.26it/s, v_num=gbfj]train step 1370; scene = [['36df585860d0ad88']]; loss = 0.036591
+Epoch 0: |                                                                          | 1370/? [1:27:19<00:00,  0.26it/s, v_num=gbfj]context = [[41, 42, 45, 55, 59, 62, 67, 68, 69, 73, 79, 87, 90, 94, 104, 114, 117, 120, 121, 125, 128, 130, 135, 138]]target = [[79, 103, 135, 133, 104, 59, 92, 71, 62, 66, 61, 109, 68, 124, 74, 54, 44, 46, 57, 96, 108, 58, 85, 83]]
+Epoch 0: |                                                                          | 1379/? [1:27:53<00:00,  0.26it/s, v_num=gbfj]train step 1380; scene = [['256ae648672281d1'], ['7043e8afce176c8c']]; loss = 0.067624
+Epoch 0: |                                                                          | 1380/? [1:27:57<00:00,  0.26it/s, v_num=gbfj]context = [[31, 33, 48, 63, 106, 115], [8, 28, 29, 44, 67, 97], [65, 72, 100, 110, 115, 124], [8, 9, 63, 70, 75, 79]]target = [[57, 76, 83, 113, 107, 38], [51, 64, 72, 39, 18, 77], [89, 108, 95, 114, 84, 116], [20, 59, 14, 56, 15, 38]]
+Epoch 0: |                                                                          | 1389/? [1:28:31<00:00,  0.26it/s, v_num=gbfj]train step 1390; scene = [['ca65a604c0f00319'], ['937ea87bb5a2047f'], ['a2b430d7bec915d8'], ['c8c116c28ca108b0']]; loss = 0.038120
+Epoch 0: |                                                                          | 1390/? [1:28:35<00:00,  0.26it/s, v_num=gbfj]context = [[0, 3, 5, 26, 31, 34, 38, 40, 44, 53, 62, 70], [1, 4, 21, 29, 36, 37, 39, 44, 52, 54, 59, 64]]target = [[36, 5, 37, 41, 54, 19, 44, 21, 40, 34, 59, 32], [59, 51, 53, 46, 27, 9, 21, 52, 24, 54, 32, 48]]
+Epoch 0: |                                                                          | 1399/? [1:29:08<00:00,  0.26it/s, v_num=gbfj]train step 1400; scene = [['73fef5139753e974'], ['4b3e117d4f50b167'], ['0e916e63743f841b']]; loss = 0.049706
+Epoch 0: |                                                                          | 1400/? [1:29:12<00:00,  0.26it/s, v_num=gbfj]context = [[23, 26, 27, 29, 31, 32, 41, 47, 49, 50, 55, 56, 58, 71, 77, 78, 87, 91, 97, 100, 101, 102, 113, 120]]target = [[55, 52, 103, 28, 68, 66, 49, 93, 76, 109, 105, 112, 100, 101, 31, 70, 64, 116, 77, 56, 46, 48, 32, 85]]
+[2026-02-25 12:09:23,940][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                          | 1409/? [1:29:51<00:00,  0.26it/s, v_num=gbfj]train step 1410; scene = [['d9ce9620cf31e776'], ['36bf8b485c1284dd']]; loss = 0.046727
+Epoch 0: |                                                                          | 1410/? [1:29:55<00:00,  0.26it/s, v_num=gbfj]context = [[44, 47, 51, 55, 57, 59, 61, 62, 68, 72, 78, 80, 82, 88, 91, 97, 109, 112, 116, 118, 135, 138, 140, 141]]target = [[54, 91, 112, 61, 115, 80, 93, 45, 105, 51, 131, 102, 55, 60, 57, 136, 129, 99, 125, 113, 84, 89, 58, 65]]
+Epoch 0: |                                                                          | 1419/? [1:30:29<00:00,  0.26it/s, v_num=gbfj]train step 1420; scene = [['df4e1717577f82c1'], ['50b38521b86dd7b6'], ['e4fc6fa4bbd6efa1'], ['54d3668b6c7ed4b8']]; loss = 0.033414
+Epoch 0: |                                                                          | 1420/? [1:30:33<00:00,  0.26it/s, v_num=gbfj]context = [[38, 43, 53, 54, 68, 87, 97, 101], [52, 53, 74, 84, 86, 96, 132, 133], [157, 173, 184, 190, 200, 203, 210, 211]]target = [[77, 71, 57, 46, 97, 67, 93, 96], [83, 127, 75, 122, 56, 78, 130, 107], [177, 183, 188, 174, 191, 203, 200, 170]]
+Epoch 0: |                                                                          | 1429/? [1:31:08<00:00,  0.26it/s, v_num=gbfj]train step 1430; scene = [['e70c21625fceaebd'], ['4cfdc3ed984caecf'], ['dfc00f3016d34131'], ['f5338d00f9c021a3'], ['89fbc4149a5d7348'], ['d2d3474ebd2be7e8'], ['0b42b8cf14bd1e13'], ['358a2d1387de3df8'], ['abe463f94db2c398'], ['d35b7c2c52c45a54'], ['12f629409a280733'], ['6b09a022387bd762']]; loss = 0.093309
+Epoch 0: |                                                                          | 1430/? [1:31:12<00:00,  0.26it/s, v_num=gbfj]context = [[146, 159, 179, 187, 191, 200], [3, 11, 37, 39, 40, 48], [3, 16, 25, 27, 47, 49], [31, 36, 39, 84, 87, 94]]target = [[154, 176, 156, 190, 172, 150], [13, 36, 28, 46, 33, 32], [33, 7, 23, 32, 20, 35], [53, 82, 44, 85, 38, 54]]
+Epoch 0: |                                                                          | 1439/? [1:31:46<00:00,  0.26it/s, v_num=gbfj]train step 1440; scene = [['83f69d126eb1528d'], ['e92e4346a6224492']]; loss = 0.034106
+Epoch 0: |                                                                          | 1440/? [1:31:50<00:00,  0.26it/s, v_num=gbfj]context = [[1, 19, 33, 39, 51, 53, 57, 61], [4, 18, 19, 43, 44, 47, 49, 75], [40, 51, 69, 84, 88, 93, 99, 104]]target = [[3, 30, 34, 24, 46, 8, 13, 4], [19, 24, 28, 56, 55, 10, 66, 21], [54, 88, 79, 100, 81, 84, 83, 72]]
+Epoch 0: |                                                                          | 1449/? [1:32:25<00:00,  0.26it/s, v_num=gbfj]train step 1450; scene = [['c05fd148d2da6d26'], ['b49cc4ec7c6b0050'], ['0d158225b3c47682']]; loss = 0.065137
+Epoch 0: |                                                                          | 1450/? [1:32:29<00:00,  0.26it/s, v_num=gbfj]context = [[2, 15, 27, 38, 41, 50, 51, 57, 58, 61, 62, 73], [16, 17, 19, 26, 41, 44, 80, 89, 90, 92, 100, 101]]target = [[37, 21, 47, 67, 70, 31, 10, 57, 34, 30, 50, 52], [84, 77, 99, 81, 19, 59, 24, 78, 64, 25, 30, 90]]
+Epoch 0: |                                                                          | 1459/? [1:33:02<00:00,  0.26it/s, v_num=gbfj]train step 1460; scene = [['8d583bfb265295b9']]; loss = 0.054825
+Epoch 0: |                                                                          | 1460/? [1:33:06<00:00,  0.26it/s, v_num=gbfj]context = [[143, 146, 157, 160, 179, 202], [1, 13, 19, 36, 45, 46], [175, 189, 227, 237, 252, 257], [22, 29, 47, 51, 54, 67]]target = [[156, 146, 191, 160, 196, 187], [28, 40, 8, 23, 33, 44], [234, 248, 199, 178, 220, 226], [38, 63, 50, 35, 66, 33]]
+Epoch 0: |                                                                          | 1469/? [1:33:41<00:00,  0.26it/s, v_num=gbfj]train step 1470; scene = [['6ebab888069161eb']]; loss = 0.040546
+Epoch 0: |                                                                          | 1470/? [1:33:45<00:00,  0.26it/s, v_num=gbfj]context = [[28, 29, 32, 37, 43, 46, 50, 65, 67, 71, 76, 77], [132, 133, 136, 137, 140, 141, 145, 147, 169, 171, 200, 204]]target = [[31, 53, 62, 64, 65, 67, 34, 72, 39, 58, 57, 68], [174, 172, 164, 145, 162, 199, 202, 142, 163, 159, 176, 200]]
+Epoch 0: |                                                                          | 1479/? [1:34:19<00:00,  0.26it/s, v_num=gbfj]train step 1480; scene = [['964d888d8d08f2aa'], ['58901334e2d813d9'], ['ea4146e3386ff1ac']]; loss = 0.085042
+Epoch 0: |                                                                          | 1480/? [1:34:23<00:00,  0.26it/s, v_num=gbfj]context = [[50, 57, 67, 77, 79, 101], [66, 67, 75, 83, 96, 117], [53, 65, 70, 81, 130, 138], [19, 45, 53, 57, 65, 66]]target = [[76, 85, 70, 53, 90, 65], [87, 116, 103, 85, 111, 97], [80, 116, 87, 117, 54, 112], [35, 47, 59, 51, 53, 28]]
+Epoch 0: |                                                                          | 1489/? [1:34:57<00:00,  0.26it/s, v_num=gbfj]train step 1490; scene = [['f73db02fdfe72073'], ['a4eeae8de8e2e98e']]; loss = 0.032256
+Epoch 0: |                                                                          | 1490/? [1:35:00<00:00,  0.26it/s, v_num=gbfj]context = [[10, 19, 23, 29, 35, 40, 41, 42, 43, 53, 54, 57, 63, 65, 66, 69, 72, 73, 77, 84, 91, 94, 95, 107]]target = [[97, 79, 11, 35, 65, 87, 80, 51, 32, 13, 83, 72, 85, 34, 105, 92, 59, 25, 81, 40, 36, 82, 88, 15]]
+Epoch 0: |                                                                          | 1499/? [1:35:35<00:00,  0.26it/s, v_num=gbfj]train step 1500; scene = [['fa1ddac84aafd9b7']]; loss = 0.150276
+Epoch 0: |                                                                          | 1500/? [1:35:38<00:00,  0.26it/s, v_num=gbfj]Validation epoch start on rank 0
+Validation: |                                                                                                | 0/? [00:00<?, ?it/s]validation step 1500; scene = ['45592a7f307bccd0'];
+target intrinsic:  tensor(0.8508, device='cuda:0') tensor(0.8510, device='cuda:0')                           | 0/1 [00:00<?, ?it/s]
+pred intrinsic:  tensor(0.8643, device='cuda:0') tensor(0.8638, device='cuda:0')
+[2026-02-25 12:16:01,606][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                          | 1500/? [1:35:54<00:00,  0.26it/s, v_num=gbfj]context = [[5, 10, 19, 23, 27, 33, 40, 57, 60, 63, 64, 68], [97, 102, 107, 111, 113, 120, 137, 148, 157, 163, 168, 169]]target = [[54, 31, 25, 44, 17, 36, 32, 65, 16, 11, 23, 38], [99, 138, 103, 159, 164, 104, 123, 135, 120, 124, 130, 148]]
+Epoch 0: |                                                                          | 1509/? [1:36:27<00:00,  0.26it/s, v_num=gbfj]train step 1510; scene = [['289a0ef9678c7c70'], ['f4fd1fee2a8f69ee'], ['a88b44d03528e2f2']]; loss = 0.043046
+Epoch 0: |                                                                          | 1510/? [1:36:31<00:00,  0.26it/s, v_num=gbfj]context = [[1, 2, 8, 18, 19, 27, 33, 35, 48, 49, 63, 77], [0, 9, 12, 15, 20, 22, 23, 30, 34, 58, 66, 68]]target = [[12, 51, 13, 69, 65, 38, 6, 30, 37, 18, 53, 2], [8, 14, 60, 49, 63, 46, 47, 3, 35, 13, 21, 44]]
+Epoch 0: |                                                                          | 1519/? [1:37:04<00:00,  0.26it/s, v_num=gbfj]train step 1520; scene = [['85cff5568e6f52e7'], ['9de970f9a14770a9'], ['a08eb87db37b694a'], ['0a8fda80930b52ae']]; loss = 0.044504
+Epoch 0: |                                                                          | 1520/? [1:37:08<00:00,  0.26it/s, v_num=gbfj]context = [[6, 32, 33, 39, 62, 69, 77, 96], [32, 33, 42, 61, 83, 93, 99, 107], [13, 27, 41, 70, 78, 84, 86, 93]]target = [[28, 30, 62, 7, 57, 86, 77, 36], [101, 43, 41, 68, 46, 36, 47, 105], [27, 16, 29, 71, 40, 45, 74, 65]]
+Epoch 0: |                                                                          | 1529/? [1:37:42<00:00,  0.26it/s, v_num=gbfj]train step 1530; scene = [['43cc195276cf0c56']]; loss = 0.081403
+Epoch 0: |                                                                          | 1530/? [1:37:46<00:00,  0.26it/s, v_num=gbfj]context = [[86, 89, 91, 102, 109, 136, 173, 175], [1, 12, 32, 33, 36, 37, 43, 47], [15, 24, 40, 41, 44, 70, 73, 102]]target = [[138, 158, 117, 118, 170, 120, 165, 133], [37, 44, 31, 32, 24, 9, 40, 38], [16, 27, 88, 46, 69, 52, 73, 44]]
+Epoch 0: |                                                                          | 1539/? [1:38:20<00:00,  0.26it/s, v_num=gbfj]train step 1540; scene = [['4b7f3f58b0838d38']]; loss = 0.035697
+Epoch 0: |                                                                          | 1540/? [1:38:24<00:00,  0.26it/s, v_num=gbfj]context = [[17, 21, 24, 40, 42, 44, 49, 50, 60, 62, 63, 64, 65, 72, 73, 76, 77, 85, 89, 93, 96, 104, 108, 114]]target = [[104, 84, 41, 96, 107, 103, 94, 44, 111, 97, 83, 54, 100, 57, 27, 38, 113, 29, 18, 99, 76, 101, 55, 36]]
+Epoch 0: |                                                                          | 1549/? [1:38:59<00:00,  0.26it/s, v_num=gbfj]train step 1550; scene = [['d6cc1a3af543a7f8'], ['f3dd12e8d9dd4c20'], ['b74b90e3a87f285c'], ['c51f5219c3d09e33'], ['3f6666062c86b73a'], ['3b7bd7e723f069b2'], ['b3992ad0aff60272'], ['30d52bc66d89221d']]; loss = 0.053549
+Epoch 0: |                                                                          | 1550/? [1:39:03<00:00,  0.26it/s, v_num=gbfj]context = [[9, 79], [29, 75], [29, 95], [124, 170], [42, 102], [92, 159], [94, 157], [6, 75], [188, 255], [5, 76], [133, 205], [2, 90]]target = [[55, 20], [47, 52], [85, 42], [136, 147], [97, 56], [158, 99], [145, 143], [17, 9], [199, 198], [34, 26], [184, 165], [39, 28]]
+Epoch 0: |                                                                          | 1559/? [1:39:38<00:00,  0.26it/s, v_num=gbfj]train step 1560; scene = [['f6a87eade96cceb1']]; loss = 0.042426
+Epoch 0: |                                                                          | 1560/? [1:39:42<00:00,  0.26it/s, v_num=gbfj]context = [[9, 17, 23, 26, 33, 40, 46, 62, 63, 68, 69, 71], [117, 126, 137, 140, 146, 163, 169, 173, 178, 186, 201, 205]]target = [[25, 36, 53, 31, 59, 20, 68, 24, 66, 13, 33, 67], [128, 179, 169, 126, 188, 187, 122, 127, 144, 165, 150, 119]]
+Epoch 0: |                                                                          | 1569/? [1:40:15<00:00,  0.26it/s, v_num=gbfj]train step 1570; scene = [['ab1c5358d3bb05db']]; loss = 0.033228
+Epoch 0: |                                                                          | 1570/? [1:40:19<00:00,  0.26it/s, v_num=gbfj]context = [[6, 8, 14, 38, 44, 69, 83, 89], [31, 47, 49, 50, 68, 77, 89, 91], [32, 46, 50, 61, 66, 84, 89, 100]]target = [[69, 79, 13, 31, 70, 24, 8, 27], [53, 42, 44, 68, 90, 65, 87, 49], [85, 91, 86, 84, 67, 83, 72, 92]]
+Epoch 0: |                                                                          | 1579/? [1:40:52<00:00,  0.26it/s, v_num=gbfj]train step 1580; scene = [['572357b6b69cb9ec'], ['326dd7b41ce515ac']]; loss = 0.038748
+Epoch 0: |                                                                          | 1580/? [1:40:56<00:00,  0.26it/s, v_num=gbfj]context = [[26, 32, 46, 57, 64, 105], [32, 38, 66, 84, 85, 95], [75, 87, 98, 106, 108, 130], [7, 9, 12, 20, 48, 60]]target = [[83, 29, 52, 46, 45, 39], [41, 73, 88, 76, 54, 82], [78, 99, 126, 113, 86, 105], [29, 45, 35, 34, 32, 16]]
+Epoch 0: |                                                                          | 1589/? [1:41:31<00:00,  0.26it/s, v_num=gbfj]train step 1590; scene = [['4558408811e71246'], ['4a3ff4b7939ec268']]; loss = 0.066115
+Epoch 0: |                                                                          | 1590/? [1:41:35<00:00,  0.26it/s, v_num=gbfj]context = [[187, 198, 222, 224, 227, 240], [196, 213, 228, 234, 257, 263], [15, 24, 48, 51, 62, 85], [64, 73, 82, 83, 109, 117]]target = [[231, 221, 188, 222, 220, 232], [257, 228, 261, 254, 244, 210], [45, 49, 23, 62, 65, 84], [74, 94, 93, 85, 66, 104]]
+Epoch 0: |                                                                          | 1599/? [1:42:09<00:00,  0.26it/s, v_num=gbfj]train step 1600; scene = [['1849a41079039a3a']]; loss = 0.045751
+Epoch 0: |                                                                          | 1600/? [1:42:12<00:00,  0.26it/s, v_num=gbfj]context = [[7, 10, 13, 17, 18, 30, 32, 34, 35, 38, 42, 49, 64, 66, 71, 74, 77, 84, 89, 91, 93, 95, 103, 104]]target = [[52, 78, 50, 26, 46, 43, 79, 25, 89, 70, 58, 18, 103, 98, 16, 74, 20, 13, 85, 96, 71, 76, 91, 34]]
+[2026-02-25 12:22:24,120][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                          | 1609/? [1:42:53<00:00,  0.26it/s, v_num=gbfj]train step 1610; scene = [['6405acc04d687493'], ['a802441c288b598f'], ['e2a52c2d94f21d4d']]; loss = 0.055257
+Epoch 0: |                                                                          | 1610/? [1:42:56<00:00,  0.26it/s, v_num=gbfj]context = [[110, 111, 116, 122, 133, 134, 135, 143, 145, 148, 155, 167, 173, 177, 178, 180, 181, 183, 192, 193, 197, 199, 203, 207]]target = [[137, 115, 169, 197, 176, 116, 146, 159, 144, 119, 129, 161, 181, 160, 151, 196, 131, 204, 201, 157, 138, 123, 180, 117]]
+Epoch 0: |                                                                          | 1619/? [1:43:31<00:00,  0.26it/s, v_num=gbfj]train step 1620; scene = [['a270004198eddd9b'], ['cc306ca65c5dbc24'], ['1a5022549d2718ae'], ['cdde30f3352829cb']]; loss = 0.054518
+Epoch 0: |                                                                          | 1620/? [1:43:35<00:00,  0.26it/s, v_num=gbfj]context = [[72, 79, 103, 136], [6, 15, 31, 60], [1, 48, 52, 80], [95, 135, 145, 162], [136, 166, 176, 206], [0, 7, 45, 61]]target = [[90, 120, 96, 123], [15, 25, 11, 32], [5, 49, 65, 22], [116, 131, 128, 139], [144, 141, 183, 190], [34, 48, 35, 12]]
+Epoch 0: |                                                                          | 1629/? [1:44:09<00:00,  0.26it/s, v_num=gbfj]train step 1630; scene = [['22c6139e04c88c0c']]; loss = 0.035687
+Epoch 0: |                                                                          | 1630/? [1:44:13<00:00,  0.26it/s, v_num=gbfj]context = [[5, 7, 10, 22, 36, 52], [7, 11, 21, 27, 46, 72], [0, 50, 64, 79, 88, 90], [4, 24, 28, 39, 44, 49]]target = [[41, 40, 13, 50, 28, 25], [39, 20, 47, 50, 25, 55], [75, 69, 56, 70, 5, 13], [27, 35, 24, 13, 14, 40]]
+Epoch 0: |                                                                          | 1639/? [1:44:48<00:00,  0.26it/s, v_num=gbfj]train step 1640; scene = [['62ce0e4e9490317d']]; loss = 0.030188
+Epoch 0: |                                                                          | 1640/? [1:44:52<00:00,  0.26it/s, v_num=gbfj]context = [[4, 6, 8, 15, 23, 24, 26, 32, 35, 39, 50, 55], [0, 10, 22, 26, 27, 29, 35, 42, 60, 66, 73, 77]]target = [[41, 43, 30, 44, 33, 16, 39, 51, 12, 54, 53, 29], [4, 16, 21, 43, 47, 46, 44, 53, 45, 24, 51, 50]]
+Epoch 0: |                                                                          | 1649/? [1:45:26<00:00,  0.26it/s, v_num=gbfj]train step 1650; scene = [['bad5f833677cd32f'], ['2cf78f93fd569aa1']]; loss = 0.059602
+Epoch 0: |                                                                          | 1650/? [1:45:30<00:00,  0.26it/s, v_num=gbfj]context = [[9, 71], [34, 102], [46, 110], [10, 61], [137, 186], [1, 52], [128, 195], [10, 100], [198, 258], [16, 67], [12, 66], [5, 66]]target = [[26, 42], [83, 46], [67, 48], [14, 57], [154, 155], [49, 29], [155, 140], [41, 56], [236, 235], [32, 61], [50, 32], [35, 61]]
+Epoch 0: |                                                                          | 1659/? [1:46:05<00:00,  0.26it/s, v_num=gbfj]train step 1660; scene = [['1f3f484a027f93d9'], ['12e85fb6e140ee85'], ['197edde42c1eaac3'], ['59058fb21817aa6b']]; loss = 0.047706
+Epoch 0: |                                                                          | 1660/? [1:46:09<00:00,  0.26it/s, v_num=gbfj]context = [[24, 30, 39, 55, 81, 105], [182, 183, 195, 207, 215, 233], [25, 65, 77, 78, 93, 105], [20, 40, 46, 77, 82, 103]]target = [[48, 70, 100, 51, 59, 97], [197, 190, 194, 208, 198, 218], [44, 91, 86, 70, 101, 30], [65, 21, 102, 25, 30, 54]]
+Epoch 0: |                                                                          | 1669/? [1:46:43<00:00,  0.26it/s, v_num=gbfj]train step 1670; scene = [['25aff15f6c54558b']]; loss = 0.033758
+Epoch 0: |                                                                          | 1670/? [1:46:47<00:00,  0.26it/s, v_num=gbfj]context = [[154, 158, 162, 163, 165, 191, 194, 196, 201, 203, 207, 211], [137, 138, 151, 153, 161, 165, 166, 167, 185, 186, 197, 203]]target = [[203, 173, 193, 192, 207, 165, 187, 157, 174, 190, 182, 176], [165, 166, 189, 176, 201, 140, 139, 163, 184, 169, 186, 157]]
+Epoch 0: |                                                                          | 1679/? [1:47:22<00:00,  0.26it/s, v_num=gbfj]train step 1680; scene = [['c513a3c2f59aa548'], ['493538f3442cb9fd']]; loss = 0.039473
+Epoch 0: |                                                                          | 1680/? [1:47:25<00:00,  0.26it/s, v_num=gbfj]context = [[8, 9, 12, 14, 16, 17, 18, 20, 23, 25, 29, 36, 38, 46, 52, 63, 64, 78, 82, 90, 95, 97, 102, 105]]target = [[19, 24, 49, 13, 77, 40, 51, 54, 85, 10, 74, 88, 50, 94, 78, 71, 68, 87, 44, 95, 63, 81, 82, 96]]
+Epoch 0: |                                                                          | 1689/? [1:48:00<00:00,  0.26it/s, v_num=gbfj]train step 1690; scene = [['da5de01cf7e41541']]; loss = 0.056705
+Epoch 0: |                                                                          | 1690/? [1:48:03<00:00,  0.26it/s, v_num=gbfj]context = [[166, 168, 170, 180, 181, 183, 184, 191, 219, 234, 239, 240], [52, 57, 62, 79, 87, 99, 104, 107, 111, 115, 118, 124]]target = [[226, 177, 191, 171, 214, 212, 213, 234, 229, 186, 238, 219], [60, 111, 110, 109, 72, 56, 96, 101, 61, 66, 118, 69]]
+Epoch 0: |                                                                          | 1699/? [1:48:38<00:00,  0.26it/s, v_num=gbfj]train step 1700; scene = [['3e763e3c28e87eed']]; loss = 0.023062
+Epoch 0: |                                                                          | 1700/? [1:48:42<00:00,  0.26it/s, v_num=gbfj]context = [[45, 50, 54, 60, 92, 105, 108, 110], [0, 8, 30, 31, 41, 42, 43, 45], [22, 28, 31, 33, 41, 59, 72, 99]]target = [[71, 52, 86, 64, 72, 69, 73, 59], [14, 36, 2, 1, 35, 4, 16, 20], [74, 61, 93, 94, 31, 42, 26, 28]]
+Epoch 0: |                                                                          | 1709/? [1:49:14<00:00,  0.26it/s, v_num=gbfj]train step 1710; scene = [['3727bb4b44708f89']]; loss = 0.082919
+Epoch 0: |                                                                          | 1710/? [1:49:18<00:00,  0.26it/s, v_num=gbfj]context = [[59, 62, 71, 76, 105, 110, 112, 114], [1, 2, 12, 23, 30, 34, 44, 48], [75, 78, 86, 87, 90, 114, 117, 122]]target = [[104, 100, 89, 101, 94, 102, 96, 84], [4, 24, 32, 21, 39, 26, 25, 20], [89, 94, 76, 90, 85, 96, 83, 77]]
+Epoch 0: |                                                                          | 1719/? [1:49:53<00:00,  0.26it/s, v_num=gbfj]train step 1720; scene = [['d938c73738634cbf'], ['d7f3b4e12f3f3af6'], ['1a17332c1d690519']]; loss = 0.030647
+Epoch 0: |                                                                          | 1720/? [1:49:56<00:00,  0.26it/s, v_num=gbfj]context = [[26, 28, 33, 44, 45, 49, 55, 57, 58, 59, 67, 72, 75, 79, 82, 94, 98, 100, 113, 115, 117, 118, 122, 123]]target = [[107, 48, 44, 86, 57, 93, 73, 51, 58, 88, 78, 59, 33, 99, 100, 87, 62, 38, 36, 84, 119, 122, 91, 74]]
+Epoch 0: |                                                                          | 1729/? [1:50:31<00:00,  0.26it/s, v_num=gbfj]train step 1730; scene = [['2d9ea631e6423141'], ['b0c6597c77c51a8c']]; loss = 0.044294
+Epoch 0: |                                                                          | 1730/? [1:50:35<00:00,  0.26it/s, v_num=gbfj]context = [[87, 105, 125, 127, 131, 138, 143, 150], [1, 14, 30, 33, 45, 48, 57, 66], [8, 18, 21, 26, 59, 92, 93, 94]]target = [[89, 146, 124, 104, 103, 96, 110, 143], [29, 33, 7, 12, 20, 27, 53, 51], [57, 81, 93, 74, 29, 30, 33, 60]]
+Epoch 0: |                                                                          | 1739/? [1:51:10<00:00,  0.26it/s, v_num=gbfj]train step 1740; scene = [['56863fb499e2ff9a'], ['f5a3eca31fcdabf8'], ['946597adeb926d39'], ['23eecb3bfb301179'], ['4d999bce04f7516a'], ['b1f32a7b0a8e25ce'], ['72ac5af57c88795c'], ['cc45417d1c5dab8d']]; loss = 0.066207
+Epoch 0: |                                                                          | 1740/? [1:51:13<00:00,  0.26it/s, v_num=gbfj]context = [[1, 4, 8, 12, 19, 26, 28, 29, 39, 42, 47, 50, 55, 66, 67, 68, 70, 76, 83, 85, 91, 92, 97, 98]]target = [[72, 40, 83, 3, 21, 13, 14, 61, 46, 53, 36, 57, 6, 10, 12, 37, 7, 22, 19, 78, 56, 25, 54, 80]]
+Epoch 0: |                                                                          | 1749/? [1:51:49<00:00,  0.26it/s, v_num=gbfj]train step 1750; scene = [['7351b1a8a7405871'], ['edacb8db81943446']]; loss = 0.047966
+Epoch 0: |                                                                          | 1750/? [1:51:52<00:00,  0.26it/s, v_num=gbfj]Validation epoch start on rank 0
+Validation: |                                                                                                | 0/? [00:00<?, ?it/s]validation step 1750; scene = ['3b273cb40c55db95'];
+target intrinsic:  tensor(1.0504, device='cuda:0') tensor(1.0506, device='cuda:0')                           | 0/1 [00:00<?, ?it/s]
+pred intrinsic:  tensor(1.0974, device='cuda:0') tensor(1.0976, device='cuda:0')
+[2026-02-25 12:32:00,789][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                          | 1750/? [1:51:54<00:00,  0.26it/s, v_num=gbfj]context = [[6, 12, 18, 21, 26, 27, 30, 33, 34, 35, 50, 55], [2, 5, 11, 19, 32, 36, 39, 44, 45, 46, 47, 56]]target = [[43, 26, 45, 30, 52, 34, 39, 12, 21, 11, 37, 19], [8, 19, 54, 25, 33, 4, 10, 55, 46, 34, 52, 3]]
+Epoch 0: |                                                                          | 1759/? [1:52:27<00:00,  0.26it/s, v_num=gbfj]train step 1760; scene = [['616d045c5963ecb2'], ['4bbb9fadc993969a'], ['c8b833961ffd8ac5'], ['321addf5693a66aa']]; loss = 0.041379
+Epoch 0: |                                                                          | 1760/? [1:52:30<00:00,  0.26it/s, v_num=gbfj]context = [[111, 116, 130, 132, 142, 146, 147, 158, 160, 164, 176, 181], [19, 20, 21, 24, 28, 31, 47, 58, 61, 70, 71, 77]]target = [[125, 122, 167, 145, 144, 152, 130, 121, 153, 165, 113, 139], [70, 73, 42, 59, 66, 23, 39, 72, 22, 60, 26, 25]]
+Epoch 0: |                                                                          | 1769/? [1:53:04<00:00,  0.26it/s, v_num=gbfj]train step 1770; scene = [['8eb7ab71f603c9d4'], ['cc966a9b2af2232f']]; loss = 0.056167
+Epoch 0: |                                                                          | 1770/? [1:53:08<00:00,  0.26it/s, v_num=gbfj]context = [[102, 104, 107, 108, 112, 122, 123, 126, 129, 133, 136, 142, 146, 147, 150, 161, 162, 163, 164, 184, 189, 191, 193, 199]]target = [[120, 136, 118, 149, 133, 122, 193, 137, 187, 174, 159, 156, 194, 170, 121, 189, 103, 178, 197, 196, 129, 195, 115, 181]]
+Epoch 0: |                                                                          | 1779/? [1:53:43<00:00,  0.26it/s, v_num=gbfj]train step 1780; scene = [['bb28a1c09df8a484']]; loss = 0.037628
+Epoch 0: |                                                                          | 1780/? [1:53:46<00:00,  0.26it/s, v_num=gbfj]context = [[11, 70], [25, 75], [78, 152], [51, 119], [24, 81], [136, 193], [20, 96], [30, 109], [7, 87], [58, 129], [66, 145], [27, 74]]target = [[17, 37], [64, 73], [135, 104], [69, 118], [42, 58], [145, 168], [30, 83], [99, 43], [42, 16], [61, 111], [134, 98], [55, 71]]
+Epoch 0: |                                                                          | 1789/? [1:54:20<00:00,  0.26it/s, v_num=gbfj]train step 1790; scene = [['48c2b63b452555af'], ['1aa5fdc9ff855ee2']]; loss = 0.065300
+Epoch 0: |                                                                          | 1790/? [1:54:24<00:00,  0.26it/s, v_num=gbfj]context = [[32, 36, 37, 42, 43, 52, 63, 67, 68, 73, 74, 90], [27, 40, 53, 55, 57, 63, 68, 79, 80, 81, 100, 102]]target = [[70, 67, 89, 83, 52, 35, 74, 73, 84, 44, 54, 33], [44, 60, 41, 98, 100, 51, 46, 99, 47, 92, 37, 31]]
+Epoch 0: |                                                                          | 1799/? [1:54:59<00:00,  0.26it/s, v_num=gbfj]train step 1800; scene = [['b41ece74dd5aa87d'], ['e620345f5468d2e3']]; loss = 0.022640
+Epoch 0: |                                                                          | 1800/? [1:55:02<00:00,  0.26it/s, v_num=gbfj]context = [[2, 47], [107, 163], [22, 107], [67, 146], [82, 130], [87, 151], [59, 133], [191, 242], [121, 203], [113, 167], [106, 159], [27, 94]]target = [[37, 42], [161, 109], [92, 85], [142, 139], [116, 104], [106, 134], [116, 87], [201, 206], [142, 129], [159, 155], [116, 134], [57, 36]]
+[2026-02-25 12:35:14,407][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                          | 1809/? [1:55:36<00:00,  0.26it/s, v_num=gbfj]train step 1810; scene = [['9e1b58ec292d6690'], ['63f6e847b2e2a2e7'], ['aa570297256d99b6'], ['02195bc2cdded89e'], ['8839e65c6f6bb394'], ['c6bd8d3b3367444f']]; loss = 0.065755
+Epoch 0: |                                                                          | 1810/? [1:55:39<00:00,  0.26it/s, v_num=gbfj]context = [[3, 14, 18, 21, 23, 31, 32, 34, 36, 63, 70, 78], [24, 32, 33, 47, 62, 69, 70, 73, 80, 85, 86, 88]]target = [[5, 7, 41, 28, 48, 67, 12, 68, 47, 26, 10, 31], [25, 68, 40, 79, 82, 58, 26, 28, 36, 48, 66, 29]]
+Epoch 0: |                                                                          | 1819/? [1:56:14<00:00,  0.26it/s, v_num=gbfj]train step 1820; scene = [['8ad3918394be8d98']]; loss = 0.043300
+Epoch 0: |                                                                          | 1820/? [1:56:18<00:00,  0.26it/s, v_num=gbfj]context = [[0, 4, 7, 9, 13, 15, 17, 35, 37, 61, 69, 72], [5, 23, 24, 25, 26, 31, 50, 56, 60, 68, 74, 76]]target = [[45, 49, 51, 46, 6, 14, 52, 22, 65, 69, 10, 37], [9, 37, 72, 6, 28, 14, 64, 47, 15, 16, 55, 33]]
+Epoch 0: |                                                                          | 1829/? [1:56:52<00:00,  0.26it/s, v_num=gbfj]train step 1830; scene = [['af4565fb713ed79f']]; loss = 0.032563
+Epoch 0: |                                                                          | 1830/? [1:56:56<00:00,  0.26it/s, v_num=gbfj]context = [[133, 138, 168, 169, 171, 180, 190, 192, 196, 203, 204, 213], [81, 82, 84, 87, 92, 93, 95, 97, 105, 110, 118, 131]]target = [[147, 196, 136, 153, 201, 185, 205, 161, 169, 149, 210, 189], [114, 103, 99, 119, 107, 110, 88, 124, 86, 122, 126, 120]]
+Epoch 0: |                                                                          | 1839/? [1:57:31<00:00,  0.26it/s, v_num=gbfj]train step 1840; scene = [['c690f7b93b2b75c5'], ['f0dbc908f65693ae'], ['ee81b7d704303a2c'], ['a2a3a75cafb630f5']]; loss = 0.068916
+Epoch 0: |                                                                          | 1840/? [1:57:35<00:00,  0.26it/s, v_num=gbfj]context = [[95, 106, 107, 115, 116, 118, 120, 126, 128, 130, 133, 139, 148, 149, 150, 153, 159, 163, 173, 178, 182, 183, 184, 192]]target = [[167, 153, 132, 96, 110, 126, 111, 129, 162, 144, 185, 176, 106, 97, 156, 108, 177, 172, 148, 157, 133, 137, 149, 141]]
+Epoch 0: |                                                                          | 1849/? [1:58:10<00:00,  0.26it/s, v_num=gbfj]train step 1850; scene = [['a1fa4bf737381a53'], ['2d7243929156069e'], ['201287bd653fa906'], ['2d7243929156069e'], ['d25d6a9b1356b134'], ['4a0f95a3db913b56']]; loss = 0.062521
+Epoch 0: |                                                                          | 1850/? [1:58:13<00:00,  0.26it/s, v_num=gbfj]context = [[30, 32, 34, 52, 72, 85, 90, 108], [9, 25, 30, 33, 41, 46, 48, 84], [51, 72, 76, 82, 83, 99, 109, 115]]target = [[46, 41, 107, 87, 40, 64, 57, 53], [35, 56, 83, 38, 62, 21, 53, 37], [109, 111, 114, 53, 86, 67, 91, 104]]
+Epoch 0: |                                                                          | 1859/? [1:58:46<00:00,  0.26it/s, v_num=gbfj]train step 1860; scene = [['082779aebfbf4a46']]; loss = 0.030753
+Epoch 0: |                                                                          | 1860/? [1:58:50<00:00,  0.26it/s, v_num=gbfj]context = [[3, 17, 39, 49], [112, 121, 139, 157], [128, 136, 147, 178], [2, 10, 33, 87], [25, 50, 81, 98], [28, 48, 69, 113]]target = [[8, 40, 43, 26], [113, 124, 154, 133], [156, 164, 137, 168], [62, 24, 86, 11], [68, 70, 78, 73], [73, 100, 109, 29]]
+Epoch 0: |                                                                          | 1869/? [1:59:24<00:00,  0.26it/s, v_num=gbfj]train step 1870; scene = [['01c143c81a4d2145'], ['9b0b82db99ff360a'], ['80f5da17b4119bbf'], ['8c5dce5d79b3d2aa'], ['d3a0a89d951a6101'], ['da1f9f2859b59142'], ['20b791440b7ec0b5'], ['00703cbf7531ef11'], ['4aef5d4b9287e08a'], ['27ed8e7077af6540'], ['04e7f97215df7078'], ['08735c801ab7efb5']]; loss = 0.086264
+Epoch 0: |                                                                          | 1870/? [1:59:27<00:00,  0.26it/s, v_num=gbfj]context = [[41, 44, 47, 48, 50, 51, 56, 67, 72, 81, 82, 83, 84, 85, 89, 90, 97, 105, 107, 110, 115, 125, 135, 138]]target = [[79, 108, 90, 99, 85, 65, 59, 69, 73, 126, 131, 100, 114, 52, 87, 47, 123, 54, 43, 137, 94, 88, 70, 75]]
+Epoch 0: |                                                                          | 1879/? [2:00:02<00:00,  0.26it/s, v_num=gbfj]train step 1880; scene = [['42b2dabdc5ea4d93']]; loss = 0.026983
+Epoch 0: |                                                                          | 1880/? [2:00:06<00:00,  0.26it/s, v_num=gbfj]context = [[17, 29, 31, 34, 36, 39, 48, 59, 64, 66, 67, 79], [42, 47, 51, 56, 57, 61, 64, 70, 74, 83, 92, 93]]target = [[53, 20, 25, 74, 39, 30, 21, 59, 50, 66, 40, 44], [43, 84, 45, 72, 82, 85, 56, 73, 92, 76, 75, 46]]
+Epoch 0: |                                                                          | 1889/? [2:00:41<00:00,  0.26it/s, v_num=gbfj]train step 1890; scene = [['ed4855892fd5fa4a'], ['9683be82b6c1e851']]; loss = 0.051504
+Epoch 0: |                                                                          | 1890/? [2:00:45<00:00,  0.26it/s, v_num=gbfj]context = [[22, 37, 39, 49, 50, 52, 54, 56, 59, 61, 72, 74, 84, 88, 93, 94, 97, 102, 104, 105, 108, 109, 112, 119]]target = [[59, 53, 102, 34, 27, 44, 100, 45, 32, 65, 36, 42, 87, 82, 85, 26, 80, 60, 90, 113, 86, 78, 40, 68]]
+Epoch 0: |                                                                          | 1899/? [2:01:19<00:00,  0.26it/s, v_num=gbfj]train step 1900; scene = [['1844e80dafb62927'], ['b43f32da9a7800ee'], ['11094b4b71a9ab00'], ['0f5daf32c2e8fefd'], ['f8e7bd9e403fc04a'], ['b11afc47f2feb21c'], ['5994966dd0897ead'], ['6d2aae2a7dd35e14'], ['e545aecc18cfa501'], ['82d896f5142ee6dd'], ['140b10a4f6bb5aa5'], ['2ec8edfc07c8841f']]; loss = 0.082255
+Epoch 0: |                                                                          | 1900/? [2:01:24<00:00,  0.26it/s, v_num=gbfj]context = [[1, 20, 26, 32, 34, 53], [83, 87, 95, 106, 125, 139], [0, 13, 29, 39, 46, 77], [90, 122, 126, 130, 159, 167]]target = [[36, 12, 39, 17, 4, 7], [92, 86, 107, 112, 135, 137], [32, 69, 36, 28, 50, 38], [132, 161, 105, 165, 142, 102]]
+Epoch 0: |                                                                          | 1909/? [2:01:58<00:00,  0.26it/s, v_num=gbfj]train step 1910; scene = [['50f7971dda42084f'], ['159a472b24f1c395'], ['04a191933c5b05ec']]; loss = 0.064187
+Epoch 0: |                                                                          | 1910/? [2:02:02<00:00,  0.26it/s, v_num=gbfj]context = [[74, 78, 86, 94, 96, 101, 104, 107, 108, 109, 115, 117, 119, 131, 133, 135, 137, 144, 151, 152, 155, 158, 161, 171]]target = [[108, 142, 163, 121, 87, 111, 149, 96, 120, 145, 97, 122, 147, 101, 123, 95, 94, 132, 86, 89, 99, 140, 104, 136]]
+Epoch 0: |                                                                          | 1919/? [2:02:36<00:00,  0.26it/s, v_num=gbfj]train step 1920; scene = [['bf4bbf858718317d'], ['39ed8d2efe760b94'], ['d9644f4985e51a1f']]; loss = 0.044219
+Epoch 0: |                                                                          | 1920/? [2:02:40<00:00,  0.26it/s, v_num=gbfj]context = [[9, 79], [15, 63], [28, 73], [101, 167], [5, 70], [53, 102], [2, 75], [86, 135], [1, 58], [5, 84], [1, 76], [135, 208]]target = [[43, 20], [62, 45], [70, 64], [114, 144], [60, 52], [93, 101], [13, 68], [120, 89], [30, 23], [43, 16], [57, 14], [194, 205]]
+Epoch 0: |                                                                          | 1929/? [2:03:12<00:00,  0.26it/s, v_num=gbfj]train step 1930; scene = [['6efa62598fececd0'], ['b25a0f4ffca51d79'], ['90dbfac63e6b89be'], ['08a366317a388734']]; loss = 0.071024
+Epoch 0: |                                                                          | 1930/? [2:03:15<00:00,  0.26it/s, v_num=gbfj]context = [[3, 19, 23, 28, 32, 40, 48, 50, 53, 60, 63, 64, 66, 70, 74, 78, 80, 82, 87, 93, 96, 97, 98, 100]]target = [[63, 24, 82, 55, 68, 93, 95, 7, 53, 65, 76, 35, 83, 11, 22, 34, 52, 16, 61, 92, 26, 47, 32, 46]]
+Epoch 0: |                                                                          | 1939/? [2:03:50<00:00,  0.26it/s, v_num=gbfj]train step 1940; scene = [['1236365ec263ad76']]; loss = 0.033096
+Epoch 0: |                                                                          | 1940/? [2:03:54<00:00,  0.26it/s, v_num=gbfj]context = [[10, 11, 16, 23, 26, 33, 34, 43, 44, 48, 54, 58, 70, 73, 75, 78, 82, 86, 89, 91, 102, 105, 106, 107]]target = [[88, 68, 24, 39, 22, 100, 19, 44, 57, 94, 41, 37, 53, 69, 96, 63, 81, 104, 50, 64, 101, 15, 40, 26]]
+Epoch 0: |                                                                          | 1949/? [2:04:29<00:00,  0.26it/s, v_num=gbfj]train step 1950; scene = [['2bc8b64aafc5870c'], ['1202c32d91ad3ee3'], ['300571576edc008c']]; loss = 0.084702
+Epoch 0: |                                                                          | 1950/? [2:04:33<00:00,  0.26it/s, v_num=gbfj]context = [[11, 14, 25, 42, 47, 49, 58, 66, 68, 69, 79, 81], [39, 55, 56, 60, 63, 70, 74, 86, 93, 96, 99, 104]]target = [[25, 55, 33, 13, 26, 62, 22, 52, 32, 67, 30, 40], [95, 42, 43, 41, 59, 96, 102, 88, 48, 66, 100, 40]]
+Epoch 0: |                                                                          | 1959/? [2:05:06<00:00,  0.26it/s, v_num=gbfj]train step 1960; scene = [['3ded3e3c1fe76ee3']]; loss = 0.042275
+Epoch 0: |                                                                          | 1960/? [2:05:10<00:00,  0.26it/s, v_num=gbfj]context = [[109, 112, 117, 120, 130, 137, 142, 144, 145, 150, 151, 152, 155, 159, 160, 162, 166, 171, 175, 179, 194, 195, 196, 206]]target = [[168, 171, 125, 169, 131, 150, 188, 139, 145, 152, 126, 184, 205, 142, 119, 196, 148, 155, 185, 197, 154, 203, 143, 147]]
+Epoch 0: |                                                                          | 1969/? [2:05:45<00:00,  0.26it/s, v_num=gbfj]train step 1970; scene = [['3b21f48e23e4917f']]; loss = 0.037742
+Epoch 0: |                                                                          | 1970/? [2:05:49<00:00,  0.26it/s, v_num=gbfj]context = [[13, 15, 19, 21, 30, 33, 39, 49, 54, 57, 72, 85], [18, 26, 35, 36, 39, 46, 50, 60, 70, 71, 74, 80]]target = [[39, 30, 38, 35, 26, 78, 75, 56, 18, 44, 77, 71], [22, 24, 70, 65, 49, 19, 62, 59, 71, 73, 51, 39]]
+Epoch 0: |                                                                          | 1979/? [2:06:24<00:00,  0.26it/s, v_num=gbfj]train step 1980; scene = [['723db63d24c84d1d']]; loss = 0.031240
+Epoch 0: |                                                                          | 1980/? [2:06:27<00:00,  0.26it/s, v_num=gbfj]context = [[114, 115, 120, 122, 123, 125, 126, 140, 141, 145, 147, 161, 170, 179, 180, 181, 193, 195, 196, 197, 199, 203, 207, 211]]target = [[201, 148, 171, 190, 135, 143, 189, 141, 205, 151, 187, 206, 183, 144, 200, 147, 181, 184, 120, 207, 152, 128, 170, 204]]
+Epoch 0: |                                                                          | 1989/? [2:07:02<00:00,  0.26it/s, v_num=gbfj]train step 1990; scene = [['12eb36bba5c89eeb'], ['40c5311e3b3accef'], ['06d2876e8c40a3b6'], ['2da17464ef895b63'], ['21951a6ae1c4b225'], ['ab78b3eb64029b73'], ['f6ef16edbf87f358'], ['66e4f3268dafe823']]; loss = 0.076294
+Epoch 0: |                                                                          | 1990/? [2:07:05<00:00,  0.26it/s, v_num=gbfj]context = [[6, 9, 11, 12, 24, 34, 39, 44, 45, 53, 55, 59, 61, 66, 70, 71, 76, 78, 79, 82, 85, 87, 92, 103]]target = [[32, 63, 22, 65, 39, 36, 57, 91, 64, 13, 66, 60, 14, 71, 26, 41, 23, 101, 29, 93, 92, 90, 98, 73]]
+Epoch 0: |                                                                          | 1999/? [2:07:39<00:00,  0.26it/s, v_num=gbfj]train step 2000; scene = [['1ac1373478877088']]; loss = 0.046730
+Epoch 0: |                                                                          | 2000/? [2:07:43<00:00,  0.26it/s, v_num=gbfj]Validation epoch start on rank 0
+Validation: |                                                                                                | 0/? [00:00<?, ?it/s]validation step 2000; scene = ['be75142d4652fe3e'];
+target intrinsic:  tensor(0.9402, device='cuda:0') tensor(0.9404, device='cuda:0')                           | 0/1 [00:00<?, ?it/s]
+pred intrinsic:  tensor(0.8905, device='cuda:0') tensor(0.8897, device='cuda:0')
+[2026-02-25 12:47:51,723][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                          | 2000/? [2:07:44<00:00,  0.26it/s, v_num=gbfj]context = [[16, 17, 18, 27, 35, 40, 41, 47, 48, 51, 52, 53, 54, 56, 79, 80, 87, 89, 92, 96, 100, 101, 106, 113]]target = [[102, 53, 81, 57, 21, 101, 52, 64, 43, 58, 59, 94, 46, 108, 32, 79, 36, 104, 26, 106, 31, 29, 60, 41]]
+[2026-02-25 12:47:56,086][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                          | 2009/? [2:08:22<00:00,  0.26it/s, v_num=gbfj]train step 2010; scene = [['e2f2a27bfce53270']]; loss = 0.038367
+Epoch 0: |                                                                          | 2010/? [2:08:26<00:00,  0.26it/s, v_num=gbfj]context = [[32, 34, 44, 61, 73, 79], [66, 91, 112, 119, 124, 128], [52, 79, 88, 91, 97, 100], [65, 83, 97, 105, 110, 128]]target = [[68, 72, 41, 73, 74, 40], [74, 67, 110, 72, 105, 98], [93, 66, 74, 77, 83, 65], [81, 72, 117, 80, 83, 114]]
+Epoch 0: |                                                                          | 2019/? [2:09:00<00:00,  0.26it/s, v_num=gbfj]train step 2020; scene = [['71f80e4a8d79031c'], ['aec60a6dd8090690'], ['475ee0875ccb635a']]; loss = 0.040954
+Epoch 0: |                                                                          | 2020/? [2:09:04<00:00,  0.26it/s, v_num=gbfj]context = [[1, 4, 12, 16, 21, 23, 29, 40, 49, 54, 58, 60, 62, 74, 75, 79, 81, 82, 85, 91, 92, 94, 97, 98]]target = [[52, 69, 55, 22, 50, 24, 41, 46, 80, 58, 32, 92, 54, 81, 38, 23, 3, 29, 97, 40, 25, 39, 78, 73]]
+Epoch 0: |                                                                          | 2029/? [2:09:39<00:00,  0.26it/s, v_num=gbfj]train step 2030; scene = [['60b6914bafa3c3f2']]; loss = 0.057160
+Epoch 0: |                                                                          | 2030/? [2:09:42<00:00,  0.26it/s, v_num=gbfj]context = [[45, 87, 105], [54, 118, 143], [79, 120, 143], [186, 243, 262], [14, 67, 94], [27, 68, 76], [13, 28, 58], [1, 69, 80]]target = [[68, 84, 80], [134, 122, 96], [131, 97, 136], [244, 198, 209], [34, 77, 22], [70, 43, 37], [43, 32, 33], [15, 54, 19]]
+Epoch 0: |                                                                          | 2039/? [2:10:17<00:00,  0.26it/s, v_num=gbfj]train step 2040; scene = [['8e94de9c1bc0732c'], ['0bb8a7807f7095fd']]; loss = 0.026530
+Epoch 0: |                                                                          | 2040/? [2:10:20<00:00,  0.26it/s, v_num=gbfj]context = [[25, 79, 84, 91], [12, 32, 41, 66], [10, 17, 31, 64], [69, 71, 109, 114], [31, 49, 67, 84], [14, 27, 46, 84]]target = [[48, 80, 51, 88], [16, 41, 21, 33], [63, 61, 13, 38], [73, 107, 79, 90], [41, 35, 60, 56], [29, 80, 26, 25]]
+Epoch 0: |                                                                          | 2049/? [2:10:55<00:00,  0.26it/s, v_num=gbfj]train step 2050; scene = [['c4e12df63403eadf'], ['8359c9726f078a38'], ['e0b75e74fdeffde9']]; loss = 0.060440
+Epoch 0: |                                                                          | 2050/? [2:10:59<00:00,  0.26it/s, v_num=gbfj]context = [[152, 157, 160, 167, 191, 197], [71, 81, 105, 126, 127, 139], [10, 12, 47, 54, 66, 83], [85, 88, 106, 117, 127, 136]]target = [[167, 195, 187, 184, 157, 176], [120, 107, 92, 124, 115, 110], [14, 13, 80, 40, 24, 47], [93, 96, 97, 132, 102, 131]]
+Epoch 0: |                                                                          | 2059/? [2:11:32<00:00,  0.26it/s, v_num=gbfj]train step 2060; scene = [['22062ed897320134'], ['08e4f6a5098b0d3a'], ['d3057752d15cc3ed']]; loss = 0.084239
+Epoch 0: |                                                                          | 2060/? [2:11:36<00:00,  0.26it/s, v_num=gbfj]context = [[164, 195, 232], [18, 42, 81], [5, 55, 93], [175, 199, 220], [6, 42, 65], [2, 7, 60], [149, 190, 195], [33, 42, 82]]target = [[209, 178, 225], [53, 24, 75], [32, 35, 24], [201, 183, 204], [50, 59, 38], [5, 37, 42], [187, 161, 189], [44, 78, 62]]
+Epoch 0: |                                                                          | 2069/? [2:12:10<00:00,  0.26it/s, v_num=gbfj]train step 2070; scene = [['85ef0eb4a42e3425'], ['703430ad773c95bc'], ['4fd9d45647d536e5']]; loss = 0.112393
+Epoch 0: |                                                                          | 2070/? [2:12:14<00:00,  0.26it/s, v_num=gbfj]context = [[78, 84, 92, 97, 108, 109, 115, 124, 138, 150, 158, 159], [42, 43, 53, 57, 69, 71, 77, 83, 84, 86, 88, 92]]target = [[127, 113, 118, 102, 153, 144, 132, 139, 125, 129, 84, 79], [57, 81, 79, 87, 72, 61, 48, 88, 54, 84, 44, 65]]
+Epoch 0: |                                                                          | 2079/? [2:12:48<00:00,  0.26it/s, v_num=gbfj]train step 2080; scene = [['968b857dda7e955a'], ['8e713ad26d00feac']]; loss = 0.036433
+Epoch 0: |                                                                          | 2080/? [2:12:52<00:00,  0.26it/s, v_num=gbfj]context = [[33, 57, 88, 112], [20, 29, 43, 76], [20, 56, 96, 110], [3, 13, 50, 53], [44, 50, 64, 108], [65, 92, 120, 152]]target = [[101, 99, 69, 88], [37, 25, 36, 30], [99, 72, 91, 75], [14, 32, 43, 39], [105, 93, 56, 106], [69, 98, 70, 122]]
+Epoch 0: |                                                                          | 2089/? [2:13:27<00:00,  0.26it/s, v_num=gbfj]train step 2090; scene = [['0565bd311bf73bbb'], ['eceeb7a49f302da9'], ['2073f379b98e47e8'], ['c5536f755d325407'], ['06ed257e33ae67f5'], ['b12f64d6002ec745']]; loss = 0.052003
+Epoch 0: |                                                                          | 2090/? [2:13:31<00:00,  0.26it/s, v_num=gbfj]context = [[14, 20, 22, 23, 24, 26, 36, 41, 74, 81, 83, 87], [2, 10, 11, 16, 25, 26, 34, 35, 41, 49, 62, 63]]target = [[16, 23, 39, 54, 53, 59, 48, 70, 20, 63, 50, 36], [60, 32, 15, 7, 5, 51, 40, 52, 10, 56, 22, 41]]
+Epoch 0: |                                                                          | 2099/? [2:14:06<00:00,  0.26it/s, v_num=gbfj]train step 2100; scene = [['3101309753e2f063'], ['d55fbb3dcd24f08e']]; loss = 0.030428
+Epoch 0: |                                                                          | 2100/? [2:14:10<00:00,  0.26it/s, v_num=gbfj]context = [[145, 173, 174, 182, 187, 197, 204, 211], [65, 79, 86, 88, 93, 112, 118, 122], [98, 107, 122, 145, 156, 159, 162, 163]]target = [[208, 167, 187, 146, 173, 180, 166, 172], [108, 72, 116, 104, 92, 115, 83, 68], [160, 128, 158, 103, 134, 125, 101, 109]]
+Epoch 0: |                                                                          | 2109/? [2:14:43<00:00,  0.26it/s, v_num=gbfj]train step 2110; scene = [['4fd151a48542df52'], ['c53e0b350f04f159'], ['ec1dcf652eae675d'], ['f001500643d191d6']]; loss = 0.117542
+Epoch 0: |                                                                          | 2110/? [2:14:47<00:00,  0.26it/s, v_num=gbfj]context = [[42, 45, 48, 60, 81, 84, 88, 90, 102, 104, 121, 130], [22, 29, 34, 38, 39, 44, 49, 50, 53, 56, 59, 74]]target = [[108, 62, 127, 115, 43, 114, 52, 51, 100, 126, 61, 87], [64, 41, 45, 69, 25, 27, 65, 43, 68, 71, 38, 35]]
+Epoch 0: |                                                                          | 2119/? [2:15:22<00:00,  0.26it/s, v_num=gbfj]train step 2120; scene = [['4f515c197a061a67'], ['0c7171edef36d44d'], ['ec5f9801aa83c8aa']]; loss = 0.062899
+Epoch 0: |                                                                          | 2120/? [2:15:26<00:00,  0.26it/s, v_num=gbfj]context = [[124, 126, 135, 171], [32, 69, 83, 84], [30, 85, 88, 105], [27, 33, 42, 117], [2, 33, 53, 56], [24, 47, 86, 102]]target = [[165, 167, 132, 145], [80, 75, 52, 61], [73, 92, 100, 67], [87, 74, 112, 34], [45, 41, 49, 35], [80, 73, 95, 30]]
+Epoch 0: |                                                                          | 2129/? [2:16:00<00:00,  0.26it/s, v_num=gbfj]train step 2130; scene = [['2dd8ae2b71457753'], ['3670e4d9d26e7534']]; loss = 0.047809
+Epoch 0: |                                                                          | 2130/? [2:16:02<00:00,  0.26it/s, v_num=gbfj]context = [[24, 25, 27, 28, 32, 34, 36, 39, 48, 50, 55, 61, 62, 63, 64, 67, 77, 87, 102, 106, 110, 116, 117, 121]]target = [[45, 42, 59, 107, 40, 101, 31, 75, 70, 54, 81, 53, 83, 73, 64, 100, 51, 37, 47, 117, 60, 43, 48, 90]]
+Epoch 0: |                                                                          | 2139/? [2:16:37<00:00,  0.26it/s, v_num=gbfj]train step 2140; scene = [['158ecf8d21e5af57'], ['4dfd4268f80ef274'], ['04c4eef824be2a53']]; loss = 0.044609
+Epoch 0: |                                                                          | 2140/? [2:16:42<00:00,  0.26it/s, v_num=gbfj]context = [[131, 152, 157, 167, 188, 191], [139, 146, 149, 153, 171, 223], [126, 136, 156, 187, 188, 202], [32, 37, 41, 56, 82, 87]]target = [[189, 157, 139, 148, 184, 180], [151, 183, 209, 179, 185, 140], [159, 166, 155, 170, 182, 131], [78, 79, 34, 85, 50, 59]]
+Epoch 0: |                                                                          | 2149/? [2:17:16<00:00,  0.26it/s, v_num=gbfj]train step 2150; scene = [['db62795c284bf764'], ['916b86f95631b480']]; loss = 0.057492
+Epoch 0: |                                                                          | 2150/? [2:17:20<00:00,  0.26it/s, v_num=gbfj]context = [[4, 6, 16, 19, 21, 30, 35, 38, 41, 48, 51, 52, 54, 62, 63, 67, 69, 77, 80, 81, 86, 93, 95, 101]]target = [[56, 16, 36, 50, 25, 34, 65, 87, 40, 5, 42, 54, 18, 32, 68, 76, 98, 52, 37, 85, 41, 79, 13, 91]]
+Epoch 0: |                                                                          | 2159/? [2:17:55<00:00,  0.26it/s, v_num=gbfj]train step 2160; scene = [['72077f7ff39fc73e'], ['9ae93c878c7dbe8a'], ['4bac79c3a17ed149'], ['208bd0af6bc8937b'], ['84e6b90f0c2567d8'], ['f4ba6d204cb14df7'], ['758770f2884e9a79'], ['36df585860d0ad88'], ['69a6e3951e138ca8'], ['5d986af113fbac56'], ['d46599d6e4a2b451'], ['ee020a8773034321']]; loss = 0.074343
+Epoch 0: |                                                                          | 2160/? [2:17:59<00:00,  0.26it/s, v_num=gbfj]context = [[6, 8, 10, 50, 66, 87], [50, 69, 72, 95, 105, 111], [126, 165, 170, 172, 176, 211], [5, 9, 19, 42, 47, 50]]target = [[9, 68, 72, 19, 24, 67], [80, 85, 64, 70, 104, 91], [184, 172, 136, 189, 179, 175], [48, 14, 45, 22, 40, 16]]
+Epoch 0: |                                                                          | 2169/? [2:18:33<00:00,  0.26it/s, v_num=gbfj]train step 2170; scene = [['e1d9afaa8899ee32'], ['1060ca933281b55c'], ['fbf253fca4a29e87'], ['5ff87250a0eb913b'], ['d02e6b104723d39a'], ['42b208082fce3bc2'], ['ee6e5709a57be759'], ['a191c34eb75bbaec'], ['0cbafecfcb0f7727'], ['e6461cee8a9474d5'], ['fda8bac8ddac590f'], ['465fa8314b741006']]; loss = 0.101343
+Epoch 0: |                                                                          | 2170/? [2:18:37<00:00,  0.26it/s, v_num=gbfj]context = [[5, 20, 23, 37, 49, 52, 59, 76], [11, 28, 31, 35, 41, 43, 44, 57], [5, 15, 30, 36, 47, 59, 61, 62]]target = [[53, 50, 40, 18, 39, 33, 23, 17], [27, 38, 40, 28, 55, 45, 26, 25], [56, 9, 61, 23, 59, 30, 45, 35]]
+Epoch 0: |                                                                          | 2179/? [2:19:11<00:00,  0.26it/s, v_num=gbfj]train step 2180; scene = [['91599919681fac69'], ['f9cece9ebde532d0']]; loss = 0.051214
+Epoch 0: |                                                                          | 2180/? [2:19:15<00:00,  0.26it/s, v_num=gbfj]context = [[46, 63, 73, 75, 76, 83, 99, 102], [17, 31, 32, 39, 47, 52, 58, 68], [83, 91, 110, 113, 116, 117, 121, 133]]target = [[72, 92, 67, 101, 68, 55, 49, 74], [30, 31, 53, 26, 41, 35, 20, 62], [93, 131, 116, 96, 125, 107, 127, 109]]
+Epoch 0: |                                                                            | 2189/? [2:19:49<00:00,  0.26it/s, v_num=gbfj]train step 2190; scene = [['4d48befa72535f0a']]; loss = 0.045415
+Epoch 0: |                                                                            | 2190/? [2:19:53<00:00,  0.26it/s, v_num=gbfj]context = [[113, 123, 125, 126, 132, 133, 135, 138, 149, 150, 154, 160, 167, 172, 175, 191, 194, 197, 198, 200, 201, 205, 206, 210]]target = [[120, 130, 147, 187, 142, 115, 202, 171, 117, 163, 191, 170, 139, 169, 181, 155, 150, 141, 192, 146, 188, 174, 205, 179]]
+Epoch 0: |                                                                            | 2199/? [2:20:27<00:00,  0.26it/s, v_num=gbfj]train step 2200; scene = [['76ce9bd95ed81200'], ['91ac7d7027dcc46d'], ['3c3e1619744887ca'], ['003d2563b3c1023e']]; loss = 0.046998
+Epoch 0: |                                                                            | 2200/? [2:20:31<00:00,  0.26it/s, v_num=gbfj]context = [[11, 13, 17, 19, 42, 43, 50, 51, 58, 60, 61, 63, 65, 71, 74, 77, 82, 85, 89, 95, 99, 101, 103, 108]]target = [[61, 31, 48, 27, 88, 78, 23, 53, 24, 93, 63, 73, 20, 32, 55, 35, 29, 75, 21, 76, 49, 42, 28, 40]]
+[2026-02-25 13:00:42,868][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                            | 2209/? [2:21:12<00:00,  0.26it/s, v_num=gbfj]train step 2210; scene = [['40873337bb9786ab'], ['4f354a704f70f53b'], ['57cea8a71cab48cf'], ['19c383ad9f21d0d3'], ['a98ec507d448dea2'], ['b663a474fd1e4ca4']]; loss = 0.071344
+Epoch 0: |                                                                            | 2210/? [2:21:15<00:00,  0.26it/s, v_num=gbfj]context = [[9, 12, 24, 32, 37, 38, 44, 46, 51, 65, 71, 75], [87, 89, 90, 92, 104, 114, 118, 119, 120, 122, 143, 144]]target = [[61, 31, 40, 37, 52, 13, 14, 68, 57, 25, 70, 54], [95, 130, 128, 134, 91, 114, 133, 102, 129, 98, 138, 116]]
+Epoch 0: |                                                                            | 2219/? [2:21:50<00:00,  0.26it/s, v_num=gbfj]train step 2220; scene = [['d85f0322f215aa54'], ['1318e656455d56d2'], ['e5f41c9021b0b7c1']]; loss = 0.049646
+Epoch 0: |                                                                            | 2220/? [2:21:54<00:00,  0.26it/s, v_num=gbfj]context = [[12, 17, 27, 29, 36, 37, 44, 50, 52, 54, 55, 65, 75, 80, 81, 83, 84, 85, 86, 89, 91, 94, 95, 109]]target = [[83, 45, 76, 92, 104, 41, 30, 59, 79, 28, 86, 38, 85, 64, 66, 51, 106, 15, 89, 16, 46, 108, 99, 33]]
+Epoch 0: |                                                                            | 2229/? [2:22:29<00:00,  0.26it/s, v_num=gbfj]train step 2230; scene = [['9af18a1c4c45a179']]; loss = 0.097594
+Epoch 0: |                                                                            | 2230/? [2:22:33<00:00,  0.26it/s, v_num=gbfj]context = [[40, 43, 44, 61, 67, 70, 74, 77, 79, 85, 87, 92, 93, 98, 100, 103, 108, 115, 117, 123, 128, 134, 135, 137]]target = [[119, 88, 102, 62, 79, 131, 53, 122, 46, 128, 130, 59, 54, 76, 71, 57, 107, 126, 93, 65, 72, 115, 69, 66]]
+Epoch 0: |                                                                            | 2239/? [2:23:07<00:00,  0.26it/s, v_num=gbfj]train step 2240; scene = [['e454026f5348630e'], ['d6a1f3e13c45df99'], ['4dd9c5fab7e6ec75'], ['352d2bdc1900b5e0']]; loss = 0.037153
+Epoch 0: |                                                                            | 2240/? [2:23:11<00:00,  0.26it/s, v_num=gbfj]context = [[5, 53], [14, 60], [21, 91], [60, 113], [2, 85], [31, 99], [27, 81], [3, 54], [15, 101], [11, 69], [0, 45], [193, 272]]target = [[39, 37], [57, 23], [71, 41], [71, 104], [30, 23], [39, 89], [58, 57], [31, 40], [83, 33], [61, 53], [28, 1], [235, 232]]
+Epoch 0: |                                                                            | 2249/? [2:23:45<00:00,  0.26it/s, v_num=gbfj]train step 2250; scene = [['5afa3097bb38b159'], ['c0f67af5cd34e8d8']]; loss = 0.043426
+Epoch 0: |                                                                            | 2250/? [2:23:49<00:00,  0.26it/s, v_num=gbfj]Validation epoch start on rank 0
+Validation: |                                                                                                  | 0/? [00:00<?, ?it/s]validation step 2250; scene = ['651a7f83ed093001'];
+target intrinsic:  tensor(0.8796, device='cuda:0') tensor(0.8798, device='cuda:0')                             | 0/1 [00:00<?, ?it/s]
+pred intrinsic:  tensor(0.8968, device='cuda:0') tensor(0.8959, device='cuda:0')
+[2026-02-25 13:03:57,852][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                            | 2250/? [2:23:51<00:00,  0.26it/s, v_num=gbfj]context = [[0, 21, 34, 39, 59, 63, 83, 84], [23, 26, 33, 34, 53, 58, 59, 68], [118, 137, 141, 150, 154, 170, 188, 192]]target = [[14, 79, 44, 19, 83, 18, 29, 23], [48, 24, 60, 52, 35, 61, 29, 64], [136, 187, 135, 171, 137, 131, 147, 125]]
+Epoch 0: |                                                                            | 2259/? [2:24:23<00:00,  0.26it/s, v_num=gbfj]train step 2260; scene = [['39cafa06c9c431dc']]; loss = 0.054318
+Epoch 0: |                                                                            | 2260/? [2:24:27<00:00,  0.26it/s, v_num=gbfj]context = [[46, 51, 80, 81, 83, 97, 105, 114], [2, 9, 10, 12, 28, 29, 51, 70], [38, 41, 42, 46, 69, 72, 118, 124]]target = [[60, 58, 103, 89, 80, 51, 99, 109], [25, 68, 19, 67, 43, 14, 52, 15], [91, 55, 98, 96, 74, 116, 83, 113]]
+Epoch 0: |                       | 2269/? [2:25:02<00:00,  0.26it/s, v_num=gbfj]train step 2270; scene = [['10a2d0db5c8c0962']]; loss = 0.037845                                                                                   
+Epoch 0: |                       | 2270/? [2:25:06<00:00,  0.26it/s, v_num=gbfj]context = [[33, 39, 52, 59, 85, 90, 93, 112], [16, 18, 22, 27, 40, 46, 55, 70], [2, 32, 40, 41, 42, 46, 51, 71]]target = [[40, 55, 82, 107, 111, 35, 102, 36], [25, 31, 19, 58, 55, 64, 62, 28], [48, 13, 68, 46, 30, 12, 42, 40]]
+Epoch 0: |                       | 2279/? [2:25:40<00:00,  0.26it/s, v_num=gbfj]train step 2280; scene = [['bcbd422c5506815b'], ['dd1a25142bac8d29'], ['ba3e38a071a523f0'], ['2248f7eaf18cca06'], ['d0edef000b9ca743'], ['d9aacea21e110a52']]; loss = 0.060200
+Epoch 0: |                       | 2280/? [2:25:44<00:00,  0.26it/s, v_num=gbfj]context = [[103, 107, 133, 140, 142, 146, 151, 159, 168, 169, 172, 177], [2, 4, 9, 11, 12, 17, 28, 38, 40, 46, 56, 59]]target = [[132, 133, 104, 118, 122, 149, 173, 175, 125, 120, 168, 164], [39, 49, 57, 47, 31, 13, 28, 52, 21, 16, 55, 29]]
+Epoch 0: |                       | 2289/? [2:26:19<00:00,  0.26it/s, v_num=gbfj]train step 2290; scene = [['fa6cb78e1503d22c'], ['f592013dce557cce']]; loss = 0.043143
+Epoch 0: |                       | 2290/? [2:26:23<00:00,  0.26it/s, v_num=gbfj]context = [[30, 35, 41, 49, 50, 59, 65, 78, 89, 91, 113, 116], [126, 127, 128, 134, 152, 160, 162, 166, 171, 172, 176, 177]]target = [[51, 61, 81, 100, 48, 110, 54, 112, 60, 113, 86, 55], [140, 169, 144, 127, 174, 150, 129, 143, 163, 132, 173, 152]]
+Epoch 0: |                       | 2299/? [2:26:56<00:00,  0.26it/s, v_num=gbfj]train step 2300; scene = [['e23f945703f61bfc']]; loss = 0.047680
+Epoch 0: |                       | 2300/? [2:27:00<00:00,  0.26it/s, v_num=gbfj]context = [[73, 94, 106, 123, 128, 130], [6, 22, 33, 42, 45, 51], [165, 166, 167, 196, 205, 228], [98, 109, 112, 134, 135, 152]]target = [[128, 88, 106, 120, 129, 82], [23, 48, 38, 26, 11, 14], [208, 193, 188, 218, 183, 210], [134, 143, 122, 104, 117, 137]]
+Epoch 0: |                       | 2309/? [2:27:34<00:00,  0.26it/s, v_num=gbfj]train step 2310; scene = [['347f4e7f9f627a12'], ['d1d992e581136ac6'], ['59e7800dec3fa9f5'], ['cf6a4349d0ffdfcf']]; loss = 0.038587
+Epoch 0: |                       | 2310/? [2:27:38<00:00,  0.26it/s, v_num=gbfj]context = [[0, 5, 8, 13, 15, 43, 47, 51, 61, 68, 72, 74], [8, 13, 17, 27, 29, 38, 49, 53, 56, 60, 63, 65]]target = [[5, 42, 38, 57, 31, 53, 36, 35, 59, 55, 2, 11], [23, 48, 28, 17, 61, 47, 12, 64, 36, 9, 30, 57]]
+Epoch 0: |                       | 2319/? [2:28:12<00:00,  0.26it/s, v_num=gbfj]train step 2320; scene = [['60c37b519a01205d'], ['b0ee123a8cfc8e62'], ['c5b4562390525d10'], ['8b950107c02ffaa9']]; loss = 0.062199
+Epoch 0: |                       | 2320/? [2:28:16<00:00,  0.26it/s, v_num=gbfj]context = [[8, 11, 13, 15, 17, 25, 29, 39, 40, 45, 48, 58], [4, 18, 21, 36, 47, 50, 60, 63, 71, 76, 79, 82]]target = [[56, 37, 21, 47, 26, 51, 36, 12, 49, 27, 24, 16], [62, 43, 80, 40, 30, 39, 37, 19, 6, 13, 35, 10]]
+Epoch 0: |                       | 2329/? [2:28:49<00:00,  0.26it/s, v_num=gbfj]train step 2330; scene = [['5c9b898102b16eae'], ['583ab14553881ee8'], ['e204af0947f704ad'], ['39edfd183c4f5b5b'], ['a85c79f15c396d71'], ['3d7a200dab472990']]; loss = 0.051215
+Epoch 0: |                       | 2330/? [2:28:52<00:00,  0.26it/s, v_num=gbfj]context = [[9, 23, 91], [5, 23, 61], [94, 164, 165], [149, 165, 237], [73, 137, 159], [1, 13, 48], [5, 55, 59], [25, 55, 75]]target = [[33, 46, 62], [42, 29, 22], [125, 112, 119], [187, 202, 170], [139, 87, 131], [7, 2, 23], [57, 39, 50], [62, 34, 56]]
+Epoch 0: |                       | 2339/? [2:29:27<00:00,  0.26it/s, v_num=gbfj]train step 2340; scene = [['c4005922f59686ae']]; loss = 0.047285
+Epoch 0: |                       | 2340/? [2:29:31<00:00,  0.26it/s, v_num=gbfj]context = [[9, 13, 14, 15, 29, 42, 47, 48, 52, 54, 58, 60, 61, 68, 76, 77, 81, 88, 89, 97, 98, 99, 105, 106]]target = [[72, 73, 28, 65, 82, 67, 96, 56, 75, 94, 16, 101, 63, 80, 83, 33, 41, 61, 93, 100, 14, 86, 32, 11]]
+Epoch 0: |                       | 2349/? [2:30:05<00:00,  0.26it/s, v_num=gbfj]train step 2350; scene = [['009e573e59c8c393'], ['7c48a30f23ea42c3'], ['739123afdcc19a64'], ['ddc11c891f471dd0'], ['38b7b864ae7b21e9'], ['997656bdb430ad43']]; loss = 0.045434
+Epoch 0: |                       | 2350/? [2:30:09<00:00,  0.26it/s, v_num=gbfj]context = [[115, 120, 127, 130, 134, 143, 147, 148, 149, 150, 159, 163, 173, 175, 184, 186, 187, 188, 190, 195, 199, 202, 205, 212]]target = [[148, 147, 199, 184, 190, 152, 134, 189, 127, 120, 201, 163, 186, 165, 171, 193, 117, 210, 183, 211, 195, 156, 204, 145]]
+Epoch 0: |                       | 2359/? [2:30:43<00:00,  0.26it/s, v_num=gbfj]train step 2360; scene = [['9a447c89080e9b56'], ['9eb8e7f262b10c23'], ['c2b8b3e74c64553a'], ['b6f9cfe435a0fde7']]; loss = 0.043503
+Epoch 0: |                       | 2360/? [2:30:47<00:00,  0.26it/s, v_num=gbfj]context = [[1, 4, 8, 16, 17, 28, 40, 45, 51, 53, 60, 62], [1, 4, 5, 11, 12, 13, 14, 15, 17, 29, 40, 82]]target = [[8, 52, 12, 39, 55, 43, 33, 16, 53, 18, 25, 2], [71, 5, 21, 6, 62, 55, 45, 49, 37, 14, 27, 56]]
+Epoch 0: |                       | 2369/? [2:31:21<00:00,  0.26it/s, v_num=gbfj]train step 2370; scene = [['090ced9a667843cb']]; loss = 0.035265
+Epoch 0: |                       | 2370/? [2:31:25<00:00,  0.26it/s, v_num=gbfj]context = [[13, 19, 35, 37, 43, 61, 92, 94], [0, 8, 19, 21, 24, 25, 27, 45], [1, 5, 38, 42, 45, 47, 75, 82]]target = [[46, 77, 90, 47, 83, 21, 76, 54], [3, 11, 9, 33, 20, 41, 42, 4], [72, 28, 74, 38, 52, 40, 35, 34]]
+Epoch 0: |                       | 2379/? [2:32:00<00:00,  0.26it/s, v_num=gbfj]train step 2380; scene = [['8ef9ff3189c85eee'], ['7e8630a890a85545']]; loss = 0.040850
+Epoch 0: |                       | 2380/? [2:32:03<00:00,  0.26it/s, v_num=gbfj]context = [[48, 55, 58, 63, 67, 68, 71, 73, 75, 76, 79, 80, 86, 93, 107, 108, 109, 118, 119, 120, 129, 133, 135, 145]]target = [[133, 59, 121, 87, 96, 110, 67, 101, 49, 142, 60, 134, 109, 132, 98, 122, 103, 100, 80, 57, 65, 86, 128, 143]]
+Epoch 0: |                       | 2389/? [2:32:38<00:00,  0.26it/s, v_num=gbfj]train step 2390; scene = [['343a98bd8cfda2de'], ['c09d7898ef37ba32']]; loss = 0.047163
+Epoch 0: |                       | 2390/? [2:32:42<00:00,  0.26it/s, v_num=gbfj]context = [[19, 20, 31, 32, 41, 46, 49, 50, 51, 53, 59, 60, 62, 63, 74, 77, 82, 84, 85, 91, 93, 97, 98, 116]]target = [[56, 31, 77, 102, 39, 54, 21, 57, 66, 75, 100, 115, 26, 53, 34, 113, 97, 90, 25, 82, 108, 60, 67, 38]]
+Epoch 0: |                       | 2399/? [2:33:17<00:00,  0.26it/s, v_num=gbfj]train step 2400; scene = [['8d758914077e5926']]; loss = 0.047124
+Epoch 0: |                       | 2400/? [2:33:21<00:00,  0.26it/s, v_num=gbfj]context = [[114, 117, 119, 120, 131, 136, 141, 148, 149, 151, 163, 168], [44, 47, 52, 76, 77, 78, 85, 88, 89, 90, 97, 99]]target = [[141, 153, 135, 128, 126, 119, 140, 147, 161, 120, 155, 127], [82, 75, 49, 62, 84, 54, 78, 70, 55, 72, 96, 92]]
+[2026-02-25 13:13:32,568][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                       | 2409/? [2:33:57<00:00,  0.26it/s, v_num=gbfj]train step 2410; scene = [['d35650707515c2cf']]; loss = 0.045309
+Epoch 0: |                       | 2410/? [2:34:00<00:00,  0.26it/s, v_num=gbfj]context = [[4, 8, 16, 30, 45, 53, 70, 77], [123, 139, 144, 149, 166, 184, 187, 207], [38, 44, 51, 66, 68, 90, 94, 98]]target = [[7, 17, 15, 70, 47, 48, 35, 72], [190, 168, 157, 135, 200, 160, 161, 128], [84, 75, 51, 67, 64, 46, 95, 49]]
+Epoch 0: |                       | 2419/? [2:34:35<00:00,  0.26it/s, v_num=gbfj]train step 2420; scene = [['ea5def9e91076788']]; loss = 0.038371
+Epoch 0: |                       | 2420/? [2:34:39<00:00,  0.26it/s, v_num=gbfj]context = [[93, 107, 110, 121, 127, 148], [165, 169, 170, 208, 209, 214], [0, 6, 7, 23, 45, 83], [12, 33, 38, 45, 81, 91]]target = [[131, 99, 135, 127, 142, 120], [167, 177, 176, 213, 171, 191], [22, 45, 64, 29, 67, 51], [47, 31, 65, 87, 60, 85]]
+Epoch 0: |                       | 2429/? [2:35:13<00:00,  0.26it/s, v_num=gbfj]train step 2430; scene = [['45fe4bbb2526ca6e'], ['0db2c3f2775880de'], ['4a0f95a3db913b56']]; loss = 0.029525
+Epoch 0: |                       | 2430/? [2:35:17<00:00,  0.26it/s, v_num=gbfj]context = [[22, 66, 68, 80, 92, 99], [26, 44, 52, 76, 80, 86], [3, 38, 40, 69, 77, 89], [43, 83, 90, 109, 121, 126]]target = [[93, 85, 61, 37, 46, 63], [48, 57, 64, 35, 27, 84], [43, 41, 48, 23, 25, 67], [111, 55, 61, 105, 114, 116]]
+Epoch 0: |                       | 2439/? [2:35:52<00:00,  0.26it/s, v_num=gbfj]train step 2440; scene = [['512f1df8266be984'], ['50c8a233bd82a613']]; loss = 0.060466
+Epoch 0: |                       | 2440/? [2:35:55<00:00,  0.26it/s, v_num=gbfj]context = [[96, 106, 114, 124, 131, 158], [48, 54, 56, 57, 87, 102], [2, 8, 16, 43, 50, 59], [22, 27, 37, 53, 69, 77]]target = [[112, 148, 103, 120, 104, 132], [72, 96, 86, 90, 52, 98], [46, 13, 56, 3, 57, 55], [58, 57, 71, 67, 28, 45]]
+Epoch 0: |                       | 2449/? [2:36:29<00:00,  0.26it/s, v_num=gbfj]train step 2450; scene = [['ac584e6fc77676a4'], ['19a3235d680e11c4'], ['61b9def6cdf00024'], ['fc86266e2fcb72fd']]; loss = 0.039205
+Epoch 0: |                       | 2450/? [2:36:32<00:00,  0.26it/s, v_num=gbfj]context = [[16, 41, 71], [43, 46, 97], [10, 18, 90], [3, 16, 53], [143, 187, 198], [25, 36, 70], [98, 136, 179], [19, 65, 78]]target = [[45, 18, 43], [95, 96, 51], [32, 21, 70], [5, 8, 27], [146, 154, 151], [28, 31, 48], [133, 137, 151], [33, 53, 64]]
+Epoch 0: |                       | 2459/? [2:37:07<00:00,  0.26it/s, v_num=gbfj]train step 2460; scene = [['dc5f38f005c3ebd6']]; loss = 0.069907
+Epoch 0: |                       | 2460/? [2:37:11<00:00,  0.26it/s, v_num=gbfj]context = [[4, 5, 11, 12, 16, 17, 19, 22, 23, 30, 39, 44, 49, 50, 51, 61, 77, 82, 87, 89, 95, 96, 97, 101]]target = [[53, 36, 13, 57, 86, 80, 97, 72, 84, 27, 61, 94, 35, 51, 54, 67, 43, 66, 62, 89, 7, 92, 10, 47]]
+Epoch 0: |                       | 2469/? [2:37:45<00:00,  0.26it/s, v_num=gbfj]train step 2470; scene = [['c7620995ebe9c4e6'], ['06241ebed1658f34'], ['1f214117250f089a'], ['5e31e0691d426537'], ['11c4a7d67bc2629e'], ['715e8695976cdb61'], ['6888f7ca14081419'], ['8fe341dcd0880bd5']]; loss = 0.062375
+Epoch 0: |                       | 2470/? [2:37:49<00:00,  0.26it/s, v_num=gbfj]context = [[17, 28, 38, 42, 68, 86], [2, 4, 28, 37, 51, 58], [7, 21, 24, 54, 64, 70], [41, 42, 61, 71, 81, 89]]target = [[55, 30, 52, 28, 44, 76], [22, 36, 3, 57, 34, 9], [16, 35, 34, 61, 56, 43], [56, 87, 85, 73, 68, 50]]
+Epoch 0: |                       | 2479/? [2:38:23<00:00,  0.26it/s, v_num=gbfj]train step 2480; scene = [['cf98d3219d144500']]; loss = 0.071758
+Epoch 0: |                       | 2480/? [2:38:27<00:00,  0.26it/s, v_num=gbfj]context = [[151, 158, 171, 173, 176, 205, 206, 230], [74, 88, 94, 98, 119, 130, 146, 163], [5, 8, 33, 42, 52, 53, 57, 59]]target = [[177, 223, 212, 220, 205, 207, 225, 222], [102, 132, 115, 112, 145, 156, 119, 100], [12, 23, 49, 20, 55, 32, 10, 39]]
+Epoch 0: |                       | 2489/? [2:39:01<00:00,  0.26it/s, v_num=gbfj]train step 2490; scene = [['ebff5d05f1bb086f'], ['880427ff150f7b4d'], ['9dd0efd4b4626604'], ['f52c70025f40e56d']]; loss = 0.049369
+Epoch 0: |                       | 2490/? [2:39:05<00:00,  0.26it/s, v_num=gbfj]context = [[19, 27, 31, 35, 36, 42, 57, 60, 63, 64, 65, 70], [21, 26, 31, 32, 50, 56, 62, 67, 74, 81, 90, 93]]target = [[51, 33, 64, 68, 53, 29, 54, 27, 26, 69, 35, 48], [59, 60, 83, 76, 86, 68, 61, 36, 71, 22, 69, 82]]
+Epoch 0: |                                                                            | 2499/? [2:39:37<00:00,  0.26it/s, v_num=gbfj]train step 2500; scene = [['7dc5c394263df267']]; loss = 0.061793
+Epoch 0: |                                                                            | 2500/? [2:39:41<00:00,  0.26it/s, v_num=gbfj]Validation epoch start on rank 0
+Validation: |                                                                                                  | 0/? [00:00<?, ?it/s]validation step 2500; scene = ['97ef4323919c5e8a'];
+target intrinsic:  tensor(0.8889, device='cuda:0') tensor(0.8892, device='cuda:0')                             | 0/1 [00:00<?, ?it/s]
+pred intrinsic:  tensor(0.9565, device='cuda:0') tensor(0.9542, device='cuda:0')
+[2026-02-25 13:19:49,814][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                            | 2500/? [2:39:42<00:00,  0.26it/s, v_num=gbfj]context = [[17, 21, 30, 44, 52, 84], [24, 34, 39, 45, 53, 84], [159, 163, 179, 192, 194, 207], [115, 116, 136, 154, 172, 188]]target = [[31, 20, 44, 37, 73, 59], [47, 48, 59, 36, 52, 44], [198, 165, 170, 193, 188, 175], [173, 128, 152, 148, 158, 172]]
+Epoch 0: |                                                                                                                                                                          | 2509/? [2:40:16<00:00,  0.26it/s, v_num=gbfj]train step 2510; scene = [['e806eb496df1dfa0'], ['3caa89905a59e7e6'], ['3fc603b4c4531c11'], ['08da23838ee6e23b'], ['89a0f0553f7f2bdb'], ['5080347450bbcb08']]; loss = 0.053238
+Epoch 0: |                                                                                                                                                                          | 2510/? [2:40:20<00:00,  0.26it/s, v_num=gbfj]context = [[7, 16, 17, 33, 34, 42, 43, 45, 48, 49, 52, 60], [16, 27, 29, 31, 38, 42, 58, 64, 71, 89, 93, 104]]target = [[59, 11, 58, 34, 22, 51, 55, 46, 9, 12, 31, 56], [90, 95, 100, 19, 82, 44, 96, 91, 97, 28, 88, 77]]
+Epoch 0: |                                                                                                                                                                          | 2519/? [2:40:55<00:00,  0.26it/s, v_num=gbfj]train step 2520; scene = [['0a94493d6f4cd4be'], ['1c3a8fcf1547dcf7'], ['c34950273c4d538b'], ['397652e91be52496'], ['d9a133a4747493d2'], ['46dc3900c302593a'], ['e281213868014707'], ['83c959de5ae5b86c']]; loss = 0.069382
+Epoch 0: |                                                                                                                                                                          | 2520/? [2:40:58<00:00,  0.26it/s, v_num=gbfj]context = [[22, 26, 34, 62, 68, 89, 103, 111], [16, 23, 45, 57, 69, 77, 101, 105], [9, 21, 23, 24, 56, 60, 66, 68]]target = [[29, 88, 85, 106, 103, 79, 65, 23], [61, 100, 46, 104, 23, 66, 18, 40], [25, 38, 15, 16, 64, 45, 34, 30]]
+Epoch 0: |                                                                                                                                                                          | 2529/? [2:41:33<00:00,  0.26it/s, v_num=gbfj]train step 2530; scene = [['871ec8d951a81c62']]; loss = 0.049964
+Epoch 0: |                                                                                                                                                                          | 2530/? [2:41:37<00:00,  0.26it/s, v_num=gbfj]context = [[39, 41, 46, 48, 52, 53, 55, 66, 68, 70, 83, 92, 93, 97, 103, 106, 110, 111, 118, 124, 125, 131, 133, 136]]target = [[125, 130, 53, 128, 124, 75, 61, 112, 64, 70, 99, 120, 57, 47, 69, 60, 43, 85, 79, 63, 45, 135, 104, 129]]
+Epoch 0: |                                                                                                                                                                          | 2539/? [2:42:09<00:00,  0.26it/s, v_num=gbfj]train step 2540; scene = [['8e78ce55e3180547']]; loss = 0.037685
+Epoch 0: |                                                                                                                                                                          | 2540/? [2:42:13<00:00,  0.26it/s, v_num=gbfj]context = [[19, 22, 26, 27, 29, 35, 40, 42, 54, 59, 60, 61, 64, 74, 77, 86, 92, 102, 106, 109, 110, 111, 115, 116]]target = [[89, 69, 46, 77, 65, 57, 110, 49, 70, 97, 38, 58, 31, 40, 101, 74, 20, 88, 92, 90, 80, 28, 94, 37]]
+Epoch 0: |                                                                                                                                                                          | 2549/? [2:42:47<00:00,  0.26it/s, v_num=gbfj]train step 2550; scene = [['6dfaec91f745fdd9'], ['3f72021b93b6224a'], ['36be66d194d57ec8']]; loss = 0.061656
+Epoch 0: |                                                                                                                                                                          | 2550/? [2:42:51<00:00,  0.26it/s, v_num=gbfj]context = [[47, 51, 57, 66, 73, 85, 93, 96, 97, 107, 113, 121], [26, 41, 43, 44, 54, 64, 69, 75, 78, 82, 85, 86]]target = [[83, 71, 53, 103, 110, 111, 55, 70, 94, 72, 74, 106], [32, 47, 85, 36, 49, 51, 41, 62, 35, 84, 31, 28]]
+Epoch 0: |                                                                                                                                                                          | 2559/? [2:43:24<00:00,  0.26it/s, v_num=gbfj]train step 2560; scene = [['7c6d160c26de6887'], ['5ef6fe9ef5309457'], ['66de8729fe760dd8'], ['faba60084d22aa27']]; loss = 0.052281
+Epoch 0: |                                                                                                                                                                          | 2560/? [2:43:28<00:00,  0.26it/s, v_num=gbfj]context = [[44, 89, 97], [157, 230, 235], [6, 8, 64], [19, 33, 76], [24, 39, 91], [14, 17, 65], [34, 59, 83], [19, 28, 77]]target = [[93, 77, 73], [195, 166, 202], [62, 61, 20], [61, 65, 30], [82, 90, 72], [32, 60, 21], [67, 74, 43], [39, 27, 37]]
+Epoch 0: |                                                                                                                                                                          | 2569/? [2:44:03<00:00,  0.26it/s, v_num=gbfj]train step 2570; scene = [['678d8464781a3de2'], ['9ab12a31f2a3b9fb']]; loss = 0.047991
+Epoch 0: |                                                                                                                                                                          | 2570/? [2:44:07<00:00,  0.26it/s, v_num=gbfj]context = [[41, 92], [2, 64], [133, 190], [7, 81], [6, 63], [33, 93], [65, 146], [18, 69], [15, 63], [13, 78], [4, 79], [66, 126]]target = [[90, 71], [12, 37], [175, 173], [56, 25], [7, 56], [61, 69], [132, 93], [28, 45], [17, 31], [21, 61], [69, 76], [120, 115]]
+Epoch 0: |                                                                            | 2579/? [2:44:41<00:00,  0.26it/s, v_num=gbfj]train step 2580; scene = [['c40b23830f7437d5'], ['a0c7cabb66c795a4'], ['df63cd7eb6e92486']]; loss = 0.050912
+Epoch 0: |                                                                            | 2580/? [2:44:43<00:00,  0.26it/s, v_num=gbfj]context = [[110, 115, 117, 128, 136, 137, 138, 141, 143, 145, 150, 168], [7, 10, 23, 30, 35, 48, 57, 59, 63, 64, 65, 69]]target = [[128, 149, 154, 126, 167, 132, 162, 151, 112, 134, 133, 131], [18, 25, 50, 30, 12, 19, 47, 39, 54, 35, 37, 56]]
+Epoch 0: |                                                                            | 2589/? [2:45:18<00:00,  0.26it/s, v_num=gbfj]train step 2590; scene = [['65cdcbcb16f0ebe5'], ['4b12a530a5ab03d0']]; loss = 0.034103
+Epoch 0: |                                                                            | 2590/? [2:45:22<00:00,  0.26it/s, v_num=gbfj]context = [[32, 42, 45, 59, 89, 100], [65, 89, 96, 104, 111, 139], [177, 197, 217, 235, 253, 264], [81, 94, 117, 131, 132, 142]]target = [[41, 75, 46, 34, 67, 60], [125, 90, 94, 114, 92, 95], [196, 223, 250, 229, 245, 259], [124, 91, 129, 94, 85, 131]]
+Epoch 0: |                                                                            | 2599/? [2:45:57<00:00,  0.26it/s, v_num=gbfj]train step 2600; scene = [['cb3bac70297d52c0']]; loss = 0.032407
+Epoch 0: |                                                                            | 2600/? [2:46:01<00:00,  0.26it/s, v_num=gbfj]context = [[3, 4, 7, 15, 37, 44, 46, 49], [71, 83, 85, 107, 113, 118, 123, 135], [4, 6, 26, 29, 32, 45, 51, 52]]target = [[38, 11, 27, 26, 16, 48, 39, 30], [81, 90, 94, 125, 75, 97, 110, 98], [22, 27, 29, 35, 7, 9, 49, 21]]
+[2026-02-25 13:26:12,524][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+Epoch 0: |                                                                            | 2609/? [2:46:35<00:00,  0.26it/s, v_num=gbfj]train step 2610; scene = [['262404ef111a096b'], ['5ac9dbde9cf64eed'], ['c32ee937dbec7221'], ['201e44ad015728c7'], ['1fb562b09fc361ea'], ['e454026f5348630e'], ['d1772c09b4b6d95f'], ['8e7cc5c956a4cf95']]; loss = 0.045618
+Epoch 0: |                                                                            | 2610/? [2:46:39<00:00,  0.26it/s, v_num=gbfj]context = [[70, 73, 74, 76, 77, 79, 82, 88, 109, 110, 115, 124, 125, 136, 141, 148, 150, 151, 155, 158, 159, 160, 161, 167]]target = [[156, 121, 159, 150, 128, 138, 162, 81, 102, 71, 103, 74, 137, 144, 108, 166, 72, 161, 129, 110, 165, 136, 106, 99]]
+Epoch 0: |                                                                            | 2619/? [2:47:13<00:00,  0.26it/s, v_num=gbfj]train step 2620; scene = [['4dd74d4d53abb812'], ['9029d8d8f6f0e98a'], ['360253c55aef692f'], ['b07a54eda9cdaccb'], ['ca553e70eff3aa6f'], ['70b45bbd1147fbf0']]; loss = 0.039478
+Epoch 0: |                                                                            | 2620/? [2:47:16<00:00,  0.26it/s, v_num=gbfj]context = [[27, 55, 94], [5, 48, 83], [56, 94, 118], [121, 137, 181], [0, 61, 78], [36, 80, 108], [2, 18, 55], [8, 60, 69]]target = [[62, 80, 57], [21, 23, 34], [84, 71, 87], [139, 178, 159], [59, 19, 76], [104, 40, 51], [43, 20, 8], [47, 68, 60]]
+Epoch 0: |                                                                            | 2629/? [2:47:51<00:00,  0.26it/s, v_num=gbfj]train step 2630; scene = [['c13076a68aeeb481'], ['0bafd80c9e2ae41b']]; loss = 0.053224
+Epoch 0: |                                                                            | 2630/? [2:47:55<00:00,  0.26it/s, v_num=gbfj]context = [[135, 142, 145, 147, 149, 150, 158, 162, 163, 169, 172, 203], [22, 29, 55, 60, 62, 63, 64, 68, 69, 70, 71, 72]]target = [[190, 143, 159, 194, 198, 175, 197, 146, 166, 181, 174, 187], [47, 36, 59, 40, 28, 46, 65, 24, 29, 26, 69, 51]]
+Epoch 0: |                                                                            | 2639/? [2:48:30<00:00,  0.26it/s, v_num=gbfj]train step 2640; scene = [['eae08bd3d5c892e7'], ['60acba38edb03894']]; loss = 0.037621
+Epoch 0: |                                                                            | 2640/? [2:48:33<00:00,  0.26it/s, v_num=gbfj]context = [[166, 176, 251], [156, 173, 220], [69, 137, 148], [197, 204, 277], [28, 29, 100], [44, 111, 118], [0, 56, 61], [4, 68, 81]]target = [[170, 244, 200], [193, 173, 188], [75, 86, 116], [253, 268, 251], [49, 30, 48], [106, 54, 50], [24, 3, 29], [24, 58, 37]]
+Epoch 0: |                                                                            | 2649/? [2:49:08<00:00,  0.26it/s, v_num=gbfj]train step 2650; scene = [['c520ae3405948a0a'], ['94340815d8708eea']]; loss = 0.027323
+Epoch 0: |                                                                            | 2650/? [2:49:12<00:00,  0.26it/s, v_num=gbfj]context = [[6, 10, 15, 16, 20, 26, 31, 32, 37, 40, 42, 47, 55, 57, 66, 69, 70, 80, 82, 85, 88, 93, 101, 103]]target = [[72, 23, 99, 11, 66, 101, 81, 102, 30, 39, 54, 38, 17, 84, 69, 32, 22, 18, 26, 41, 79, 40, 57, 46]]
+Epoch 0: |                                                                            | 2659/? [2:49:47<00:00,  0.26it/s, v_num=gbfj]train step 2660; scene = [['6666ae9375b1656e'], ['64619aa7bd88899d']]; loss = 0.082106
+Epoch 0: |                                                                            | 2660/? [2:49:51<00:00,  0.26it/s, v_num=gbfj]context = [[13, 14, 27, 29, 31, 32, 39, 48, 50, 52, 54, 57, 58, 61, 67, 73, 79, 90, 93, 95, 105, 108, 109, 110]]target = [[83, 48, 82, 104, 25, 53, 89, 72, 93, 51, 41, 86, 24, 49, 32, 98, 78, 73, 88, 45, 44, 99, 58, 79]]
+Epoch 0: |                                                                            | 2666/? [2:50:13<00:00,  0.26it/s, v_num=gbfj]