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ablation_context_train/ABLATION_1112_OURS/.hydra/config.yaml

@@ -0,0 +1,180 @@
+model:
+  encoder:
+    name: dcsplat
+    input_image_shape:
+    - 518
+    - 518
+    head_mode: pcd
+    num_level: 3
+    gs_param_dim: 256
+    align_corners: false
+    use_voxelize: true
+  decoder:
+    name: splatting_cuda
+    background_color:
+    - 0.0
+    - 0.0
+    - 0.0
+    make_scale_invariant: false
+    use_gsplat: true
+  density_control:
+    name: density_control_module
+    mean_dim: 32
+    gs_param_dim: 256
+    refinement_layer_num: 1
+    num_level: 3
+    grad_mode: absgrad
+    use_mean_features: true
+    refinement_type: voxelize
+    refinement_hidden_dim: 32
+    aggregation_mode: mean
+    num_heads: 1
+    score_mode: absgrad
+    latent_dim: 128
+    num_latents: 64
+    num_self_attn_per_block: 2
+    voxel_size: 0.001
+    aux_refine: false
+    refine_error: false
+    use_refine_module: true
+render_loss:
+  mse:
+    weight: 1.0
+  lpips:
+    weight: 0.05
+    apply_after_step: 0
+density_control_loss:
+  error_score:
+    weight: 0.01
+    log_scale: false
+    grad_scale: 10000.0
+    mode: original
+direct_loss:
+  l1:
+    weight: 0.8
+  ssim:
+    weight: 0.2
+wandb:
+  project: DCSplat
+  entity: scene-representation-group
+  name: ABLATION_1112_OURS
+  mode: online
+  tags:
+  - re10k
+  - 256x256
+mode: train
+data_loader:
+  train:
+    num_workers: 16
+    persistent_workers: true
+    batch_size: 16
+    seed: 1234
+  test:
+    num_workers: 4
+    persistent_workers: false
+    batch_size: 1
+    seed: 2345
+  val:
+    num_workers: 1
+    persistent_workers: true
+    batch_size: 1
+    seed: 3456
+optimizer:
+  lr: 0.0002
+  warm_up_steps: 25
+  backbone_lr_multiplier: 0.1
+  backbone_trainable: T+H
+  accumulate: 1
+checkpointing:
+  load: null
+  every_n_train_steps: 1875
+  save_top_k: 1
+  save_weights_only: true
+train:
+  extended_visualization: false
+  print_log_every_n_steps: 10
+  camera_loss: 10.0
+  one_sample_validation: null
+  align_corners: false
+  intrinsic_scaling: false
+  verbose: false
+  beta_dist_param:
+  - 0.5
+  - 4.0
+  use_refine_aux: false
+  train_target_set: true
+  train_gs_num: 3
+  ext_scale_detach: false
+  cam_scale_mode: sum
+  scene_scale_reg_loss: 0.01
+  train_aux: false
+  vggt_cam_loss: true
+test:
+  output_path: test/full/re10k
+  align_pose: false
+  pose_align_steps: 100
+  rot_opt_lr: 0.005
+  trans_opt_lr: 0.005
+  compute_scores: true
+  save_image: false
+  save_video: false
+  save_active_mask_image: false
+  save_error_score_image: false
+  save_compare: false
+  pred_intrinsic: false
+  error_threshold: 0.4
+  error_threshold_list:
+  - 0.2
+  - 0.4
+  - 0.6
+  - 0.8
+  - 1.0
+  threshold_mode: ratio
+  nvs_view_N_list:
+  - 3
+  - 6
+  - 16
+  - 32
+  - 64
+seed: 111123
+trainer:
+  max_steps: 3751
+  val_check_interval: 250
+  gradient_clip_val: 0.5
+  num_nodes: 1
+dataset:
+  re10k:
+    make_baseline_1: true
+    relative_pose: true
+    augment: true
+    background_color:
+    - 0.0
+    - 0.0
+    - 0.0
+    overfit_to_scene: null
+    skip_bad_shape: true
+    view_sampler:
+      name: bounded
+      num_target_views: 4
+      num_context_views: 2
+      min_distance_between_context_views: 45
+      max_distance_between_context_views: 90
+      min_distance_to_context_views: 0
+      warm_up_steps: 1875
+      initial_min_distance_between_context_views: 25
+      initial_max_distance_between_context_views: 25
+      same_target_gap: false
+      num_target_set: 3
+    name: re10k
+    roots:
+    - datasets/re10k
+    input_image_shape:
+    - 256
+    - 256
+    original_image_shape:
+    - 360
+    - 640
+    cameras_are_circular: false
+    baseline_min: 0.001
+    baseline_max: 10000000000.0
+    max_fov: 100.0

ablation_context_train/ABLATION_1112_OURS/.hydra/hydra.yaml

@@ -0,0 +1,165 @@
+hydra:
+  run:
+    dir: outputs/full/re10k/${wandb.name}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - +experiment=re10k_ablation
+    - wandb.mode=online
+    - wandb.name=ABLATION_1112_OURS
+    - train.train_aux=False
+  job:
+    name: main
+    chdir: null
+    override_dirname: +experiment=re10k_ablation,train.train_aux=False,wandb.mode=online,wandb.name=ABLATION_1112_OURS
+    id: ???
+    num: ???
+    config_name: main
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /workspace/code/CVPR2026
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /workspace/code/CVPR2026/config
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /workspace/code/CVPR2026/outputs/full/re10k/ABLATION_1112_OURS
+    choices:
+      experiment: re10k_ablation
+      dataset@dataset.re10k: re10k
+      dataset/view_sampler_dataset_specific_config@dataset.re10k.view_sampler: bounded_re10k
+      dataset/view_sampler@dataset.re10k.view_sampler: bounded
+      model/density_control: density_control_module
+      model/decoder: splatting_cuda
+      model/encoder: dcsplat
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

ablation_context_train/ABLATION_1112_OURS/.hydra/overrides.yaml

@@ -0,0 +1,4 @@
+- +experiment=re10k_ablation
+- wandb.mode=online
+- wandb.name=ABLATION_1112_OURS
+- train.train_aux=False

ablation_context_train/ABLATION_1112_OURS/main.log

@@ -0,0 +1,55 @@
+[2026-01-28 17:59:07,361][dinov2][INFO] - using MLP layer as FFN
+[2026-01-28 17:59:12,599][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(
+
+[2026-01-28 17:59:12,599][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)
+
+[2026-01-28 17:59:18,507][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=191` in the `DataLoader` to improve performance.
+
+[2026-01-28 17:59:22,333][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
+
+[2026-01-28 17:59:22,343][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)`.
+
+[2026-01-28 17:59:22,344][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(
+
+[2026-01-28 17:59:22,344][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)
+
+[2026-01-28 17:59:23,730][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]
+
+[2026-01-28 17:59:33,213][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
+
+[2026-01-28 18:00:28,011][dinov2][INFO] - using MLP layer as FFN
+[2026-01-28 18:00:34,694][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(
+
+[2026-01-28 18:00:34,696][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)
+
+[2026-01-28 18:00:38,579][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=191` in the `DataLoader` to improve performance.
+
+[2026-01-28 18:00:40,933][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
+
+[2026-01-28 18:00:40,943][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)`.
+
+[2026-01-28 18:00:40,945][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(
+
+[2026-01-28 18:00:40,945][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)
+
+[2026-01-28 18:00:42,297][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]
+
+[2026-01-28 18:00:44,469][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)
+
+[2026-01-28 18:01:48,744][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)
+

ablation_context_train/ABLATION_1112_OURS/wandb/debug-internal.log

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ablation_context_train/ABLATION_1112_OURS/wandb/debug.log

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+2026-01-28 18:00:36,525 INFO    MainThread:16831 [wandb_setup.py:_flush():81] Loading settings from environment variables
+2026-01-28 18:00:36,525 INFO    MainThread:16831 [wandb_init.py:setup_run_log_directory():717] Logging user logs to /workspace/code/CVPR2026/outputs/full/re10k/ABLATION_1112_OURS/wandb/run-20260128_180036-b57bz9uf/logs/debug.log
+2026-01-28 18:00:36,525 INFO    MainThread:16831 [wandb_init.py:setup_run_log_directory():718] Logging internal logs to /workspace/code/CVPR2026/outputs/full/re10k/ABLATION_1112_OURS/wandb/run-20260128_180036-b57bz9uf/logs/debug-internal.log
+2026-01-28 18:00:36,525 INFO    MainThread:16831 [wandb_init.py:init():844] calling init triggers
+2026-01-28 18:00:36,525 INFO    MainThread:16831 [wandb_init.py:init():849] wandb.init called with sweep_config: {}
+config: {'model': {'encoder': {'name': 'dcsplat', 'input_image_shape': [518, 518], 'head_mode': 'pcd', 'num_level': 3, 'gs_param_dim': 256, 'align_corners': False, 'use_voxelize': True}, 'decoder': {'name': 'splatting_cuda', 'background_color': [0.0, 0.0, 0.0], 'make_scale_invariant': False, 'use_gsplat': True}, 'density_control': {'name': 'density_control_module', 'mean_dim': 32, 'gs_param_dim': 256, 'refinement_layer_num': 1, 'num_level': 3, 'grad_mode': 'absgrad', 'use_mean_features': True, 'refinement_type': 'voxelize', 'refinement_hidden_dim': 32, 'aggregation_mode': 'mean', 'num_heads': 1, 'score_mode': 'absgrad', 'latent_dim': 128, 'num_latents': 64, 'num_self_attn_per_block': 2, 'voxel_size': 0.001, 'aux_refine': False, 'refine_error': False, 'use_refine_module': True}}, 'render_loss': {'mse': {'weight': 1.0}, 'lpips': {'weight': 0.05, 'apply_after_step': 0}}, 'density_control_loss': {'error_score': {'weight': 0.01, 'log_scale': False, 'grad_scale': 10000.0, 'mode': 'original'}}, 'direct_loss': {'l1': {'weight': 0.8}, 'ssim': {'weight': 0.2}}, 'wandb': {'project': 'DCSplat', 'entity': 'scene-representation-group', 'name': 'ABLATION_1112_OURS', 'mode': 'online', 'tags': ['re10k', '256x256']}, 'mode': 'train', 'data_loader': {'train': {'num_workers': 16, 'persistent_workers': True, 'batch_size': 16, 'seed': 1234}, 'test': {'num_workers': 4, 'persistent_workers': False, 'batch_size': 1, 'seed': 2345}, 'val': {'num_workers': 1, 'persistent_workers': True, 'batch_size': 1, 'seed': 3456}}, 'optimizer': {'lr': 0.0002, 'warm_up_steps': 25, 'backbone_lr_multiplier': 0.1, 'backbone_trainable': 'T+H', 'accumulate': 1}, 'checkpointing': {'load': None, 'every_n_train_steps': 1875, 'save_top_k': 1, 'save_weights_only': True}, 'train': {'extended_visualization': False, 'print_log_every_n_steps': 10, 'camera_loss': 10.0, 'one_sample_validation': None, 'align_corners': False, 'intrinsic_scaling': False, 'verbose': False, 'beta_dist_param': [0.5, 4.0], 'use_refine_aux': False, 'train_target_set': True, 'train_gs_num': 3, 'ext_scale_detach': False, 'cam_scale_mode': 'sum', 'scene_scale_reg_loss': 0.01, 'train_aux': False, 'vggt_cam_loss': True}, 'test': {'output_path': 'test/full/re10k', 'align_pose': False, 'pose_align_steps': 100, 'rot_opt_lr': 0.005, 'trans_opt_lr': 0.005, 'compute_scores': True, 'save_image': False, 'save_video': False, 'save_active_mask_image': False, 'save_error_score_image': False, 'save_compare': False, 'pred_intrinsic': False, 'error_threshold': 0.4, 'error_threshold_list': [0.2, 0.4, 0.6, 0.8, 1.0], 'threshold_mode': 'ratio', 'nvs_view_N_list': [3, 6, 16, 32, 64]}, 'seed': 111123, 'trainer': {'max_steps': 3751, 'val_check_interval': 250, 'gradient_clip_val': 0.5, 'num_nodes': 1}, 'dataset': {'re10k': {'make_baseline_1': True, 'relative_pose': True, 'augment': True, 'background_color': [0.0, 0.0, 0.0], 'overfit_to_scene': None, 'skip_bad_shape': True, 'view_sampler': {'name': 'bounded', 'num_target_views': 4, 'num_context_views': 2, 'min_distance_between_context_views': 45, 'max_distance_between_context_views': 90, 'min_distance_to_context_views': 0, 'warm_up_steps': 1875, 'initial_min_distance_between_context_views': 25, 'initial_max_distance_between_context_views': 25, 'same_target_gap': False, 'num_target_set': 3}, 'name': 're10k', 'roots': ['datasets/re10k'], 'input_image_shape': [256, 256], 'original_image_shape': [360, 640], 'cameras_are_circular': False, 'baseline_min': 0.001, 'baseline_max': 10000000000.0, 'max_fov': 100.0}}, '_wandb': {}}
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ablation_context_train/ABLATION_1112_OURS/wandb/run-20260128_175915-a37ejg97/files/config.yaml

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+_wandb:
+    value:
+        cli_version: 0.24.0
+        e:
+            ub1u5epxcjvrx93xh0mqo7xv5kjnij7b:
+                args:
+                    - +experiment=re10k_ablation
+                    - wandb.mode=online
+                    - wandb.name=ABLATION_1112_OURS
+                cpu_count: 96
+                cpu_count_logical: 192
+                cudaVersion: "12.8"
+                disk:
+                    /:
+                        total: "1219770712064"
+                        used: "605820416000"
+                email: dna9041@korea.ac.kr
+                executable: /venv/main/bin/python
+                git:
+                    commit: 3e5bcbb84918c5e9d89b86392b6022cbf335c88c
+                    remote: git@github.com:K-nowing/CVPR2026.git
+                gpu: NVIDIA H200
+                gpu_count: 8
+                gpu_nvidia:
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-9fc9f640-1049-b714-5cf1-370809c7dada
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-415cce85-f06d-8388-950d-2040cf24ec7a
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-668b6742-b633-d66f-6a5c-0adba454527e
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-28ff5e21-29eb-70c9-b3bb-ad4ddab78939
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-b810293f-263a-30c0-564f-e754c8bf4274
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-3c230576-a6ba-f2a3-2f46-6ffa14e39bae
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-d955e2e4-a8a2-9b4d-5412-afaf6538d0a4
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-f5b481f4-a291-4f81-4192-4b621b767bca
+                host: 0889cc894876
+                memory:
+                    total: "2164161441792"
+                os: Linux-5.15.0-140-generic-x86_64-with-glibc2.39
+                program: -m src.main
+                python: CPython 3.12.12
+                root: /workspace/code/CVPR2026/outputs/full/re10k/ABLATION_1112_OURS
+                startedAt: "2026-01-28T17:59:15.793677Z"
+                writerId: ub1u5epxcjvrx93xh0mqo7xv5kjnij7b
+        m:
+            - "1": trainer/global_step
+              "6":
+                - 3
+              "7": []
+            - "2": '*'
+              "5": 1
+              "6":
+                - 1
+              "7": []
+        python_version: 3.12.12
+        t:
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+                - 66
+            "4": 3.12.12
+            "5": 0.24.0
+            "12": 0.24.0
+            "13": linux-x86_64
+checkpointing:
+    value:
+        every_n_train_steps: 1875
+        load: null
+        save_top_k: 1
+        save_weights_only: true
+data_loader:
+    value:
+        test:
+            batch_size: 1
+            num_workers: 4
+            persistent_workers: false
+            seed: 2345
+        train:
+            batch_size: 16
+            num_workers: 16
+            persistent_workers: true
+            seed: 1234
+        val:
+            batch_size: 1
+            num_workers: 1
+            persistent_workers: true
+            seed: 3456
+dataset:
+    value:
+        re10k:
+            augment: true
+            background_color:
+                - 0
+                - 0
+                - 0
+            baseline_max: 1e+10
+            baseline_min: 0.001
+            cameras_are_circular: false
+            input_image_shape:
+                - 256
+                - 256
+            make_baseline_1: true
+            max_fov: 100
+            name: re10k
+            original_image_shape:
+                - 360
+                - 640
+            overfit_to_scene: null
+            relative_pose: true
+            roots:
+                - datasets/re10k
+            skip_bad_shape: true
+            view_sampler:
+                initial_max_distance_between_context_views: 25
+                initial_min_distance_between_context_views: 25
+                max_distance_between_context_views: 90
+                min_distance_between_context_views: 45
+                min_distance_to_context_views: 0
+                name: bounded
+                num_context_views: 2
+                num_target_set: 3
+                num_target_views: 4
+                same_target_gap: false
+                warm_up_steps: 1875
+density_control_loss:
+    value:
+        error_score:
+            grad_scale: 10000
+            log_scale: false
+            mode: original
+            weight: 0.01
+direct_loss:
+    value:
+        l1:
+            weight: 0.8
+        ssim:
+            weight: 0.2
+mode:
+    value: train
+model:
+    value:
+        decoder:
+            background_color:
+                - 0
+                - 0
+                - 0
+            make_scale_invariant: false
+            name: splatting_cuda
+            use_gsplat: true
+        density_control:
+            aggregation_mode: mean
+            aux_refine: false
+            grad_mode: absgrad
+            gs_param_dim: 256
+            latent_dim: 128
+            mean_dim: 32
+            name: density_control_module
+            num_heads: 1
+            num_latents: 64
+            num_level: 3
+            num_self_attn_per_block: 2
+            refine_error: false
+            refinement_hidden_dim: 32
+            refinement_layer_num: 1
+            refinement_type: voxelize
+            score_mode: absgrad
+            use_mean_features: true
+            use_refine_module: true
+            voxel_size: 0.001
+        encoder:
+            align_corners: false
+            gs_param_dim: 256
+            head_mode: pcd
+            input_image_shape:
+                - 518
+                - 518
+            name: dcsplat
+            num_level: 3
+            use_voxelize: true
+optimizer:
+    value:
+        accumulate: 1
+        backbone_lr_multiplier: 0.1
+        backbone_trainable: T+H
+        lr: 0.0002
+        warm_up_steps: 25
+render_loss:
+    value:
+        lpips:
+            apply_after_step: 0
+            weight: 0.05
+        mse:
+            weight: 1
+seed:
+    value: 111123
+test:
+    value:
+        align_pose: false
+        compute_scores: true
+        error_threshold: 0.4
+        error_threshold_list:
+            - 0.2
+            - 0.4
+            - 0.6
+            - 0.8
+            - 1
+        nvs_view_N_list:
+            - 3
+            - 6
+            - 16
+            - 32
+            - 64
+        output_path: test/full/re10k
+        pose_align_steps: 100
+        pred_intrinsic: false
+        rot_opt_lr: 0.005
+        save_active_mask_image: false
+        save_compare: false
+        save_error_score_image: false
+        save_image: false
+        save_video: false
+        threshold_mode: ratio
+        trans_opt_lr: 0.005
+train:
+    value:
+        align_corners: false
+        beta_dist_param:
+            - 0.5
+            - 4
+        cam_scale_mode: sum
+        camera_loss: 10
+        ext_scale_detach: false
+        extended_visualization: false
+        intrinsic_scaling: false
+        one_sample_validation: null
+        print_log_every_n_steps: 10
+        scene_scale_reg_loss: 0.01
+        train_aux: true
+        train_gs_num: 3
+        train_target_set: true
+        use_refine_aux: false
+        verbose: false
+        vggt_cam_loss: true
+trainer:
+    value:
+        gradient_clip_val: 0.5
+        max_steps: 3751
+        num_nodes: 1
+        val_check_interval: 250
+wandb:
+    value:
+        entity: scene-representation-group
+        mode: online
+        name: ABLATION_1112_OURS
+        project: DCSplat
+        tags:
+            - re10k
+            - 256x256

ablation_context_train/ABLATION_1112_OURS/wandb/run-20260128_175915-a37ejg97/files/output.log

@@ -0,0 +1,61 @@
+LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
+
+  | 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
+3,564.328 Total estimated model params size (MB)
+1231      Modules in train mode
+522       Modules in eval mode
+Sanity Checking: |                                                                                             | 0/? [00:00<?, ?it/s][2026-01-28 17:59:18,507][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=191` in the `DataLoader` to improve performance.
+
+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')
+W0128 17:59:22.282000 16265 site-packages/torch/utils/cpp_extension.py:2425] TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation.
+W0128 17:59:22.282000 16265 site-packages/torch/utils/cpp_extension.py:2425] If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'] to specific architectures.
+[2026-01-28 17:59:22,333][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
+
+[2026-01-28 17:59:22,343][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]
+[2026-01-28 17:59:22,344][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(
+
+[2026-01-28 17:59:22,344][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
+[2026-01-28 17:59:23,730][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]
+
+Epoch 0: |                                                                                                     | 0/? [00:00<?, ?it/s]context = [[96, 121], [19, 44], [2, 27], [215, 240], [105, 130], [29, 54], [80, 105], [26, 51], [33, 58], [39, 64], [124, 149], [9, 34], [46, 71], [62, 87], [16, 41], [36, 61]]target = [[97, 103, 110, 100], [21, 33, 43, 31], [15, 11, 18, 17], [232, 239, 236, 223], [112, 123, 111, 106], [45, 32, 41, 51], [83, 90, 99, 103], [38, 48, 30, 41], [53, 48, 40, 38], [51, 44, 62, 48], [125, 146, 143, 133], [29, 13, 20, 27], [50, 49, 62, 70], [84, 75, 72, 86], [25, 22, 24, 37], [53, 51, 56, 38]]
+[2026-01-28 17:59:33,213][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/? [00:27<00:00,  0.33it/s, v_num=jg97]train step 10; scene = ['78784c6ffe218407', '2144f1fd5b00dc66', 'f568ab2fa64994e9', 'eac6cedeba1f720b', '216d5454333d29b5', 'b628b7d46a07cb57', '3b07094586f67024', '044df93e59024ee2', '167c67586a8c0846', '3931c6a7e69ffff1', 'c9c67636b9d521be', '0908c09364f54c42', '2d92b7321e1039c5', '3bc0044f0678f39f', 'e51ef9945ae527c4', 'bb32e9a89ca9387e']; loss = 0.650682
+Epoch 0: |                                                                                | 10/? [00:30<00:00,  0.33it/s, v_num=jg97]context = [[71, 96], [101, 126], [238, 263], [68, 93], [104, 129], [20, 45], [52, 77], [53, 78], [32, 57], [243, 268], [0, 25], [24, 49], [13, 38], [67, 92], [15, 40], [198, 223]]target = [[79, 86, 92, 81], [108, 123, 102, 109], [243, 253, 262, 245], [86, 90, 70, 80], [117, 125, 111, 123], [38, 36, 30, 39], [60, 76, 69, 68], [69, 64, 73, 55], [38, 44, 55, 40], [259, 264, 251, 249], [13, 4, 10, 2], [46, 29, 43, 39], [17, 23, 20, 14], [73, 71, 70, 69], [30, 23, 39, 17], [204, 217, 214, 201]]
+Epoch 0: |                                                                                | 19/? [00:56<00:00,  0.33it/s, v_num=jg97]train step 20; scene = ['6546295c3cec469a', 'b2186a798ad4fb49', 'b3232677872b2974', 'b3edac66be582f84', '420ca2704db5b476', 'db1723893a3a6277', '9e88bf87287fd8fe', '9e302a18a294b945', '4581bdd74b6ee0a9', '1f9574f1e0c1c2b2', 'e8674463d514e8a5', 'eedd397acee4cb4f', '47240d3fcf37fc1b', '5140967fcd51092e', 'c18ea6a77949e219', '08234c2181c4db46']; loss = 0.362112
+Epoch 0: |                                                                                | 20/? [00:59<00:00,  0.33it/s, v_num=jg97]context = [[21, 46], [2, 27], [154, 179], [3, 28], [25, 50], [177, 202], [25, 50], [9, 34], [61, 86], [13, 38], [132, 157], [24, 49], [46, 71], [42, 67], [108, 133], [78, 103]]target = [[43, 45, 33, 28], [19, 14, 23, 26], [171, 177, 173, 168], [16, 24, 15, 17], [41, 26, 47, 30], [200, 199, 201, 180], [28, 33, 37, 27], [10, 26, 17, 28], [77, 65, 72, 62], [14, 30, 18, 25], [153, 139, 154, 134], [37, 44, 42, 47], [54, 65, 67, 53], [58, 65, 43, 66], [120, 123, 113, 119], [98, 80, 96, 94]]
+Epoch 0: |                                                                                | 24/? [01:11<00:00,  0.33it/s, v_num=jg97][2026-01-28 18:00:44,469][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/? [01:26<00:00,  0.34it/s, v_num=jg97]train step 30; scene = ['6dd4b348223c880c', 'b730ba2045aa78eb', '5dbc84083496e415', 'fd4c9fb0fae56ccd', 'a8cef6a851fbea3c', '66c3771cf7cb96c2', '590f0b63f12a500d', '75790c62002de4f2', 'dff181c503e5c202', 'bbde6840d9d8b008', '5a2ad43377e9d18d', 'a597e94e50eb917a', 'cfb20f8971e6a591', '67e69f3a4701dfd8', 'b91dfcb3102d1482', '9c763036f1d84e18']; loss = 0.240503
+Epoch 0: |                                                                                | 30/? [01:29<00:00,  0.34it/s, v_num=jg97]context = [[37, 62], [104, 129], [45, 70], [55, 80], [47, 72], [6, 31], [12, 37], [64, 89], [36, 61], [7, 32], [1, 26], [184, 209], [3, 28], [14, 39], [96, 121], [34, 59]]target = [[47, 60, 53, 49], [118, 126, 106, 113], [55, 60, 54, 53], [62, 60, 66, 65], [56, 62, 65, 60], [20, 30, 27, 17], [23, 15, 27, 28], [85, 81, 69, 83], [48, 59, 55, 50], [19, 31, 13, 16], [25, 13, 18, 3], [190, 198, 196, 188], [18, 24, 20, 21], [15, 23, 31, 17], [104, 106, 98, 118], [55, 47, 50, 42]]
+Epoch 0: |                                                                                | 39/? [01:56<00:00,  0.34it/s, v_num=jg97]train step 40; scene = ['d69c7df5913f4f60', 'c46e81f142867e29', '0207b0ec0cc851f6', '70dfdf6911373a48', '437474fa4196e1b7', '55cf2bbe9e017ea4', 'c49bd62c183dd925', '629f07baec1cbad5', '0066ed3711a7240d', 'd066040e500bd58b', '99e9f09b456ef23e', '3ef8d3ae25b575f3', '7e7b53917bcf337b', 'd7ca14c855d58875', 'd1772c09b4b6d95f', '0f0bbb6510ca3018']; loss = 0.175532
+Epoch 0: |                                                                                | 40/? [01:59<00:00,  0.34it/s, v_num=jg97]context = [[28, 53], [6, 31], [24, 49], [74, 99], [22, 47], [38, 63], [24, 49], [34, 59], [35, 60], [0, 25], [13, 38], [107, 132], [50, 75], [5, 30], [28, 53], [79, 104]]target = [[45, 32, 40, 47], [21, 22, 11, 26], [29, 34, 27, 38], [75, 92, 91, 90], [42, 33, 37, 28], [41, 43, 55, 53], [43, 40, 28, 25], [37, 52, 39, 56], [41, 36, 38, 58], [3, 21, 24, 18], [31, 24, 20, 26], [119, 126, 115, 111], [52, 71, 64, 62], [10, 20, 27, 26], [39, 33, 34, 47], [81, 96, 91, 95]]
+Epoch 0: |                                                                                | 49/? [02:25<00:00,  0.34it/s, v_num=jg97]train step 50; scene = ['ea5a39bd855fdd91', 'f47abcad22b7b6c4', '604b0838aa3321c5', 'c2fd6e5ebbff57b3', '9794641b7e015578', 'f3135a7492955a8a', '5041701491a4b930', '23d17b97a9d3674e', '2dd4d2a252e34405', '1e339189e5782868', '7e58b6857e275547', 'fe1cf5504260d4ea', '06dfdeca94f15bc0', 'c6b5c4c06be45afd', '96b163f47895beee', '83c9baf5bbc941ee']; loss = 0.151590
+Epoch 0: |                                                                                | 50/? [02:28<00:00,  0.34it/s, v_num=jg97]context = [[93, 118], [16, 41], [3, 28], [162, 187], [90, 115], [2, 27], [60, 85], [61, 86], [12, 37], [4, 29], [3, 28], [134, 159], [231, 256], [68, 93], [215, 240], [190, 215]]target = [[98, 116, 95, 110], [32, 28, 25, 31], [15, 9, 20, 17], [168, 185, 177, 164], [100, 91, 93, 103], [15, 12, 25, 11], [83, 72, 77, 69], [81, 80, 71, 70], [14, 33, 35, 31], [20, 6, 5, 21], [8, 12, 26, 9], [156, 145, 151, 150], [243, 238, 241, 249], [91, 71, 73, 77], [223, 236, 216, 217], [203, 205, 201, 193]]
+Epoch 0: |                                                                                | 59/? [02:55<00:00,  0.34it/s, v_num=jg97]
+
+Detected KeyboardInterrupt, attempting graceful shutdown ...

ablation_context_train/ABLATION_1112_OURS/wandb/run-20260128_175915-a37ejg97/files/requirements.txt

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ablation_context_train/ABLATION_1112_OURS/wandb/run-20260128_175915-a37ejg97/files/wandb-metadata.json

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+  "os": "Linux-5.15.0-140-generic-x86_64-with-glibc2.39",
+  "python": "CPython 3.12.12",
+  "startedAt": "2026-01-28T17:59:15.793677Z",
+  "args": [
+    "+experiment=re10k_ablation",
+    "wandb.mode=online",
+    "wandb.name=ABLATION_1112_OURS"
+  ],
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+  "git": {
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+    "commit": "3e5bcbb84918c5e9d89b86392b6022cbf335c88c"
+  },
+  "email": "dna9041@korea.ac.kr",
+  "root": "/workspace/code/CVPR2026/outputs/full/re10k/ABLATION_1112_OURS",
+  "host": "0889cc894876",
+  "executable": "/venv/main/bin/python",
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+  "writerId": "ub1u5epxcjvrx93xh0mqo7xv5kjnij7b"
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+
+  | 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
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+1231      Modules in train mode
+522       Modules in eval mode
+Sanity Checking: |                                                                                             | 0/? [00:00<?, ?it/s][2026-01-28 18:00:38,579][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=191` in the `DataLoader` to improve performance.
+
+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')
+W0128 18:00:40.884000 16831 site-packages/torch/utils/cpp_extension.py:2425] TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation.
+W0128 18:00:40.884000 16831 site-packages/torch/utils/cpp_extension.py:2425] If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'] to specific architectures.
+[2026-01-28 18:00:40,933][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
+
+[2026-01-28 18:00:40,943][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]
+[2026-01-28 18:00:40,945][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(
+
+[2026-01-28 18:00:40,945][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
+[2026-01-28 18:00:42,297][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]
+
+Epoch 0: |                                                                                                     | 0/? [00:00<?, ?it/s]context = [[96, 121], [19, 44], [2, 27], [215, 240], [105, 130], [29, 54], [80, 105], [26, 51], [33, 58], [39, 64], [124, 149], [9, 34], [46, 71], [62, 87], [16, 41], [36, 61]]target = [[97, 103, 110, 100], [21, 33, 43, 31], [15, 11, 18, 17], [232, 239, 236, 223], [112, 123, 111, 106], [45, 32, 41, 51], [83, 90, 99, 103], [38, 48, 30, 41], [53, 48, 40, 38], [51, 44, 62, 48], [125, 146, 143, 133], [29, 13, 20, 27], [50, 49, 62, 70], [84, 75, 72, 86], [25, 22, 24, 37], [53, 51, 56, 38]]
+Epoch 0: |                                                                                 | 9/? [00:23<00:00,  0.39it/s, v_num=z9uf]train step 10; scene = ['78784c6ffe218407', '2144f1fd5b00dc66', 'f568ab2fa64994e9', 'eac6cedeba1f720b', '216d5454333d29b5', 'b628b7d46a07cb57', '3b07094586f67024', '044df93e59024ee2', '167c67586a8c0846', '3931c6a7e69ffff1', 'c9c67636b9d521be', '0908c09364f54c42', '2d92b7321e1039c5', '3bc0044f0678f39f', 'e51ef9945ae527c4', 'bb32e9a89ca9387e']; loss = 0.157460
+Epoch 0: |                                                                                | 10/? [00:25<00:00,  0.39it/s, v_num=z9uf]context = [[71, 96], [101, 126], [238, 263], [68, 93], [104, 129], [20, 45], [52, 77], [53, 78], [32, 57], [243, 268], [0, 25], [24, 49], [13, 38], [67, 92], [15, 40], [198, 223]]target = [[79, 86, 92, 81], [108, 123, 102, 109], [243, 253, 262, 245], [86, 90, 70, 80], [117, 125, 111, 123], [38, 36, 30, 39], [60, 76, 69, 68], [69, 64, 73, 55], [38, 44, 55, 40], [259, 264, 251, 249], [13, 4, 10, 2], [46, 29, 43, 39], [17, 23, 20, 14], [73, 71, 70, 69], [30, 23, 39, 17], [204, 217, 214, 201]]
+Epoch 0: |                                                                                | 19/? [00:47<00:00,  0.40it/s, v_num=z9uf]train step 20; scene = ['6546295c3cec469a', 'b2186a798ad4fb49', 'b3232677872b2974', 'b3edac66be582f84', '420ca2704db5b476', 'db1723893a3a6277', '9e88bf87287fd8fe', '9e302a18a294b945', '4581bdd74b6ee0a9', '1f9574f1e0c1c2b2', 'e8674463d514e8a5', 'eedd397acee4cb4f', '47240d3fcf37fc1b', '5140967fcd51092e', 'c18ea6a77949e219', '08234c2181c4db46']; loss = 0.090015
+Epoch 0: |                                                                                | 20/? [00:50<00:00,  0.40it/s, v_num=z9uf]context = [[21, 46], [2, 27], [154, 179], [3, 28], [25, 50], [177, 202], [25, 50], [9, 34], [61, 86], [13, 38], [132, 157], [24, 49], [46, 71], [42, 67], [108, 133], [78, 103]]target = [[43, 45, 33, 28], [19, 14, 23, 26], [171, 177, 173, 168], [16, 24, 15, 17], [41, 26, 47, 30], [200, 199, 201, 180], [28, 33, 37, 27], [10, 26, 17, 28], [77, 65, 72, 62], [14, 30, 18, 25], [153, 139, 154, 134], [37, 44, 42, 47], [54, 65, 67, 53], [58, 65, 43, 66], [120, 123, 113, 119], [98, 80, 96, 94]]
+Epoch 0: |                                                                                | 24/? [01:00<00:00,  0.40it/s, v_num=z9uf][2026-01-28 18:01:48,744][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/? [01:12<00:00,  0.40it/s, v_num=z9uf]train step 30; scene = ['6dd4b348223c880c', 'b730ba2045aa78eb', '5dbc84083496e415', 'fd4c9fb0fae56ccd', 'a8cef6a851fbea3c', '66c3771cf7cb96c2', '590f0b63f12a500d', '75790c62002de4f2', 'dff181c503e5c202', 'bbde6840d9d8b008', '5a2ad43377e9d18d', 'a597e94e50eb917a', 'cfb20f8971e6a591', '67e69f3a4701dfd8', 'b91dfcb3102d1482', '9c763036f1d84e18']; loss = 0.065553
+Epoch 0: |                                                                                | 30/? [01:15<00:00,  0.40it/s, v_num=z9uf]context = [[37, 62], [104, 129], [45, 70], [55, 80], [47, 72], [6, 31], [12, 37], [64, 89], [36, 61], [7, 32], [1, 26], [184, 209], [3, 28], [14, 39], [96, 121], [34, 59]]target = [[47, 60, 53, 49], [118, 126, 106, 113], [55, 60, 54, 53], [62, 60, 66, 65], [56, 62, 65, 60], [20, 30, 27, 17], [23, 15, 27, 28], [85, 81, 69, 83], [48, 59, 55, 50], [19, 31, 13, 16], [25, 13, 18, 3], [190, 198, 196, 188], [18, 24, 20, 21], [15, 23, 31, 17], [104, 106, 98, 118], [55, 47, 50, 42]]
+Epoch 0: |                                                                                | 39/? [01:37<00:00,  0.40it/s, v_num=z9uf]
+
+Detected KeyboardInterrupt, attempting graceful shutdown ...

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+{"time":"2026-01-28T18:03:49.344954146Z","level":"INFO","msg":"fileTransfer: Close: file transfer manager closed"}
+{"time":"2026-01-28T18:03:49.447646645Z","level":"INFO","msg":"handler: closed","stream_id":"b57bz9uf"}
+{"time":"2026-01-28T18:03:49.447916291Z","level":"INFO","msg":"sender: closed","stream_id":"b57bz9uf"}
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ablation_context_train/ABLATION_1112_OURS/wandb/run-20260128_180036-b57bz9uf/logs/debug.log

@@ -0,0 +1,21 @@
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+2026-01-28 18:00:36,525 INFO    MainThread:16831 [wandb_setup.py:_flush():81] Configure stats pid to 16831
+2026-01-28 18:00:36,525 INFO    MainThread:16831 [wandb_setup.py:_flush():81] Loading settings from environment variables
+2026-01-28 18:00:36,525 INFO    MainThread:16831 [wandb_init.py:setup_run_log_directory():717] Logging user logs to /workspace/code/CVPR2026/outputs/full/re10k/ABLATION_1112_OURS/wandb/run-20260128_180036-b57bz9uf/logs/debug.log
+2026-01-28 18:00:36,525 INFO    MainThread:16831 [wandb_init.py:setup_run_log_directory():718] Logging internal logs to /workspace/code/CVPR2026/outputs/full/re10k/ABLATION_1112_OURS/wandb/run-20260128_180036-b57bz9uf/logs/debug-internal.log
+2026-01-28 18:00:36,525 INFO    MainThread:16831 [wandb_init.py:init():844] calling init triggers
+2026-01-28 18:00:36,525 INFO    MainThread:16831 [wandb_init.py:init():849] wandb.init called with sweep_config: {}
+config: {'model': {'encoder': {'name': 'dcsplat', 'input_image_shape': [518, 518], 'head_mode': 'pcd', 'num_level': 3, 'gs_param_dim': 256, 'align_corners': False, 'use_voxelize': True}, 'decoder': {'name': 'splatting_cuda', 'background_color': [0.0, 0.0, 0.0], 'make_scale_invariant': False, 'use_gsplat': True}, 'density_control': {'name': 'density_control_module', 'mean_dim': 32, 'gs_param_dim': 256, 'refinement_layer_num': 1, 'num_level': 3, 'grad_mode': 'absgrad', 'use_mean_features': True, 'refinement_type': 'voxelize', 'refinement_hidden_dim': 32, 'aggregation_mode': 'mean', 'num_heads': 1, 'score_mode': 'absgrad', 'latent_dim': 128, 'num_latents': 64, 'num_self_attn_per_block': 2, 'voxel_size': 0.001, 'aux_refine': False, 'refine_error': False, 'use_refine_module': True}}, 'render_loss': {'mse': {'weight': 1.0}, 'lpips': {'weight': 0.05, 'apply_after_step': 0}}, 'density_control_loss': {'error_score': {'weight': 0.01, 'log_scale': False, 'grad_scale': 10000.0, 'mode': 'original'}}, 'direct_loss': {'l1': {'weight': 0.8}, 'ssim': {'weight': 0.2}}, 'wandb': {'project': 'DCSplat', 'entity': 'scene-representation-group', 'name': 'ABLATION_1112_OURS', 'mode': 'online', 'tags': ['re10k', '256x256']}, 'mode': 'train', 'data_loader': {'train': {'num_workers': 16, 'persistent_workers': True, 'batch_size': 16, 'seed': 1234}, 'test': {'num_workers': 4, 'persistent_workers': False, 'batch_size': 1, 'seed': 2345}, 'val': {'num_workers': 1, 'persistent_workers': True, 'batch_size': 1, 'seed': 3456}}, 'optimizer': {'lr': 0.0002, 'warm_up_steps': 25, 'backbone_lr_multiplier': 0.1, 'backbone_trainable': 'T+H', 'accumulate': 1}, 'checkpointing': {'load': None, 'every_n_train_steps': 1875, 'save_top_k': 1, 'save_weights_only': True}, 'train': {'extended_visualization': False, 'print_log_every_n_steps': 10, 'camera_loss': 10.0, 'one_sample_validation': None, 'align_corners': False, 'intrinsic_scaling': False, 'verbose': False, 'beta_dist_param': [0.5, 4.0], 'use_refine_aux': False, 'train_target_set': True, 'train_gs_num': 3, 'ext_scale_detach': False, 'cam_scale_mode': 'sum', 'scene_scale_reg_loss': 0.01, 'train_aux': False, 'vggt_cam_loss': True}, 'test': {'output_path': 'test/full/re10k', 'align_pose': False, 'pose_align_steps': 100, 'rot_opt_lr': 0.005, 'trans_opt_lr': 0.005, 'compute_scores': True, 'save_image': False, 'save_video': False, 'save_active_mask_image': False, 'save_error_score_image': False, 'save_compare': False, 'pred_intrinsic': False, 'error_threshold': 0.4, 'error_threshold_list': [0.2, 0.4, 0.6, 0.8, 1.0], 'threshold_mode': 'ratio', 'nvs_view_N_list': [3, 6, 16, 32, 64]}, 'seed': 111123, 'trainer': {'max_steps': 3751, 'val_check_interval': 250, 'gradient_clip_val': 0.5, 'num_nodes': 1}, 'dataset': {'re10k': {'make_baseline_1': True, 'relative_pose': True, 'augment': True, 'background_color': [0.0, 0.0, 0.0], 'overfit_to_scene': None, 'skip_bad_shape': True, 'view_sampler': {'name': 'bounded', 'num_target_views': 4, 'num_context_views': 2, 'min_distance_between_context_views': 45, 'max_distance_between_context_views': 90, 'min_distance_to_context_views': 0, 'warm_up_steps': 1875, 'initial_min_distance_between_context_views': 25, 'initial_max_distance_between_context_views': 25, 'same_target_gap': False, 'num_target_set': 3}, 'name': 're10k', 'roots': ['datasets/re10k'], 'input_image_shape': [256, 256], 'original_image_shape': [360, 640], 'cameras_are_circular': False, 'baseline_min': 0.001, 'baseline_max': 10000000000.0, 'max_fov': 100.0}}, '_wandb': {}}
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+2026-01-28 18:03:48,997 INFO    wandb-AsyncioManager-main:16831 [mailbox.py:close():137] Closing mailbox, abandoning 1 handles.

ablation_context_train/ABLATION_1112_noRefineModule/.hydra/config.yaml

@@ -0,0 +1,180 @@
+model:
+  encoder:
+    name: dcsplat
+    input_image_shape:
+    - 518
+    - 518
+    head_mode: pcd
+    num_level: 3
+    gs_param_dim: 256
+    align_corners: false
+    use_voxelize: true
+  decoder:
+    name: splatting_cuda
+    background_color:
+    - 0.0
+    - 0.0
+    - 0.0
+    make_scale_invariant: false
+    use_gsplat: true
+  density_control:
+    name: density_control_module
+    mean_dim: 32
+    gs_param_dim: 256
+    refinement_layer_num: 1
+    num_level: 3
+    grad_mode: absgrad
+    use_mean_features: true
+    refinement_type: voxelize
+    refinement_hidden_dim: 32
+    aggregation_mode: mean
+    num_heads: 1
+    score_mode: absgrad
+    latent_dim: 128
+    num_latents: 64
+    num_self_attn_per_block: 2
+    voxel_size: 0.001
+    aux_refine: false
+    refine_error: false
+    use_refine_module: false
+render_loss:
+  mse:
+    weight: 1.0
+  lpips:
+    weight: 0.05
+    apply_after_step: 0
+density_control_loss:
+  error_score:
+    weight: 0.01
+    log_scale: false
+    grad_scale: 10000.0
+    mode: original
+direct_loss:
+  l1:
+    weight: 0.8
+  ssim:
+    weight: 0.2
+wandb:
+  project: DCSplat
+  entity: scene-representation-group
+  name: ABLATION_1112_noRefineModule
+  mode: online
+  tags:
+  - re10k
+  - 256x256
+mode: train
+data_loader:
+  train:
+    num_workers: 16
+    persistent_workers: true
+    batch_size: 16
+    seed: 1234
+  test:
+    num_workers: 4
+    persistent_workers: false
+    batch_size: 1
+    seed: 2345
+  val:
+    num_workers: 1
+    persistent_workers: true
+    batch_size: 1
+    seed: 3456
+optimizer:
+  lr: 0.0002
+  warm_up_steps: 25
+  backbone_lr_multiplier: 0.1
+  backbone_trainable: T+H
+  accumulate: 1
+checkpointing:
+  load: null
+  every_n_train_steps: 1875
+  save_top_k: 1
+  save_weights_only: true
+train:
+  extended_visualization: false
+  print_log_every_n_steps: 10
+  camera_loss: 10.0
+  one_sample_validation: null
+  align_corners: false
+  intrinsic_scaling: false
+  verbose: false
+  beta_dist_param:
+  - 0.5
+  - 4.0
+  use_refine_aux: false
+  train_target_set: true
+  train_gs_num: 3
+  ext_scale_detach: false
+  cam_scale_mode: sum
+  scene_scale_reg_loss: 0.01
+  train_aux: true
+  vggt_cam_loss: true
+test:
+  output_path: test/full/re10k
+  align_pose: false
+  pose_align_steps: 100
+  rot_opt_lr: 0.005
+  trans_opt_lr: 0.005
+  compute_scores: true
+  save_image: false
+  save_video: false
+  save_active_mask_image: false
+  save_error_score_image: false
+  save_compare: false
+  pred_intrinsic: false
+  error_threshold: 0.4
+  error_threshold_list:
+  - 0.2
+  - 0.4
+  - 0.6
+  - 0.8
+  - 1.0
+  threshold_mode: ratio
+  nvs_view_N_list:
+  - 3
+  - 6
+  - 16
+  - 32
+  - 64
+seed: 111123
+trainer:
+  max_steps: 3751
+  val_check_interval: 250
+  gradient_clip_val: 0.5
+  num_nodes: 1
+dataset:
+  re10k:
+    make_baseline_1: true
+    relative_pose: true
+    augment: true
+    background_color:
+    - 0.0
+    - 0.0
+    - 0.0
+    overfit_to_scene: null
+    skip_bad_shape: true
+    view_sampler:
+      name: bounded
+      num_target_views: 4
+      num_context_views: 2
+      min_distance_between_context_views: 45
+      max_distance_between_context_views: 90
+      min_distance_to_context_views: 0
+      warm_up_steps: 1875
+      initial_min_distance_between_context_views: 25
+      initial_max_distance_between_context_views: 25
+      same_target_gap: false
+      num_target_set: 3
+    name: re10k
+    roots:
+    - datasets/re10k
+    input_image_shape:
+    - 256
+    - 256
+    original_image_shape:
+    - 360
+    - 640
+    cameras_are_circular: false
+    baseline_min: 0.001
+    baseline_max: 10000000000.0
+    max_fov: 100.0

ablation_context_train/ABLATION_1112_noRefineModule/.hydra/hydra.yaml

@@ -0,0 +1,165 @@
+hydra:
+  run:
+    dir: outputs/full/re10k/${wandb.name}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - +experiment=re10k_ablation
+    - wandb.mode=online
+    - wandb.name=ABLATION_1112_noRefineModule
+    - model.density_control.use_refine_module=false
+  job:
+    name: main
+    chdir: null
+    override_dirname: +experiment=re10k_ablation,model.density_control.use_refine_module=false,wandb.mode=online,wandb.name=ABLATION_1112_noRefineModule
+    id: ???
+    num: ???
+    config_name: main
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /workspace/code/CVPR2026
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /workspace/code/CVPR2026/config
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /workspace/code/CVPR2026/outputs/full/re10k/ABLATION_1112_noRefineModule
+    choices:
+      experiment: re10k_ablation
+      dataset@dataset.re10k: re10k
+      dataset/view_sampler_dataset_specific_config@dataset.re10k.view_sampler: bounded_re10k
+      dataset/view_sampler@dataset.re10k.view_sampler: bounded
+      model/density_control: density_control_module
+      model/decoder: splatting_cuda
+      model/encoder: dcsplat
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

ablation_context_train/ABLATION_1112_noRefineModule/.hydra/overrides.yaml

@@ -0,0 +1,4 @@
+- +experiment=re10k_ablation
+- wandb.mode=online
+- wandb.name=ABLATION_1112_noRefineModule
+- model.density_control.use_refine_module=false

ablation_context_train/ABLATION_1112_noSceneScaleReg/.hydra/config.yaml

@@ -0,0 +1,180 @@
+model:
+  encoder:
+    name: dcsplat
+    input_image_shape:
+    - 518
+    - 518
+    head_mode: pcd
+    num_level: 3
+    gs_param_dim: 256
+    align_corners: false
+    use_voxelize: true
+  decoder:
+    name: splatting_cuda
+    background_color:
+    - 0.0
+    - 0.0
+    - 0.0
+    make_scale_invariant: false
+    use_gsplat: true
+  density_control:
+    name: density_control_module
+    mean_dim: 32
+    gs_param_dim: 256
+    refinement_layer_num: 1
+    num_level: 3
+    grad_mode: absgrad
+    use_mean_features: true
+    refinement_type: voxelize
+    refinement_hidden_dim: 32
+    aggregation_mode: mean
+    num_heads: 1
+    score_mode: absgrad
+    latent_dim: 128
+    num_latents: 64
+    num_self_attn_per_block: 2
+    voxel_size: 0.001
+    aux_refine: false
+    refine_error: false
+    use_refine_module: true
+render_loss:
+  mse:
+    weight: 1.0
+  lpips:
+    weight: 0.05
+    apply_after_step: 0
+density_control_loss:
+  error_score:
+    weight: 0.01
+    log_scale: false
+    grad_scale: 10000.0
+    mode: original
+direct_loss:
+  l1:
+    weight: 0.8
+  ssim:
+    weight: 0.2
+wandb:
+  project: DCSplat
+  entity: scene-representation-group
+  name: ABLATION_1112_noSceneScaleReg
+  mode: online
+  tags:
+  - re10k
+  - 256x256
+mode: train
+data_loader:
+  train:
+    num_workers: 16
+    persistent_workers: true
+    batch_size: 16
+    seed: 1234
+  test:
+    num_workers: 4
+    persistent_workers: false
+    batch_size: 1
+    seed: 2345
+  val:
+    num_workers: 1
+    persistent_workers: true
+    batch_size: 1
+    seed: 3456
+optimizer:
+  lr: 0.0002
+  warm_up_steps: 25
+  backbone_lr_multiplier: 0.1
+  backbone_trainable: T+H
+  accumulate: 1
+checkpointing:
+  load: null
+  every_n_train_steps: 1875
+  save_top_k: 1
+  save_weights_only: true
+train:
+  extended_visualization: false
+  print_log_every_n_steps: 10
+  camera_loss: 10.0
+  one_sample_validation: null
+  align_corners: false
+  intrinsic_scaling: false
+  verbose: false
+  beta_dist_param:
+  - 0.5
+  - 4.0
+  use_refine_aux: false
+  train_target_set: true
+  train_gs_num: 3
+  ext_scale_detach: false
+  cam_scale_mode: sum
+  scene_scale_reg_loss: 0.0
+  train_aux: true
+  vggt_cam_loss: true
+test:
+  output_path: test/full/re10k
+  align_pose: false
+  pose_align_steps: 100
+  rot_opt_lr: 0.005
+  trans_opt_lr: 0.005
+  compute_scores: true
+  save_image: false
+  save_video: false
+  save_active_mask_image: false
+  save_error_score_image: false
+  save_compare: false
+  pred_intrinsic: false
+  error_threshold: 0.4
+  error_threshold_list:
+  - 0.2
+  - 0.4
+  - 0.6
+  - 0.8
+  - 1.0
+  threshold_mode: ratio
+  nvs_view_N_list:
+  - 3
+  - 6
+  - 16
+  - 32
+  - 64
+seed: 111123
+trainer:
+  max_steps: 3751
+  val_check_interval: 250
+  gradient_clip_val: 0.5
+  num_nodes: 1
+dataset:
+  re10k:
+    make_baseline_1: true
+    relative_pose: true
+    augment: true
+    background_color:
+    - 0.0
+    - 0.0
+    - 0.0
+    overfit_to_scene: null
+    skip_bad_shape: true
+    view_sampler:
+      name: bounded
+      num_target_views: 4
+      num_context_views: 2
+      min_distance_between_context_views: 45
+      max_distance_between_context_views: 90
+      min_distance_to_context_views: 0
+      warm_up_steps: 1875
+      initial_min_distance_between_context_views: 25
+      initial_max_distance_between_context_views: 25
+      same_target_gap: false
+      num_target_set: 3
+    name: re10k
+    roots:
+    - datasets/re10k
+    input_image_shape:
+    - 256
+    - 256
+    original_image_shape:
+    - 360
+    - 640
+    cameras_are_circular: false
+    baseline_min: 0.001
+    baseline_max: 10000000000.0
+    max_fov: 100.0

ablation_context_train/ABLATION_1112_noSceneScaleReg/.hydra/hydra.yaml

@@ -0,0 +1,165 @@
+hydra:
+  run:
+    dir: outputs/full/re10k/${wandb.name}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - +experiment=re10k_ablation
+    - wandb.mode=online
+    - wandb.name=ABLATION_1112_noSceneScaleReg
+    - train.scene_scale_reg_loss=0.0
+  job:
+    name: main
+    chdir: null
+    override_dirname: +experiment=re10k_ablation,train.scene_scale_reg_loss=0.0,wandb.mode=online,wandb.name=ABLATION_1112_noSceneScaleReg
+    id: ???
+    num: ???
+    config_name: main
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /workspace/code/CVPR2026
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /workspace/code/CVPR2026/config
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /workspace/code/CVPR2026/outputs/full/re10k/ABLATION_1112_noSceneScaleReg
+    choices:
+      experiment: re10k_ablation
+      dataset@dataset.re10k: re10k
+      dataset/view_sampler_dataset_specific_config@dataset.re10k.view_sampler: bounded_re10k
+      dataset/view_sampler@dataset.re10k.view_sampler: bounded
+      model/density_control: density_control_module
+      model/decoder: splatting_cuda
+      model/encoder: dcsplat
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

ablation_context_train/ABLATION_1112_noSceneScaleReg/.hydra/overrides.yaml

@@ -0,0 +1,4 @@
+- +experiment=re10k_ablation
+- wandb.mode=online
+- wandb.name=ABLATION_1112_noSceneScaleReg
+- train.scene_scale_reg_loss=0.0

ablation_context_train/ABLATION_1112_noSceneScaleReg/main.log

@@ -0,0 +1,46 @@
+[2026-01-28 18:04:00,500][dinov2][INFO] - using MLP layer as FFN
+[2026-01-28 18:04:00,910][dinov2][INFO] - using MLP layer as FFN
+[2026-01-28 18:04:07,690][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(
+
+[2026-01-28 18:04:07,691][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)
+
+[2026-01-28 18:04:08,382][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(
+
+[2026-01-28 18:04:08,383][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)
+
+[2026-01-28 18:04:12,389][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=191` in the `DataLoader` to improve performance.
+
+[2026-01-28 18:04:13,034][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=191` in the `DataLoader` to improve performance.
+
+[2026-01-28 18:04:16,154][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
+
+[2026-01-28 18:04:16,169][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)`.
+
+[2026-01-28 18:04:16,170][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(
+
+[2026-01-28 18:04:16,170][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)
+
+[2026-01-28 18:04:16,775][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
+
+[2026-01-28 18:04:16,794][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)`.
+
+[2026-01-28 18:04:16,796][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(
+
+[2026-01-28 18:04:16,797][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)
+
+[2026-01-28 18:04:18,448][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]
+
+[2026-01-28 18:04:18,879][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]
+

ablation_context_train/ABLATION_1112_noSceneScaleReg/wandb/debug-internal.log

@@ -0,0 +1,10 @@
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+{"time":"2026-01-28T18:04:11.397646248Z","level":"INFO","msg":"stream: started","id":"s61twks1"}
+{"time":"2026-01-28T18:04:11.397719401Z","level":"INFO","msg":"writer: started","stream_id":"s61twks1"}
+{"time":"2026-01-28T18:04:11.397792752Z","level":"INFO","msg":"sender: started","stream_id":"s61twks1"}
+{"time":"2026-01-28T18:05:27.737025966Z","level":"INFO","msg":"flowcontrol: backed up, offloading to disk","recordNumber":197}
+{"time":"2026-01-28T18:05:27.737654722Z","level":"INFO","msg":"stream: closing","id":"s61twks1"}
+{"time":"2026-01-28T18:05:27.739297639Z","level":"ERROR","msg":"flowcontrol: failed reading after 0 records: transactionlog: bad header: leveldb/record: reader not in first block","chunk":{"InitialOffset":51346,"InitialNumber":197,"Count":17}}
+{"time":"2026-01-28T18:05:27.740544683Z","level":"INFO","msg":"flowcontrol: unblocked","totalOffloaded":17}

ablation_context_train/ABLATION_1112_noSceneScaleReg/wandb/debug.log

@@ -0,0 +1,21 @@
+2026-01-28 18:04:10,734 INFO    MainThread:17433 [wandb_setup.py:_flush():81] Current SDK version is 0.24.0
+2026-01-28 18:04:10,734 INFO    MainThread:17433 [wandb_setup.py:_flush():81] Configure stats pid to 17433
+2026-01-28 18:04:10,734 INFO    MainThread:17433 [wandb_setup.py:_flush():81] Loading settings from environment variables
+2026-01-28 18:04:10,734 INFO    MainThread:17433 [wandb_init.py:setup_run_log_directory():717] Logging user logs to /workspace/code/CVPR2026/outputs/full/re10k/ABLATION_1112_noSceneScaleReg/wandb/run-20260128_180410-s61twks1/logs/debug.log
+2026-01-28 18:04:10,734 INFO    MainThread:17433 [wandb_init.py:setup_run_log_directory():718] Logging internal logs to /workspace/code/CVPR2026/outputs/full/re10k/ABLATION_1112_noSceneScaleReg/wandb/run-20260128_180410-s61twks1/logs/debug-internal.log
+2026-01-28 18:04:10,734 INFO    MainThread:17433 [wandb_init.py:init():844] calling init triggers
+2026-01-28 18:04:10,734 INFO    MainThread:17433 [wandb_init.py:init():849] wandb.init called with sweep_config: {}
+config: {'model': {'encoder': {'name': 'dcsplat', 'input_image_shape': [518, 518], 'head_mode': 'pcd', 'num_level': 3, 'gs_param_dim': 256, 'align_corners': False, 'use_voxelize': True}, 'decoder': {'name': 'splatting_cuda', 'background_color': [0.0, 0.0, 0.0], 'make_scale_invariant': False, 'use_gsplat': True}, 'density_control': {'name': 'density_control_module', 'mean_dim': 32, 'gs_param_dim': 256, 'refinement_layer_num': 1, 'num_level': 3, 'grad_mode': 'absgrad', 'use_mean_features': True, 'refinement_type': 'voxelize', 'refinement_hidden_dim': 32, 'aggregation_mode': 'mean', 'num_heads': 1, 'score_mode': 'absgrad', 'latent_dim': 128, 'num_latents': 64, 'num_self_attn_per_block': 2, 'voxel_size': 0.001, 'aux_refine': False, 'refine_error': False, 'use_refine_module': True}}, 'render_loss': {'mse': {'weight': 1.0}, 'lpips': {'weight': 0.05, 'apply_after_step': 0}}, 'density_control_loss': {'error_score': {'weight': 0.01, 'log_scale': False, 'grad_scale': 10000.0, 'mode': 'original'}}, 'direct_loss': {'l1': {'weight': 0.8}, 'ssim': {'weight': 0.2}}, 'wandb': {'project': 'DCSplat', 'entity': 'scene-representation-group', 'name': 'ABLATION_1112_noSceneScaleReg', 'mode': 'online', 'tags': ['re10k', '256x256']}, 'mode': 'train', 'data_loader': {'train': {'num_workers': 16, 'persistent_workers': True, 'batch_size': 16, 'seed': 1234}, 'test': {'num_workers': 4, 'persistent_workers': False, 'batch_size': 1, 'seed': 2345}, 'val': {'num_workers': 1, 'persistent_workers': True, 'batch_size': 1, 'seed': 3456}}, 'optimizer': {'lr': 0.0002, 'warm_up_steps': 25, 'backbone_lr_multiplier': 0.1, 'backbone_trainable': 'T+H', 'accumulate': 1}, 'checkpointing': {'load': None, 'every_n_train_steps': 1875, 'save_top_k': 1, 'save_weights_only': True}, 'train': {'extended_visualization': False, 'print_log_every_n_steps': 10, 'camera_loss': 10.0, 'one_sample_validation': None, 'align_corners': False, 'intrinsic_scaling': False, 'verbose': False, 'beta_dist_param': [0.5, 4.0], 'use_refine_aux': False, 'train_target_set': True, 'train_gs_num': 3, 'ext_scale_detach': False, 'cam_scale_mode': 'sum', 'scene_scale_reg_loss': 0.0, 'train_aux': True, 'vggt_cam_loss': True}, 'test': {'output_path': 'test/full/re10k', 'align_pose': False, 'pose_align_steps': 100, 'rot_opt_lr': 0.005, 'trans_opt_lr': 0.005, 'compute_scores': True, 'save_image': False, 'save_video': False, 'save_active_mask_image': False, 'save_error_score_image': False, 'save_compare': False, 'pred_intrinsic': False, 'error_threshold': 0.4, 'error_threshold_list': [0.2, 0.4, 0.6, 0.8, 1.0], 'threshold_mode': 'ratio', 'nvs_view_N_list': [3, 6, 16, 32, 64]}, 'seed': 111123, 'trainer': {'max_steps': 3751, 'val_check_interval': 250, 'gradient_clip_val': 0.5, 'num_nodes': 1}, 'dataset': {'re10k': {'make_baseline_1': True, 'relative_pose': True, 'augment': True, 'background_color': [0.0, 0.0, 0.0], 'overfit_to_scene': None, 'skip_bad_shape': True, 'view_sampler': {'name': 'bounded', 'num_target_views': 4, 'num_context_views': 2, 'min_distance_between_context_views': 45, 'max_distance_between_context_views': 90, 'min_distance_to_context_views': 0, 'warm_up_steps': 1875, 'initial_min_distance_between_context_views': 25, 'initial_max_distance_between_context_views': 25, 'same_target_gap': False, 'num_target_set': 3}, 'name': 're10k', 'roots': ['datasets/re10k'], 'input_image_shape': [256, 256], 'original_image_shape': [360, 640], 'cameras_are_circular': False, 'baseline_min': 0.001, 'baseline_max': 10000000000.0, 'max_fov': 100.0}}, '_wandb': {}}
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ablation_context_train/ABLATION_1112_noSceneScaleReg/wandb/run-20260128_180409-npo9zheb/files/config.yaml

@@ -0,0 +1,302 @@
+_wandb:
+    value:
+        cli_version: 0.24.0
+        e:
+            bbelvnpdzcoxnhchrj7gsd2jmzq3fh80:
+                args:
+                    - +experiment=re10k_ablation
+                    - wandb.mode=online
+                    - wandb.name=ABLATION_1112_noSceneScaleReg
+                    - train.scene_scale_reg_loss=0.0
+                cpu_count: 96
+                cpu_count_logical: 192
+                cudaVersion: "12.8"
+                disk:
+                    /:
+                        total: "1219770712064"
+                        used: "605828562944"
+                email: dna9041@korea.ac.kr
+                executable: /venv/main/bin/python
+                git:
+                    commit: 3e5bcbb84918c5e9d89b86392b6022cbf335c88c
+                    remote: git@github.com:K-nowing/CVPR2026.git
+                gpu: NVIDIA H200
+                gpu_count: 8
+                gpu_nvidia:
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-9fc9f640-1049-b714-5cf1-370809c7dada
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-415cce85-f06d-8388-950d-2040cf24ec7a
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-668b6742-b633-d66f-6a5c-0adba454527e
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-28ff5e21-29eb-70c9-b3bb-ad4ddab78939
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-b810293f-263a-30c0-564f-e754c8bf4274
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-3c230576-a6ba-f2a3-2f46-6ffa14e39bae
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-d955e2e4-a8a2-9b4d-5412-afaf6538d0a4
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-f5b481f4-a291-4f81-4192-4b621b767bca
+                host: 0889cc894876
+                memory:
+                    total: "2164161441792"
+                os: Linux-5.15.0-140-generic-x86_64-with-glibc2.39
+                program: -m src.main
+                python: CPython 3.12.12
+                root: /workspace/code/CVPR2026/outputs/full/re10k/ABLATION_1112_noSceneScaleReg
+                startedAt: "2026-01-28T18:04:09.753910Z"
+                writerId: bbelvnpdzcoxnhchrj7gsd2jmzq3fh80
+        m:
+            - "1": trainer/global_step
+              "6":
+                - 3
+              "7": []
+            - "2": '*'
+              "5": 1
+              "6":
+                - 1
+              "7": []
+        python_version: 3.12.12
+        t:
+            "1":
+                - 1
+                - 41
+                - 49
+                - 50
+                - 106
+            "2":
+                - 1
+                - 41
+                - 49
+                - 50
+                - 106
+            "3":
+                - 7
+                - 13
+                - 15
+                - 16
+                - 66
+            "4": 3.12.12
+            "5": 0.24.0
+            "12": 0.24.0
+            "13": linux-x86_64
+checkpointing:
+    value:
+        every_n_train_steps: 1875
+        load: null
+        save_top_k: 1
+        save_weights_only: true
+data_loader:
+    value:
+        test:
+            batch_size: 1
+            num_workers: 4
+            persistent_workers: false
+            seed: 2345
+        train:
+            batch_size: 16
+            num_workers: 16
+            persistent_workers: true
+            seed: 1234
+        val:
+            batch_size: 1
+            num_workers: 1
+            persistent_workers: true
+            seed: 3456
+dataset:
+    value:
+        re10k:
+            augment: true
+            background_color:
+                - 0
+                - 0
+                - 0
+            baseline_max: 1e+10
+            baseline_min: 0.001
+            cameras_are_circular: false
+            input_image_shape:
+                - 256
+                - 256
+            make_baseline_1: true
+            max_fov: 100
+            name: re10k
+            original_image_shape:
+                - 360
+                - 640
+            overfit_to_scene: null
+            relative_pose: true
+            roots:
+                - datasets/re10k
+            skip_bad_shape: true
+            view_sampler:
+                initial_max_distance_between_context_views: 25
+                initial_min_distance_between_context_views: 25
+                max_distance_between_context_views: 90
+                min_distance_between_context_views: 45
+                min_distance_to_context_views: 0
+                name: bounded
+                num_context_views: 2
+                num_target_set: 3
+                num_target_views: 4
+                same_target_gap: false
+                warm_up_steps: 1875
+density_control_loss:
+    value:
+        error_score:
+            grad_scale: 10000
+            log_scale: false
+            mode: original
+            weight: 0.01
+direct_loss:
+    value:
+        l1:
+            weight: 0.8
+        ssim:
+            weight: 0.2
+mode:
+    value: train
+model:
+    value:
+        decoder:
+            background_color:
+                - 0
+                - 0
+                - 0
+            make_scale_invariant: false
+            name: splatting_cuda
+            use_gsplat: true
+        density_control:
+            aggregation_mode: mean
+            aux_refine: false
+            grad_mode: absgrad
+            gs_param_dim: 256
+            latent_dim: 128
+            mean_dim: 32
+            name: density_control_module
+            num_heads: 1
+            num_latents: 64
+            num_level: 3
+            num_self_attn_per_block: 2
+            refine_error: false
+            refinement_hidden_dim: 32
+            refinement_layer_num: 1
+            refinement_type: voxelize
+            score_mode: absgrad
+            use_mean_features: true
+            use_refine_module: true
+            voxel_size: 0.001
+        encoder:
+            align_corners: false
+            gs_param_dim: 256
+            head_mode: pcd
+            input_image_shape:
+                - 518
+                - 518
+            name: dcsplat
+            num_level: 3
+            use_voxelize: true
+optimizer:
+    value:
+        accumulate: 1
+        backbone_lr_multiplier: 0.1
+        backbone_trainable: T+H
+        lr: 0.0002
+        warm_up_steps: 25
+render_loss:
+    value:
+        lpips:
+            apply_after_step: 0
+            weight: 0.05
+        mse:
+            weight: 1
+seed:
+    value: 111123
+test:
+    value:
+        align_pose: false
+        compute_scores: true
+        error_threshold: 0.4
+        error_threshold_list:
+            - 0.2
+            - 0.4
+            - 0.6
+            - 0.8
+            - 1
+        nvs_view_N_list:
+            - 3
+            - 6
+            - 16
+            - 32
+            - 64
+        output_path: test/full/re10k
+        pose_align_steps: 100
+        pred_intrinsic: false
+        rot_opt_lr: 0.005
+        save_active_mask_image: false
+        save_compare: false
+        save_error_score_image: false
+        save_image: false
+        save_video: false
+        threshold_mode: ratio
+        trans_opt_lr: 0.005
+train:
+    value:
+        align_corners: false
+        beta_dist_param:
+            - 0.5
+            - 4
+        cam_scale_mode: sum
+        camera_loss: 10
+        ext_scale_detach: false
+        extended_visualization: false
+        intrinsic_scaling: false
+        one_sample_validation: null
+        print_log_every_n_steps: 10
+        scene_scale_reg_loss: 0
+        train_aux: true
+        train_gs_num: 3
+        train_target_set: true
+        use_refine_aux: false
+        verbose: false
+        vggt_cam_loss: true
+trainer:
+    value:
+        gradient_clip_val: 0.5
+        max_steps: 3751
+        num_nodes: 1
+        val_check_interval: 250
+wandb:
+    value:
+        entity: scene-representation-group
+        mode: online
+        name: ABLATION_1112_noSceneScaleReg
+        project: DCSplat
+        tags:
+            - re10k
+            - 256x256

ablation_context_train/ABLATION_1112_noSceneScaleReg/wandb/run-20260128_180409-npo9zheb/files/output.log

@@ -0,0 +1,128 @@
+LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
+
+  | 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
+3,564.328 Total estimated model params size (MB)
+1231      Modules in train mode
+522       Modules in eval mode
+Sanity Checking: |                                                                                             | 0/? [00:00<?, ?it/s][2026-01-28 18:04:12,389][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=191` in the `DataLoader` to improve performance.
+
+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')
+W0128 18:04:16.066000 17497 site-packages/torch/utils/cpp_extension.py:2425] TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation.
+W0128 18:04:16.066000 17497 site-packages/torch/utils/cpp_extension.py:2425] If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'] to specific architectures.
+[2026-01-28 18:04:16,154][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
+
+[2026-01-28 18:04:16,169][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]
+[2026-01-28 18:04:16,170][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(
+
+[2026-01-28 18:04:16,170][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
+[2026-01-28 18:04:18,448][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]
+
+Epoch 0: |                                                                                                     | 0/? [00:00<?, ?it/s]context = [[96, 121], [19, 44], [2, 27], [215, 240], [105, 130], [29, 54], [80, 105], [26, 51], [33, 58], [39, 64], [124, 149], [9, 34], [46, 71], [62, 87], [16, 41], [36, 61]]target = [[97, 103, 110, 100], [21, 33, 43, 31], [15, 11, 18, 17], [232, 239, 236, 223], [112, 123, 111, 106], [45, 32, 41, 51], [83, 90, 99, 103], [38, 48, 30, 41], [53, 48, 40, 38], [51, 44, 62, 48], [125, 146, 143, 133], [29, 13, 20, 27], [50, 49, 62, 70], [84, 75, 72, 86], [25, 22, 24, 37], [53, 51, 56, 38]]
+Epoch 0: |                                                                                 | 9/? [00:26<00:00,  0.33it/s, v_num=zheb]train step 10; scene = ['78784c6ffe218407', '2144f1fd5b00dc66', 'f568ab2fa64994e9', 'eac6cedeba1f720b', '216d5454333d29b5', 'b628b7d46a07cb57', '3b07094586f67024', '044df93e59024ee2', '167c67586a8c0846', '3931c6a7e69ffff1', 'c9c67636b9d521be', '0908c09364f54c42', '2d92b7321e1039c5', '3bc0044f0678f39f', 'e51ef9945ae527c4', 'bb32e9a89ca9387e']; loss = 0.656019
+Epoch 0: |                                                                                | 10/? [00:29<00:00,  0.34it/s, v_num=zheb]context = [[71, 96], [101, 126], [238, 263], [68, 93], [104, 129], [20, 45], [52, 77], [53, 78], [32, 57], [243, 268], [0, 25], [24, 49], [13, 38], [67, 92], [15, 40], [198, 223]]target = [[79, 86, 92, 81], [108, 123, 102, 109], [243, 253, 262, 245], [86, 90, 70, 80], [117, 125, 111, 123], [38, 36, 30, 39], [60, 76, 69, 68], [69, 64, 73, 55], [38, 44, 55, 40], [259, 264, 251, 249], [13, 4, 10, 2], [46, 29, 43, 39], [17, 23, 20, 14], [73, 71, 70, 69], [30, 23, 39, 17], [204, 217, 214, 201]]
+Epoch 0: |                                                                                | 19/? [00:56<00:00,  0.34it/s, v_num=zheb]train step 20; scene = ['6546295c3cec469a', 'b2186a798ad4fb49', 'b3232677872b2974', 'b3edac66be582f84', '420ca2704db5b476', 'db1723893a3a6277', '9e88bf87287fd8fe', '9e302a18a294b945', '4581bdd74b6ee0a9', '1f9574f1e0c1c2b2', 'e8674463d514e8a5', 'eedd397acee4cb4f', '47240d3fcf37fc1b', '5140967fcd51092e', 'c18ea6a77949e219', '08234c2181c4db46']; loss = 0.380293
+Epoch 0: |                                                                                | 20/? [00:59<00:00,  0.34it/s, v_num=zheb]context = [[21, 46], [2, 27], [154, 179], [3, 28], [25, 50], [177, 202], [25, 50], [9, 34], [61, 86], [13, 38], [132, 157], [24, 49], [46, 71], [42, 67], [108, 133], [78, 103]]target = [[43, 45, 33, 28], [19, 14, 23, 26], [171, 177, 173, 168], [16, 24, 15, 17], [41, 26, 47, 30], [200, 199, 201, 180], [28, 33, 37, 27], [10, 26, 17, 28], [77, 65, 72, 62], [14, 30, 18, 25], [153, 139, 154, 134], [37, 44, 42, 47], [54, 65, 67, 53], [58, 65, 43, 66], [120, 123, 113, 119], [98, 80, 96, 94]]
+
+Detected KeyboardInterrupt, attempting graceful shutdown ...
+Error executing job with overrides: ['+experiment=re10k_ablation', 'wandb.mode=online', 'wandb.name=ABLATION_1112_noSceneScaleReg', 'train.scene_scale_reg_loss=0.0']
+Traceback (most recent call last):
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/call.py", line 48, in _call_and_handle_interrupt
+    return trainer_fn(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/trainer.py", line 599, in _fit_impl
+    self._run(model, ckpt_path=ckpt_path)
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/trainer.py", line 1012, in _run
+    results = self._run_stage()
+              ^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/trainer.py", line 1056, in _run_stage
+    self.fit_loop.run()
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/loops/fit_loop.py", line 216, in run
+    self.advance()
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/loops/fit_loop.py", line 455, in advance
+    self.epoch_loop.run(self._data_fetcher)
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/loops/training_epoch_loop.py", line 150, in run
+    self.advance(data_fetcher)
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/loops/training_epoch_loop.py", line 322, in advance
+    batch_output = self.manual_optimization.run(kwargs)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/loops/optimization/manual.py", line 94, in run
+    self.advance(kwargs)
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/loops/optimization/manual.py", line 114, in advance
+    training_step_output = call._call_strategy_hook(trainer, "training_step", *kwargs.values())
+                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/call.py", line 328, in _call_strategy_hook
+    output = fn(*args, **kwargs)
+             ^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/strategies/strategy.py", line 391, in training_step
+    return self.lightning_module.training_step(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/jaxtyping/_decorator.py", line 562, in wrapped_fn
+    return wrapped_fn_impl(args, kwargs, bound, memos)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/jaxtyping/_decorator.py", line 486, in wrapped_fn_impl
+    out = fn(*args, **kwargs)
+          ^^^^^^^^^^^^^^^^^^^
+  File "/workspace/code/CVPR2026/src/model/model_wrapper.py", line 480, in training_step
+    torch.autograd.backward(tensors=all_gs_params, grad_tensors=all_gs_params_grad)
+  File "/venv/main/lib/python3.12/site-packages/torch/autograd/__init__.py", line 354, in backward
+    _engine_run_backward(
+  File "/venv/main/lib/python3.12/site-packages/torch/autograd/graph.py", line 829, in _engine_run_backward
+    return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+KeyboardInterrupt
+
+During handling of the above exception, another exception occurred:
+
+Traceback (most recent call last):
+  File "/workspace/code/CVPR2026/src/main.py", line 203, in train
+    trainer.fit(model_wrapper, datamodule=data_module)#, ckpt_path=checkpoint_path)
+    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/trainer.py", line 561, in fit
+    call._call_and_handle_interrupt(
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/call.py", line 61, in _call_and_handle_interrupt
+    trainer._teardown()
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/trainer.py", line 1035, in _teardown
+    self.strategy.teardown()
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/strategies/strategy.py", line 532, in teardown
+    _optimizers_to_device(self.optimizers, torch.device("cpu"))
+  File "/venv/main/lib/python3.12/site-packages/lightning/fabric/utilities/optimizer.py", line 27, in _optimizers_to_device
+    _optimizer_to_device(opt, device)
+  File "/venv/main/lib/python3.12/site-packages/lightning/fabric/utilities/optimizer.py", line 41, in _optimizer_to_device
+    v[key] = move_data_to_device(val, device)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/lightning/fabric/utilities/apply_func.py", line 110, in move_data_to_device
+    return apply_to_collection(batch, dtype=_TransferableDataType, function=batch_to)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/lightning_utilities/core/apply_func.py", line 66, in apply_to_collection
+    return function(data, *args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/lightning/fabric/utilities/apply_func.py", line 104, in batch_to
+    data_output = data.to(device, **kwargs)
+                  ^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/torch/utils/data/_utils/signal_handling.py", line 73, in handler
+    _error_if_any_worker_fails()
+RuntimeError: DataLoader worker (pid 18356) exited unexpectedly with exit code 1. Details are lost due to multiprocessing. Rerunning with num_workers=0 may give better error trace.
+
+Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

ablation_context_train/ABLATION_1112_noSceneScaleReg/wandb/run-20260128_180409-npo9zheb/files/requirements.txt

@@ -0,0 +1,158 @@
+wheel==0.45.1
+triton==3.4.0
+nvidia-nccl-cu12==2.27.3
+torch==2.8.0+cu128
+torchvision==0.23.0+cu128
+packaging==24.2
+torchaudio==2.8.0+cu128
+pytz==2025.2
+easydict==1.13
+antlr4-python3-runtime==4.9.3
+wadler_lindig==0.1.7
+ninja==1.13.0
+urllib3==2.5.0
+tzdata==2025.2
+typing-inspection==0.4.1
+tabulate==0.9.0
+smmap==5.0.2
+opt_einsum==3.4.0
+setuptools==78.1.1
+safetensors==0.5.3
+PyYAML==6.0.2
+PySocks==1.7.1
+pyparsing==3.2.5
+pydantic_core==2.33.2
+pycparser==2.23
+protobuf==6.32.1
+propcache==0.3.2
+proglog==0.1.12
+platformdirs==4.4.0
+pip==25.2
+numpy==1.26.4
+pillow==10.4.0
+networkx==3.4.2
+multidict==6.6.4
+mdurl==0.1.2
+torchmetrics==1.8.2
+MarkupSafe==3.0.2
+kornia_rs==0.1.9
+kiwisolver==1.4.9
+imageio-ffmpeg==0.6.0
+e3nn==0.5.9
+idna==3.7
+hf-xet==1.1.10
+gmpy2==2.2.1
+fsspec==2024.6.1
+frozenlist==1.7.0
+fonttools==4.60.0
+kornia==0.8.1
+filelock==3.17.0
+einops==0.8.1
+decorator==4.4.2
+dacite==1.9.2
+cycler==0.12.1
+colorama==0.4.6
+click==8.3.0
+charset-normalizer==3.3.2
+certifi==2025.8.3
+beartype==0.19.0
+attrs==25.3.0
+async-timeout==5.0.1
+annotated-types==0.7.0
+aiohappyeyeballs==2.6.1
+yarl==1.20.1
+tifffile==2025.5.10
+sentry-sdk==2.39.0
+scipy==1.15.3
+pydantic==2.11.9
+pandas==2.3.2
+opencv-python==4.11.0.86
+omegaconf==2.3.0
+markdown-it-py==4.0.0
+lightning-utilities==0.14.3
+lazy_loader==0.4
+jaxtyping==0.2.37
+imageio==2.37.0
+gitdb==4.0.12
+contourpy==1.3.2
+colorspacious==1.1.2
+cffi==1.17.1
+aiosignal==1.4.0
+scikit-video==1.1.11
+scikit-image==0.25.2
+rich==14.1.0
+moviepy==1.0.3
+matplotlib==3.10.6
+hydra-core==1.3.2
+huggingface-hub==0.35.1
+GitPython==3.1.45
+brotlicffi==1.0.9.2
+aiohttp==3.12.15
+opt-einsum-fx==0.1.4
+pytorch-lightning==2.5.1
+lpips==0.1.4
+lightning==2.5.1
+torch_scatter==2.1.2+pt28cu128
+gsplat==1.5.3
+wandb==0.24.0
+cuda-bindings==12.9.4
+cuda-pathfinder==1.3.3
+Jinja2==3.1.6
+mpmath==1.3.0
+nvidia-cublas-cu12==12.8.4.1
+nvidia-cuda-cupti-cu12==12.8.90
+nvidia-cuda-nvrtc-cu12==12.8.93
+nvidia-cuda-runtime-cu12==12.8.90
+nvidia-cudnn-cu12==9.10.2.21
+nvidia-cufft-cu12==11.3.3.83
+nvidia-cufile-cu12==1.13.1.3
+nvidia-curand-cu12==10.3.9.90
+nvidia-cusolver-cu12==11.7.3.90
+nvidia-cusparse-cu12==12.5.8.93
+nvidia-cusparselt-cu12==0.7.1
+nvidia-nvjitlink-cu12==12.8.93
+nvidia-nvshmem-cu12==3.4.5
+nvidia-nvtx-cu12==12.8.90
+requests==2.32.5
+sentencepiece==0.2.1
+sympy==1.14.0
+torchcodec==0.10.0
+torchdata==0.10.0
+torchtext==0.6.0
+anyio==4.12.0
+asttokens==3.0.1
+comm==0.2.3
+debugpy==1.8.19
+executing==2.2.1
+h11==0.16.0
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ablation_context_train/ABLATION_1112_noSceneScaleReg/wandb/run-20260128_180409-npo9zheb/files/wandb-metadata.json

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