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ABLATION_0225_ctxTrain_depth_vggtDistl/.hydra/config.yaml

@@ -0,0 +1,189 @@
+model:
+  encoder:
+    name: dcsplat
+    input_image_shape:
+    - 518
+    - 518
+    head_mode: depth
+    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
+  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
+    voxelize_activate: true
+    use_depth: true
+render_loss:
+  mse:
+    weight: 1.0
+  lpips:
+    weight: 0.05
+    apply_after_step: 0
+  depth_consis:
+    weight: 1.0
+    sigma_image: null
+    use_second_derivative: false
+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_0225_ctxTrain_depth_vggtDistl
+  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: 1500
+  save_top_k: 2
+  save_weights_only: false
+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: 1
+  ext_scale_detach: false
+  cam_scale_mode: sum
+  scene_scale_reg_loss: 0.01
+  train_aux: true
+  vggt_cam_loss: true
+  vggt_distil: true
+  context_view_train: true
+test:
+  output_path: test/ablation/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: 3001
+  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: 1000
+      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
+    dynamic_context_views: true
+    max_context_views_per_gpu: 24

ABLATION_0225_ctxTrain_depth_vggtDistl/.hydra/hydra.yaml

@@ -0,0 +1,168 @@
+hydra:
+  run:
+    dir: outputs/ablation/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_24v_depthloss
+    - wandb.mode=online
+    - wandb.name=ABLATION_0225_ctxTrain_depth_vggtDistl
+    - model.encoder.head_mode=depth
+    - model.density_control.use_depth=true
+    - train.context_view_train=true
+    - train.vggt_distil=true
+  job:
+    name: main
+    chdir: null
+    override_dirname: +experiment=re10k_ablation_24v_depthloss,model.density_control.use_depth=true,model.encoder.head_mode=depth,train.context_view_train=true,train.vggt_distil=true,wandb.mode=online,wandb.name=ABLATION_0225_ctxTrain_depth_vggtDistl
+    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/ablation/re10k/ABLATION_0225_ctxTrain_depth_vggtDistl
+    choices:
+      experiment: re10k_ablation_24v_depthloss
+      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_0225_ctxTrain_depth_vggtDistl/.hydra/overrides.yaml

@@ -0,0 +1,7 @@
+- +experiment=re10k_ablation_24v_depthloss
+- wandb.mode=online
+- wandb.name=ABLATION_0225_ctxTrain_depth_vggtDistl
+- model.encoder.head_mode=depth
+- model.density_control.use_depth=true
+- train.context_view_train=true
+- train.vggt_distil=true

ABLATION_0225_ctxTrain_depth_vggtDistl/main.log

@@ -0,0 +1,45 @@
+[2026-02-25 13:52:21,786][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:52:28,031][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 13:52:28,032][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)
+
+[2026-02-25 13:52:29,480][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:54:48,808][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:425: The 'val_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=31` in the `DataLoader` to improve performance.
+
+[2026-02-25 13:54:48,809][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user. 
+  warnings.warn(  # warn only once
+
+[2026-02-25 13:54:51,686][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+[2026-02-25 13:54:51,695][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)`.
+
+[2026-02-25 13:54:51,696][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 13:54:51,696][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)
+
+[2026-02-25 13:54:53,564][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]
+
+[2026-02-25 13:54:53,845][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('val/psnr', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+[2026-02-25 13:54:53,847][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('val/lpips', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+[2026-02-25 13:54:53,847][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('val/ssim', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+[2026-02-25 13:54:53,848][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('val/gaussian_num_ratio', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+[2026-02-25 13:54:53,848][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('info/global_step', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+[2026-02-25 14:29:16,843][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 14:29:23,026][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 14:29:23,026][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)
+
+[2026-02-25 14:29:24,307][dinov2][INFO] - using MLP layer as FFN

ABLATION_0225_ctxTrain_depth_vggtDistl/train_ddp_process_1.log

@@ -0,0 +1,19 @@
+[2026-02-25 13:52:46,873][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:53:20,123][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 13:53:20,123][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)
+
+[2026-02-25 13:53:24,223][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:54:48,809][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user. 
+  warnings.warn(  # warn only once
+
+[2026-02-25 14:29:41,340][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 14:29:59,908][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 14:29:59,909][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)
+
+[2026-02-25 14:30:04,698][dinov2][INFO] - using MLP layer as FFN

ABLATION_0225_ctxTrain_depth_vggtDistl/train_ddp_process_2.log

@@ -0,0 +1,19 @@
+[2026-02-25 13:52:46,752][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:53:19,432][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 13:53:19,433][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)
+
+[2026-02-25 13:53:22,571][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:54:48,809][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user. 
+  warnings.warn(  # warn only once
+
+[2026-02-25 14:29:41,333][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 14:30:12,121][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 14:30:12,123][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)
+
+[2026-02-25 14:30:17,034][dinov2][INFO] - using MLP layer as FFN

ABLATION_0225_ctxTrain_depth_vggtDistl/train_ddp_process_3.log

@@ -0,0 +1,19 @@
+[2026-02-25 13:52:46,815][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:53:19,826][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 13:53:19,827][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)
+
+[2026-02-25 13:53:23,871][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:54:48,809][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user. 
+  warnings.warn(  # warn only once
+
+[2026-02-25 14:29:41,170][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 14:30:12,406][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 14:30:12,406][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)
+
+[2026-02-25 14:30:17,604][dinov2][INFO] - using MLP layer as FFN

ABLATION_0225_ctxTrain_depth_vggtDistl/train_ddp_process_4.log

@@ -0,0 +1,19 @@
+[2026-02-25 13:52:46,821][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:53:15,687][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 13:53:15,687][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)
+
+[2026-02-25 13:53:20,106][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:54:48,809][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user. 
+  warnings.warn(  # warn only once
+
+[2026-02-25 14:29:41,163][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 14:30:12,743][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 14:30:12,745][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)
+
+[2026-02-25 14:30:17,884][dinov2][INFO] - using MLP layer as FFN

ABLATION_0225_ctxTrain_depth_vggtDistl/train_ddp_process_5.log

@@ -0,0 +1,19 @@
+[2026-02-25 13:52:46,848][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:53:17,936][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 13:53:17,940][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)
+
+[2026-02-25 13:53:20,315][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:54:48,813][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user. 
+  warnings.warn(  # warn only once
+
+[2026-02-25 14:29:41,164][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 14:30:09,668][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 14:30:09,670][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)
+
+[2026-02-25 14:30:13,767][dinov2][INFO] - using MLP layer as FFN

ABLATION_0225_ctxTrain_depth_vggtDistl/train_ddp_process_6.log

@@ -0,0 +1,19 @@
+[2026-02-25 13:52:46,807][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:53:19,201][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 13:53:19,203][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)
+
+[2026-02-25 13:53:21,001][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:54:48,809][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user. 
+  warnings.warn(  # warn only once
+
+[2026-02-25 14:29:41,135][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 14:30:01,944][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 14:30:01,944][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)
+
+[2026-02-25 14:30:07,824][dinov2][INFO] - using MLP layer as FFN

ABLATION_0225_ctxTrain_depth_vggtDistl/train_ddp_process_7.log

@@ -0,0 +1,19 @@
+[2026-02-25 13:52:46,799][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:53:19,450][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 13:53:19,450][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)
+
+[2026-02-25 13:53:22,975][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 13:54:48,809][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user. 
+  warnings.warn(  # warn only once
+
+[2026-02-25 14:29:41,375][dinov2][INFO] - using MLP layer as FFN
+[2026-02-25 14:30:00,005][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 14:30:00,006][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)
+
+[2026-02-25 14:30:04,401][dinov2][INFO] - using MLP layer as FFN

ABLATION_0225_ctxTrain_depth_vggtDistl/wandb/debug-internal.log

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ABLATION_0225_ctxTrain_depth_vggtDistl/wandb/debug.log

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+2026-02-25 13:54:41,864 INFO    MainThread:168367 [wandb_init.py:init():849] wandb.init called with sweep_config: {}
+config: {'model': {'encoder': {'name': 'dcsplat', 'input_image_shape': [518, 518], 'head_mode': 'depth', '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}, '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, 'voxelize_activate': True, 'use_depth': 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_0225_ctxTrain_depth_vggtDistl', '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': 1500, 'save_top_k': 2, 'save_weights_only': False}, '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': 1, 'ext_scale_detach': False, 'cam_scale_mode': 'sum', 'scene_scale_reg_loss': 0.01, 'train_aux': True, 'vggt_cam_loss': True, 'vggt_distil': True, 'context_view_train': True}, 'test': {'output_path': 'test/ablation/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': 3001, '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': 1000, '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, 'dynamic_context_views': True, 'max_context_views_per_gpu': 24}}, '_wandb': {}}
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ABLATION_0225_ctxTrain_depth_vggtDistl/wandb/run-20260225_135441-g2qj8ry7/files/config.yaml

@@ -0,0 +1,310 @@
+_wandb:
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+        cli_version: 0.25.0
+        e:
+            q96rx8ljkgqkb464effa7lv06bj6w0fc:
+                args:
+                    - +experiment=re10k_ablation_24v
+                    - wandb.mode=online
+                    - wandb.name=ABLATION_0225_ctxTrain_depth_vggtDistl
+                    - model.encoder.head_mode=depth
+                    - model.density_control.use_depth=true
+                    - train.context_view_train=true
+                    - train.vggt_distil=true
+                cpu_count: 128
+                cpu_count_logical: 256
+                cudaVersion: "13.1"
+                disk:
+                    /:
+                        total: "1170378588160"
+                        used: "756693458944"
+                email: dna9041@korea.ac.kr
+                executable: /venv/main/bin/python
+                git:
+                    commit: 488f8178913cf0d68a295e744f2709f488f576cd
+                    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-2649ab80-a3a6-5a1c-0fa5-12bc11bd75e9
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-e92921d9-c681-246f-af93-637e0dc938ca
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-ffe12ffc-9bb7-82de-5692-1ec0ee2e68d8
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-499e5acd-b6ab-2010-c51b-ee9b5aa65825
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-3b2522d9-1c72-e49b-2c30-96165680b74a
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-a9a280c5-b2f9-dc1e-a8a9-7326a74001ff
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-07d0167b-a6a1-1900-2d27-7c6c11598409
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-8362a999-20d1-c27b-5d18-032d23f859ab
+                host: 27d18dedec6d
+                memory:
+                    total: "1622948257792"
+                os: Linux-6.8.0-90-generic-x86_64-with-glibc2.39
+                program: -m src.main
+                python: CPython 3.12.12
+                root: /workspace/code/CVPR2026/outputs/ablation/re10k/ABLATION_0225_ctxTrain_depth_vggtDistl
+                startedAt: "2026-02-25T13:54:41.861013Z"
+                writerId: q96rx8ljkgqkb464effa7lv06bj6w0fc
+        m:
+            - "1": trainer/global_step
+              "6":
+                - 3
+              "7": []
+            - "2": '*'
+              "5": 1
+              "6":
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+              "7": []
+        python_version: 3.12.12
+        t:
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+            "4": 3.12.12
+            "5": 0.25.0
+            "12": 0.25.0
+            "13": linux-x86_64
+checkpointing:
+    value:
+        every_n_train_steps: 1500
+        load: null
+        save_top_k: 2
+        save_weights_only: false
+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
+            dynamic_context_views: true
+            input_image_shape:
+                - 256
+                - 256
+            make_baseline_1: true
+            max_context_views_per_gpu: 24
+            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: 1000
+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
+        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_depth: true
+            use_mean_features: true
+            use_refine_module: true
+            voxel_size: 0.001
+            voxelize_activate: true
+        encoder:
+            align_corners: false
+            gs_param_dim: 256
+            head_mode: depth
+            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/ablation/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
+        context_view_train: true
+        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: 1
+        train_target_set: true
+        use_refine_aux: false
+        verbose: false
+        vggt_cam_loss: true
+        vggt_distil: true
+trainer:
+    value:
+        gradient_clip_val: 0.5
+        max_steps: 3001
+        num_nodes: 1
+        val_check_interval: 250
+wandb:
+    value:
+        entity: scene-representation-group
+        mode: online
+        name: ABLATION_0225_ctxTrain_depth_vggtDistl
+        project: DCSplat
+        tags:
+            - re10k
+            - 256x256

ABLATION_0225_ctxTrain_depth_vggtDistl/wandb/run-20260225_135441-g2qj8ry7/files/output.log

@@ -0,0 +1,140 @@
+LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2,3,4,5,6,7]
+
+  | Name                   | Type                 | Params | Mode
+------------------------------------------------------------------------
+0 | encoder                | OurSplat             | 888 M  | train
+1 | density_control_module | DensityControlModule | 2.6 M  | train
+2 | decoder                | DecoderSplattingCUDA | 0      | train
+3 | render_losses          | ModuleList           | 0      | train
+4 | density_control_losses | ModuleList           | 0      | train
+5 | direct_losses          | ModuleList           | 0      | train
+6 | distill_aggregator     | Aggregator           | 909 M  | train
+7 | distill_camera_head    | CameraHead           | 216 M  | train
+8 | distill_depth_head     | DPTHead              | 32.7 M | train
+9 | loss_distill           | DistillLoss          | 0      | train
+------------------------------------------------------------------------
+891 M     Trainable params
+1.2 B     Non-trainable params
+2.0 B     Total params
+8,196.093 Total estimated model params size (MB)
+2778      Modules in train mode
+522       Modules in eval mode
+Sanity Checking: |                                                                                             | 0/? [00:00<?, ?it/s][2026-02-25 13:54:48,808][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:425: The 'val_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=31` in the `DataLoader` to improve performance.
+
+[2026-02-25 13:54:48,809][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4807: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user.
+  warnings.warn(  # warn only once
+
+Validation epoch start on rank 0
+Sanity Checking DataLoader 0:   0%|                                                                            | 0/1 [00:00<?, ?it/s]validation step 0; scene = ['306e2b7785657539'];
+target intrinsic:  tensor(0.8595, device='cuda:0') tensor(0.8597, device='cuda:0')
+pred intrinsic:  tensor(0.8779, device='cuda:0') tensor(0.8773, device='cuda:0')
+[rank0]:W0225 13:54:51.619000 168367 site-packages/torch/utils/cpp_extension.py:2425] TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation.
+[rank0]:W0225 13:54:51.619000 168367 site-packages/torch/utils/cpp_extension.py:2425] If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'] to specific architectures.
+[2026-02-25 13:54:51,686][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+[2026-02-25 13:54:51,695][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/utilities/data.py:79: Trying to infer the `batch_size` from an ambiguous collection. The batch size we found is 1. To avoid any miscalculations, use `self.log(..., batch_size=batch_size)`.
+
+Setting up [LPIPS] perceptual loss: trunk [vgg], v[0.1], spatial [off]
+[2026-02-25 13:54:51,696][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
+  warnings.warn(
+
+[2026-02-25 13:54:51,696][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)
+
+Loading model from: /venv/main/lib/python3.12/site-packages/lpips/weights/v0.1/vgg.pth
+[2026-02-25 13:54:53,564][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/functional.py:554: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /pytorch/aten/src/ATen/native/TensorShape.cpp:4322.)
+  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
+
+Sanity Checking DataLoader 0: 100%|████████████████████████████████████████████████████████████████████| 1/1 [00:04<00:00,  0.23it/s][2026-02-25 13:54:53,845][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('val/psnr', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+[2026-02-25 13:54:53,847][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('val/lpips', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+[2026-02-25 13:54:53,847][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('val/ssim', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+[2026-02-25 13:54:53,848][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('val/gaussian_num_ratio', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+[2026-02-25 13:54:53,848][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py:434: It is recommended to use `self.log('info/global_step', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
+
+Epoch 0: |                                                                                                     | 0/? [00:00<?, ?it/s]context = [[34, 36, 50, 53, 54, 60, 63, 70, 76, 78, 79, 80, 81, 88, 92, 94, 102, 110, 112, 114, 122, 125, 126, 131]]target = [[126, 96, 109, 55, 99, 116, 43, 60, 113, 85, 103, 90, 130, 62, 76, 123, 35, 102, 125, 128, 98, 67, 129, 79]]
+Error executing job with overrides: ['+experiment=re10k_ablation_24v', 'wandb.mode=online', 'wandb.name=ABLATION_0225_ctxTrain_depth_vggtDistl', 'model.encoder.head_mode=depth', 'model.density_control.use_depth=true', 'train.context_view_train=true', 'train.vggt_distil=true']
+Traceback (most recent call last):
+  File "/workspace/code/CVPR2026/src/main.py", line 226, 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 47, in _call_and_handle_interrupt
+    return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/strategies/launchers/subprocess_script.py", line 105, in launch
+    return function(*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 390, in training_step
+    return self._forward_redirection(self.model, self.lightning_module, "training_step", *args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/strategies/strategy.py", line 641, in __call__
+    wrapper_output = wrapper_module(*args, **kwargs)
+                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1773, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1784, in _call_impl
+    return forward_call(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/torch/nn/parallel/distributed.py", line 1648, in forward
+    else self._run_ddp_forward(*inputs, **kwargs)
+         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/torch/nn/parallel/distributed.py", line 1474, in _run_ddp_forward
+    return self.module(*inputs, **kwargs)  # type: ignore[index]
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1773, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1784, in _call_impl
+    return forward_call(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/strategies/strategy.py", line 634, in wrapped_forward
+    out = method(*_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 563, in training_step
+    depth_consis_loss = self.render_losses[2].forward(output, batch, depth_dict, self.global_step)
+                        ~~~~~~~~~~~~~~~~~~^^^
+  File "/venv/main/lib/python3.12/site-packages/torch/nn/modules/container.py", line 377, in __getitem__
+    return self._modules[self._get_abs_string_index(idx)]
+                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/torch/nn/modules/container.py", line 361, in _get_abs_string_index
+    raise IndexError(f"index {idx} is out of range")
+IndexError: index 2 is out of range
+
+Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

ABLATION_0225_ctxTrain_depth_vggtDistl/wandb/run-20260225_135441-g2qj8ry7/files/requirements.txt

@@ -0,0 +1,172 @@
+wheel==0.45.1
+pytz==2025.2
+easydict==1.13
+antlr4-python3-runtime==4.9.3
+wadler_lindig==0.1.7
+urllib3==2.5.0
+tzdata==2025.2
+typing-inspection==0.4.1
+tabulate==0.9.0
+smmap==5.0.2
+kornia_rs==0.1.9
+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
+fsspec==2024.6.1
+platformdirs==4.4.0
+pip==25.2
+pillow==10.4.0
+frozenlist==1.7.0
+packaging==24.2
+opt_einsum==3.4.0
+numpy==1.26.4
+ninja==1.13.0
+fonttools==4.60.0
+networkx==3.4.2
+multidict==6.6.4
+mdurl==0.1.2
+MarkupSafe==3.0.2
+kiwisolver==1.4.9
+imageio-ffmpeg==0.6.0
+idna==3.7
+hf-xet==1.1.10
+gmpy2==2.2.1
+einops==0.8.1
+filelock==3.17.0
+decorator==4.4.2
+dacite==1.9.2
+cycler==0.12.1
+colorama==0.4.6
+click==8.3.0
+nvidia-nvtx-cu12==12.8.90
+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
+nvidia-nccl-cu12==2.27.3
+huggingface-hub==0.35.1
+GitPython==3.1.45
+brotlicffi==1.0.9.2
+aiohttp==3.12.15
+torchmetrics==1.8.2
+opt-einsum-fx==0.1.4
+kornia==0.8.1
+pytorch-lightning==2.5.1
+lpips==0.1.4
+e3nn==0.6.0
+lightning==2.5.1
+nvidia-cusparselt-cu12==0.7.1
+triton==3.4.0
+nvidia-nvjitlink-cu12==12.8.93
+nvidia-curand-cu12==10.3.9.90
+nvidia-cufile-cu12==1.13.1.3
+nvidia-cuda-runtime-cu12==12.8.90
+nvidia-cuda-nvrtc-cu12==12.8.93
+nvidia-cuda-cupti-cu12==12.8.90
+nvidia-cublas-cu12==12.8.4.1
+nvidia-cusparse-cu12==12.5.8.93
+nvidia-cufft-cu12==11.3.3.83
+nvidia-cudnn-cu12==9.10.2.21
+nvidia-cusolver-cu12==11.7.3.90
+torch==2.8.0+cu128
+torchvision==0.23.0+cu128
+torchaudio==2.8.0+cu128
+torch_scatter==2.1.2+pt28cu128
+gsplat==1.5.3
+wandb==0.25.0
+cuda-bindings==13.0.3
+cuda-pathfinder==1.3.3
+Jinja2==3.1.6
+mpmath==1.3.0
+nvidia-cublas==13.1.0.3
+nvidia-cuda-cupti==13.0.85
+nvidia-cuda-nvrtc==13.0.88
+nvidia-cuda-runtime==13.0.96
+nvidia-cudnn-cu13==9.15.1.9
+nvidia-cufft==12.0.0.61
+nvidia-cufile==1.15.1.6
+nvidia-curand==10.4.0.35
+nvidia-cusolver==12.0.4.66
+nvidia-cusparse==12.6.3.3
+nvidia-cusparselt-cu13==0.8.0
+nvidia-nccl-cu13==2.28.9
+nvidia-nvjitlink==13.0.88
+nvidia-nvshmem-cu13==3.4.5
+nvidia-nvtx==13.0.85
+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
+httpcore==1.0.9
+httpx==0.28.1
+ipykernel==7.1.0
+ipython==9.8.0
+ipython_pygments_lexers==1.1.1
+ipywidgets==8.1.8
+jedi==0.19.2
+jupyter_client==8.7.0
+jupyter_core==5.9.1
+jupyterlab_widgets==3.0.16
+matplotlib-inline==0.2.1
+nest-asyncio==1.6.0
+parso==0.8.5
+pexpect==4.9.0
+prompt_toolkit==3.0.52
+psutil==7.2.1
+ptyprocess==0.7.0
+pure_eval==0.2.3
+Pygments==2.19.2
+python-dateutil==2.9.0.post0
+pyzmq==27.1.0
+shellingham==1.5.4
+six==1.17.0
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ABLATION_0225_ctxTrain_depth_vggtDistl/wandb/run-20260225_135441-g2qj8ry7/files/wandb-metadata.json

@@ -0,0 +1,96 @@
+{
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+  "python":  "CPython 3.12.12",
+  "startedAt":  "2026-02-25T13:54:41.861013Z",
+  "args":  [
+    "+experiment=re10k_ablation_24v",
+    "wandb.mode=online",
+    "wandb.name=ABLATION_0225_ctxTrain_depth_vggtDistl",
+    "model.encoder.head_mode=depth",
+    "model.density_control.use_depth=true",
+    "train.context_view_train=true",
+    "train.vggt_distil=true"
+  ],
+  "program":  "-m src.main",
+  "git":  {
+    "remote":  "git@github.com:K-nowing/CVPR2026.git",
+    "commit":  "488f8178913cf0d68a295e744f2709f488f576cd"
+  },
+  "email":  "dna9041@korea.ac.kr",
+  "root":  "/workspace/code/CVPR2026/outputs/ablation/re10k/ABLATION_0225_ctxTrain_depth_vggtDistl",
+  "host":  "27d18dedec6d",
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+  "gpu":  "NVIDIA H200",
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+  "disk":  {
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+    },
+    {
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+      "cudaCores":  16896,
+      "architecture":  "Hopper",
+      "uuid":  "GPU-a9a280c5-b2f9-dc1e-a8a9-7326a74001ff"
+    },
+    {
+      "name":  "NVIDIA H200",
+      "memoryTotal":  "150754820096",
+      "cudaCores":  16896,
+      "architecture":  "Hopper",
+      "uuid":  "GPU-07d0167b-a6a1-1900-2d27-7c6c11598409"
+    },
+    {
+      "name":  "NVIDIA H200",
+      "memoryTotal":  "150754820096",
+      "cudaCores":  16896,
+      "architecture":  "Hopper",
+      "uuid":  "GPU-8362a999-20d1-c27b-5d18-032d23f859ab"
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+}

ABLATION_0225_ctxTrain_depth_vggtDistl/wandb/run-20260225_135441-g2qj8ry7/files/wandb-summary.json

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ABLATION_0225_ctxTrain_depth_vggtDistl/wandb/run-20260225_135441-g2qj8ry7/logs/debug-core.log

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ABLATION_0225_ctxTrain_depth_vggtDistl/wandb/run-20260225_135441-g2qj8ry7/logs/debug-internal.log

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ABLATION_0225_ctxTrain_depth_vggtDistl/wandb/run-20260225_135441-g2qj8ry7/logs/debug.log

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ABLATION_0225_randomSelect/main.log

@@ -114,3 +114,15 @@ bucket_view.sizes() = [256, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered in
 [2026-02-25 13:26:12,524][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
   result[selector] = overlay
 
+[2026-02-25 13:35:42,292][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+[2026-02-25 13:38:57,687][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+[2026-02-25 13:51:58,139][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+[2026-02-25 13:52:01,499][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
+

ABLATION_0225_randomSelect/peak_vram_memory.json

@@ -0,0 +1,6 @@
+{
+  "peak_memory_allocated_gb": 103.167,
+  "peak_memory_reserved_gb": 137.896,
+  "total_elapsed_hours": 3.21,
+  "mode": "train"
+}

ABLATION_0225_randomSelect/train_ddp_process_1.log

@@ -58,3 +58,9 @@ bucket_view.sizes() = [256, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered in
 [2026-02-25 13:26:12,524][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
   result[selector] = overlay
 
+[2026-02-25 13:38:57,685][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+[2026-02-25 13:52:01,499][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
+

ABLATION_0225_randomSelect/train_ddp_process_2.log

@@ -58,3 +58,9 @@ bucket_view.sizes() = [256, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered in
 [2026-02-25 13:26:12,524][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
   result[selector] = overlay
 
+[2026-02-25 13:38:57,685][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+[2026-02-25 13:52:01,499][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
+

ABLATION_0225_randomSelect/train_ddp_process_3.log

@@ -58,3 +58,9 @@ bucket_view.sizes() = [256, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered in
 [2026-02-25 13:26:12,526][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
   result[selector] = overlay
 
+[2026-02-25 13:38:57,685][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+[2026-02-25 13:52:01,499][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
+

ABLATION_0225_randomSelect/train_ddp_process_4.log

@@ -58,3 +58,9 @@ bucket_view.sizes() = [256, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered in
 [2026-02-25 13:26:12,524][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
   result[selector] = overlay
 
+[2026-02-25 13:38:57,685][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+[2026-02-25 13:52:01,499][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
+

ABLATION_0225_randomSelect/train_ddp_process_5.log

@@ -58,3 +58,9 @@ bucket_view.sizes() = [256, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered in
 [2026-02-25 13:26:12,524][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
   result[selector] = overlay
 
+[2026-02-25 13:38:57,685][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+[2026-02-25 13:52:01,499][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
+

ABLATION_0225_randomSelect/train_ddp_process_6.log

@@ -58,3 +58,9 @@ bucket_view.sizes() = [256, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered in
 [2026-02-25 13:26:12,524][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
   result[selector] = overlay
 
+[2026-02-25 13:38:57,685][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+[2026-02-25 13:52:01,499][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
+

ABLATION_0225_randomSelect/train_ddp_process_7.log

@@ -58,3 +58,9 @@ bucket_view.sizes() = [256, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered in
 [2026-02-25 13:26:12,524][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
   result[selector] = overlay
 
+[2026-02-25 13:38:57,685][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+
+[2026-02-25 13:52:01,501][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
+

ABLATION_0225_randomSelect/wandb/debug-internal.log

@@ -4,3 +4,8 @@
 {"time":"2026-02-25T10:39:56.464733133Z","level":"INFO","msg":"stream: started","id":"n76tgbfj"}
 {"time":"2026-02-25T10:39:56.464769993Z","level":"INFO","msg":"sender: started","stream_id":"n76tgbfj"}
 {"time":"2026-02-25T10:39:56.464783063Z","level":"INFO","msg":"writer: started","stream_id":"n76tgbfj"}
+{"time":"2026-02-25T13:52:10.426476781Z","level":"INFO","msg":"stream: closing","id":"n76tgbfj"}
+{"time":"2026-02-25T13:52:11.22551075Z","level":"INFO","msg":"fileTransfer: Close: file transfer manager closed"}
+{"time":"2026-02-25T13:52:11.503165049Z","level":"INFO","msg":"handler: closed","stream_id":"n76tgbfj"}
+{"time":"2026-02-25T13:52:11.503344582Z","level":"INFO","msg":"sender: closed","stream_id":"n76tgbfj"}
+{"time":"2026-02-25T13:52:11.503360133Z","level":"INFO","msg":"stream: closed","id":"n76tgbfj"}

ABLATION_0225_randomSelect/wandb/debug.log

@@ -17,3 +17,5 @@ config: {'model': {'encoder': {'name': 'dcsplat', 'input_image_shape': [518, 518
 2026-02-25 10:39:57,797 INFO    MainThread:145562 [wandb_run.py:_redirect():2442] Wrapping output streams.
 2026-02-25 10:39:57,797 INFO    MainThread:145562 [wandb_run.py:_redirect():2465] Redirects installed.
 2026-02-25 10:39:57,800 INFO    MainThread:145562 [wandb_init.py:init():1082] run started, returning control to user process
+2026-02-25 13:52:10,426 INFO    wandb-AsyncioManager-main:145562 [service_client.py:_forward_responses():134] Reached EOF.
+2026-02-25 13:52:10,426 INFO    wandb-AsyncioManager-main:145562 [mailbox.py:close():155] Closing mailbox, abandoning 1 handles.

ABLATION_0225_randomSelect/wandb/run-20260225_103955-n76tgbfj/files/config.yaml

@@ -0,0 +1,307 @@
+_wandb:
+    value:
+        cli_version: 0.25.0
+        e:
+            81z9i9czdg5aqgfjdth6b57yriddztva:
+                args:
+                    - +experiment=re10k_ablation_24v
+                    - wandb.mode=online
+                    - wandb.name=ABLATION_0225_randomSelect
+                    - model.density_control.score_mode=random
+                cpu_count: 128
+                cpu_count_logical: 256
+                cudaVersion: "13.1"
+                disk:
+                    /:
+                        total: "1170378588160"
+                        used: "732546121728"
+                email: dna9041@korea.ac.kr
+                executable: /venv/main/bin/python
+                git:
+                    commit: 2512754c6c27ca5150bf17fbcbdde3f192fd53cc
+                    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-2649ab80-a3a6-5a1c-0fa5-12bc11bd75e9
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-e92921d9-c681-246f-af93-637e0dc938ca
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-ffe12ffc-9bb7-82de-5692-1ec0ee2e68d8
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-499e5acd-b6ab-2010-c51b-ee9b5aa65825
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-3b2522d9-1c72-e49b-2c30-96165680b74a
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-a9a280c5-b2f9-dc1e-a8a9-7326a74001ff
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-07d0167b-a6a1-1900-2d27-7c6c11598409
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-8362a999-20d1-c27b-5d18-032d23f859ab
+                host: 27d18dedec6d
+                memory:
+                    total: "1622948257792"
+                os: Linux-6.8.0-90-generic-x86_64-with-glibc2.39
+                program: -m src.main
+                python: CPython 3.12.12
+                root: /workspace/code/CVPR2026/outputs/ablation/re10k/ABLATION_0225_randomSelect
+                startedAt: "2026-02-25T10:39:55.441642Z"
+                writerId: 81z9i9czdg5aqgfjdth6b57yriddztva
+        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": 0.25.0
+            "12": 0.25.0
+            "13": linux-x86_64
+checkpointing:
+    value:
+        every_n_train_steps: 1500
+        load: null
+        save_top_k: 2
+        save_weights_only: false
+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
+            dynamic_context_views: true
+            input_image_shape:
+                - 256
+                - 256
+            make_baseline_1: true
+            max_context_views_per_gpu: 24
+            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: 1000
+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
+        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: random
+            use_depth: false
+            use_mean_features: true
+            use_refine_module: true
+            voxel_size: 0.001
+            voxelize_activate: true
+        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/ablation/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
+        context_view_train: false
+        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: 1
+        train_target_set: true
+        use_refine_aux: false
+        verbose: false
+        vggt_cam_loss: true
+        vggt_distil: false
+trainer:
+    value:
+        gradient_clip_val: 0.5
+        max_steps: 3001
+        num_nodes: 1
+        val_check_interval: 250
+wandb:
+    value:
+        entity: scene-representation-group
+        mode: online
+        name: ABLATION_0225_randomSelect
+        project: DCSplat
+        tags:
+            - re10k
+            - 256x256

ABLATION_0225_randomSelect/wandb/run-20260225_103955-n76tgbfj/files/wandb-summary.json

@@ -0,0 +1 @@
+{"loss/total":0.08273646980524063,"info/global_step":3000,"loss/aux_2/lpips":0.009566728956997395,"loss/final_3dgs/lpips":0.009549135342240334,"train/error_scores":{"width":1328,"height":2120,"format":"png","count":1,"filenames":["media/images/train/error_scores_201_05456dc706694ddf5d92.png"],"captions":[["0621c7675fab1418"]],"_type":"images/separated"},"_runtime":11532,"lr-AdamW/pg1-momentum":0.9,"lr-AdamW/pg2-momentum":0.9,"train/psnr_probabilistic":20.13189697265625,"loss/aux_1/error_score":0.4180681109428406,"loss/aux_1/lpips":0.009899786673486233,"val/ssim":0.7995258569717407,"loss/scene_scale_reg":0.00020948528253939003,"val/lpips":0.23768818378448486,"comparison":{"filenames":["media/images/comparison_197_ddc312f116aae122416e.png"],"captions":["a76028640ffa1ef9"],"_type":"images/separated","width":1064,"height":1098,"format":"png","count":1},"trainer/global_step":3001,"loss/final_3dgs/mse":0.010063939727842808,"loss/aux_0/error_score":0.7389501333236694,"train/scene_scale":1.003704309463501,"val/psnr":21.38949203491211,"loss/camera":0.0002018376690102741,"active_mask_imgs":{"captions":["a76028640ffa1ef9"],"_type":"images/separated","width":536,"height":800,"format":"png","count":1,"filenames":["media/images/active_mask_imgs_198_399ec9b2f678832e0977.png"]},"_timestamp":1.7720275236574388e+09,"loss/aux_1/mse":0.010359433479607105,"loss/aux_0/mse":0.00995652750134468,"_wandb":{"runtime":11532},"loss/aux_2/mse":0.010155964642763138,"lr-AdamW/pg2":2e-05,"error_scores":{"width":800,"height":536,"format":"png","count":1,"filenames":["media/images/error_scores_199_b1c8e80e7cf22aab1c67.png"],"captions":["a76028640ffa1ef9"],"_type":"images/separated"},"loss/aux_0/lpips":0.010957089252769947,"epoch":0,"val/gaussian_num_ratio":0.39984893798828125,"train/comparison":{"format":"png","count":1,"filenames":["media/images/train/comparison_202_b207767914aae1b684b5.png"],"captions":[["0621c7675fab1418"]],"_type":"images/separated","width":1328,"height":2154},"_step":202,"lr-AdamW/pg1":2.003594834351718e-05}

ABLATION_0225_randomSelect/wandb/run-20260225_103955-n76tgbfj/logs/debug-core.log

@@ -5,3 +5,11 @@
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+{"time":"2026-02-25T13:52:10.426527162Z","level":"INFO","msg":"connection: closed successfully","id":"1(@)"}
+{"time":"2026-02-25T13:52:10.426686075Z","level":"INFO","msg":"server: listener closed","addr":{"Name":"/tmp/wandb-145562-147994-3073551312/socket","Net":"unix"}}
+{"time":"2026-02-25T13:52:11.504270148Z","level":"INFO","msg":"handleInformTeardown: server shutdown complete","id":"1(@)"}
+{"time":"2026-02-25T13:52:11.504299818Z","level":"INFO","msg":"connection: ManageConnectionData: connection closed","id":"1(@)"}
+{"time":"2026-02-25T13:52:11.504311038Z","level":"INFO","msg":"server is closed"}

ABLATION_0225_randomSelect/wandb/run-20260225_103955-n76tgbfj/logs/debug-internal.log

@@ -4,3 +4,8 @@
 {"time":"2026-02-25T10:39:56.464733133Z","level":"INFO","msg":"stream: started","id":"n76tgbfj"}
 {"time":"2026-02-25T10:39:56.464769993Z","level":"INFO","msg":"sender: started","stream_id":"n76tgbfj"}
 {"time":"2026-02-25T10:39:56.464783063Z","level":"INFO","msg":"writer: started","stream_id":"n76tgbfj"}
+{"time":"2026-02-25T13:52:10.426476781Z","level":"INFO","msg":"stream: closing","id":"n76tgbfj"}
+{"time":"2026-02-25T13:52:11.22551075Z","level":"INFO","msg":"fileTransfer: Close: file transfer manager closed"}
+{"time":"2026-02-25T13:52:11.503165049Z","level":"INFO","msg":"handler: closed","stream_id":"n76tgbfj"}
+{"time":"2026-02-25T13:52:11.503344582Z","level":"INFO","msg":"sender: closed","stream_id":"n76tgbfj"}
+{"time":"2026-02-25T13:52:11.503360133Z","level":"INFO","msg":"stream: closed","id":"n76tgbfj"}

ABLATION_0225_randomSelect/wandb/run-20260225_103955-n76tgbfj/logs/debug.log

@@ -17,3 +17,5 @@ config: {'model': {'encoder': {'name': 'dcsplat', 'input_image_shape': [518, 518
 2026-02-25 10:39:57,797 INFO    MainThread:145562 [wandb_run.py:_redirect():2442] Wrapping output streams.
 2026-02-25 10:39:57,797 INFO    MainThread:145562 [wandb_run.py:_redirect():2465] Redirects installed.
 2026-02-25 10:39:57,800 INFO    MainThread:145562 [wandb_init.py:init():1082] run started, returning control to user process
+2026-02-25 13:52:10,426 INFO    wandb-AsyncioManager-main:145562 [service_client.py:_forward_responses():134] Reached EOF.
+2026-02-25 13:52:10,426 INFO    wandb-AsyncioManager-main:145562 [mailbox.py:close():155] Closing mailbox, abandoning 1 handles.