Add files using upload-large-folder tool

.gitattributes

@@ -58,3 +58,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+ABLATION_0302_FreqSelect/wandb/run-20260302_164522-8h1p5i95/run-8h1p5i95.wandb filter=lfs diff=lfs merge=lfs -text

ABLATION_0302_FreqSelect/checkpoints/epoch_0-step_1500.ckpt

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+oid sha256:9905f9951634363d9e0582b2282eaacefe4f1b93637184b1fd0b8984ee9d77fd
+size 11880857960

ABLATION_0302_FreqSelect/wandb/run-20260302_164522-8h1p5i95/run-8h1p5i95.wandb

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+oid sha256:97304ca2cc941f3f04e6359c6f0e44f3f0af7ad6c82c5fda66a78a456d1bd836
+size 4279158

ABLATION_0302_noAux/.hydra/config.yaml

@@ -0,0 +1,188 @@
+model:
+  encoder:
+    name: dcsplat
+    input_image_shape:
+    - 518
+    - 518
+    head_mode: pcd
+    num_level: 3
+    gs_param_dim: 256
+    align_corners: false
+    use_voxelize: true
+  decoder:
+    name: splatting_cuda
+    background_color:
+    - 0.0
+    - 0.0
+    - 0.0
+    make_scale_invariant: false
+  density_control:
+    name: density_control_module
+    mean_dim: 32
+    gs_param_dim: 256
+    refinement_layer_num: 1
+    num_level: 3
+    grad_mode: absgrad
+    use_mean_features: true
+    refinement_type: voxelize
+    refinement_hidden_dim: 32
+    aggregation_mode: mean
+    num_heads: 1
+    score_mode: absgrad
+    latent_dim: 128
+    num_latents: 64
+    num_self_attn_per_block: 2
+    voxel_size: 0.001
+    aux_refine: false
+    refine_error: false
+    use_refine_module: false
+    voxelize_activate: false
+    use_depth: false
+render_loss:
+  mse:
+    weight: 1.0
+  lpips:
+    weight: 0.05
+    apply_after_step: 0
+density_control_loss:
+  error_score:
+    weight: 0.0001
+    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_0302_noAux
+  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: false
+  vggt_cam_loss: true
+  vggt_distil: false
+  context_view_train: false
+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
+  save_gs: false
+  save_sample_wise_metrics: true
+  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
+      target_align: true
+    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_0302_noAux/.hydra/hydra.yaml

@@ -0,0 +1,165 @@
+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
+    - wandb.mode=online
+    - wandb.name=ABLATION_0302_noAux
+    - train.train_aux=false
+  job:
+    name: main
+    chdir: null
+    override_dirname: +experiment=re10k_ablation_24v,train.train_aux=false,wandb.mode=online,wandb.name=ABLATION_0302_noAux
+    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_0302_noAux
+    choices:
+      experiment: re10k_ablation_24v
+      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_0302_noAux/.hydra/overrides.yaml

@@ -0,0 +1,4 @@
+- +experiment=re10k_ablation_24v
+- wandb.mode=online
+- wandb.name=ABLATION_0302_noAux
+- train.train_aux=false

ABLATION_0302_noAux/wandb/debug-internal.log

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ABLATION_0302_noAux/wandb/debug.log

@@ -0,0 +1,21 @@
+2026-03-03 14:34:53,293 INFO    MainThread:854556 [wandb_setup.py:_flush():81] Current SDK version is 0.25.0
+2026-03-03 14:34:53,293 INFO    MainThread:854556 [wandb_setup.py:_flush():81] Configure stats pid to 854556
+2026-03-03 14:34:53,293 INFO    MainThread:854556 [wandb_setup.py:_flush():81] Loading settings from environment variables
+2026-03-03 14:34:53,293 INFO    MainThread:854556 [wandb_init.py:setup_run_log_directory():717] Logging user logs to /workspace/code/CVPR2026/outputs/ablation/re10k/ABLATION_0302_noAux/wandb/run-20260303_143453-l8o7jl7r/logs/debug.log
+2026-03-03 14:34:53,293 INFO    MainThread:854556 [wandb_init.py:setup_run_log_directory():718] Logging internal logs to /workspace/code/CVPR2026/outputs/ablation/re10k/ABLATION_0302_noAux/wandb/run-20260303_143453-l8o7jl7r/logs/debug-internal.log
+2026-03-03 14:34:53,294 INFO    MainThread:854556 [wandb_init.py:init():844] calling init triggers
+2026-03-03 14:34:53,294 INFO    MainThread:854556 [wandb_init.py:init():849] wandb.init called with sweep_config: {}
+config: {'model': {'encoder': {'name': 'dcsplat', 'input_image_shape': [518, 518], 'head_mode': 'pcd', 'num_level': 3, 'gs_param_dim': 256, 'align_corners': False, 'use_voxelize': True}, 'decoder': {'name': 'splatting_cuda', 'background_color': [0.0, 0.0, 0.0], 'make_scale_invariant': False}, 'density_control': {'name': 'density_control_module', 'mean_dim': 32, 'gs_param_dim': 256, 'refinement_layer_num': 1, 'num_level': 3, 'grad_mode': 'absgrad', 'use_mean_features': True, 'refinement_type': 'voxelize', 'refinement_hidden_dim': 32, 'aggregation_mode': 'mean', 'num_heads': 1, 'score_mode': 'absgrad', 'latent_dim': 128, 'num_latents': 64, 'num_self_attn_per_block': 2, 'voxel_size': 0.001, 'aux_refine': False, 'refine_error': False, 'use_refine_module': False, 'voxelize_activate': False, 'use_depth': False}}, 'render_loss': {'mse': {'weight': 1.0}, 'lpips': {'weight': 0.05, 'apply_after_step': 0}}, 'density_control_loss': {'error_score': {'weight': 0.0001, '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_0302_noAux', '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': False, 'vggt_cam_loss': True, 'vggt_distil': False, 'context_view_train': False}, '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, 'save_gs': False, 'save_sample_wise_metrics': True, '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, 'target_align': True}, '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_0302_noAux/wandb/run-20260303_143453-l8o7jl7r/files/config.yaml

@@ -0,0 +1,310 @@
+_wandb:
+    value:
+        cli_version: 0.25.0
+        e:
+            ycd5umfcq5p6rih4lqfm265f2qblrtrn:
+                args:
+                    - +experiment=re10k_ablation_24v
+                    - wandb.mode=online
+                    - wandb.name=ABLATION_0302_noAux
+                    - train.train_aux=false
+                cpu_count: 128
+                cpu_count_logical: 256
+                cudaVersion: "13.0"
+                disk:
+                    /:
+                        total: "735513149440"
+                        used: "676972425216"
+                email: dna9041@korea.ac.kr
+                executable: /venv/main/bin/python
+                git:
+                    commit: 9dfce172a0f8c7ce85e763899f7ef741ecffc454
+                    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-9a20101e-d876-facd-5f05-805081aede41
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-84736a77-ee75-3324-e4e1-99cc15bfb5e9
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-423d3161-cdc4-3fc0-caee-d15cfaa83ca6
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-5b0058b2-cdb9-c952-04f9-87dcaa7ea742
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-08b37f98-4603-d483-2f2b-fe5311aa42f2
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-03273b5b-2fdd-a5fe-4460-c897334ae464
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-292d466c-d00d-25a4-28b6-e6c978d3e70c
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-46f38561-3148-e442-7f7f-bfe447bab7fe
+                host: e9d3310a05da
+                memory:
+                    total: "1622950240256"
+                os: Linux-6.8.0-94-generic-x86_64-with-glibc2.39
+                program: -m src.main
+                python: CPython 3.12.12
+                root: /workspace/code/CVPR2026/outputs/ablation/re10k/ABLATION_0302_noAux
+                startedAt: "2026-03-03T14:34:53.292304Z"
+                writerId: ycd5umfcq5p6rih4lqfm265f2qblrtrn
+        m:
+            - "1": trainer/global_step
+              "6":
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+2026-03-03 14:34:53,293 INFO    MainThread:854556 [wandb_init.py:setup_run_log_directory():717] Logging user logs to /workspace/code/CVPR2026/outputs/ablation/re10k/ABLATION_0302_noAux/wandb/run-20260303_143453-l8o7jl7r/logs/debug.log
+2026-03-03 14:34:53,293 INFO    MainThread:854556 [wandb_init.py:setup_run_log_directory():718] Logging internal logs to /workspace/code/CVPR2026/outputs/ablation/re10k/ABLATION_0302_noAux/wandb/run-20260303_143453-l8o7jl7r/logs/debug-internal.log
+2026-03-03 14:34:53,294 INFO    MainThread:854556 [wandb_init.py:init():844] calling init triggers
+2026-03-03 14:34:53,294 INFO    MainThread:854556 [wandb_init.py:init():849] wandb.init called with sweep_config: {}
+config: {'model': {'encoder': {'name': 'dcsplat', 'input_image_shape': [518, 518], 'head_mode': 'pcd', 'num_level': 3, 'gs_param_dim': 256, 'align_corners': False, 'use_voxelize': True}, 'decoder': {'name': 'splatting_cuda', 'background_color': [0.0, 0.0, 0.0], 'make_scale_invariant': False}, 'density_control': {'name': 'density_control_module', 'mean_dim': 32, 'gs_param_dim': 256, 'refinement_layer_num': 1, 'num_level': 3, 'grad_mode': 'absgrad', 'use_mean_features': True, 'refinement_type': 'voxelize', 'refinement_hidden_dim': 32, 'aggregation_mode': 'mean', 'num_heads': 1, 'score_mode': 'absgrad', 'latent_dim': 128, 'num_latents': 64, 'num_self_attn_per_block': 2, 'voxel_size': 0.001, 'aux_refine': False, 'refine_error': False, 'use_refine_module': False, 'voxelize_activate': False, 'use_depth': False}}, 'render_loss': {'mse': {'weight': 1.0}, 'lpips': {'weight': 0.05, 'apply_after_step': 0}}, 'density_control_loss': {'error_score': {'weight': 0.0001, '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_0302_noAux', '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': False, 'vggt_cam_loss': True, 'vggt_distil': False, 'context_view_train': False}, '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, 'save_gs': False, 'save_sample_wise_metrics': True, '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, 'target_align': True}, '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': {}}
+2026-03-03 14:34:53,294 INFO    MainThread:854556 [wandb_init.py:init():892] starting backend
+2026-03-03 14:34:53,535 INFO    MainThread:854556 [wandb_init.py:init():895] sending inform_init request
+2026-03-03 14:34:53,540 INFO    MainThread:854556 [wandb_init.py:init():903] backend started and connected
+2026-03-03 14:34:53,542 INFO    MainThread:854556 [wandb_init.py:init():973] updated telemetry
+2026-03-03 14:34:53,548 INFO    MainThread:854556 [wandb_init.py:init():997] communicating run to backend with 90.0 second timeout
+2026-03-03 14:34:54,767 INFO    MainThread:854556 [wandb_init.py:init():1042] starting run threads in backend
+2026-03-03 14:34:54,895 INFO    MainThread:854556 [wandb_run.py:_console_start():2524] atexit reg
+2026-03-03 14:34:54,895 INFO    MainThread:854556 [wandb_run.py:_redirect():2373] redirect: wrap_raw
+2026-03-03 14:34:54,895 INFO    MainThread:854556 [wandb_run.py:_redirect():2442] Wrapping output streams.
+2026-03-03 14:34:54,896 INFO    MainThread:854556 [wandb_run.py:_redirect():2465] Redirects installed.
+2026-03-03 14:34:54,899 INFO    MainThread:854556 [wandb_init.py:init():1082] run started, returning control to user process
+2026-03-03 17:25:37,368 INFO    wandb-AsyncioManager-main:854556 [service_client.py:_forward_responses():134] Reached EOF.
+2026-03-03 17:25:37,368 INFO    wandb-AsyncioManager-main:854556 [mailbox.py:close():155] Closing mailbox, abandoning 1 handles.

ABLATION_0302_noTgtAlign/.hydra/config.yaml

@@ -0,0 +1,188 @@
+model:
+  encoder:
+    name: dcsplat
+    input_image_shape:
+    - 518
+    - 518
+    head_mode: pcd
+    num_level: 3
+    gs_param_dim: 256
+    align_corners: false
+    use_voxelize: true
+  decoder:
+    name: splatting_cuda
+    background_color:
+    - 0.0
+    - 0.0
+    - 0.0
+    make_scale_invariant: false
+  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: random
+    latent_dim: 128
+    num_latents: 64
+    num_self_attn_per_block: 2
+    voxel_size: 0.001
+    aux_refine: false
+    refine_error: false
+    use_refine_module: false
+    voxelize_activate: false
+    use_depth: false
+render_loss:
+  mse:
+    weight: 1.0
+  lpips:
+    weight: 0.05
+    apply_after_step: 0
+density_control_loss:
+  error_score:
+    weight: 0.0001
+    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_0302_noTgtAlign
+  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: false
+  context_view_train: false
+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
+  save_gs: false
+  save_sample_wise_metrics: true
+  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
+      target_align: true
+    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_0302_noTgtAlign/.hydra/hydra.yaml

@@ -0,0 +1,165 @@
+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
+    - wandb.mode=online
+    - wandb.name=ABLATION_0302_noTgtAlign
+    - model.density_control.score_mode=random
+  job:
+    name: main
+    chdir: null
+    override_dirname: +experiment=re10k_ablation_24v,model.density_control.score_mode=random,wandb.mode=online,wandb.name=ABLATION_0302_noTgtAlign
+    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_0302_noTgtAlign
+    choices:
+      experiment: re10k_ablation_24v
+      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_0302_noTgtAlign/.hydra/overrides.yaml

@@ -0,0 +1,4 @@
+- +experiment=re10k_ablation_24v
+- wandb.mode=online
+- wandb.name=ABLATION_0302_noTgtAlign
+- model.density_control.score_mode=random

ABLATION_0302_noTgtAlign/main.log

@@ -0,0 +1,83 @@
+[2026-03-03 17:25:57,101][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:26:03,305][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(
+
+[2026-03-03 17:26:03,305][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)
+
+[2026-03-03 17:26:08,283][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=255` in the `DataLoader` to improve performance.
+
+[2026-03-03 17:29:31,696][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:29:37,687][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(
+
+[2026-03-03 17:29:37,687][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)
+
+[2026-03-03 17:30:28,360][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.
+
+[2026-03-03 17:30:28,362][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
+
+[2026-03-03 17:32:05,291][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:32:11,332][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(
+
+[2026-03-03 17:32:11,332][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)
+
+[2026-03-03 17:33:01,336][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.
+
+[2026-03-03 17:33:01,337][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
+
+[2026-03-03 17:34:59,889][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:35:05,864][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(
+
+[2026-03-03 17:35:05,864][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)
+
+[2026-03-03 17:35:58,952][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.
+
+[2026-03-03 17:35:58,954][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
+
+[2026-03-03 17:36:01,340][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
+
+[2026-03-03 17:36:01,350][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)`.
+
+[2026-03-03 17:36:01,350][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(
+
+[2026-03-03 17:36:01,351][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)
+
+[2026-03-03 17:36:03,034][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]
+
+[2026-03-03 17:36:03,326][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.
+
+[2026-03-03 17:36:03,327][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.
+
+[2026-03-03 17:36:03,328][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.
+
+[2026-03-03 17:36:03,328][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.
+
+[2026-03-03 17:36:03,328][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.
+
+[2026-03-03 17:36:13,075][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
+grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
+bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
+  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+
+[2026-03-03 17:36:13,149][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
+
+[2026-03-03 17:37:46,051][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
+  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
+
+[2026-03-03 17:48:34,774][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_0302_noTgtAlign/train_ddp_process_1.log

@@ -0,0 +1,44 @@
+[2026-03-03 17:29:48,213][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:30:11,285][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(
+
+[2026-03-03 17:30:11,285][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)
+
+[2026-03-03 17:30:28,361][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
+
+[2026-03-03 17:32:21,762][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:32:48,615][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(
+
+[2026-03-03 17:32:48,616][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)
+
+[2026-03-03 17:33:01,337][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
+
+[2026-03-03 17:35:16,082][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:35:42,645][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(
+
+[2026-03-03 17:35:42,646][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)
+
+[2026-03-03 17:35:58,953][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
+
+[2026-03-03 17:36:13,070][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
+grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
+bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
+  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+
+[2026-03-03 17:36:13,172][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
+
+[2026-03-03 17:37:46,051][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
+  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
+
+[2026-03-03 17:48:34,774][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_0302_noTgtAlign/train_ddp_process_2.log

@@ -0,0 +1,44 @@
+[2026-03-03 17:29:48,269][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:30:16,899][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(
+
+[2026-03-03 17:30:16,900][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)
+
+[2026-03-03 17:30:28,361][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
+
+[2026-03-03 17:32:21,758][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:32:48,877][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(
+
+[2026-03-03 17:32:48,877][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)
+
+[2026-03-03 17:33:01,337][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
+
+[2026-03-03 17:35:16,091][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:35:47,851][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(
+
+[2026-03-03 17:35:47,851][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)
+
+[2026-03-03 17:35:58,953][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
+
+[2026-03-03 17:36:13,078][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
+grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
+bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
+  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+
+[2026-03-03 17:36:13,182][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
+
+[2026-03-03 17:37:46,051][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
+  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
+
+[2026-03-03 17:48:34,774][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_0302_noTgtAlign/train_ddp_process_3.log

@@ -0,0 +1,44 @@
+[2026-03-03 17:29:48,206][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:30:16,857][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(
+
+[2026-03-03 17:30:16,857][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)
+
+[2026-03-03 17:30:28,361][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
+
+[2026-03-03 17:32:21,762][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:32:48,656][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(
+
+[2026-03-03 17:32:48,657][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)
+
+[2026-03-03 17:33:01,336][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
+
+[2026-03-03 17:35:16,096][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:35:47,666][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(
+
+[2026-03-03 17:35:47,666][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)
+
+[2026-03-03 17:35:58,953][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
+
+[2026-03-03 17:36:13,076][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
+grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
+bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
+  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+
+[2026-03-03 17:36:13,191][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
+
+[2026-03-03 17:37:46,079][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
+  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
+
+[2026-03-03 17:48:34,775][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+

ABLATION_0302_noTgtAlign/train_ddp_process_4.log

@@ -0,0 +1,44 @@
+[2026-03-03 17:29:48,312][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:30:03,981][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(
+
+[2026-03-03 17:30:03,981][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)
+
+[2026-03-03 17:30:28,361][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
+
+[2026-03-03 17:32:21,721][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:32:48,708][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(
+
+[2026-03-03 17:32:48,708][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)
+
+[2026-03-03 17:33:01,337][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
+
+[2026-03-03 17:35:16,084][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:35:47,371][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(
+
+[2026-03-03 17:35:47,371][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)
+
+[2026-03-03 17:35:58,953][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
+
+[2026-03-03 17:36:13,073][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
+grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
+bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
+  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+
+[2026-03-03 17:36:13,182][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
+
+[2026-03-03 17:37:46,076][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
+  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
+
+[2026-03-03 17:48:34,775][py.warnings][WARNING] - /workspace/code/CVPR2026/src/visualization/layout.py:105: UserWarning: Using a non-tuple sequence for multidimensional indexing is deprecated and will be changed in pytorch 2.9; use x[tuple(seq)] instead of x[seq]. In pytorch 2.9 this will be interpreted as tensor index, x[torch.tensor(seq)], which will result either in an error or a different result (Triggered internally at /pytorch/torch/csrc/autograd/python_variable_indexing.cpp:316.)
+  result[selector] = overlay
+

ABLATION_0302_noTgtAlign/train_ddp_process_5.log

@@ -0,0 +1,44 @@
+[2026-03-03 17:29:48,314][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:30:17,098][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(
+
+[2026-03-03 17:30:17,098][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)
+
+[2026-03-03 17:30:28,361][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
+
+[2026-03-03 17:32:21,789][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:32:37,905][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(
+
+[2026-03-03 17:32:37,906][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)
+
+[2026-03-03 17:33:01,336][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
+
+[2026-03-03 17:35:16,102][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:35:45,673][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(
+
+[2026-03-03 17:35:45,676][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)
+
+[2026-03-03 17:35:58,953][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
+
+[2026-03-03 17:36:12,327][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
+grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
+bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
+  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+
+[2026-03-03 17:36:13,191][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
+
+[2026-03-03 17:37:46,079][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
+  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
+
+[2026-03-03 17:48:34,774][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_0302_noTgtAlign/train_ddp_process_6.log

@@ -0,0 +1,44 @@
+[2026-03-03 17:29:48,277][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:30:16,775][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(
+
+[2026-03-03 17:30:16,775][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)
+
+[2026-03-03 17:30:28,361][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
+
+[2026-03-03 17:32:21,773][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:32:38,406][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(
+
+[2026-03-03 17:32:38,406][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)
+
+[2026-03-03 17:33:01,337][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
+
+[2026-03-03 17:35:16,116][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:35:47,749][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(
+
+[2026-03-03 17:35:47,749][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)
+
+[2026-03-03 17:35:58,953][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
+
+[2026-03-03 17:36:12,560][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
+grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
+bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
+  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+
+[2026-03-03 17:36:13,180][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
+
+[2026-03-03 17:37:46,058][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
+  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
+
+[2026-03-03 17:48:34,774][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_0302_noTgtAlign/train_ddp_process_7.log

@@ -0,0 +1,44 @@
+[2026-03-03 17:29:48,209][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:30:15,376][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(
+
+[2026-03-03 17:30:15,376][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)
+
+[2026-03-03 17:30:28,361][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
+
+[2026-03-03 17:32:21,793][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:32:48,771][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(
+
+[2026-03-03 17:32:48,771][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)
+
+[2026-03-03 17:33:01,336][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
+
+[2026-03-03 17:35:16,110][dinov2][INFO] - using MLP layer as FFN
+[2026-03-03 17:35:47,614][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(
+
+[2026-03-03 17:35:47,614][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)
+
+[2026-03-03 17:35:58,954][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
+
+[2026-03-03 17:36:12,568][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
+grad.sizes() = [57, 256, 1, 1], strides() = [256, 1, 256, 256]
+bucket_view.sizes() = [57, 256, 1, 1], strides() = [256, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:334.)
+  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+
+[2026-03-03 17:36:13,185][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
+
+[2026-03-03 17:37:46,051][py.warnings][WARNING] - /venv/main/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:209: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
+  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
+
+[2026-03-03 17:48:34,774][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_0302_noTgtAlign/wandb/debug-internal.log

@@ -0,0 +1,6 @@
+{"time":"2026-03-03T17:35:55.708502915Z","level":"INFO","msg":"stream: starting","core version":"0.25.0"}
+{"time":"2026-03-03T17:35:56.156384015Z","level":"INFO","msg":"stream: created new stream","id":"et94mfhp"}
+{"time":"2026-03-03T17:35:56.156522256Z","level":"INFO","msg":"handler: started","stream_id":"et94mfhp"}
+{"time":"2026-03-03T17:35:56.156785449Z","level":"INFO","msg":"stream: started","id":"et94mfhp"}
+{"time":"2026-03-03T17:35:56.156813659Z","level":"INFO","msg":"sender: started","stream_id":"et94mfhp"}
+{"time":"2026-03-03T17:35:56.156835559Z","level":"INFO","msg":"writer: started","stream_id":"et94mfhp"}

ABLATION_0302_noTgtAlign/wandb/debug.log

@@ -0,0 +1,19 @@
+2026-03-03 17:35:55,409 INFO    MainThread:870906 [wandb_setup.py:_flush():81] Current SDK version is 0.25.0
+2026-03-03 17:35:55,409 INFO    MainThread:870906 [wandb_setup.py:_flush():81] Configure stats pid to 870906
+2026-03-03 17:35:55,409 INFO    MainThread:870906 [wandb_setup.py:_flush():81] Loading settings from environment variables
+2026-03-03 17:35:55,409 INFO    MainThread:870906 [wandb_init.py:setup_run_log_directory():717] Logging user logs to /workspace/code/CVPR2026/outputs/ablation/re10k/ABLATION_0302_noTgtAlign/wandb/run-20260303_173555-et94mfhp/logs/debug.log
+2026-03-03 17:35:55,409 INFO    MainThread:870906 [wandb_init.py:setup_run_log_directory():718] Logging internal logs to /workspace/code/CVPR2026/outputs/ablation/re10k/ABLATION_0302_noTgtAlign/wandb/run-20260303_173555-et94mfhp/logs/debug-internal.log
+2026-03-03 17:35:55,410 INFO    MainThread:870906 [wandb_init.py:init():844] calling init triggers
+2026-03-03 17:35:55,410 INFO    MainThread:870906 [wandb_init.py:init():849] wandb.init called with sweep_config: {}
+config: {'model': {'encoder': {'name': 'dcsplat', 'input_image_shape': [518, 518], 'head_mode': 'pcd', 'num_level': 3, 'gs_param_dim': 256, 'align_corners': False, 'use_voxelize': True}, 'decoder': {'name': 'splatting_cuda', 'background_color': [0.0, 0.0, 0.0], 'make_scale_invariant': False}, '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': 'random', 'latent_dim': 128, 'num_latents': 64, 'num_self_attn_per_block': 2, 'voxel_size': 0.001, 'aux_refine': False, 'refine_error': False, 'use_refine_module': False, 'voxelize_activate': False, 'use_depth': False}}, 'render_loss': {'mse': {'weight': 1.0}, 'lpips': {'weight': 0.05, 'apply_after_step': 0}}, 'density_control_loss': {'error_score': {'weight': 0.0001, '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_0302_noTgtAlign', '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': False, 'context_view_train': False}, '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, 'save_gs': False, 'save_sample_wise_metrics': True, '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, 'target_align': True}, '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': {}}
+2026-03-03 17:35:55,410 INFO    MainThread:870906 [wandb_init.py:init():892] starting backend
+2026-03-03 17:35:55,698 INFO    MainThread:870906 [wandb_init.py:init():895] sending inform_init request
+2026-03-03 17:35:55,705 INFO    MainThread:870906 [wandb_init.py:init():903] backend started and connected
+2026-03-03 17:35:55,709 INFO    MainThread:870906 [wandb_init.py:init():973] updated telemetry
+2026-03-03 17:35:55,716 INFO    MainThread:870906 [wandb_init.py:init():997] communicating run to backend with 90.0 second timeout
+2026-03-03 17:35:56,664 INFO    MainThread:870906 [wandb_init.py:init():1042] starting run threads in backend
+2026-03-03 17:35:56,791 INFO    MainThread:870906 [wandb_run.py:_console_start():2524] atexit reg
+2026-03-03 17:35:56,791 INFO    MainThread:870906 [wandb_run.py:_redirect():2373] redirect: wrap_raw
+2026-03-03 17:35:56,791 INFO    MainThread:870906 [wandb_run.py:_redirect():2442] Wrapping output streams.
+2026-03-03 17:35:56,791 INFO    MainThread:870906 [wandb_run.py:_redirect():2465] Redirects installed.
+2026-03-03 17:35:56,794 INFO    MainThread:870906 [wandb_init.py:init():1082] run started, returning control to user process

ABLATION_0302_noTgtAlign/wandb/run-20260303_172605-beokhgg2/files/config.yaml

@@ -0,0 +1,311 @@
+_wandb:
+    value:
+        cli_version: 0.25.0
+        e:
+            vpcdp2qfp7cgu3zf4ilibu30q5on1nko:
+                args:
+                    - +experiment=re10k_ablation_24v
+                    - wandb.mode=online
+                    - wandb.name=ABLATION_0302_noTgtAlign
+                    - model.density_control.score_mode=random
+                cpu_count: 128
+                cpu_count_logical: 256
+                cudaVersion: "13.0"
+                disk:
+                    /:
+                        total: "735513149440"
+                        used: "700800790528"
+                email: dna9041@korea.ac.kr
+                executable: /venv/main/bin/python
+                git:
+                    commit: 9dfce172a0f8c7ce85e763899f7ef741ecffc454
+                    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-9a20101e-d876-facd-5f05-805081aede41
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-84736a77-ee75-3324-e4e1-99cc15bfb5e9
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-423d3161-cdc4-3fc0-caee-d15cfaa83ca6
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-5b0058b2-cdb9-c952-04f9-87dcaa7ea742
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-08b37f98-4603-d483-2f2b-fe5311aa42f2
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-03273b5b-2fdd-a5fe-4460-c897334ae464
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-292d466c-d00d-25a4-28b6-e6c978d3e70c
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-46f38561-3148-e442-7f7f-bfe447bab7fe
+                host: e9d3310a05da
+                memory:
+                    total: "1622950240256"
+                os: Linux-6.8.0-94-generic-x86_64-with-glibc2.39
+                program: -m src.main
+                python: CPython 3.12.12
+                root: /workspace/code/CVPR2026/outputs/ablation/re10k/ABLATION_0302_noTgtAlign
+                startedAt: "2026-03-03T17:26:05.471917Z"
+                writerId: vpcdp2qfp7cgu3zf4ilibu30q5on1nko
+        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":
+                - 2
+                - 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
+                target_align: true
+                warm_up_steps: 1000
+density_control_loss:
+    value:
+        error_score:
+            grad_scale: 10000
+            log_scale: false
+            mode: original
+            weight: 0.0001
+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: false
+            voxel_size: 0.001
+            voxelize_activate: false
+        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_gs: false
+        save_image: false
+        save_sample_wise_metrics: true
+        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_0302_noTgtAlign
+        project: DCSplat
+        tags:
+            - re10k
+            - 256x256

ABLATION_0302_noTgtAlign/wandb/run-20260303_172605-beokhgg2/files/output.log

@@ -0,0 +1,72 @@
+LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
+
+  | Name                   | Type                 | Params | Mode
+------------------------------------------------------------------------
+0 | encoder                | OurSplat             | 888 M  | train
+1 | density_control_module | DensityControlModule | 0      | 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
+------------------------------------------------------------------------
+888 M     Trainable params
+0         Non-trainable params
+888 M     Total params
+3,553.933 Total estimated model params size (MB)
+1202      Modules in train mode
+522       Modules in eval mode
+Sanity Checking: |                                                                                             | 0/? [00:00<?, ?it/s][2026-03-03 17:26:08,283][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=255` in the `DataLoader` to improve performance.
+
+Validation epoch start on rank 0
+Sanity Checking DataLoader 0:   0%|                                                                            | 0/1 [00:00<?, ?it/s]validation step 0; scene = ['306e2b7785657539'];
+> /workspace/code/CVPR2026/src/model/model_wrapper.py(1570)get_normalized_target_cam()
+-> gt_left_c2w = gt_context_c2w[:, 0:1, :, :]
+tensor([[0.0369]], device='cuda:0')
+tensor([[0.0369, 0.0369, 0.0369, 0.0369]], device='cuda:0')
+tensor([[[1, 0],
+         [0, 1],
+         [0, 1],
+         [0, 1]]], device='cuda:0')
+tensor([[[[0.8595, 0.0000, 0.5000],
+          [0.0000, 0.8597, 0.5000],
+          [0.0000, 0.0000, 1.0000]],
+
+         [[0.8595, 0.0000, 0.5000],
+          [0.0000, 0.8597, 0.5000],
+          [0.0000, 0.0000, 1.0000]],
+
+         [[0.8595, 0.0000, 0.5000],
+          [0.0000, 0.8597, 0.5000],
+          [0.0000, 0.0000, 1.0000]],
+
+         [[0.8595, 0.0000, 0.5000],
+          [0.0000, 0.8597, 0.5000],
+          [0.0000, 0.0000, 1.0000]]]], device='cuda:0')
+tensor([[[[0.8837, 0.0000, 0.5000],
+          [0.0000, 0.8834, 0.5000],
+          [0.0000, 0.0000, 1.0000]],
+
+         [[0.8721, 0.0000, 0.5000],
+          [0.0000, 0.8713, 0.5000],
+          [0.0000, 0.0000, 1.0000]]]], device='cuda:0')
+torch.Size([1, 4, 3, 3])
+torch.Size([1, 2, 3, 3])
+tensor([[[[0.8779, 0.0000, 0.5000],
+          [0.0000, 0.8773, 0.5000],
+          [0.0000, 0.0000, 1.0000]],
+
+         [[0.8779, 0.0000, 0.5000],
+          [0.0000, 0.8773, 0.5000],
+          [0.0000, 0.0000, 1.0000]],
+
+         [[0.8779, 0.0000, 0.5000],
+          [0.0000, 0.8773, 0.5000],
+          [0.0000, 0.0000, 1.0000]],
+
+         [[0.8779, 0.0000, 0.5000],
+          [0.0000, 0.8773, 0.5000],
+          [0.0000, 0.0000, 1.0000]]]], device='cuda:0')
+Error executing job with overrides: ['+experiment=re10k_ablation_24v', 'wandb.mode=online', 'wandb.name=ABLATION_0302_noTgtAlign', 'model.density_control.score_mode=random']
+
+
+Received interrupt signal. Cleaning up...

ABLATION_0302_noTgtAlign/wandb/run-20260303_172605-beokhgg2/files/requirements.txt

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+            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
+                target_align: true
+                warm_up_steps: 1000
+density_control_loss:
+    value:
+        error_score:
+            grad_scale: 10000
+            log_scale: false
+            mode: original
+            weight: 0.0001
+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: false
+            voxel_size: 0.001
+            voxelize_activate: false
+        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_gs: false
+        save_image: false
+        save_sample_wise_metrics: true
+        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_0302_noTgtAlign
+        project: DCSplat
+        tags:
+            - re10k
+            - 256x256

ABLATION_0302_noTgtAlign/wandb/run-20260303_173024-phck7alc/files/output.log

@@ -0,0 +1,117 @@
+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 | 0      | 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
+------------------------------------------------------------------------
+888 M     Trainable params
+0         Non-trainable params
+888 M     Total params
+3,553.933 Total estimated model params size (MB)
+1202      Modules in train mode
+522       Modules in eval mode
+Sanity Checking: |                                                                                             | 0/? [00:00<?, ?it/s][2026-03-03 17:30:28,360][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.
+
+[2026-03-03 17:30:28,362][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'];
+Error executing job with overrides: ['+experiment=re10k_ablation_24v', 'wandb.mode=online', 'wandb.name=ABLATION_0302_noTgtAlign', 'model.density_control.score_mode=random']
+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 1054, in _run_stage
+    self._run_sanity_check()
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/trainer/trainer.py", line 1083, in _run_sanity_check
+    val_loop.run()
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/loops/utilities.py", line 179, in _decorator
+    return loop_run(self, *args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/loops/evaluation_loop.py", line 145, in run
+    self._evaluation_step(batch, batch_idx, dataloader_idx, dataloader_iter)
+  File "/venv/main/lib/python3.12/site-packages/lightning/pytorch/loops/evaluation_loop.py", line 437, in _evaluation_step
+    output = call._call_strategy_hook(trainer, hook_name, *step_args)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  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 411, in validation_step
+    return self._forward_redirection(self.model, self.lightning_module, "validation_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/lightning_utilities/core/rank_zero.py", line 41, in wrapped_fn
+    return fn(*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 1093, in validation_step
+    target_extrinsic_c2w, target_intrinsic, near_plane, far_plane = self.get_target_projections(batch, backbone_outputs, target_key=target_key_list[target_key_idx])
+                                                                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  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 1718, in get_target_projections
+    target_extrinsic_c2w, target_intrinsic, target_nearest_context_idx, near_plane, far_plane = self.get_normalized_target_cam(batch, gs_outputs, target_key, intr_scale)
+                                                                                                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  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 1595, in get_normalized_target_cam
+    target_intrinsic = pred_intrinsics.mean(dim=1, keepdim=True).repeat(1, TVN, 1, 1)
+                       ^^^^^^^^^^^^^^^
+NameError: name 'pred_intrinsics' is not defined
+
+Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

ABLATION_0302_noTgtAlign/wandb/run-20260303_173024-phck7alc/files/requirements.txt

@@ -0,0 +1,173 @@
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+pytz==2025.2
+easydict==1.13
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+wadler_lindig==0.1.7
+networkx==3.4.2
+urllib3==2.5.0
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+typing-inspection==0.4.1
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+setuptools==78.1.1
+safetensors==0.5.3
+multidict==6.6.4
+PyYAML==6.0.2
+PySocks==1.7.1
+pyparsing==3.2.5
+pydantic_core==2.33.2
+pycparser==2.23
+protobuf==6.32.1
+propcache==0.3.2
+proglog==0.1.12
+platformdirs==4.4.0
+pip==25.2
+mdurl==0.1.2
+pillow==10.4.0
+packaging==24.2
+opt_einsum==3.4.0
+frozenlist==1.7.0
+numpy==1.26.4
+ninja==1.13.0
+MarkupSafe==3.0.2
+kornia_rs==0.1.9
+kiwisolver==1.4.9
+imageio-ffmpeg==0.6.0
+idna==3.7
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+fonttools==4.60.0
+triton==3.4.0
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+decorator==4.4.2
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+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
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+annotated-types==0.7.0
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+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
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+imageio==2.37.0
+gitdb==4.0.12
+contourpy==1.3.2
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+matplotlib==3.10.6
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+huggingface-hub==0.35.1
+GitPython==3.1.45
+brotlicffi==1.0.9.2
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+torchmetrics==1.8.2
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+pytorch-lightning==2.5.1
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+e3nn==0.6.0
+lightning==2.5.1
+gsplat==1.5.3
+nvidia-cusparselt-cu12==0.7.1
+nvidia-nvjitlink-cu12==12.8.93
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+nvidia-curand-cu12==10.3.9.90
+nvidia-cufile-cu12==1.13.1.3
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+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
+plyfile==1.1.3
+wandb==0.25.0
+cuda-bindings==13.0.3
+cuda-pathfinder==1.3.3
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+mpmath==1.3.0
+nvidia-cublas==13.1.0.3
+nvidia-cuda-cupti==13.0.85
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ABLATION_0302_noTgtAlign/wandb/run-20260303_173024-phck7alc/files/wandb-metadata.json

@@ -0,0 +1,93 @@
+{
+  "os":  "Linux-6.8.0-94-generic-x86_64-with-glibc2.39",
+  "python":  "CPython 3.12.12",
+  "startedAt":  "2026-03-03T17:30:24.387912Z",
+  "args":  [
+    "+experiment=re10k_ablation_24v",
+    "wandb.mode=online",
+    "wandb.name=ABLATION_0302_noTgtAlign",
+    "model.density_control.score_mode=random"
+  ],
+  "program":  "-m src.main",
+  "git":  {
+    "remote":  "git@github.com:K-nowing/CVPR2026.git",
+    "commit":  "9dfce172a0f8c7ce85e763899f7ef741ecffc454"
+  },
+  "email":  "dna9041@korea.ac.kr",
+  "root":  "/workspace/code/CVPR2026/outputs/ablation/re10k/ABLATION_0302_noTgtAlign",
+  "host":  "e9d3310a05da",
+  "executable":  "/venv/main/bin/python",
+  "cpu_count":  128,
+  "cpu_count_logical":  256,
+  "gpu":  "NVIDIA H200",
+  "gpu_count":  8,
+  "disk":  {
+    "/":  {
+      "total":  "735513149440",
+      "used":  "700800118784"
+    }
+  },
+  "memory":  {
+    "total":  "1622950240256"
+  },
+  "gpu_nvidia":  [
+    {
+      "name":  "NVIDIA H200",
+      "memoryTotal":  "150754820096",
+      "cudaCores":  16896,
+      "architecture":  "Hopper",
+      "uuid":  "GPU-9a20101e-d876-facd-5f05-805081aede41"
+    },
+    {
+      "name":  "NVIDIA H200",
+      "memoryTotal":  "150754820096",
+      "cudaCores":  16896,
+      "architecture":  "Hopper",
+      "uuid":  "GPU-84736a77-ee75-3324-e4e1-99cc15bfb5e9"
+    },
+    {
+      "name":  "NVIDIA H200",
+      "memoryTotal":  "150754820096",
+      "cudaCores":  16896,
+      "architecture":  "Hopper",
+      "uuid":  "GPU-423d3161-cdc4-3fc0-caee-d15cfaa83ca6"
+    },
+    {
+      "name":  "NVIDIA H200",
+      "memoryTotal":  "150754820096",
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ABLATION_0302_noTgtAlign/wandb/run-20260303_173024-phck7alc/files/wandb-summary.json

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ABLATION_0302_noTgtAlign/wandb/run-20260303_173024-phck7alc/logs/debug-core.log

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