configs/hypersim_er_v5_phase0_pilot_train_v3.yaml

seed: 17
device: auto
dataset:
  name: hypersim
  root: data/hypersim_er_prepared/train
  image_size:
  - 128
  - 160
  context_views: 4
  target_views: 2
  length: 16
  sample_stride: 2
  spatial_protocol: context_local_metric
  local_bounds_m:
  - - -6.0
    - -4.0
    - 0.05
  - - 6.0
    - 4.0
    - 12.05
  scene_ids:
  - ai_037_003
  - ai_031_007
  - ai_048_003
  - ai_038_010
  - ai_003_006
  - ai_004_001
  - ai_047_002
  - ai_031_006
  - ai_018_010
  - ai_039_010
  - ai_009_006
  - ai_015_007
  - ai_046_001
  - ai_009_003
  - ai_026_001
  - ai_029_003
model:
  mode: fixed
  state_architecture: evidence_residual
  voxel_resolution:
  - 48
  - 32
  - 48
  image_feature_dim: 48
  state_feature_dim: 48
  refinement_blocks: 4
  evidence_temperature: 0.1
  observed_residual_floor: 0.1
  completion_residual_scale: 4.0
  appearance_resolution_scale: 2
  n_samples: 64
  ray_chunk_size: 4096
training:
  output_dir: outputs\hypersim_er_v6_phase0_v5_pilot_train_v3
  batch_size: 1
  learning_rate: 0.0002
  max_steps: 10000
  num_workers: 0
  amp: true
  amp_dtype: bfloat16
  log_every: 20
  checkpoint_every: 5000
  measurements:
  - rgb
  - depth
  - normal
  - point
  - visibility
  gradient_accumulation: 2
  weight_decay: 0.0001
  lr_schedule: warmup_cosine
  warmup_steps: 3000
  min_lr_ratio: 0.05
  ema_decay: 0.98
  evidence_residual_weight: 0.001