configs/train_scenedino_re10k.yaml

defaults:
  - dataset: realestate10k
  - model: dino_downsampler
  - renderer: pixelnerf
  - training: scenedino
  - validation: scenedino
  - _self_

training_type: "full_training"
mode: "nvs"
seed: 0
backend: null
nproc_per_node: null
with_amp: true
name: "training"
batch_size: 4
num_workers: 4

output:
  path: "out/features-paper"
  unique_id: scenedino-re10k

renderer:
  n_coarse : 32
  n_fine : 0
  n_fine_depth : 0
  depth_std : 1.0
  sched : []
  white_bkgd : false
  lindisp: true
  hard_alpha_cap: true
  render_mode: volumetric
  eval_batch_size: 65536
  normalize_dino: true

model:
  encoder:
    image_size: [288, 512]
  loss_renderer_strategy: 
    name: "alternate"

training:
  ray_sampler:
    args:
      patch_size: 8
      # ray_batch_size: 512

  scheduler:
    step_size: 50000