model:
  pretrained_model_name_or_path: 'pretrained_weights/TripoSG'
  vae:
    num_tokens: 512
  transformer:
    enable_local_cross_attn: true
    global_attn_block_ids: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20]
    global_attn_block_id_range: null # The average should be 10 for unet-skipping


dataset:
  config: 
    - 'datasets/object_part_configs.json' # Modify this path if you use your own dataset
  training_ratio: 0.9
  min_num_parts: 1
  max_num_parts: 16
  max_iou_mean: 0.5
  max_iou_max: 0.5
  shuffle_parts: true
  object_ratio: 0.3
  rotating_ratio: 0.2
  ratating_degree: 10

optimizer:
  name: "adamw"
  lr: 5e-5
  betas:
    - 0.9
    - 0.999
  weight_decay: 0.01
  eps: 1.e-8

lr_scheduler:
  name: "constant_warmup"
  num_warmup_steps: 1000

train:
  batch_size_per_gpu: 32
  epochs: 10
  grad_checkpoint: true
  weighting_scheme: "logit_normal"
  logit_mean: 0.0
  logit_std: 1.0
  mode_scale: 1.29
  cfg_dropout_prob: 0.1
  training_objective: "-v"
  log_freq: 1
  early_eval_freq: 500
  early_eval: 1000
  eval_freq: 1000
  save_freq: 2000
  eval_freq_epoch: 5
  save_freq_epoch: 10
  ema_kwargs:
    decay: 0.9999
    use_ema_warmup: true
    inv_gamma: 1.
    power: 0.75

val:
  batch_size_per_gpu: 1
  nrow: 4
  min_num_parts: 2
  max_num_parts: 8
  num_inference_steps: 50
  max_num_expanded_coords: 1e8
  use_flash_decoder: false
  rendering:
    radius: 4.0
    num_views: 36
    fps: 18
  metric:
    cd_num_samples: 204800
    cd_metric: "l2"
    f1_score_threshold: 0.1
    default_cd: 1e6
    default_f1: 0.0