inference: false
inference_out_dir: output
model:
  class_name: model.ar_rig_diffusion.RigARDiffusion
  diffusion:
    d: 3
    grad_checkpointing: false
    num_sampling_steps: '300'
    w: 1024
  joints_tokenizer:
    in_channels: 3
    middle_channels: 512
    n_joints: 64
  pc_tokenizer:
    in_channels: 6
    middle_channels: 512
    n_points: 1024
  transformer:
    d: 1024
    d_head: 16
    n_layer: 12
training:
  amp_dtype: bf16
  batch_size_per_gpu: 12
  beta1: 0.9
  beta2: 0.95
  checkpoint_dir: ckpt/ckpt.pt
  checkpoint_dir_s3: None
  grad_accum_steps: 1
  grad_checkpoint_every: 1
  l2_warmup_steps: 500
  lpips_loss_weight: 0.0
  lr: 0.0001
  max_fwdbwd_passes: 100000
  num_epochs: 100000
  perceptual_loss_weight: 0.5
  pointsdist_loss_weight: 0.0
  reset_lr: false
  reset_training_state: true
  reset_weight_decay: false
  resume_ckpt: ckpt/ckpt.pt
  use_amp: true
  use_tf32: true
  wandb_exp_name: None
  warmup: 500
  warmup_pointsdist: false
  weight_decay: 0.05