data:
  centered: false
  dataset: ''
  image_size: 32
  n_bits: 8
  normalization_type: score_sde
  num_channels: 3
  random_flip: true
  standardize: false
  tfds_dir: /scratch/imaging/projects/bfeng/tensorflow_datasets
  uniform_dequantization: false
eval:
  batch_size: 256
model:
  attention_type: ddpm
  attn_resolutions: !!python/tuple
  - 16
  beta_max: 20.0
  beta_min: 0.1
  ch_mult: !!python/tuple
  - 1
  - 2
  - 2
  - 2
  conditional: true
  conv_size: 3
  dropout: 0.1
  ema_rate: 0.9999
  embedding_type: positional
  fir: true
  fir_kernel:
  - 1
  - 3
  - 3
  - 1
  fourier_scale: 16
  init_scale: 0.0
  interpolation: bilinear
  name: ncsnpp
  nf: 64
  nonlinearity: swish
  normalization: GroupNorm
  num_res_blocks: 4
  num_scales: 1000
  progressive: none
  progressive_combine: sum
  progressive_input: residual
  resamp_with_conv: true
  resblock_type: biggan
  scale_by_sigma: false
  sigma_max: 50.0
  sigma_min: 0.002
  skip_rescale: true
optim:
  beta1: 0.9
  eps: 1.0e-08
  grad_clip: 1.0
  lr: 0.0002
  optimizer: Adam
  warmup: 5000
  weight_decay: 0
sampling:
  corrector: none
  method: pc
  n_steps_each: 1
  noise_removal: true
  predictor: euler_maruyama
  probability_flow: false
  snr: 0.17
seed: 42
training:
  batch_size: 128
  continuous: true
  eval_freq: 1000
  importance_weighting: false
  likelihood_weighting: false
  log_freq: 100
  n_iters: 100000
  n_jitted_steps: 1
  reduce_mean: false
  sde: vpsde
  smallest_time: 0.001
  snapshot_freq: 1000
