conf/net_conf.yaml

training:
  use_ema: True
  batch_size: 8
  adam_beta1: 0.9
  adam_beta2: 0.999
  adam_weight_decay: 1e-2
  adam_epsilon: 1e-08
  lr_scheduler: constant
  lr_warmup_steps: 0
  max_train_steps: 50000
  text_finetune_step: 50
  unet_finetune_step: 50
  alpha: 0.1
  min_lr: 1e-6
  warmup_epochs: 0
  num_train_epochs: 300
  accumulate_step: 1
  lr: 1e-6
  resume: ' '
  down_attn_shift: -1
  down_attn_map: -1
  mid_attn_shift: -1
  mid_attn_map: -1
  up_attn_shift: -1
  up_attn_map: -1

inference:
  loss_scale: 30
  batch_size: 1
  loss_threshold: 0.2
  max_iter: 5
  index_step: 10
  start_pair: 800
  iteration_interval: 400
  infer_iter: 0