model:
  checkpoint_path: "./models/aura_flow_0.3.bnb_nf4.safetensors"
  pretrained_model_name_or_path: fal/AuraFlow-v0.3

  dtype: bfloat16

  denoiser:
    use_flash_attn: true

    use_shortcut: true

  flow_matching_ratio: 0.75
  shortcut_max_steps: 128

  timestep_sampling_type: "sigmoid"

peft:
  type: lora
  rank: 4
  alpha: 4.0
  dropout: 0.0

  dtype: bfloat16

  # include the AdaLN-Zero modulation layers
  include_keys: [
      ".attn.",
      ".mlp.",
      ".mlpC.",
      ".mlpX.",
      #
      ".modC.",
      ".modX.",
      ".modCX.",
    ]
  exclude_keys: ["text_encoder", "vae", "t_embedder", "final_linear", ".modF."]

dataset:
  folder: "data/pexels-1k-random"
  num_repeats: 2
  batch_size: 2

  bucket_base_size: 1024
  step: 128
  min_size: 384
  do_upscale: false

  caption_processors: []

optimizer:
  name: "schedulefree.RAdamScheduleFree"
  args:
    lr: 0.0005

tracker:
  project_name: "auraflow-shortcut-1"
  loggers:
    - wandb

saving:
  strategy:
    per_epochs: 1
    per_steps: null
    save_last: true

  callbacks:
    - type: "hf_hub"
      # - type: "safetensors"
      name: "shortcut-09"
      save_dir: "./output/shortcut-09"

      hub_id: "p1atdev/afv03-lora"
      dir_in_repo: "shortcut-09"

preview:
  strategy:
    per_epochs: 1
    per_steps: 100

  callbacks:
    # - type: "local"
    #   save_dir: "./output/shortcut-08/preview"

    - type: "discord"
      url: "masked"

  data:
    path: "./projects/shortcut/preview.yml"

seed: 42
num_train_epochs: 20

trainer:
  # debug_mode: "1step"

  gradient_checkpointing: true
  gradient_accumulation_steps: 16

  torch_compile: true
  torch_compile_args:
    mode: max-autotune
    fullgraph: true

  fp32_matmul_precision: "medium"