# lightning.pytorch==2.6.1
seed_everything: 1234
torch_hub_dir: null
huggingface_cache_dir: null
trainer:
  accelerator: auto
  strategy: auto
  devices: auto
  num_nodes: 1
  precision: bf16-mixed
  logger:
    class_path: lightning.pytorch.loggers.WandbLogger
    init_args:
      name: PixelGen_Medical_REFUGE2
      save_dir: .
      version: null
      offline: false
      dir: null
      id: null
      anonymous: null
      project: pixelgen_medical_refuge2
      log_model: false
      experiment: null
      prefix: ''
      checkpoint_name: null
      add_file_policy: mutable
      entity: null
      notes: null
      tags: null
      config: null
      config_exclude_keys: null
      config_include_keys: null
      allow_val_change: null
      group: null
      job_type: null
      mode: null
      force: null
      reinit: null
      resume: null
      resume_from: null
      fork_from: null
      save_code: null
      tensorboard: null
      sync_tensorboard: null
      monitor_gym: null
      settings: null
  callbacks:
  - class_path: src.callbacks.model_checkpoint.CheckpointHook
    init_args:
      dirpath: null
      filename: null
      monitor: null
      verbose: false
      save_last: true
      save_top_k: -1
      save_on_exception: false
      save_weights_only: false
      mode: min
      auto_insert_metric_name: true
      every_n_train_steps: 10000
      train_time_interval: null
      every_n_epochs: null
      save_on_train_epoch_end: null
      enable_version_counter: true
  - class_path: src.callbacks.save_images.SaveImagesHook
    init_args:
      save_dir: val_samples
      save_compressed: true
  fast_dev_run: false
  max_epochs: null
  min_epochs: null
  max_steps: 100000
  min_steps: null
  max_time: null
  limit_train_batches: null
  limit_val_batches: null
  limit_test_batches: null
  limit_predict_batches: null
  overfit_batches: 0.0
  val_check_interval: 10000
  check_val_every_n_epoch: null
  num_sanity_val_steps: 0
  log_every_n_steps: 50
  enable_checkpointing: null
  enable_progress_bar: null
  enable_model_summary: null
  accumulate_grad_batches: 1
  gradient_clip_val: null
  gradient_clip_algorithm: null
  deterministic: null
  benchmark: null
  inference_mode: true
  use_distributed_sampler: false
  profiler: null
  detect_anomaly: false
  barebones: false
  plugins:
  - class_path: src.plugins.bd_env.BDEnvironment
  sync_batchnorm: false
  reload_dataloaders_every_n_epochs: 0
  default_root_dir: ./medical_workdirs
  enable_autolog_hparams: true
  model_registry: null
model:
  vae:
    class_path: src.models.autoencoder.pixel.PixelAE
    init_args:
      scale: 1.0
      shift: 0.0
  conditioner:
    class_path: src.models.conditioner.mask_conditioner.MaskConditioner
    init_args:
      hidden_size: 768
      in_channels: 1
      img_size: 256
      null_condition_p: 0.1
  denoiser:
    class_path: src.models.transformer.JiT_medical.JiTMedical
    init_args:
      input_size: 256
      patch_size: 16
      in_channels: 3
      hidden_size: 768
      depth: 12
      num_heads: 12
      mlp_ratio: 4.0
      attn_drop: 0.0
      proj_drop: 0.1
      num_classes: 1
      bottleneck_dim: 128
      use_bottleneck: true
      in_context_len: 32
      in_context_start: 4
      mask_in_channels: 1
      mask_mode: spatial
  diffusion_trainer:
    class_path: src.diffusion.flow_matching.training_medical.MedicalTrainerSimple
    init_args:
      scheduler:
        class_path: src.diffusion.flow_matching.scheduling.LinearScheduler
      loss_weight_fn: src.diffusion.flow_matching.training_medical.constant
      lognorm_t: true
      timeshift: 1.0
      P_mean: -0.8
      P_std: 0.8
      t_eps: 0.05
      lpips_weight: 0.1
      percept_t_threshold: 0.3
      noise_scale: 1.0
      patch_size: 16
      null_condition_p: 0.1
  diffusion_sampler:
    class_path: src.diffusion.flow_matching.sampling_medical.EulerSamplerMedical
    init_args:
      w_scheduler:
        class_path: src.diffusion.flow_matching.scheduling.LinearScheduler
      timeshift: 1.0
      guidance_interval_min: 0.1
      guidance_interval_max: 0.9
      step_fn: src.diffusion.flow_matching.sampling.ode_step_fn
      last_step: null
      last_step_fn: src.diffusion.flow_matching.sampling_medical.ode_step_fn
      t_eps: 0.05
      scheduler:
        class_path: src.diffusion.flow_matching.scheduling.LinearScheduler
      guidance_fn: src.diffusion.base.guidance.simple_guidance_fn
      num_steps: 50
      guidance: 2.0
  ema_tracker:
    class_path: src.callbacks.simple_ema.SimpleEMA
    init_args:
      decay: 0.9999
      every_n_steps: 1
  optimizer:
    class_path: torch.optim.AdamW
    init_args:
      lr: 0.0001
      betas:
      - 0.9
      - 0.999
      eps: 1.0e-08
      weight_decay: 0.0
      amsgrad: false
      maximize: false
      foreach: null
      capturable: false
      differentiable: false
      fused: null
  lr_scheduler: null
  eval_original_model: false
data:
  train_dataset:
    class_path: src.data.dataset.refuge2.REFUGE2Dataset
    init_args:
      data_root: /data2/sichengli/Data/test/Segmentation/REFUGE2
      resolution: 256
      splits:
      - train
      - val
      augment: true
      seed: 42
      max_samples: null
      random_flip: true
      val_ratio: 0.1
  eval_dataset:
    class_path: src.data.dataset.refuge2.REFUGE2RandnDataset
    init_args:
      data_root: /data2/sichengli/Data/test/Segmentation/REFUGE2
      resolution: 256
      max_num_instances: 200
      noise_scale: 1.0
      seed: 42
      splits:
      - train
      - val
      - test
  pred_dataset:
    class_path: src.data.dataset.refuge2.REFUGE2RandnDataset
    init_args:
      data_root: /data2/sichengli/Data/test/Segmentation/REFUGE2
      resolution: 256
      max_num_instances: 1000
      noise_scale: 1.0
      seed: 42
      splits:
      - train
      - val
      - test
  train_batch_size: 16
  train_num_workers: 4
  train_prefetch_factor: 8
  eval_batch_size: 32
  eval_num_workers: 4
  pred_batch_size: 16
  pred_num_workers: 1
tags:
  exp: PixelGen_Medical_REFUGE2
ckpt_path: null
weights_only: null