| |
| |
| |
| |
| |
| seed_everything: 1234 |
| tags: |
| exp: &exp PixelGen_Medical_REFUGE2 |
|
|
| trainer: |
| default_root_dir: ./medical_workdirs |
| accelerator: auto |
| strategy: auto |
| devices: auto |
| num_nodes: 1 |
| precision: bf16-mixed |
| logger: |
| class_path: lightning.pytorch.loggers.WandbLogger |
| init_args: |
| project: pixelgen_medical_refuge2 |
| name: *exp |
| num_sanity_val_steps: 0 |
| max_steps: 100000 |
| val_check_interval: 10000 |
| check_val_every_n_epoch: null |
| log_every_n_steps: 50 |
| deterministic: null |
| inference_mode: true |
| use_distributed_sampler: false |
| callbacks: |
| - class_path: src.callbacks.model_checkpoint.CheckpointHook |
| init_args: |
| every_n_train_steps: 10000 |
| save_top_k: -1 |
| save_last: true |
| - class_path: src.callbacks.save_images.SaveImagesHook |
| init_args: |
| save_dir: val_samples |
| save_compressed: true |
| plugins: |
| - src.plugins.bd_env.BDEnvironment |
|
|
| model: |
| vae: |
| class_path: src.models.autoencoder.pixel.PixelAE |
| init_args: |
| scale: 1.0 |
| denoiser: |
| class_path: src.models.transformer.JiT_medical.JiTMedical |
| init_args: |
| input_size: 256 |
| patch_size: 16 |
| in_channels: 3 |
| hidden_size: &hidden_dim 768 |
| depth: 12 |
| num_heads: 12 |
| mlp_ratio: 4.0 |
| attn_drop: 0.0 |
| proj_drop: 0.1 |
| num_classes: 1 |
| use_bottleneck: true |
| bottleneck_dim: 128 |
| in_context_len: 32 |
| in_context_start: 4 |
| mask_in_channels: 1 |
| mask_mode: spatial |
| conditioner: |
| class_path: src.models.conditioner.mask_conditioner.MaskConditioner |
| init_args: |
| hidden_size: *hidden_dim |
| in_channels: 1 |
| img_size: 256 |
| null_condition_p: 0.1 |
| diffusion_trainer: |
| class_path: src.diffusion.flow_matching.training_medical.MedicalTrainerSimple |
| init_args: |
| lognorm_t: true |
| P_mean: -0.8 |
| P_std: 0.8 |
| t_eps: 0.05 |
| scheduler: &scheduler src.diffusion.flow_matching.scheduling.LinearScheduler |
| lpips_weight: 0.1 |
| percept_t_threshold: 0.3 |
| null_condition_p: 0.1 |
| diffusion_sampler: |
| class_path: src.diffusion.flow_matching.sampling_medical.EulerSamplerMedical |
| init_args: |
| num_steps: 50 |
| guidance: 2.0 |
| timeshift: 1.0 |
| guidance_interval_min: 0.1 |
| guidance_interval_max: 0.9 |
| scheduler: *scheduler |
| w_scheduler: src.diffusion.flow_matching.scheduling.LinearScheduler |
| guidance_fn: src.diffusion.base.guidance.simple_guidance_fn |
| step_fn: src.diffusion.flow_matching.sampling.ode_step_fn |
| ema_tracker: |
| class_path: src.callbacks.simple_ema.SimpleEMA |
| init_args: |
| decay: 0.9999 |
| optimizer: |
| class_path: torch.optim.AdamW |
| init_args: |
| lr: 1e-4 |
| weight_decay: 0.0 |
|
|
| 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 |
| 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 |
| 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 |
| train_batch_size: 16 |
| train_num_workers: 4 |
| pred_batch_size: 16 |
| pred_num_workers: 1 |
|
|
