# SimCortex segmentation training config

dataset:
  # Single-dataset mode:
  #   set path to one derivative root and keep roots as null/empty.
  # Multi-dataset mode:
  #   keep path null and define roots below.
  path: null

  # Combined split CSV. In multi-dataset mode it must contain:
  #   subject, split, dataset
  split_file: /path/to/datasets/splits/dataset_split.csv

  roots:
    HCP_YA: /path/to/datasets/hcpya-u100/derivatives/sc-preproc
    OASIS1: /path/to/datasets/oasis-1/derivatives/sc-preproc

  train_split: train
  val_split: val
  session_label: "01"
  space: "MNI152"

  pad_mult: 16

  augment: true

model:
  in_channels: 1
  out_channels: 9

  features: [16, 32, 64, 128, 128]
  norm: instance   
  dropout: 0.10    

trainer:
  batch_size: 2
  num_workers: 4

  device: cuda:0
  use_ddp: true   
  data_parallel: false

  seed: 12345
  deterministic: false

  num_epochs: 1000
  validation_interval: 5

  optimizer: adamw
  learning_rate: 1.0e-4
  weight_decay: 1.0e-5

  dice_weight: 1.0
  dice_exclude_bg: true
  dice_ignore_absent_target_classes: true
  ce_class_weights: null

  amp: true

  grad_clip_norm: 1.0

  scheduler:
    name: cosine
    eta_min: 1.0e-6

  save_interval: 25
  keep_last_n_checkpoints: 3

  early_stop_patience: 30

  resume_from: null

outputs:
  root: /path/to/simcortex-runs/seg/exp01_hcpya+oasis1
  log_dir:  ${outputs.root}/logs_train
  ckpt_dir: ${outputs.root}/checkpoints


hydra:
  run:
    dir: ${outputs.log_dir}
  output_subdir: null
  job:
    chdir: false