data:
  name: muscle_us
  loader:
    max_num_samples_per_split: -1
    patch_shape:
      - 480
      - 512
    patch_overlap:
      - 0
      - 0
    data_augmentation:
      max_rotation: 30
      max_zoom: 0.2
      max_shear: 30
      max_shift: 0.3
      max_log_gamma: 0.3
      v_min: 0.0
      v_max: 1.0
      p: 0.5
  trainer:
    max_num_samples: 512000
    batch_size: 64
    batch_size_per_replica: 8
    num_devices_per_replica: 1
  patch_size:
    - 2
    - 2
  scale_factor:
    - 2
    - 2
task:
  name: segmentation
  model:
    _target_: imgx.model.Unet
    remat: true
    num_spatial_dims: 2
    patch_size:
      - 2
      - 2
    scale_factor:
      - 2
      - 2
    num_res_blocks: 2
    num_channels:
      - 8
      - 16
      - 32
      - 64
    out_channels: 2
    num_heads: 8
    widening_factor: 4
    num_transform_layers: 1
    dropout: 0.1
  loss:
    dice: 1.0
    cross_entropy: 0.0
    focal: 1.0
  early_stopping:
    metric: mean_binary_dice_score_without_background
    mode: max
    min_delta: 0.0001
    patience: 10
debug: false
seed: 0
half_precision: true
optimizer:
  name: adamw
  kwargs:
    b1: 0.9
    b2: 0.999
    weight_decay: 1.0e-08
  grad_norm: 1.0
  lr_schedule:
    warmup_steps: 100
    decay_steps: 10000
    init_value: 1.0e-05
    peak_value: 0.0008
    end_value: 5.0e-05
logging:
  root_dir: null
  log_freq: 10
  save_freq: 100
  wandb:
    project: imgx
    entity: entity