data_root: test_tipc/data

batch_size: 1
iters: 10

model:
  type: TransUNet
  backbone:
    type: ResNet
    block_units: [3, 4, 9]
    width_factor: 1
  classifier: seg
  decoder_channels: [256, 128, 64, 16]
  hidden_size: 768
  n_skip: 3
  patches_grid: [14, 14]
  pretrained_path: https://paddleseg.bj.bcebos.com/paddleseg3d/synapse/abdomen/transunet_abdomen_224_224_1_14k_1e-2/transunet_pretrained.zip
  skip_channels: [512, 256, 64, 16]
  attention_dropout_rate: 0.0
  dropout_rate: 0.1
  mlp_dim: 3072
  num_heads: 12
  num_layers: 12
  num_classes: 9
  img_size: 224

train_dataset:
  type: Abdomen
  dataset_root: mini_synapse_dataset
  result_dir: tset_tipc/output
  transforms:
    - type: RandomFlip3D
      flip_axis: [1, 2]
    - type: RandomQuarterTurn3D
      rotate_planes: [[ 1, 2 ]]
    - type: RandomRotation3D
      degrees: 20
      rotate_planes: [[1, 2]]
    - type: Resize3D
      size: [1 ,224, 224]
  mode: train
  num_classes: 9

val_dataset:
  type: Abdomen
  dataset_root: mini_synapse_dataset
  result_dir: test_tipc/output
  num_classes: 9
  transforms:
    - type: Resize3D
      size: [1 ,224, 224]
  mode: test

test_dataset:
  type: Abdomen
  dataset_root: mini_synapse_dataset
  result_dir: test_tipc/output
  num_classes: 9
  transforms:
    - type: Resize3D
      size: [1 ,224, 224]
  mode: test

optimizer:
  type: sgd
  momentum: 0.9
  weight_decay: 1.0e-4

lr_scheduler:
  type: PolynomialDecay
  decay_steps: 13950
  learning_rate: 0.01
  end_lr: 0
  power: 0.9

loss:
  types:
    - type: MixedLoss
      losses:
        - type: CrossEntropyLoss
          weight: Null
        - type: DiceLoss
      coef: [1, 1]
  coef: [1]

export:
  transforms:
    - type: Resize3D
      size: [ 1 ,224, 224 ]
  inference_helper:
    type: InferenceHelper2D
