# Basic configurations of SVCD dataset

datasets:
    train: !Node
        type: CDDataset
        args: 
            data_dir: ./data/svcd/
            file_list: ./data/svcd/train.txt
            label_list: null
            num_workers: 2
            shuffle: True
            with_seg_labels: False
            binarize_labels: True
    eval: !Node
        type: CDDataset
        args:
            data_dir: ./data/svcd/
            file_list: ./data/svcd/val.txt
            label_list: null
            num_workers: 0
            shuffle: False
            with_seg_labels: False
            binarize_labels: True
transforms:
    train:
        - !Node
          type: DecodeImg
        - !Node
          type: RandomFlipOrRotate
          args:
            probs: [0.35, 0.35]
            probsf: [0.5, 0.5, 0, 0, 0]
            probsr: [0.33, 0.34, 0.33]
        - !Node
          type: Normalize
          args:
            mean: [0.5, 0.5, 0.5]
            std: [0.5, 0.5, 0.5]
        - !Node
          type: ArrangeChangeDetector
          args: ['train']
    eval:
        - !Node
          type: DecodeImg
        - !Node
          type: Normalize
          args:
            mean: [0.5, 0.5, 0.5]
            std: [0.5, 0.5, 0.5]
        - !Node
          type: ArrangeChangeDetector
          args: ['eval']
download_on: False

num_epochs: 200
train_batch_size: 8
optimizer: !Node
    type: Adam
    args:
        learning_rate: !Node
            type: StepDecay
            module: paddle.optimizer.lr
            args:
                learning_rate: 0.0004
                step_size: 87500
                gamma: 0.1
save_interval_epochs: 20
log_interval_steps: 50
save_dir: ./exp/
learning_rate: 0.0004
early_stop: False
early_stop_patience: 5
use_vdl: True
resume_checkpoint: ''