Global:
  checkpoints: null
  pretrained_model: null
  output_dir: ./output
  device: gpu
  save_interval: -1
  eval_during_train: true
  eval_interval: 1
  epochs: 1024
  iter_per_epoch: 1024
  print_batch_step: 20
  use_visualdl: false
  use_dali: false
  train_mode: fixmatch_ccssl
  image_shape: [3, 32, 32]
  save_inference_dir: ./inference

SSL:
  T: 1
  threshold: 0.95

EMA:
  decay: 0.999

Arch:
  name: RecModel
  infer_output_key: logits
  infer_add_softmax: false
  head_feature_from: backbone 
  Backbone:
    name: WideResNet
    widen_factor: 8
    depth: 28
    dropout: 0 
    num_classes: 100
    low_dim: 64
    proj: false
    proj_after: false
  BackboneStopLayer:
    name: bn1
  Neck:
    name: FRFNNeck
    num_features: 512
    low_dim: 64
  Head:
    name: FC
    embedding_size: 512
    class_num: 100

  use_sync_bn: true

Loss:
  Train:
    - CELoss:
        weight: 1.0
        reduction: "mean"
  Eval:
    - CELoss:
        weight: 1.0
  
UnLabelLoss:
  Train:
    - CCSSLCELoss:
        weight: 1.
    - SoftSupConLoss:
        weight: 1.0
        temperature: 0.07

Optimizer:
  name: Momentum
  momentum: 0.9
  use_nesterov: true
  weight_decay: 0.001
  lr:
    name: 'CosineFixmatch'
    learning_rate: 0.03
    num_warmup_steps: 0

DataLoader:
  mean: [0.5071, 0.4867, 0.4408]
  std: [0.2675, 0.2565, 0.2761]
  Train:
    dataset:
      name: Cifar100
      data_file: null
      mode: 'train'
      download: true
      backend: 'pil'
      sample_per_label: 100
      expand_labels: 1
      transform_ops:
        - RandFlipImage:
            flip_code: 1
        - Pad_paddle_vision:
            padding: 4
            padding_mode: reflect
        - RandCropImageV2:
            size: [32, 32]
        - NormalizeImage:
            scale: 1.0/255.0
            mean: [0.5071, 0.4867, 0.4408]
            std: [0.2675, 0.2565, 0.2761]
            order: hwc
    
    sampler:
      name: DistributedBatchSampler
      batch_size: 16
      drop_last: true
      shuffle: true
    loader:
      num_workers: 4
      use_shared_memory: true
  
  UnLabelTrain:
    dataset:
      name: Cifar100
      data_file: null
      mode: 'train'
      backend: 'pil'
      download: true

      transform_ops_weak:
        - RandFlipImage:
            flip_code: 1
        - Pad_paddle_vision:
            padding: 4
            padding_mode: reflect
        - RandCropImageV2:
            size: [32, 32]
        - NormalizeImage:
            scale: 1.0/255.0
            mean: [0.5071, 0.4867, 0.4408]
            std: [0.2675, 0.2565, 0.2761]
            order: hwc

      transform_ops_strong:
        - RandFlipImage:
            flip_code: 1
        - Pad_paddle_vision:
            padding: 4
            padding_mode: reflect
        - RandCropImageV2:
            size: [32, 32]
        - RandAugment:
            num_layers: 2
            magnitude: 10
        - NormalizeImage:
            scale: 1.0/255.0
            mean: [0.5071, 0.4867, 0.4408]
            std: [0.2675, 0.2565, 0.2761]
            order: hwc
      
      transform_ops_strong2:
        - RandomResizedCrop:
            size: [32, 32]
        - RandFlipImage:
            flip_code: 1
        - RandomApply:
            transforms:
              - RawColorJitter:
                  brightness: 0.4
                  contrast: 0.4
                  saturation: 0.4
                  hue: 0.1
            p: 0.8
        - RandomGrayscale:
            p: 0.2
        - NormalizeImage:
            scale: 1.0/255.0
            mean: [0., 0., 0.]
            std: [1., 1., 1.]
            order: hwc


    sampler:
      name: DistributedBatchSampler
      batch_size: 112
      drop_last: true
      shuffle: true
    loader:
      num_workers: 4
      use_shared_memory: true

  Eval:
    dataset:
      name: Cifar100
      mode: 'test'
      backend: 'pil'
      download: true
      data_file: null
      transform_ops:
        - NormalizeImage:
            scale: 1.0/255.0
            mean: [0.5071, 0.4867, 0.4408]
            std: [0.2675, 0.2565, 0.2761]
            order: hwc
    sampler:
      name: DistributedBatchSampler
      batch_size: 16
      drop_last: False
      shuffle: True
    loader:
      num_workers: 4
      use_shared_memory: true

Metric:
  Eval:
    - TopkAcc:
        topk: [1, 5]