includes:
  - headers/data.yaml
  - headers/device.yaml
  # - headers/model.yaml
  # - headers/optimizer.yaml
  # - backbones/resnet12.yaml

warmup: 0


dataset: &dataset 5-datasets
data_root: /data/Dataset/5-dataset
class_order: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
              10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
              20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
              30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
              40, 41, 42, 43, 44, 45, 46, 47, 48, 49]
testing_times: 1

save_path: ./
# data
init_cls_num: 10
inc_cls_num: 10
task_num: 5


batch_size: 128

init_epoch: 1  #100
epoch: 1  #100
 
device_ids: 2
n_gpu: 1
val_per_epoch: 1


optimizer:
  name: SGD
  kwargs:
    lr: 0.1
    momentum: 0.9
    weight_decay: 0.0005

lr_scheduler:
  name: CosineAnnealingLR
  kwargs:
    T_max: 100


backbone:
  name: cifar_resnet32
  kwargs:
    num_classes: 100
    args: 
      dataset: cifar100


buffer:
  name: LinearHerdingBuffer
  kwargs:
    buffer_size: 2000
    batch_size: 64
    # strategy: herding     # random, equal_random, reservoir, herding

classifier:
  name: ICarl
  kwargs:
    num_class: 50
    feat_dim: 64
    init_cls_num: 10
    inc_cls_num: 10
    task_num: 5