text: _base_ = [
      '../../../_base_/datasets/nway_kshot/few_shot_voc.py',
      '../../../_base_/schedules/schedule.py', '../../fsdetview_r101_c4.py',
      '../../../_base_/default_runtime.py'
  ]
  # classes splits are predefined in FewShotVOCDataset
  # FewShotVOCDefaultDataset predefine ann_cfg for model reproducibility.
  data = dict(
      train=dict(
          save_dataset=True,
          dataset=dict(
              type='FewShotVOCDefaultDataset',
              ann_cfg=[dict(method='FSDetView', setting='SPLIT2_10SHOT')],
              num_novel_shots=10,
              num_base_shots=10,
              classes='ALL_CLASSES_SPLIT2',
          )),
      val=dict(classes='ALL_CLASSES_SPLIT2'),
      test=dict(classes='ALL_CLASSES_SPLIT2'),
      model_init=dict(classes='ALL_CLASSES_SPLIT2'))
  evaluation = dict(
      interval=200, class_splits=['BASE_CLASSES_SPLIT2', 'NOVEL_CLASSES_SPLIT2'])
  checkpoint_config = dict(interval=200)
  optimizer = dict(lr=0.001)
  lr_config = dict(warmup=None)
  runner = dict(max_iters=1000)
  # load_from = 'path of base training model'
  load_from = \
      'work_dirs/fsdetview_r101_c4_8xb4_voc-split2_base-training/latest.pth'
  # model settings
  model = dict(frozen_parameters=[
      'backbone', 'shared_head', 'rpn_head', 'aggregation_layer'
  ])
  