text: _base_ = 'coco_instance.py'
  dataset_type = 'LVISV1Dataset'
  data_root = 'data/lvis_v1/'
  data = dict(
      samples_per_gpu=2,
      workers_per_gpu=2,
      train=dict(
          _delete_=True,
          type='ClassBalancedDataset',
          oversample_thr=1e-3,
          dataset=dict(
              type=dataset_type,
              ann_file=data_root + 'annotations/lvis_v1_train.json',
              img_prefix=data_root)),
      val=dict(
          type=dataset_type,
          ann_file=data_root + 'annotations/lvis_v1_val.json',
          img_prefix=data_root),
      test=dict(
          type=dataset_type,
          ann_file=data_root + 'annotations/lvis_v1_val.json',
          img_prefix=data_root))
  evaluation = dict(metric=['bbox', 'segm'])
  