text: _base_ = [
      '../_base_/models/faster_rcnn_r50_fpn.py', '../_base_/datasets/voc0712.py',
      '../_base_/default_runtime.py'
  ]
  model = dict(roi_head=dict(bbox_head=dict(num_classes=20)))
  
  CLASSES = ('aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car',
             'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse', 'motorbike',
             'person', 'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor')
  
  # dataset settings
  dataset_type = 'CocoDataset'
  data_root = '/home/amax/VOCdevkit/'
  img_norm_cfg = dict(
      mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
  train_pipeline = [
      dict(type='LoadImageFromFile'),
      dict(type='LoadAnnotations', with_bbox=True),
      dict(type='Resize', img_scale=(1000, 600), keep_ratio=True),
      dict(type='RandomFlip', flip_ratio=0.5),
      dict(type='Normalize', **img_norm_cfg),
      dict(type='Pad', size_divisor=32),
      dict(type='DefaultFormatBundle'),
      dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']),
  ]
  test_pipeline = [
      dict(type='LoadImageFromFile'),
      dict(
          type='MultiScaleFlipAug',
          img_scale=(1000, 600),
          flip=False,
          transforms=[
              dict(type='Resize', keep_ratio=True),
              dict(type='RandomFlip'),
              dict(type='Normalize', **img_norm_cfg),
              dict(type='Pad', size_divisor=32),
              dict(type='ImageToTensor', keys=['img']),
              dict(type='Collect', keys=['img']),
          ])
  ]
  data = dict(
      samples_per_gpu=4,
      workers_per_gpu=2,
      train=dict(
          type='RepeatDataset',
          times=1,
          dataset=dict(
              type=dataset_type,
              ann_file=data_root+'voc0712_trainval.json',
              img_prefix=data_root,
              pipeline=train_pipeline,
              classes=CLASSES)),
      val=dict(
          type=dataset_type,
          ann_file=data_root+'voc07_test.json',
          img_prefix=data_root,
          pipeline=test_pipeline,
          classes=CLASSES),
      test=dict(
          type=dataset_type,
          ann_file=data_root+'voc07_test.json',
          img_prefix=data_root,
          pipeline=test_pipeline,
          classes=CLASSES))
  evaluation = dict(interval=1, metric='bbox')
  
  # optimizer
  optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)
  optimizer_config = dict(grad_clip=None)
  # learning policy
  # actual epoch = 3 * 3 = 9
  lr_config = dict(policy='step', step=[8,11])
  # runtime settings
  runner = dict(
      type='EpochBasedRunner', max_epochs=12)  # actual epoch = 4 * 3 = 12
  