text: _base_ = [
      './cascade_mask_rcnn_r50_fpn_1x_coco.py'
  ]
  
  model = dict(
      backbone=dict(
          type='DetectoRS_ResNet',
          conv_cfg=dict(type='ConvAWS'),
          sac=dict(type='SAC', use_deform=True),
          stage_with_sac=(False, True, True, True),
          output_img=True),
      neck=dict(
          type='RFP',
          rfp_steps=2,
          aspp_out_channels=64,
          aspp_dilations=(1, 3, 6, 1),
          rfp_backbone=dict(
              rfp_inplanes=256,
              type='DetectoRS_ResNet',
              depth=50,
              num_stages=4,
              out_indices=(0, 1, 2, 3),
              frozen_stages=1,
              norm_cfg=dict(type='BN', requires_grad=True),
              norm_eval=True,
              conv_cfg=dict(type='ConvAWS'),
              sac=dict(type='SAC', use_deform=True),
              stage_with_sac=(False, True, True, True),
              pretrained='torchvision://resnet50',
              style='pytorch')))
  