text: # model settings
  model = dict(
      type='SimDis_wNeg',
      backbone=dict(
          type='ResNet',
          depth=18,
          in_channels=3,
          out_indices=[4],  # 0: conv-1, x: stage-x
          norm_cfg=dict(type='SyncBN'),
          zero_init_residual=True),
      neck=dict(
          type='NonLinearNeck',
          in_channels=512,
          hid_channels=1024,
          out_channels=2048,
          num_layers=3,
          with_last_bn_affine=False,
          with_avg_pool=True),
      head=dict(
          type='LatentPredictHead',
          predictor=dict(
              type='NonLinearNeck',
              in_channels=2048,
              hid_channels=512,
              out_channels=2048,
              with_avg_pool=False,
              with_last_bn=False,
              with_last_bias=True)
      ),
      teacher=dict(
                  type='SimSiam',
                  backbone=dict(
                      type='ResNet',
                      depth=50,
                      in_channels=3,
                      out_indices=[4],  # 0: conv-1, x: stage-x
                      norm_cfg=dict(type='SyncBN'),
                      zero_init_residual=True),
                  neck=dict(
                      type='NonLinearNeck',
                      in_channels=2048,
                      hid_channels=2048,
                      out_channels=2048,
                      num_layers=3,
                      with_last_bn_affine=False,
                      with_avg_pool=True),
                  head=dict(
                      type='LatentPredictHead',
                      predictor=dict(
                          type='NonLinearNeck',
                          in_channels=2048,
                          hid_channels=512,
                          out_channels=2048,
                          with_avg_pool=False,
                          with_last_bn=False,
                          with_last_bias=True))
      ))
  