text: _base_ = './pspnet_r50-d8_40kx32_coco.py'
  model = dict(
      pretrained='data/models/res2net101_v1b_26w_4s-0812c246.pth',
      backbone=dict(
          type='Res2Net',
          layers=[3, 4, 23, 3],
          out_indices=(0, 1, 2, 3),
          strides=(1, 2, 1, 1),
          dilations=(1, 1, 2, 4),
          norm_eval=False),
      decode_head=dict(
          loss_decode=dict(pus_type='clamp', pus_beta=0.8, pus_k=0.8)),
      auxiliary_head=dict(
          loss_decode=dict(pus_type='clamp', pus_beta=0.8, pus_k=0.8))
  )
  