text: # model settings
  norm_cfg = dict(type='SyncBN', requires_grad=True)
  model = dict(
      type='EncoderDecoder',
      backbone=dict(
          type='BiSeNetV1',
          in_channels=3,
          context_channels=(128, 256, 512),
          spatial_channels=(64, 64, 64, 128),
          out_indices=(0, 1, 2),
          out_channels=256,
          backbone_cfg=dict(
              type='ResNet',
              in_channels=3,
              depth=18,
              num_stages=4,
              out_indices=(0, 1, 2, 3),
              dilations=(1, 1, 1, 1),
              strides=(1, 2, 2, 2),
              norm_cfg=norm_cfg,
              norm_eval=False,
              style='pytorch',
              contract_dilation=True),
          norm_cfg=norm_cfg,
          align_corners=False,
          init_cfg=None),
      decode_head=dict(
          type='FCNHead',
          in_channels=256,
          in_index=0,
          channels=256,
          num_convs=1,
          concat_input=False,
          dropout_ratio=0.1,
          num_classes=19,
          norm_cfg=norm_cfg,
          align_corners=False,
          loss_decode=dict(
              type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
      auxiliary_head=[
          dict(
              type='FCNHead',
              in_channels=128,
              channels=64,
              num_convs=1,
              num_classes=19,
              in_index=1,
              norm_cfg=norm_cfg,
              concat_input=False,
              align_corners=False,
              loss_decode=dict(
                  type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
          dict(
              type='FCNHead',
              in_channels=128,
              channels=64,
              num_convs=1,
              num_classes=19,
              in_index=2,
              norm_cfg=norm_cfg,
              concat_input=False,
              align_corners=False,
              loss_decode=dict(
                  type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
      ],
      # model training and testing settings
      train_cfg=dict(),
      test_cfg=dict(mode='whole'))
  