text: _base_ = [
      '../_base_/models/ocrnet_hr18.py',
      '../_base_/datasets/cityscapes.py',
      '../_base_/default_runtime.py', 
      '../_base_/schedules/schedule_40k.py'
  ]
  # load_from="/home/yuhui/teamdrive/yuyua/code/segmentation/mmsegmentation-logs/ocrnet_hr48_1024x1024_640k_b8_rmi_mapillary/iter_640000.pth"
  # load_from='hrnet_ocr_mapillary_524.pth'
  norm_cfg = dict(type='SyncBN', requires_grad=True)
  model = dict(
      backbone=dict(
          extra=dict(
              stage2=dict(num_channels=(48, 96)),
              stage3=dict(num_channels=(48, 96, 192)),
              stage4=dict(num_channels=(48, 96, 192, 384)))),
      decode_head=[
          dict(
              type='FCNHead',
              in_channels=[48, 96, 192, 384],
              channels=sum([48, 96, 192, 384]),
              in_index=(0, 1, 2, 3),
              input_transform='resize_concat',
              kernel_size=1,
              num_convs=1,
              concat_input=False,
              dropout_ratio=-1,
              num_classes=19,
              norm_cfg=norm_cfg,
              align_corners=True,
              loss_decode=dict(
                  type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
          dict(
              type='OCRHead',
              in_channels=[48, 96, 192, 384],
              in_index=(0, 1, 2, 3),
              input_transform='resize_concat',
              channels=512,
              ocr_channels=256,
              dropout_ratio=0.1,
              num_classes=19,
              norm_cfg=norm_cfg,
              align_corners=True,
              loss_decode=dict(
                  type='RMILoss', num_classes=19, loss_weight=1.0))
      ]
  )
  optimizer = dict(lr=0.002)
  lr_config = dict(min_lr=2e-5)
  data = dict(samples_per_gpu=2, workers_per_gpu=2)
  