code: def SeaFormer_small(pretrained, **kwags):
      seaformer = SeaFormer(
          pretrained=pretrained,
          cfgs=[
              [[3, 1, 16, 1], [3, 4, 24, 2], [3, 3, 24, 1]],
              [[5, 3, 48, 2], [5, 3, 48, 1]],
              [[3, 3, 96, 2], [3, 3, 96, 1]],
              [[5, 4, 160, 2]],
              [[3, 6, 192, 2]],
          ],
          emb_dims=[160, 192],
          channels=[16, 24, 48, 96, 160, 192],
          depths=[3, 3],
          num_heads=6,
          **kwags,
      )
      seaformer.feat_channels = [48, 160, 192]
  
      return seaformer
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models import layers
  from paddleseg.models.backbones.transformer_utils import DropPath, zeros_, ones_
  from paddleseg.utils import utils
label_desc: Use image node_id 3 for calling a global function with example usage: SeaFormer_small(pretrained) and returns: seaformer