code: def SeaFormer_tiny(pretrained, **kwags):
      seaformer = SeaFormer(
          pretrained=pretrained,
          cfgs=[
              [[3, 1, 16, 1], [3, 4, 16, 2], [3, 3, 16, 1]],
              [[5, 3, 32, 2], [5, 3, 32, 1]],
              [[3, 3, 64, 2], [3, 3, 64, 1]],
              [[5, 3, 128, 2]],
              [[3, 6, 160, 2]],
          ],
          emb_dims=[128, 160],
          channels=[16, 16, 32, 64, 128, 160],
          depths=[2, 2],
          num_heads=4,
          **kwags,
      )
      seaformer.feat_channels = [32, 128, 160]
  
      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 2 for calling a global function with example usage: SeaFormer_tiny(pretrained) and returns: seaformer