code: def __init__(
      self, input_resolution, dim, dim_scale=2, norm_layer=nn.LayerNorm
  ):
      super().__init__()
      self.input_resolution = input_resolution
      self.dim = dim
      self.expand = (
          nn.Linear(dim, 2 * dim, bias_attr=False)
          if dim_scale == 2
          else nn.Identity()
      )
      self.norm = norm_layer(dim // dim_scale)
  
imports: import numpy
  import paddle
  import paddle.nn
  from medicalseg.cvlibs import manager, param_init
  from medicalseg.models.backbones.swin_transformer import SwinTransformerBlock, window_partition
  from medicalseg.utils import load_pretrained_model
label_desc: Use image node_id 1 to create a new PatchExpand object from inherited base classes: nn with example: obj = PatchExpand(input_resolution, dim, dim_scale, norm_layer)