code: def __init__(self, ham_channels=512, num_groups=32, ham_kwargs=None):
      super().__init__()
      self.ham_in = nn.Conv2D(ham_channels, ham_channels, kernel_size=1)
  
      self.ham = NMF2D(ham_kwargs)
  
      self.ham_out = ConvGNAct(
          ham_channels,
          ham_channels,
          kernel_size=1,
          num_groups=num_groups,
          bias_attr=False,
      )
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.models.backbones.mscan import MSCAN
  from paddleseg.models.layers import NMF2D, ConvGNAct
  from paddleseg.utils import utils
label_desc: Use image node_id 1 to create a new Hamburger object from inherited base classes: nn with example: obj = Hamburger(ham_channels, num_groups, ham_kwargs)