code: def init_weight(self):
      super().init_weight()
      for p in self.parameters():
          if p.dim() > 1:
              param_init.xavier_uniform(p)
      for m in self.sublayers():
          if isinstance(m, MSDeformAttn):
              m.init_weight()
      param_init.normal_init(self.level_embed)
  
imports: import copy
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import param_init
  from paddlepanseg.models.param_init import c2_xavier_fill, THLinearInitMixin
  from .common import Conv2D, PositionEmbeddingSine
  from ._ms_deform_attn import MSDeformAttn
label_desc: Use image node_id 2 for calling the MSDeformAttnTransformerEncoderOnly obj's underlying member method code with example usage: obj.init_weight() without return types