code: def _init_weights(self, m):
      if isinstance(m, nn.Linear):
          trunc_normal_init(m.weight, std=0.02)
          if m.bias is not None:
              constant_init(m.bias, value=0)
      elif isinstance(m, (nn.SyncBatchNorm, nn.BatchNorm2D)):
          constant_init(m.weight, value=1.0)
          constant_init(m.bias, value=0)
      elif isinstance(m, nn.Conv2D):
          kaiming_normal_init(m.weight)
          if m.bias is not None:
              constant_init(m.bias, value=0)
  
imports: from functools import partial
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models import layers
  from paddleseg.utils import utils
  from paddleseg.models.backbones.transformer_utils import DropPath, Identity
  from paddleseg.cvlibs.param_init import constant_init, kaiming_normal_init, trunc_normal_init
label_desc: Use image node_id 2 for calling the MLP obj's underlying member method code with example usage: obj._init_weights(m) without return types