class_docstr: Semantic to Visual adaptation module
code: def init_weights(self, m):
      if isinstance(m, nn.Conv2D):
          kaiming_init_(m.weight)
          if isinstance(m, nn.Conv2D) and m.bias is not None:
              zeros_(m.bias)
      elif isinstance(
          m, (nn.BatchNorm, nn.BatchNorm2D, nn.BatchNorm1D)
      ):
          zeros_(m.bias)
          ones_(m.weight)
  
file_path: PaddleOCR/ppocr/modeling/necks/rf_adaptor.py
imports: import paddle
  import paddle.nn
  from paddle.nn.initializer import TruncatedNormal, Constant, Normal, KaimingNormal
label_desc: Use image node_id 2 for calling the S2VAdaptor obj's underlying member method code with example usage: obj.init_weights(m) without return types