class_docstr: Visual to Semantic adaptation module
code: def __init__(self, in_channels=512, return_mask=False):
      super(V2SAdaptor, self).__init__()
  
      # parameter initialization
      self.in_channels = in_channels
      self.return_mask = return_mask
  
      # output transformation
      self.channel_inter = nn.Linear(
          self.in_channels, self.in_channels, bias_attr=False
      )
      self.channel_bn = nn.BatchNorm1D(self.in_channels)
      self.channel_act = nn.ReLU()
  
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 1 to create a new V2SAdaptor object from inherited base classes: nn with example: obj = V2SAdaptor(in_channels, return_mask)