code: def forward(self, x):
      visual_feature, rcg_feature = x
      if visual_feature is not None:
          (
              batch,
              source_channels,
              v_source_height,
              v_source_width,
          ) = visual_feature.shape
          visual_feature = visual_feature.reshape(
              [
                  batch,
                  source_channels,
                  1,
                  v_source_height * v_source_width,
              ]
          )
  
      if self.neck_v2s is not None:
          v_rcg_feature = rcg_feature * self.neck_v2s(visual_feature)
      else:
          v_rcg_feature = rcg_feature
  
      if self.neck_s2v is not None:
          v_visual_feature = visual_feature + self.neck_s2v(rcg_feature)
      else:
          v_visual_feature = visual_feature
      if v_rcg_feature is not None:
          (
              batch,
              source_channels,
              source_height,
              source_width,
          ) = v_rcg_feature.shape
          v_rcg_feature = v_rcg_feature.reshape(
              [batch, source_channels, 1, source_height * source_width]
          )
  
          v_rcg_feature = v_rcg_feature.squeeze(2).transpose([0, 2, 1])
      return v_visual_feature, v_rcg_feature
  
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 RFAdaptor obj's underlying member method code with example usage: obj.forward(x) and returns: v_visual_feature,  v_rcg_feature