class_docstr: Feature extraction in RPN head
  
  Args:
      in_channel (int): Input channel
      out_channel (int): Output channel
class_docstr_tok: ["Feature","extraction","in","RPN","head","Args",":","in_channel","(","int",")",":","Input","channel","out_channel","(","int",")",":","Output","channel"]
code: def forward(self, feats):
      rpn_feats = []
      for feat in feats:
          rpn_feats.append(F.relu(self.rpn_conv(feat)))
      return rpn_feats
  
file_path: PaddleDetection/ppdet/modeling/proposal_generator/rpn_head.py
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.nn.initializer import Normal
  from ppdet.core.workspace import register
  from .anchor_generator import AnchorGenerator
  from .target_layer import RPNTargetAssign
  from .proposal_generator import ProposalGenerator
  from ..cls_utils import _get_class_default_kwargs
label_desc: Use image node_id 2 for calling the RPNFeat obj's underlying member method code with example usage: obj.forward(feats) and returns: rpn_feats