code: def _forward(self):
      body_feats = self.backbone(self.inputs)
      fpn_feats = self.neck(body_feats)
      head_outs = self.head(fpn_feats, self.inputs["img_whwh"])
  
      if not self.training:
          bbox_pred, bbox_num = self.postprocess(
              head_outs["pred_logits"],
              head_outs["pred_boxes"],
              self.inputs["scale_factor_whwh"],
              self.inputs["ori_shape"],
          )
          return bbox_pred, bbox_num
      else:
          return head_outs
  
file_path: PaddleDetection/ppdet/modeling/architectures/sparse_rcnn.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from ppdet.core.workspace import register, create
  from .meta_arch import BaseArch
label_desc: Use image node_id 3 for calling the SparseRCNN obj's underlying member method code with example usage: obj._forward() and returns: bbox_pred,  bbox_num, head_outs