class_docstr: Generalized Focal Loss network, see https://arxiv.org/abs/2006.04388
  
  Args:
      backbone (object): backbone instance
      neck (object): 'FPN' instance
      head (object): 'PicoHead' instance
class_docstr_tok: ["Generalized","Focal","Loss","network",",","see","https",":","\/\/arxiv.org\/abs\/2006.04388","Args",":","backbone","(","object",")",":","backbone","instance","neck","(","object",")",":","'FPN","'","instance","head","(","object",")",":","'PicoHead","'","instance"]
code: def _forward(self):
      body_feats = self.backbone(self.inputs)
      fpn_feats = self.neck(body_feats)
      head_outs = self.head(fpn_feats, self.export_post_process)
      if self.training or not self.export_post_process:
          return head_outs, None
      else:
          scale_factor = self.inputs["scale_factor"]
          bboxes, bbox_num = self.head.post_process(
              head_outs,
              scale_factor,
              export_nms=self.export_nms,
              nms_cpu=self.nms_cpu,
          )
          return bboxes, bbox_num
  
file_path: PaddleDetection/ppdet/modeling/architectures/picodet.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  from ppdet.core.workspace import register, create
  from .meta_arch import BaseArch
label_desc: Use image node_id 3 for calling the PicoDet obj's underlying member method code with example usage: obj._forward() and returns: head_outs,  None, bboxes,  bbox_num