class_docstr: Args:
      in_channels (list): number of input feature channels from backbone
      out_channel (int): number of output feature channels
      share_conv (bool): whether to share conv for different layers' reduction
      extra_stage (int): add extra stage for returning HRFPN fpn_feats
      spatial_scales (list): feature map scaling factor
class_docstr_tok: ["Args",":","in_channels","(","list",")",":","number","of","input","feature","channels","from","backbone","out_channel","(","int",")",":","number","of","output","feature","channels","share_conv","(","bool",")",":","whether","to","share","conv","for","different","layers","'","reduction","extra_stage","(","int",")",":","add","extra","stage","for","returning","HRFPN","fpn_feats","spatial_scales","(","list",")",":","feature","map","scaling","factor"]
code: def out_shape(self):
      return [
          ShapeSpec(channels=self.out_channel, stride=1.0 / s)
          for s in self.spatial_scales
      ]
  
file_path: PaddleDetection/ppdet/modeling/necks/hrfpn.py
imports: import paddle
  import paddle.nn.functional
  import paddle.nn
  from ppdet.core.workspace import register
  from ..shape_spec import ShapeSpec
label_desc: Use image node_id 4 for calling the HRFPN obj's underlying member method code with example usage: obj.out_shape() and returns: unknown