class_docstr: DLA, see https://arxiv.org/pdf/1707.06484.pdf
  
  Args:
      depth (int): DLA depth, only support 34 now.
      residual_root (bool): whether use a reidual layer in the root block
      pre_img (bool): add pre_img, only used in CenterTrack
      pre_hm (bool): add pre_hm, only used in CenterTrack
class_docstr_tok: ["DLA",",","see","https",":","\/\/arxiv.org\/pdf\/1707.06484.pdf","Args",":","depth","(","int",")",":","DLA","depth",",","only","support","34","now",".","residual_root","(","bool",")",":","whether","use","a","reidual","layer","in","the","root","block","pre_img","(","bool",")",":","add","pre_img",",","only","used","in","CenterTrack","pre_hm","(","bool",")",":","add","pre_hm",",","only","used","in","CenterTrack"]
code: def forward(self, inputs):
      outs = []
      feats = self.base_layer(inputs["image"])
  
      if (
          self.pre_img
          and "pre_image" in inputs
          and inputs["pre_image"] is not None
      ):
          feats = feats + self.pre_img_layer(inputs["pre_image"])
  
      if (
          self.pre_hm
          and "pre_hm" in inputs
          and inputs["pre_hm"] is not None
      ):
          feats = feats + self.pre_hm_layer(inputs["pre_hm"])
  
      for i in range(self.num_levels):
          feats = getattr(self, "level{}".format(i))(feats)
          outs.append(feats)
  
      return outs
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register, serializable
  from ppdet.modeling.layers import ConvNormLayer
  from ..shape_spec import ShapeSpec
label_desc: Use image node_id 4 for calling the DLA obj's underlying member method code with example usage: obj.forward(inputs) and returns: outs