class_docstr: Args:
      in_channels (int): the channel number of input to CenterNetHead.
      num_classes (int): the number of classes, 1 (MOT17 dataset) by default.
      head_planes (int): the channel number in all head, 256 by default.
      task (str): the type of task for regression, 'tracking' by default.
      loss_weight (dict): the weight of each loss.
      add_ltrb_amodal (bool): whether to add ltrb_amodal branch, False by default.
class_docstr_tok: ["Args",":","in_channels","(","int",")",":","the","channel","number","of","input","to","CenterNetHead",".","num_classes","(","int",")",":","the","number","of","classes",",","1","(","MOT17","dataset",")","by","default",".","head_planes","(","int",")",":","the","channel","number","in","all","head",",","256","by","default",".","task","(","str",")",":","the","type","of","task","for","regression",",","'tracking","'","by","default",".","loss_weight","(","dict",")",":","the","weight","of","each","loss",".","add_ltrb_amodal","(","bool",")",":","whether","to","add","ltrb_amodal","branch",",","False","by","default","."]
code: def forward(
      self,
      feat,
      inputs,
      bboxes=None,
      bbox_inds=None,
      topk_clses=None,
      topk_ys=None,
      topk_xs=None,
  ):
      tracking = self.tracking(feat)
      head_outs = {"tracking": tracking}
      if self.add_ltrb_amodal and "ltrb_amodal" in self.loss_weight:
          ltrb_amodal = self.ltrb_amodal(feat)
          head_outs.update({"ltrb_amodal": ltrb_amodal})
  
      if self.training:
          losses = self.get_loss(inputs, self.loss_weight, head_outs)
          return losses
      else:
          ret = self.generic_decode(
              head_outs, bboxes, bbox_inds, topk_ys, topk_xs
          )
          return ret
  
file_path: PaddleDetection/ppdet/modeling/heads/centertrack_head.py
imports: import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register
  from .centernet_head import ConvLayer
  from ..keypoint_utils import get_affine_transform
label_desc: Use image node_id 3 for calling the CenterTrackHead obj's underlying member method code with example usage: obj.forward(feat, inputs, bboxes, bbox_inds, topk_clses, topk_ys, topk_xs) and returns: losses, ret