class_docstr: Split to two transformer header at the last layer.
  Cls_layer is used to structure token classification.
  Bbox_layer is used to regress bbox coord.
code: def forward(self, feat, targets=None):
      feat = feat[-1]
      b, c, h, w = feat.shape
      feat = feat.reshape([b, c, h * w])  # flatten 2D feature map
      feat = feat.transpose((0, 2, 1))
      out_enc = self.positional_encoding(feat)
      if self.training:
          return self.forward_train(out_enc, targets)
  
      return self.forward_test(out_enc)
  
imports: import copy
  import math
  import paddle
  from paddle import nn
  from paddle.nn import functional
label_desc: Use image node_id 7 for calling the TableMasterHead obj's underlying member method code with example usage: obj.forward(feat, targets) and returns: self, self