code: def arrange_targets(self, tensor_dict):
      has_answer = tensor_dict["has_answer"]
      if not self.is_kd:
          (
              _,
              _,
              _,
              _,
              _,
              _,
              answer_start_idx,
              answer_end_idx,
          ) = tensor_dict["squad_input"]
          return answer_start_idx, answer_end_idx, has_answer
      else:
          (
              _,
              _,
              _,
              _,
              _,
              _,
              answer_start_idx,
              answer_end_idx,
              start_logits,
              end_logits,
              has_answer_logits,
          ) = tensor_dict["squad_input"]
          return (
              answer_start_idx,
              answer_end_idx,
              has_answer,
              start_logits,
              end_logits,
              has_answer_logits,
          )
  
imports: from typing import Dict, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from pytext.data.squad_tensorizer import SquadTensorizer
  from pytext.data.tensorizers import LabelTensorizer, Tensorizer
  from pytext.data.utils import Vocabulary
  from pytext.models.decoders.mlp_decoder import MLPDecoder
  from pytext.models.embeddings import WordEmbedding
  from pytext.models.model import BaseModel
  from pytext.models.module import create_module
  from pytext.models.output_layers.squad_output_layer import SquadOutputLayer
  from pytext.models.representations.attention import DotProductSelfAttention, MultiplicativeAttention, SequenceAlignedAttention
  from pytext.models.representations.pooling import SelfAttention
  from pytext.models.representations.stacked_bidirectional_rnn import StackedBidirectionalRNN
  from pytext.utils.usage import log_class_usage
label_desc: Use image node_id 5 for calling the DrQAModel obj's underlying member method code with example usage: obj.arrange_targets(tensor_dict) and returns: answer_start_idx,  answer_end_idx,  has_answer, answer_start_idx,  answer_end_idx,  has_answer,  start_logits,  end_logits,  has_answer_logits