code: def forward(
      self,
      *args,
      input_ids: Optional[torch.LongTensor] = None,
      start_positions: Optional[torch.LongTensor] = None,
      end_positions: Optional[torch.LongTensor] = None,
      **kwargs,
  ):
      return super().forward(
          *args,
          input_ids=input_ids,
          start_positions=start_positions,
          end_positions=end_positions,
          **kwargs,
      )
  
imports: from typing import Iterable, Optional, Tuple
  import torch
  import torch.nn
  from ...methods.bottleneck import BottleneckLayer
  from ...methods.lora import LoRALinear
  from ...methods.prefix_tuning import PrefixTuningLayer
  from ...model_mixin import EmbeddingAdaptersMixin, InvertibleAdaptersMixin, InvertibleAdaptersWrapperMixin, ModelBaseAdaptersMixin, ModelWithHeadsAdaptersMixin
label_desc: Use image node_id 1 for calling the T5ForQuestionAnsweringWithHeadsMixin obj's underlying member method code with example usage: obj.forward() and returns: super