code: def forward(
      self,
      *args,
      input_ids: Optional[torch.LongTensor] = None,
      labels: Optional[torch.LongTensor] = None,
      **kwargs,
  ):
      return super().forward(
          *args, input_ids=input_ids, labels=labels, **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 T5ForCondiditionalGenerationWithHeadsMixin obj's underlying member method code with example usage: obj.forward() and returns: super