class_docstr: Adds adapters to the BartDecoder module of BART.
code: def forward(
      self,
      input_ids: torch.LongTensor = None,
      encoder_hidden_states: Optional[torch.FloatTensor] = None,
      **kwargs,
  ):
      (input_ids,) = adjust_tensors_for_parallel(
          encoder_hidden_states, input_ids
      )
      return super().forward(
          input_ids=input_ids,
          encoder_hidden_states=encoder_hidden_states,
          **kwargs,
      )
  
imports: from typing import Iterable, Optional, Tuple
  import torch
  import torch.nn
  from ...composition import adjust_tensors_for_parallel
  from ...methods.bottleneck import BottleneckLayer
  from ...methods.lora import LoRALinear
  from ...methods.prefix_tuning import PrefixTuningLayer
  from ...model_mixin import EmbeddingAdaptersMixin, EmbeddingAdaptersWrapperMixin, InvertibleAdaptersMixin, InvertibleAdaptersWrapperMixin, ModelBaseAdaptersMixin
label_desc: Use image node_id 1 for calling the BartDecoderAdaptersMixin obj's underlying member method code with example usage: obj.forward(input_ids, encoder_hidden_states) and returns: super