code: def forward(self, sample_list):
      text_embedding_total = self.process_text_embedding(sample_list)
      text_embedding_total = text_embedding_total.new_zeros(
          text_embedding_total.size()
      )
  
      fa_txt = self.image_text_multi_modal_combine_layer.module.fa_txt
      dropout = self.image_text_multi_modal_combine_layer.module.dropout
  
      joint_embedding = dropout(fa_txt(text_embedding_total))
  
      linear_text = self.classifier.module.linear_text
      f_o_text = self.classifier.module.f_o_text
      scores = linear_text(f_o_text(joint_embedding))
  
      model_output = {"scores": scores}
  
      return model_output
  
imports: import copy
  import omegaconf
  import torch
  from mmf.common.registry import registry
  from mmf.models.base_model import BaseModel
  from mmf.modules.embeddings import ImageFeatureEmbedding, MultiHeadImageFeatureEmbedding, PreExtractedEmbedding, TextEmbedding
  from mmf.modules.layers import ClassifierLayer, ModalCombineLayer
  from mmf.utils.build import build_image_encoder
  from torch import nn
label_desc: Use image node_id 2 for calling the PythiaQuestionOnly obj's underlying member method code with example usage: obj.forward(sample_list) and returns: model_output