class_docstr: Use Transformer to fuse different models' features (single-modal and multimodal).
  Specifically, it adapts the features of each model to specified dimensions,
  concatenates the adapted features, and fuses the features through Transformer.
class_docstr_tok: ["Use","Transformer","to","fuse","different","models","'","features","(","single-modal","and","multimodal",")",".","Specifically",",","it","adapts","the","features","of","each","model","to","specified","dimensions",",","concatenates","the","adapted","features",",","and","fuses","the","features","through","Transformer","."]
code: def label_key(self):
      return f"{self.prefix}_{LABEL}"
  
file_path: autogluon/multimodal/src/autogluon/multimodal/models/fusion/fusion_transformer.py
imports: import logging
  from typing import Optional
  import torch
  from torch import nn
  from ...constants import AUTOMM, FEATURES, LABEL, LOGITS, WEIGHT
  from ..custom_transformer import CLSToken, Custom_Transformer
  from ..utils import init_weights, run_model
  from .base import AbstractMultimodalFusionModel
label_desc: Use image node_id 2 for calling the MultimodalFusionTransformer obj's underlying member method code with example usage: obj.label_key() and returns: self, str, LABEL