code: def forward(
      self, hidden_states1, input_tensor1, hidden_states2, input_tensor2
  ):
      hidden_states1 = self.bert_output1(hidden_states1, input_tensor1)
      hidden_states2 = self.bert_output2(hidden_states2, input_tensor2)
  
      return hidden_states1, hidden_states2
  
file_path: allennlp/allennlp/modules/transformer/bimodal_connection_layer.py
imports: from allennlp.common import FromParams
  from allennlp.modules.transformer.activation_layer import ActivationLayer
  from allennlp.modules.transformer.output_layer import OutputLayer
  from allennlp.modules.transformer.bimodal_attention import BiModalAttention
  from allennlp.modules.transformer.transformer_module import TransformerModule
label_desc: Use image node_id 2 for calling the BiModalOutput obj's underlying member method code with example usage: obj.forward(hidden_states1, input_tensor1, hidden_states2, input_tensor2) and returns: hidden_states1,  hidden_states2