code: def test_forward_runs(bimodal_encoder, params_dict):
      embedding1 = torch.randn(16, 34, params_dict["hidden_size1"])
      embedding2 = torch.randn(16, 2, params_dict["hidden_size2"])
      attn_mask1 = torch.randint(0, 2, (16, 1, 1, 34)) == 1
      attn_mask2 = torch.randint(0, 2, (16, 1, 1, 2)) == 1
      bimodal_encoder(embedding1, embedding2, attn_mask1, attn_mask2)
  
file_path: allennlp/tests/modules/transformer/bimodal_encoder_test.py
imports: import torch
  from torch.testing import assert_allclose
  from transformers import AutoModel
  import pytest
  from allennlp.common import Params
  from allennlp.modules.transformer import BiModalEncoder
label_desc: Use image node_id 5 for calling a global function with example usage: test_forward_runs(bimodal_encoder, params_dict) without return types