code: def test_transformer_encoder_forward(self):
      encoder = encoders.TransformerEncoder.from_params()
      self.assertEqual(
          encoder.embeddings.word_embeddings.weight.size(1), 768
      )
      self.assertEqual(
          encoder.embeddings.word_embeddings.weight.size(0), 30522
      )
      text_ids = torch.randint(
          encoder.embeddings.word_embeddings.weight.size(0), (2, 16)
      )
      text_embeddings = encoder(text_ids)
  
      text_embeddings_cls = encoder(text_ids)
      self.assertEqual(text_embeddings_cls.dim(), 2)
      self.assertEqual(list(text_embeddings_cls.size()), [2, 768])
  
      text_embeddings = encoder(text_ids, return_sequence=True)
      self.assertEqual(text_embeddings.dim(), 3)
      self.assertEqual(list(text_embeddings.size()), [2, 16, 768])
  
imports: import tempfile
  import unittest
  import torch
  from mmf.modules import encoders
  from omegaconf import OmegaConf
  from tests.test_utils import setup_proxy, skip_if_no_pytorchvideo, skip_if_old_transformers
  from torch import nn
label_desc: Use image node_id 9 for calling the TestEncoders obj's underlying member method code with example usage: obj.test_transformer_encoder_forward() without return types