class_docstr: Test MMT model
code: def test_mmt_txt(self):
      batch_size = 8
  
      class MockBert(nn.Module):
          """
          Mock BERT model in transformers
          """
  
          def __init__(self, hidden_size):
              super().__init__()
              self.hidden_size = hidden_size
  
              class Struct:
                  def __init__(self, **entries):
                      self.__dict__.update(entries)
  
              config = Struct(**{"hidden_size": hidden_size})
              self.config = config
  
          def forward(self, **kwargs):
              x = kwargs["input_ids"]
              return torch.rand(
                  x.shape[0], x.shape[1], self.hidden_size
              ), torch.rand(x.shape[0], self.hidden_size)
  
      class MockTokenizer:
          """
          Mock tokenizer in transformers
          """
  
          def __init__(self, vocab_size):
              self.vocab_size = vocab_size
  
          def __call__(
              self,
              text,
              max_length=30,
              truncation=True,
              add_special_tokens=None,
              padding=True,
              return_tensors="pt",
          ):
              print("tokenize text:", text)
  
              return {
                  "input_ids": torch.randint(
                      low=0,
                      high=self.vocab_size,
                      size=(
                          batch_size,
                          max_length,
                      ),
                  )
              }
  
      mmttxt_model = MMTTXT(
          txt_bert=MockBert(hidden_size=768),
          tokenizer=MockTokenizer(vocab_size=100),
          max_length=30,
          modalities=["CLIP", "tf_vggish"],
          add_special_tokens=True,
          add_dot=True,
          same_dim=512,
          dout_prob=0.2,
      )
      output = mmttxt_model(["hello world", "how are you"])
      self.assertTrue(output.shape == (batch_size, 1024))
  
imports: import unittest
  import torch
  from torch import nn
  from towhee.models.mdmmt.mmt import MMTVID, MMTTXT
label_desc: Use image node_id 2 for calling the TestMMT obj's underlying member method code with example usage: obj.test_mmt_txt() and returns: torch,  torch, dict