code: def forward(self, list_of_text):
      return torch.randn(len(list_of_text), 32)
  
imports: import os
  import unittest
  import uuid
  import faiss
  import torch
  import torchvision
  from torchvision import datasets, transforms
  from pytorch_metric_learning.utils.inference import InferenceModel
  from ..None import TEST_DEVICE
label_desc: Use image node_id 1 for calling the TextModel obj's underlying member method code with example usage: obj.forward(list_of_text) and returns: torch