code: def forward(self, text):
      text = self.tokenize(text)
      text_features = self.clip.encode_text(text)
      return text_features
  
imports: import copy
  from typing import List, Union
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from mmengine.logging import print_log
  from torch import Tensor
  from mmdet.datasets import LVISV1Dataset
  from mmdet.models.detectors.cascade_rcnn import CascadeRCNN
  from mmdet.registry import MODELS
  from mmdet.structures import SampleList
label_desc: Use image node_id 5 for calling the CLIPTextEncoder obj's underlying member method code with example usage: obj.forward(text) and returns: text_features