code: def __init__(self, model_name="ViT-B/32"):
      super().__init__()
      import clip
      from clip.simple_tokenizer import SimpleTokenizer
  
      self.tokenizer = SimpleTokenizer()
      pretrained_model, _ = clip.load(model_name, device="cpu")
      self.clip = pretrained_model
  
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 1 to create a new CLIPTextEncoder object from inherited base classes: nn with example: obj = CLIPTextEncoder(model_name)