code: def test_clip_tokenizer():
      opts = Namespace()
  
      setattr(
          opts,
          "text_tokenizer.clip.merges_path",
          "http://download.pytorch.org/models/text/clip_merges.bpe",
      )
      setattr(
          opts,
          "text_tokenizer.clip.encoder_json_path",
          "http://download.pytorch.org/models/text/clip_encoder.json",
      )
  
      tokenizer = ClipTokenizer(opts=opts)
      out = tokenizer("the quick brown fox jumped over the lazy dog")
  
      expected_data = [
          49406,  # Start token
          518,
          3712,
          2866,
          3240,
          16901,
          962,
          518,
          10753,
          1929,
          49407,  # end token
      ]
      expected_out = torch.tensor(expected_data, dtype=out.dtype)
      torch.testing.assert_close(actual=out, expected=expected_out)
  
imports: import sys
  from argparse import Namespace
  import torch
  from data.text_tokenizer.clip_tokenizer import ClipTokenizer
label_desc: Use image node_id 1 for calling a global function with example usage: test_clip_tokenizer() without return types