code: def test_tokenizer(self, falcon_gpt_model, test_text):
      assert isinstance(falcon_gpt_model.tokenizer, AutoTokenizer)
      assert (
          falcon_gpt_model.tokenizer.name == "PreTrainedTokenizerFast"
      )
      assert falcon_gpt_model.tokenizer.vocab_size == 65024
  
      ids = [
          falcon_gpt_model.tokenizer.text_to_ids(text)
          for text in test_text
      ]
  
      true_ids = [
          [30835, 23, 1079],
          [18584, 5179, 273, 5144, 909, 2323],
          [4560, 601, 304, 3991],
          [1424, 299, 889, 4258, 2400, 276, 20201, 986],
      ]
      assert (
          sum(
              [
                  id_list == true_id_list
                  for id_list, true_id_list in zip(ids, true_ids)
              ]
          )
          == 4
      )
  
file_path: NeMo/tests/collections/nlp/test_falcon_model.py
imports: import pytest
  import torch
  from omegaconf import DictConfig
  from pytorch_lightning import Trainer
  from nemo.collections.common.tokenizers.huggingface.auto_tokenizer import AutoTokenizer
  from nemo.collections.nlp.models.language_modeling.megatron_gpt_model import MegatronGPTModel
  from nemo.collections.nlp.modules.common.megatron.utils import get_ltor_masks_and_position_ids
  from nemo.collections.nlp.parts.nlp_overrides import NLPDDPStrategy
label_desc: Use image node_id 2 for calling the TestFalconGPTModel obj's underlying member method code with example usage: obj.test_tokenizer(falcon_gpt_model, test_text) without return types