class_docstr: This is a generic tokenizer class that will be instantiated as one of the tokenizer classes of the library when
  created with the [`AutoTokenizer.from_pretrained`] class method.
  
  This class cannot be instantiated directly using `__init__()` (throws an error).
class_docstr_tok: ["This","is","a","generic","tokenizer","class","that","will","be","instantiated","as","one","of","the","tokenizer","classes","of","the","library","when","created","with","the","[","`","AutoTokenizer.from_pretrained","`","]","class","method",".","This","class","can","not","be","instantiated","directly","using","`","__init__","(",")","`","(","throws","an","error",")","."]
code: def __init__(self):
      raise EnvironmentError(
          "AutoTokenizer is designed to be instantiated "
          "using the `AutoTokenizer.from_pretrained(pretrained_model_name_or_path)` method."
      )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/auto/tokenization_auto.py
imports: import importlib
  import json
  import os
  from collections import OrderedDict
  from typing import TYPE_CHECKING, Dict, Optional, Tuple, Union
  from ...configuration_utils import PretrainedConfig
  from ...dynamic_module_utils import get_class_from_dynamic_module
  from ...tokenization_utils import PreTrainedTokenizer
  from ...tokenization_utils_base import TOKENIZER_CONFIG_FILE
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import cached_file, extract_commit_hash, is_sentencepiece_available, is_tokenizers_available, logging
  from ..encoder_decoder import EncoderDecoderConfig
  from .auto_factory import _LazyAutoMapping
  from .configuration_auto import CONFIG_MAPPING_NAMES, AutoConfig, config_class_to_model_type, model_type_to_module_name, replace_list_option_in_docstrings
label_desc: Use image node_id 1 to create a new AutoTokenizer object  with example: obj = AutoTokenizer()