


"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


snake_case__		:     Optional[Any]    				=				{
    '''configuration_blenderbot''': [
        '''BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BlenderbotConfig''',
        '''BlenderbotOnnxConfig''',
    ],
    '''tokenization_blenderbot''': ['''BlenderbotTokenizer'''],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__		:     Optional[Any]    				=				['''BlenderbotTokenizerFast''']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__		:     Union[str, Any]    				=				[
     '''BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''BlenderbotForCausalLM''',
     '''BlenderbotForConditionalGeneration''',
     '''BlenderbotModel''',
     '''BlenderbotPreTrainedModel''',
 ]


try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__		:     List[Any]    				=				[
     '''TFBlenderbotForConditionalGeneration''',
     '''TFBlenderbotModel''',
     '''TFBlenderbotPreTrainedModel''',
 ]


try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__		:     int    				=				[
     '''FlaxBlenderbotForConditionalGeneration''',
     '''FlaxBlenderbotModel''',
     '''FlaxBlenderbotPreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_blenderbot import (
     BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
     BlenderbotConfig,
     BlenderbotOnnxConfig,
 )
 from .tokenization_blenderbot import BlenderbotTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_blenderbot import (
      BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
      BlenderbotForCausalLM,
      BlenderbotForConditionalGeneration,
      BlenderbotModel,
      BlenderbotPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_blenderbot import (
      TFBlenderbotForConditionalGeneration,
      TFBlenderbotModel,
      TFBlenderbotPreTrainedModel,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_blenderbot import (
      FlaxBlenderbotForConditionalGeneration,
      FlaxBlenderbotModel,
      FlaxBlenderbotPreTrainedModel,
  )

else:
 import sys

 snake_case__		:     Tuple    				=				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






"""simple docstring"""





import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path

import pytest

import transformers
from transformers import (
    BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
    GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
    AutoTokenizer,
    BertConfig,
    BertTokenizer,
    BertTokenizerFast,
    CTRLTokenizer,
    GPTaTokenizer,
    GPTaTokenizerFast,
    PreTrainedTokenizerFast,
    RobertaTokenizer,
    RobertaTokenizerFast,
    is_tokenizers_available,
)
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.auto.tokenization_auto import (
    TOKENIZER_MAPPING,
    get_tokenizer_config,
    tokenizer_class_from_name,
)
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import (
    DUMMY_DIFF_TOKENIZER_IDENTIFIER,
    DUMMY_UNKNOWN_IDENTIFIER,
    SMALL_MODEL_IDENTIFIER,
    RequestCounter,
    require_tokenizers,
    slow,
)


sys.path.append(str(Path(__file__).parent.parent.parent.parent / '''utils'''))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_tokenization import CustomTokenizer  # noqa E402


if is_tokenizers_available():
 from test_module.custom_tokenization_fast import CustomTokenizerFast



class 		snake_case_(       unittest.TestCase			):






     def      lowerCamelCase__     (	self  :					Optional[int]				):
           lowerCAmelCase					:	Optional[Any]       =   0






     @slow
     def      lowerCamelCase__     (	self  :					Dict				):
           for model_name in (x for x in BERT_PRETRAINED_CONFIG_ARCHIVE_MAP.keys() if "japanese" not in x):
                 lowerCAmelCase					:	Optional[Any]       =   AutoTokenizer.from_pretrained(UpperCamelCase_				)
                 self.assertIsNotNone(UpperCamelCase_				)
                 self.assertIsInstance(UpperCamelCase_					,				(BertTokenizer, BertTokenizerFast)				)
                 self.assertGreater(len(UpperCamelCase_				)					,				0				)

           for model_name in GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP.keys():
                 lowerCAmelCase					:	Tuple       =   AutoTokenizer.from_pretrained(UpperCamelCase_				)
                 self.assertIsNotNone(UpperCamelCase_				)
                 self.assertIsInstance(UpperCamelCase_					,				(GPTaTokenizer, GPTaTokenizerFast)				)
                 self.assertGreater(len(UpperCamelCase_				)					,				0				)






     def      lowerCamelCase__     (	self  :					Union[str, Any]				):
           lowerCAmelCase					:	Optional[Any]       =   AutoTokenizer.from_pretrained(UpperCamelCase_				)
           self.assertIsInstance(UpperCamelCase_					,				(BertTokenizer, BertTokenizerFast)				)
           self.assertEqual(tokenizer.vocab_size					,				1_2				)






     def      lowerCamelCase__     (	self  :					Dict				):
           lowerCAmelCase					:	Tuple       =   AutoTokenizer.from_pretrained(UpperCamelCase_				)
           self.assertIsInstance(UpperCamelCase_					,				(RobertaTokenizer, RobertaTokenizerFast)				)
           self.assertEqual(tokenizer.vocab_size					,				2_0				)






     def      lowerCamelCase__     (	self  :					Dict				):
           lowerCAmelCase					:	int       =   AutoConfig.from_pretrained(UpperCamelCase_				)
           self.assertIsInstance(UpperCamelCase_					,				UpperCamelCase_				)
           # Check that tokenizer_type ≠ model_type
           lowerCAmelCase					:	List[Any]       =   AutoTokenizer.from_pretrained(UpperCamelCase_					,				config=UpperCamelCase_				)
           self.assertIsInstance(UpperCamelCase_					,				(BertTokenizer, BertTokenizerFast)				)
           self.assertEqual(tokenizer.vocab_size					,				1_2				)






     def      lowerCamelCase__     (	self  :					Any				):
           with tempfile.TemporaryDirectory() as tmp_dir:
                 shutil.copy('''./tests/fixtures/vocab.txt'''					,				os.path.join(UpperCamelCase_					,				'''vocab.txt'''				)				)

                 lowerCAmelCase					:	Any       =   AutoTokenizer.from_pretrained(UpperCamelCase_					,				tokenizer_type='''bert'''					,				use_fast=UpperCamelCase_				)
                 self.assertIsInstance(UpperCamelCase_					,				UpperCamelCase_				)

           with tempfile.TemporaryDirectory() as tmp_dir:
                 shutil.copy('''./tests/fixtures/vocab.json'''					,				os.path.join(UpperCamelCase_					,				'''vocab.json'''				)				)
                 shutil.copy('''./tests/fixtures/merges.txt'''					,				os.path.join(UpperCamelCase_					,				'''merges.txt'''				)				)

                 lowerCAmelCase					:	List[Any]       =   AutoTokenizer.from_pretrained(UpperCamelCase_					,				tokenizer_type='''gpt2'''					,				use_fast=UpperCamelCase_				)
                 self.assertIsInstance(UpperCamelCase_					,				UpperCamelCase_				)






     @require_tokenizers
     def      lowerCamelCase__     (	self  :					Union[str, Any]				):
           with tempfile.TemporaryDirectory() as tmp_dir:
                 shutil.copy('''./tests/fixtures/vocab.txt'''					,				os.path.join(UpperCamelCase_					,				'''vocab.txt'''				)				)

                 lowerCAmelCase					:	Optional[Any]       =   AutoTokenizer.from_pretrained(UpperCamelCase_					,				tokenizer_type='''bert'''				)
                 self.assertIsInstance(UpperCamelCase_					,				UpperCamelCase_				)

           with tempfile.TemporaryDirectory() as tmp_dir:
                 shutil.copy('''./tests/fixtures/vocab.json'''					,				os.path.join(UpperCamelCase_					,				'''vocab.json'''				)				)
                 shutil.copy('''./tests/fixtures/merges.txt'''					,				os.path.join(UpperCamelCase_					,				'''merges.txt'''				)				)

                 lowerCAmelCase					:	int       =   AutoTokenizer.from_pretrained(UpperCamelCase_					,				tokenizer_type='''gpt2'''				)
                 self.assertIsInstance(UpperCamelCase_					,				UpperCamelCase_				)






     def      lowerCamelCase__     (	self  :					Dict				):
           with pytest.raises(UpperCamelCase_				):
                 AutoTokenizer.from_pretrained('''./'''					,				tokenizer_type='''xxx'''				)






     @require_tokenizers
     def      lowerCamelCase__     (	self  :					str				):
           for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
                 lowerCAmelCase					:	Dict       =   tokenizer_class.from_pretrained('''wietsedv/bert-base-dutch-cased'''				)
                 self.assertIsInstance(UpperCamelCase_					,				(BertTokenizer, BertTokenizerFast)				)

                 if isinstance(UpperCamelCase_					,				UpperCamelCase_				):
                       self.assertEqual(tokenizer.basic_tokenizer.do_lower_case					,				UpperCamelCase_				)
                 else:
                       self.assertEqual(tokenizer.do_lower_case					,				UpperCamelCase_				)

                 self.assertEqual(tokenizer.model_max_length					,				5_1_2				)






     @require_tokenizers
     def      lowerCamelCase__     (	self  :					Optional[int]				):
           for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
                 with self.assertRaisesRegex(
                     UpperCamelCase_					,				'''julien-c/herlolip-not-exists is not a local folder and is not a valid model identifier'''					,				):
                       lowerCAmelCase					:	Any       =   tokenizer_class.from_pretrained('''julien-c/herlolip-not-exists'''				)






     def      lowerCamelCase__     (	self  :					Tuple				):
           # tests: https://github.com/huggingface/transformers/pull/13251
           # 1. models with `-`, e.g. xlm-roberta -> xlm_roberta
           # 2. models that don't remap 1-1 from model-name to model file, e.g., openai-gpt -> openai
           lowerCAmelCase					:	Optional[Any]       =   TOKENIZER_MAPPING.values()
           lowerCAmelCase					:	Optional[Any]       =   []

           for slow_tok, fast_tok in tokenizers:
                 if slow_tok is not None:
                       tokenizer_names.append(slow_tok.__name__				)

                 if fast_tok is not None:
                       tokenizer_names.append(fast_tok.__name__				)

           for tokenizer_name in tokenizer_names:
                 # must find the right class
                 tokenizer_class_from_name(UpperCamelCase_				)






     @require_tokenizers
     def      lowerCamelCase__     (	self  :					Any				):
           self.assertIsInstance(AutoTokenizer.from_pretrained('''bert-base-cased'''					,				use_fast=UpperCamelCase_				)					,				UpperCamelCase_				)
           self.assertIsInstance(AutoTokenizer.from_pretrained('''bert-base-cased'''				)					,				UpperCamelCase_				)






     @require_tokenizers
     def      lowerCamelCase__     (	self  :					Dict				):
           lowerCAmelCase					:	List[Any]       =   AutoTokenizer.from_pretrained('''distilbert-base-uncased'''					,				do_lower_case=UpperCamelCase_				)
           lowerCAmelCase					:	Union[str, Any]       =   '''Hello, world. How are you?'''
           lowerCAmelCase					:	Optional[Any]       =   tokenizer.tokenize(UpperCamelCase_				)
           self.assertEqual('''[UNK]'''					,				tokens[0]				)

           lowerCAmelCase					:	List[str]       =   AutoTokenizer.from_pretrained('''microsoft/mpnet-base'''					,				do_lower_case=UpperCamelCase_				)
           lowerCAmelCase					:	Optional[int]       =   tokenizer.tokenize(UpperCamelCase_				)
           self.assertEqual('''[UNK]'''					,				tokens[0]				)






     @require_tokenizers
     def      lowerCamelCase__     (	self  :					int				):
           lowerCAmelCase					:	Union[str, Any]       =   AutoTokenizer.from_pretrained('''robot-test/dummy-tokenizer-fast-with-model-config'''				)
           self.assertEqual(type(UpperCamelCase_				)					,				UpperCamelCase_				)
           self.assertEqual(tokenizer.model_max_length					,				5_1_2				)
           self.assertEqual(tokenizer.vocab_size					,				3_0_0_0_0				)
           self.assertEqual(tokenizer.unk_token					,				'''[UNK]'''				)
           self.assertEqual(tokenizer.padding_side					,				'''right'''				)
           self.assertEqual(tokenizer.truncation_side					,				'''right'''				)






     def      lowerCamelCase__     (	self  :					List[Any]				):
           lowerCAmelCase					:	int       =   AutoTokenizer.from_pretrained(UpperCamelCase_				)
           self.assertIsInstance(UpperCamelCase_					,				(BertTokenizer, BertTokenizerFast)				)
           with tempfile.TemporaryDirectory() as tmp_dir:
                 tokenizer.save_pretrained(UpperCamelCase_				)
                 lowerCAmelCase					:	List[Any]       =   AutoTokenizer.from_pretrained(UpperCamelCase_				)

           self.assertIsInstance(UpperCamelCase_					,				tokenizer.__class__				)
           self.assertEqual(tokenizera.vocab_size					,				1_2				)






     def      lowerCamelCase__     (	self  :					List[str]				):
           lowerCAmelCase					:	List[Any]       =   AutoTokenizer.from_pretrained('''ctrl'''				)
           # There is no fast CTRL so this always gives us a slow tokenizer.
           self.assertIsInstance(UpperCamelCase_					,				UpperCamelCase_				)






     def      lowerCamelCase__     (	self  :					Dict				):
           # Check we can load the tokenizer config of an online model.
           lowerCAmelCase					:	Any       =   get_tokenizer_config('''bert-base-cased'''				)
           lowerCAmelCase					:	Optional[int]       =   config.pop('''_commit_hash'''					,				UpperCamelCase_				)
           # If we ever update bert-base-cased tokenizer config, this dict here will need to be updated.
           self.assertEqual(UpperCamelCase_					,				{'''do_lower_case''': False}				)

           # This model does not have a tokenizer_config so we get back an empty dict.
           lowerCAmelCase					:	Union[str, Any]       =   get_tokenizer_config(UpperCamelCase_				)
           self.assertDictEqual(UpperCamelCase_					,				{}				)

           # A tokenizer saved with `save_pretrained` always creates a tokenizer config.
           lowerCAmelCase					:	List[Any]       =   AutoTokenizer.from_pretrained(UpperCamelCase_				)
           with tempfile.TemporaryDirectory() as tmp_dir:
                 tokenizer.save_pretrained(UpperCamelCase_				)
                 lowerCAmelCase					:	Dict       =   get_tokenizer_config(UpperCamelCase_				)

           # Check the class of the tokenizer was properly saved (note that it always saves the slow class).
           self.assertEqual(config['''tokenizer_class''']					,				'''BertTokenizer'''				)






     def      lowerCamelCase__     (	self  :					Optional[int]				):
           try:
                 AutoConfig.register('''custom'''					,				UpperCamelCase_				)

                 AutoTokenizer.register(UpperCamelCase_					,				slow_tokenizer_class=UpperCamelCase_				)
                 # Trying to register something existing in the Transformers library will raise an error
                 with self.assertRaises(UpperCamelCase_				):
                       AutoTokenizer.register(UpperCamelCase_					,				slow_tokenizer_class=UpperCamelCase_				)

                 lowerCAmelCase					:	Union[str, Any]       =   CustomTokenizer.from_pretrained(UpperCamelCase_				)
                 with tempfile.TemporaryDirectory() as tmp_dir:
                       tokenizer.save_pretrained(UpperCamelCase_				)

                       lowerCAmelCase					:	Tuple       =   AutoTokenizer.from_pretrained(UpperCamelCase_				)
                       self.assertIsInstance(UpperCamelCase_					,				UpperCamelCase_				)

           finally:
                 if "custom" in CONFIG_MAPPING._extra_content:
                       del CONFIG_MAPPING._extra_content["custom"]
                 if CustomConfig in TOKENIZER_MAPPING._extra_content:
                       del TOKENIZER_MAPPING._extra_content[CustomConfig]






     @require_tokenizers
     def      lowerCamelCase__     (	self  :					str				):
           try:
                 AutoConfig.register('''custom'''					,				UpperCamelCase_				)

                 # Can register in two steps
                 AutoTokenizer.register(UpperCamelCase_					,				slow_tokenizer_class=UpperCamelCase_				)
                 self.assertEqual(TOKENIZER_MAPPING[CustomConfig]					,				(CustomTokenizer, None)				)
                 AutoTokenizer.register(UpperCamelCase_					,				fast_tokenizer_class=UpperCamelCase_				)
                 self.assertEqual(TOKENIZER_MAPPING[CustomConfig]					,				(CustomTokenizer, CustomTokenizerFast)				)

                 del TOKENIZER_MAPPING._extra_content[CustomConfig]
                 # Can register in one step
                 AutoTokenizer.register(
                     UpperCamelCase_					,				slow_tokenizer_class=UpperCamelCase_					,				fast_tokenizer_class=UpperCamelCase_				)
                 self.assertEqual(TOKENIZER_MAPPING[CustomConfig]					,				(CustomTokenizer, CustomTokenizerFast)				)

                 # Trying to register something existing in the Transformers library will raise an error
                 with self.assertRaises(UpperCamelCase_				):
                       AutoTokenizer.register(UpperCamelCase_					,				fast_tokenizer_class=UpperCamelCase_				)

                 # We pass through a bert tokenizer fast cause there is no converter slow to fast for our new toknizer
                 # and that model does not have a tokenizer.json
                 with tempfile.TemporaryDirectory() as tmp_dir:
                       lowerCAmelCase					:	Dict       =   BertTokenizerFast.from_pretrained(UpperCamelCase_				)
                       bert_tokenizer.save_pretrained(UpperCamelCase_				)
                       lowerCAmelCase					:	int       =   CustomTokenizerFast.from_pretrained(UpperCamelCase_				)

                 with tempfile.TemporaryDirectory() as tmp_dir:
                       tokenizer.save_pretrained(UpperCamelCase_				)

                       lowerCAmelCase					:	Optional[int]       =   AutoTokenizer.from_pretrained(UpperCamelCase_				)
                       self.assertIsInstance(UpperCamelCase_					,				UpperCamelCase_				)

                       lowerCAmelCase					:	List[str]       =   AutoTokenizer.from_pretrained(UpperCamelCase_					,				use_fast=UpperCamelCase_				)
                       self.assertIsInstance(UpperCamelCase_					,				UpperCamelCase_				)

           finally:
                 if "custom" in CONFIG_MAPPING._extra_content:
                       del CONFIG_MAPPING._extra_content["custom"]
                 if CustomConfig in TOKENIZER_MAPPING._extra_content:
                       del TOKENIZER_MAPPING._extra_content[CustomConfig]






     def      lowerCamelCase__     (	self  :					Optional[int]				):
           # If remote code is not set, we will time out when asking whether to load the model.
           with self.assertRaises(UpperCamelCase_				):
                 lowerCAmelCase					:	int       =   AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer'''				)
           # If remote code is disabled, we can't load this config.
           with self.assertRaises(UpperCamelCase_				):
                 lowerCAmelCase					:	str       =   AutoTokenizer.from_pretrained(
                     '''hf-internal-testing/test_dynamic_tokenizer'''					,				trust_remote_code=UpperCamelCase_				)

           lowerCAmelCase					:	List[str]       =   AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer'''					,				trust_remote_code=UpperCamelCase_				)
           self.assertTrue(tokenizer.special_attribute_present				)
           # Test tokenizer can be reloaded.
           with tempfile.TemporaryDirectory() as tmp_dir:
                 tokenizer.save_pretrained(UpperCamelCase_				)
                 lowerCAmelCase					:	Optional[Any]       =   AutoTokenizer.from_pretrained(UpperCamelCase_					,				trust_remote_code=UpperCamelCase_				)
           self.assertTrue(reloaded_tokenizer.special_attribute_present				)

           if is_tokenizers_available():
                 self.assertEqual(tokenizer.__class__.__name__					,				'''NewTokenizerFast'''				)
                 self.assertEqual(reloaded_tokenizer.__class__.__name__					,				'''NewTokenizerFast'''				)

                 # Test we can also load the slow version
                 lowerCAmelCase					:	Union[str, Any]       =   AutoTokenizer.from_pretrained(
                     '''hf-internal-testing/test_dynamic_tokenizer'''					,				trust_remote_code=UpperCamelCase_					,				use_fast=UpperCamelCase_				)
                 self.assertTrue(tokenizer.special_attribute_present				)
                 self.assertEqual(tokenizer.__class__.__name__					,				'''NewTokenizer'''				)
                 # Test tokenizer can be reloaded.
                 with tempfile.TemporaryDirectory() as tmp_dir:
                       tokenizer.save_pretrained(UpperCamelCase_				)
                       lowerCAmelCase					:	List[str]       =   AutoTokenizer.from_pretrained(UpperCamelCase_					,				trust_remote_code=UpperCamelCase_					,				use_fast=UpperCamelCase_				)
                 self.assertEqual(reloaded_tokenizer.__class__.__name__					,				'''NewTokenizer'''				)
                 self.assertTrue(reloaded_tokenizer.special_attribute_present				)
           else:
                 self.assertEqual(tokenizer.__class__.__name__					,				'''NewTokenizer'''				)
                 self.assertEqual(reloaded_tokenizer.__class__.__name__					,				'''NewTokenizer'''				)






     @require_tokenizers
     def      lowerCamelCase__     (	self  :					Optional[int]				):



           class 		snake_case_(       a__			):
                __UpperCamelCase  =					False



           class 		snake_case_(       a__			):
                __UpperCamelCase  =					NewTokenizer
                __UpperCamelCase  =					False

           try:
                 AutoConfig.register('''custom'''					,				UpperCamelCase_				)
                 AutoTokenizer.register(UpperCamelCase_					,				slow_tokenizer_class=UpperCamelCase_				)
                 AutoTokenizer.register(UpperCamelCase_					,				fast_tokenizer_class=UpperCamelCase_				)
                 # If remote code is not set, the default is to use local
                 lowerCAmelCase					:	Optional[int]       =   AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer'''				)
                 self.assertEqual(tokenizer.__class__.__name__					,				'''NewTokenizerFast'''				)
                 self.assertFalse(tokenizer.special_attribute_present				)
                 lowerCAmelCase					:	str       =   AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer'''					,				use_fast=UpperCamelCase_				)
                 self.assertEqual(tokenizer.__class__.__name__					,				'''NewTokenizer'''				)
                 self.assertFalse(tokenizer.special_attribute_present				)

                 # If remote code is disabled, we load the local one.
                 lowerCAmelCase					:	Union[str, Any]       =   AutoTokenizer.from_pretrained(
                     '''hf-internal-testing/test_dynamic_tokenizer'''					,				trust_remote_code=UpperCamelCase_				)
                 self.assertEqual(tokenizer.__class__.__name__					,				'''NewTokenizerFast'''				)
                 self.assertFalse(tokenizer.special_attribute_present				)
                 lowerCAmelCase					:	Dict       =   AutoTokenizer.from_pretrained(
                     '''hf-internal-testing/test_dynamic_tokenizer'''					,				trust_remote_code=UpperCamelCase_					,				use_fast=UpperCamelCase_				)
                 self.assertEqual(tokenizer.__class__.__name__					,				'''NewTokenizer'''				)
                 self.assertFalse(tokenizer.special_attribute_present				)

                 # If remote is enabled, we load from the Hub
                 lowerCAmelCase					:	int       =   AutoTokenizer.from_pretrained(
                     '''hf-internal-testing/test_dynamic_tokenizer'''					,				trust_remote_code=UpperCamelCase_				)
                 self.assertEqual(tokenizer.__class__.__name__					,				'''NewTokenizerFast'''				)
                 self.assertTrue(tokenizer.special_attribute_present				)
                 lowerCAmelCase					:	int       =   AutoTokenizer.from_pretrained(
                     '''hf-internal-testing/test_dynamic_tokenizer'''					,				trust_remote_code=UpperCamelCase_					,				use_fast=UpperCamelCase_				)
                 self.assertEqual(tokenizer.__class__.__name__					,				'''NewTokenizer'''				)
                 self.assertTrue(tokenizer.special_attribute_present				)

           finally:
                 if "custom" in CONFIG_MAPPING._extra_content:
                       del CONFIG_MAPPING._extra_content["custom"]
                 if CustomConfig in TOKENIZER_MAPPING._extra_content:
                       del TOKENIZER_MAPPING._extra_content[CustomConfig]






     def      lowerCamelCase__     (	self  :					Tuple				):
           lowerCAmelCase					:	str       =   AutoTokenizer.from_pretrained(
               '''hf-internal-testing/test_dynamic_tokenizer_legacy'''					,				trust_remote_code=UpperCamelCase_				)
           self.assertTrue(tokenizer.special_attribute_present				)
           if is_tokenizers_available():
                 self.assertEqual(tokenizer.__class__.__name__					,				'''NewTokenizerFast'''				)

                 # Test we can also load the slow version
                 lowerCAmelCase					:	List[str]       =   AutoTokenizer.from_pretrained(
                     '''hf-internal-testing/test_dynamic_tokenizer_legacy'''					,				trust_remote_code=UpperCamelCase_					,				use_fast=UpperCamelCase_				)
                 self.assertTrue(tokenizer.special_attribute_present				)
                 self.assertEqual(tokenizer.__class__.__name__					,				'''NewTokenizer'''				)
           else:
                 self.assertEqual(tokenizer.__class__.__name__					,				'''NewTokenizer'''				)






     def      lowerCamelCase__     (	self  :					str				):
           with self.assertRaisesRegex(
               UpperCamelCase_					,				'''bert-base is not a local folder and is not a valid model identifier'''				):
                 lowerCAmelCase					:	List[str]       =   AutoTokenizer.from_pretrained('''bert-base'''				)






     def      lowerCamelCase__     (	self  :					int				):
           with self.assertRaisesRegex(
               UpperCamelCase_					,				r'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''				):
                 lowerCAmelCase					:	List[Any]       =   AutoTokenizer.from_pretrained(UpperCamelCase_					,				revision='''aaaaaa'''				)






     def      lowerCamelCase__     (	self  :					Optional[int]				):
           # Make sure we have cached the tokenizer.
           lowerCAmelCase					:	List[str]       =   AutoTokenizer.from_pretrained('''hf-internal-testing/tiny-random-bert'''				)
           with RequestCounter() as counter:
                 lowerCAmelCase					:	int       =   AutoTokenizer.from_pretrained('''hf-internal-testing/tiny-random-bert'''				)
                 self.assertEqual(counter.get_request_count					,				0				)
                 self.assertEqual(counter.head_request_count					,				1				)
                 self.assertEqual(counter.other_request_count					,				0				)


