






def 		lowercase__  (				_UpperCamelCase) ->			Any:
      """simple docstring"""

      UpperCamelCase					       =  []
      UpperCamelCase					       =  []
      UpperCamelCase					       =  {
          '^': 3,
          '*': 2,
          '/': 2,
          '%': 2,
          '+': 1,
          '-': 1,
      }  # Priority of each operator
      UpperCamelCase					       =  len(_UpperCamelCase) if (len(_UpperCamelCase) > 7) else 7

      # Print table header for output
      print(
          'Symbol'.center(8)       ,							'Stack'.center(_UpperCamelCase)       ,							'Postfix'.center(_UpperCamelCase)       ,							sep=' | '       ,							)
      print('-' * (print_width * 3 + 7))

      for x in infix:
            if x.isalpha() or x.isdigit():
                  post_fix.append(_UpperCamelCase)  # if x is Alphabet / Digit, add it to Postfix
            elif x == "(":
                  stack.append(_UpperCamelCase)  # if x is "(" push to Stack
            elif x == ")":  # if x is ")" pop stack until "(" is encountered
                  while stack[-1] != "(":
                        post_fix.append(stack.pop())  # Pop stack & add the content to Postfix
                  stack.pop()
            else:
                  if len(_UpperCamelCase) == 0:
                        stack.append(_UpperCamelCase)  # If stack is empty, push x to stack
                  else:  # while priority of x is not > priority of element in the stack
                        while len(_UpperCamelCase) > 0 and priority[x] <= priority[stack[-1]]:
                              post_fix.append(stack.pop())  # pop stack & add to Postfix
                        stack.append(_UpperCamelCase)  # push x to stack

            print(
                x.center(8)       ,							(''.join(_UpperCamelCase)).ljust(_UpperCamelCase)       ,							(''.join(_UpperCamelCase)).ljust(_UpperCamelCase)       ,							sep=' | '       ,							)  # Output in tabular format

      while len(_UpperCamelCase) > 0:  # while stack is not empty
            post_fix.append(stack.pop())  # pop stack & add to Postfix
            print(
                ' '.center(8)       ,							(''.join(_UpperCamelCase)).ljust(_UpperCamelCase)       ,							(''.join(_UpperCamelCase)).ljust(_UpperCamelCase)       ,							sep=' | '       ,							)  # Output in tabular format

      return "".join(_UpperCamelCase)  # return Postfix as str
def 		lowercase__  (				_UpperCamelCase) ->			Optional[Any]:
      """simple docstring"""

      UpperCamelCase					       =  list(infix[::-1])  # reverse the infix equation

      for i in range(len(_UpperCamelCase)):
            if infix[i] == "(":
                  UpperCamelCase					       =  ')'  # change "(" to ")"
            elif infix[i] == ")":
                  UpperCamelCase					       =  '('  # change ")" to "("

      return (infix_2_postfix(''.join(_UpperCamelCase)))[
          ::-1
      ]  # call infix_2_postfix on Infix, return reverse of Postfix


if __name__ == "__main__":
       __magic_name__   :  int        =							input('''\nEnter an Infix Equation = ''')  # Input an Infix equation
       __magic_name__   :  Optional[Any]        =							''''''.join(Infix.split())  # Remove spaces from the input
       print('''\n\t''', Infix, '''(Infix) -> ''', infix_2_prefix(Infix), '''(Prefix)''')











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 					A__     (     unittest.TestCase ):

     '''simple docstring'''






     def   _SCREAMING_SNAKE_CASE     ( self      :    int ):






           """simple docstring"""




           UpperCamelCase					       =  0







     @slow
     def   _SCREAMING_SNAKE_CASE     ( self      :    Any ):






           """simple docstring"""




           for model_name in (x for x in BERT_PRETRAINED_CONFIG_ARCHIVE_MAP.keys() if "japanese" not in x):
                 UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE )
                 self.assertIsNotNone(_SCREAMING_SNAKE_CASE )
                 self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						(BertTokenizer, BertTokenizerFast) )
                 self.assertGreater(len(_SCREAMING_SNAKE_CASE )   ,						0 )

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







     def   _SCREAMING_SNAKE_CASE     ( self      :    Union[str, Any] ):






           """simple docstring"""




           UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE )
           self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						(BertTokenizer, BertTokenizerFast) )
           self.assertEqual(tokenizer.vocab_size   ,						12 )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Optional[int] ):






           """simple docstring"""




           UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE )
           self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						(RobertaTokenizer, RobertaTokenizerFast) )
           self.assertEqual(tokenizer.vocab_size   ,						20 )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Dict ):






           """simple docstring"""




           UpperCamelCase					       =  AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE )
           self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE )
           # Check that tokenizer_type ≠ model_type
           UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE   ,						config=_SCREAMING_SNAKE_CASE )
           self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						(BertTokenizer, BertTokenizerFast) )
           self.assertEqual(tokenizer.vocab_size   ,						12 )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Tuple ):






           """simple docstring"""




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

                 UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE   ,						tokenizer_type='bert'   ,						use_fast=_SCREAMING_SNAKE_CASE )
                 self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE )

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

                 UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE   ,						tokenizer_type='gpt2'   ,						use_fast=_SCREAMING_SNAKE_CASE )
                 self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE )







     @require_tokenizers
     def   _SCREAMING_SNAKE_CASE     ( self      :    str ):






           """simple docstring"""




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

                 UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE   ,						tokenizer_type='bert' )
                 self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE )

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

                 UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE   ,						tokenizer_type='gpt2' )
                 self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE )







     def   _SCREAMING_SNAKE_CASE     ( self      :    str ):






           """simple docstring"""




           with pytest.raises(_SCREAMING_SNAKE_CASE ):
                 AutoTokenizer.from_pretrained('./'   ,						tokenizer_type='xxx' )







     @require_tokenizers
     def   _SCREAMING_SNAKE_CASE     ( self      :    Tuple ):






           """simple docstring"""




           for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
                 UpperCamelCase					       =  tokenizer_class.from_pretrained('wietsedv/bert-base-dutch-cased' )
                 self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						(BertTokenizer, BertTokenizerFast) )

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

                 self.assertEqual(tokenizer.model_max_length   ,						512 )







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






           """simple docstring"""




           for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
                 with self.assertRaisesRegex(
                     _SCREAMING_SNAKE_CASE   ,						'julien-c/herlolip-not-exists is not a local folder and is not a valid model identifier'   ,						):
                       UpperCamelCase					       =  tokenizer_class.from_pretrained('julien-c/herlolip-not-exists' )







     def   _SCREAMING_SNAKE_CASE     ( self      :    int ):






           """simple docstring"""




           UpperCamelCase					       =  TOKENIZER_MAPPING.values()
           UpperCamelCase					       =  []

           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(_SCREAMING_SNAKE_CASE )







     @require_tokenizers
     def   _SCREAMING_SNAKE_CASE     ( self      :    List[Any] ):






           """simple docstring"""




           self.assertIsInstance(AutoTokenizer.from_pretrained('bert-base-cased'   ,						use_fast=_SCREAMING_SNAKE_CASE )   ,						_SCREAMING_SNAKE_CASE )
           self.assertIsInstance(AutoTokenizer.from_pretrained('bert-base-cased' )   ,						_SCREAMING_SNAKE_CASE )







     @require_tokenizers
     def   _SCREAMING_SNAKE_CASE     ( self      :    Dict ):






           """simple docstring"""




           UpperCamelCase					       =  AutoTokenizer.from_pretrained('distilbert-base-uncased'   ,						do_lower_case=_SCREAMING_SNAKE_CASE )
           UpperCamelCase					       =  'Hello, world. How are you?'
           UpperCamelCase					       =  tokenizer.tokenize(_SCREAMING_SNAKE_CASE )
           self.assertEqual('[UNK]'   ,						tokens[0] )

           UpperCamelCase					       =  AutoTokenizer.from_pretrained('microsoft/mpnet-base'   ,						do_lower_case=_SCREAMING_SNAKE_CASE )
           UpperCamelCase					       =  tokenizer.tokenize(_SCREAMING_SNAKE_CASE )
           self.assertEqual('[UNK]'   ,						tokens[0] )







     @require_tokenizers
     def   _SCREAMING_SNAKE_CASE     ( self      :    Optional[Any] ):






           """simple docstring"""




           UpperCamelCase					       =  AutoTokenizer.from_pretrained('robot-test/dummy-tokenizer-fast-with-model-config' )
           self.assertEqual(type(_SCREAMING_SNAKE_CASE )   ,						_SCREAMING_SNAKE_CASE )
           self.assertEqual(tokenizer.model_max_length   ,						512 )
           self.assertEqual(tokenizer.vocab_size   ,						3_0000 )
           self.assertEqual(tokenizer.unk_token   ,						'[UNK]' )
           self.assertEqual(tokenizer.padding_side   ,						'right' )
           self.assertEqual(tokenizer.truncation_side   ,						'right' )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Optional[int] ):






           """simple docstring"""




           UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE )
           self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						(BertTokenizer, BertTokenizerFast) )
           with tempfile.TemporaryDirectory() as tmp_dir:
                 tokenizer.save_pretrained(_SCREAMING_SNAKE_CASE )
                 UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE )

           self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						tokenizer.__class__ )
           self.assertEqual(tokenizera.vocab_size   ,						12 )







     def   _SCREAMING_SNAKE_CASE     ( self      :    int ):






           """simple docstring"""




           UpperCamelCase					       =  AutoTokenizer.from_pretrained('ctrl' )
           # There is no fast CTRL so this always gives us a slow tokenizer.
           self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Dict ):






           """simple docstring"""




           UpperCamelCase					       =  get_tokenizer_config('bert-base-cased' )
           UpperCamelCase					       =  config.pop('_commit_hash'   ,						_SCREAMING_SNAKE_CASE )
           # If we ever update bert-base-cased tokenizer config, this dict here will need to be updated.
           self.assertEqual(_SCREAMING_SNAKE_CASE   ,						{'do_lower_case': False} )

           # This model does not have a tokenizer_config so we get back an empty dict.
           UpperCamelCase					       =  get_tokenizer_config(_SCREAMING_SNAKE_CASE )
           self.assertDictEqual(_SCREAMING_SNAKE_CASE   ,						{} )

           # A tokenizer saved with `save_pretrained` always creates a tokenizer config.
           UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE )
           with tempfile.TemporaryDirectory() as tmp_dir:
                 tokenizer.save_pretrained(_SCREAMING_SNAKE_CASE )
                 UpperCamelCase					       =  get_tokenizer_config(_SCREAMING_SNAKE_CASE )

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







     def   _SCREAMING_SNAKE_CASE     ( self      :    int ):






           """simple docstring"""




           try:
                 AutoConfig.register('custom'   ,						_SCREAMING_SNAKE_CASE )

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

                 UpperCamelCase					       =  CustomTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE )
                 with tempfile.TemporaryDirectory() as tmp_dir:
                       tokenizer.save_pretrained(_SCREAMING_SNAKE_CASE )

                       UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE )
                       self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE )

           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   _SCREAMING_SNAKE_CASE     ( self      :    List[Any] ):






           """simple docstring"""




           try:
                 AutoConfig.register('custom'   ,						_SCREAMING_SNAKE_CASE )

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

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

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

                 # 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:
                       UpperCamelCase					       =  BertTokenizerFast.from_pretrained(_SCREAMING_SNAKE_CASE )
                       bert_tokenizer.save_pretrained(_SCREAMING_SNAKE_CASE )
                       UpperCamelCase					       =  CustomTokenizerFast.from_pretrained(_SCREAMING_SNAKE_CASE )

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

                       UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE )
                       self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE )

                       UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE   ,						use_fast=_SCREAMING_SNAKE_CASE )
                       self.assertIsInstance(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE )

           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   _SCREAMING_SNAKE_CASE     ( self      :    int ):






           """simple docstring"""




           with self.assertRaises(_SCREAMING_SNAKE_CASE ):
                 UpperCamelCase					       =  AutoTokenizer.from_pretrained('hf-internal-testing/test_dynamic_tokenizer' )
           # If remote code is disabled, we can't load this config.
           with self.assertRaises(_SCREAMING_SNAKE_CASE ):
                 UpperCamelCase					       =  AutoTokenizer.from_pretrained(
                     'hf-internal-testing/test_dynamic_tokenizer'   ,						trust_remote_code=_SCREAMING_SNAKE_CASE )

           UpperCamelCase					       =  AutoTokenizer.from_pretrained('hf-internal-testing/test_dynamic_tokenizer'   ,						trust_remote_code=_SCREAMING_SNAKE_CASE )
           self.assertTrue(tokenizer.special_attribute_present )
           # Test tokenizer can be reloaded.
           with tempfile.TemporaryDirectory() as tmp_dir:
                 tokenizer.save_pretrained(_SCREAMING_SNAKE_CASE )
                 UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE   ,						trust_remote_code=_SCREAMING_SNAKE_CASE )
           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
                 UpperCamelCase					       =  AutoTokenizer.from_pretrained(
                     'hf-internal-testing/test_dynamic_tokenizer'   ,						trust_remote_code=_SCREAMING_SNAKE_CASE   ,						use_fast=_SCREAMING_SNAKE_CASE )
                 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(_SCREAMING_SNAKE_CASE )
                       UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE   ,						trust_remote_code=_SCREAMING_SNAKE_CASE   ,						use_fast=_SCREAMING_SNAKE_CASE )
                 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   _SCREAMING_SNAKE_CASE     ( self      :    Optional[int] ):






           """simple docstring"""




           class 					A__     (     __snake_case ):

                '''simple docstring'''






                snake_case__					=					False





           class 					A__     (     __snake_case ):

                '''simple docstring'''






                snake_case__					=					NewTokenizer
                snake_case__					=					False

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

                 # If remote code is disabled, we load the local one.
                 UpperCamelCase					       =  AutoTokenizer.from_pretrained(
                     'hf-internal-testing/test_dynamic_tokenizer'   ,						trust_remote_code=_SCREAMING_SNAKE_CASE )
                 self.assertEqual(tokenizer.__class__.__name__   ,						'NewTokenizerFast' )
                 self.assertFalse(tokenizer.special_attribute_present )
                 UpperCamelCase					       =  AutoTokenizer.from_pretrained(
                     'hf-internal-testing/test_dynamic_tokenizer'   ,						trust_remote_code=_SCREAMING_SNAKE_CASE   ,						use_fast=_SCREAMING_SNAKE_CASE )
                 self.assertEqual(tokenizer.__class__.__name__   ,						'NewTokenizer' )
                 self.assertFalse(tokenizer.special_attribute_present )

                 # If remote is enabled, we load from the Hub
                 UpperCamelCase					       =  AutoTokenizer.from_pretrained(
                     'hf-internal-testing/test_dynamic_tokenizer'   ,						trust_remote_code=_SCREAMING_SNAKE_CASE )
                 self.assertEqual(tokenizer.__class__.__name__   ,						'NewTokenizerFast' )
                 self.assertTrue(tokenizer.special_attribute_present )
                 UpperCamelCase					       =  AutoTokenizer.from_pretrained(
                     'hf-internal-testing/test_dynamic_tokenizer'   ,						trust_remote_code=_SCREAMING_SNAKE_CASE   ,						use_fast=_SCREAMING_SNAKE_CASE )
                 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   _SCREAMING_SNAKE_CASE     ( self      :    Optional[Any] ):






           """simple docstring"""




           UpperCamelCase					       =  AutoTokenizer.from_pretrained(
               'hf-internal-testing/test_dynamic_tokenizer_legacy'   ,						trust_remote_code=_SCREAMING_SNAKE_CASE )
           self.assertTrue(tokenizer.special_attribute_present )
           if is_tokenizers_available():
                 self.assertEqual(tokenizer.__class__.__name__   ,						'NewTokenizerFast' )

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







     def   _SCREAMING_SNAKE_CASE     ( self      :    Tuple ):






           """simple docstring"""




           with self.assertRaisesRegex(
               _SCREAMING_SNAKE_CASE   ,						'bert-base is not a local folder and is not a valid model identifier' ):
                 UpperCamelCase					       =  AutoTokenizer.from_pretrained('bert-base' )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Dict ):






           """simple docstring"""




           with self.assertRaisesRegex(
               _SCREAMING_SNAKE_CASE   ,						r'aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)' ):
                 UpperCamelCase					       =  AutoTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE   ,						revision='aaaaaa' )







     def   _SCREAMING_SNAKE_CASE     ( self      :    str ):






           """simple docstring"""




           UpperCamelCase					       =  AutoTokenizer.from_pretrained('hf-internal-testing/tiny-random-bert' )
           with RequestCounter() as counter:
                 UpperCamelCase					       =  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 )



