




'''simple docstring'''




import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class     __UpperCamelCase			(					a__     ,   unittest.TestCase							):
       lowercase      :       Optional[int] 		=OpenAIGPTTokenizer
       lowercase      :       str 		=OpenAIGPTTokenizerFast
       lowercase      :       Dict 		=True
       lowercase      :       Union[str, Any] 		=False






       def 	lowercase__	(				self    ):



              """simple docstring"""







              super().setUp()

              # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
              lowerCamelCase_				=[
                  'l',
                  'o',
                  'w',
                  'e',
                  'r',
                  's',
                  't',
                  'i',
                  'd',
                  'n',
                  'w</w>',
                  'r</w>',
                  't</w>',
                  'lo',
                  'low',
                  'er</w>',
                  'low</w>',
                  'lowest</w>',
                  'newer</w>',
                  'wider</w>',
                  '<unk>',
              ]
              lowerCamelCase_				=dict(zip(_UpperCAmelCase,						range(len(_UpperCAmelCase    )    )    )    )
              lowerCamelCase_				=['#version: 0.2', 'l o', 'lo w', 'e r</w>', '']

              lowerCamelCase_				=os.path.join(self.tmpdirname,						VOCAB_FILES_NAMES['''vocab_file''']    )
              lowerCamelCase_				=os.path.join(self.tmpdirname,						VOCAB_FILES_NAMES['''merges_file''']    )
              with open(self.vocab_file,						'''w'''    ) as fp:
                     fp.write(json.dumps(_UpperCAmelCase    )    )
              with open(self.merges_file,						'''w'''    ) as fp:
                     fp.write('''\n'''.join(_UpperCAmelCase    )    )






       def 	lowercase__	(				self,						lowerCAmelCase    ):



              """simple docstring"""







              return "lower newer", "lower newer"






       def 	lowercase__	(				self    ):



              """simple docstring"""







              lowerCamelCase_				=OpenAIGPTTokenizer(self.vocab_file,						self.merges_file    )

              lowerCamelCase_				='lower'
              lowerCamelCase_				=['low', 'er</w>']
              lowerCamelCase_				=tokenizer.tokenize(_UpperCAmelCase    )
              self.assertListEqual(_UpperCAmelCase,						_UpperCAmelCase    )

              lowerCamelCase_				=tokens + ['<unk>']
              lowerCamelCase_				=[14, 15, 20]
              self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCAmelCase    ),						_UpperCAmelCase    )






       def 	lowercase__	(				self,						lowerCAmelCase=15    ):



              """simple docstring"""







              for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                     with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''    ):
                            lowerCamelCase_				=self.rust_tokenizer_class.from_pretrained(_UpperCAmelCase,						**_UpperCAmelCase    )

                            # Simple input
                            lowerCamelCase_				='This is a simple input'
                            lowerCamelCase_				=['This is a simple input 1', 'This is a simple input 2']
                            lowerCamelCase_				=('This is a simple input', 'This is a pair')
                            lowerCamelCase_				=[
                                ('This is a simple input 1', 'This is a simple input 2'),
                                ('This is a simple pair 1', 'This is a simple pair 2'),
                            ]

                            # Simple input tests
                            self.assertRaises(_UpperCAmelCase,						tokenizer_r.encode,						_UpperCAmelCase,						max_length=_UpperCAmelCase,						padding='''max_length'''    )

                            # Simple input
                            self.assertRaises(_UpperCAmelCase,						tokenizer_r.encode_plus,						_UpperCAmelCase,						max_length=_UpperCAmelCase,						padding='''max_length'''    )

                            # Simple input
                            self.assertRaises(
                                _UpperCAmelCase,						tokenizer_r.batch_encode_plus,						_UpperCAmelCase,						max_length=_UpperCAmelCase,						padding='''max_length''',						)

                            # Pair input
                            self.assertRaises(_UpperCAmelCase,						tokenizer_r.encode,						_UpperCAmelCase,						max_length=_UpperCAmelCase,						padding='''max_length'''    )

                            # Pair input
                            self.assertRaises(_UpperCAmelCase,						tokenizer_r.encode_plus,						_UpperCAmelCase,						max_length=_UpperCAmelCase,						padding='''max_length'''    )

                            # Pair input
                            self.assertRaises(
                                _UpperCAmelCase,						tokenizer_r.batch_encode_plus,						_UpperCAmelCase,						max_length=_UpperCAmelCase,						padding='''max_length''',						)






       def 	lowercase__	(				self    ):



              """simple docstring"""







              pass





@require_ftfy
@require_spacy
@require_tokenizers
class     __UpperCamelCase			(					a__							):
       pass











'''simple docstring'''




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
  from .tokenization_camembert import CamembertTokenizer
else:
  lowercase__       : Optional[int]         =       None


lowercase__       : List[str]         =       logging.get_logger(__name__)

lowercase__       : Optional[Any]         =       {'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

lowercase__       : List[str]         =       {
    '''vocab_file''': {
        '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model''',
    },
    '''tokenizer_file''': {
        '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/tokenizer.json''',
    },
}

lowercase__       : Dict         =       {
    '''camembert-base''': 5_12,
}

lowercase__       : str         =       '''▁'''


class 					SCREAMING_SNAKE_CASE       (a__				):
     lowerCAmelCase						     =			VOCAB_FILES_NAMES
     lowerCAmelCase						     =			PRETRAINED_VOCAB_FILES_MAP
     lowerCAmelCase						     =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowerCAmelCase						     =			['''input_ids''', '''attention_mask''']
     lowerCAmelCase						     =			CamembertTokenizer


     def __init__(		self		,      _UpperCAmelCase=None		,      _UpperCAmelCase=None		,      _UpperCAmelCase="<s>"		,      _UpperCAmelCase="</s>"		,      _UpperCAmelCase="</s>"		,      _UpperCAmelCase="<s>"		,      _UpperCAmelCase="<unk>"		,      _UpperCAmelCase="<pad>"		,      _UpperCAmelCase="<mask>"		,      _UpperCAmelCase=["<s>NOTUSED", "</s>NOTUSED"]		,      **_UpperCAmelCase		,      ):

          '''simple docstring'''






          __A		:					int						=			AddedToken(_UpperCAmelCase		,      lstrip=_UpperCAmelCase		,      rstrip=_UpperCAmelCase) if isinstance(_UpperCAmelCase		,      _UpperCAmelCase) else mask_token

          super().__init__(
              _UpperCAmelCase		,      tokenizer_file=_UpperCAmelCase		,      bos_token=_UpperCAmelCase		,      eos_token=_UpperCAmelCase		,      sep_token=_UpperCAmelCase		,      cls_token=_UpperCAmelCase		,      unk_token=_UpperCAmelCase		,      pad_token=_UpperCAmelCase		,      mask_token=_UpperCAmelCase		,      additional_special_tokens=_UpperCAmelCase		,      **_UpperCAmelCase		,      )

          __A		:					List[str]						=			vocab_file
          __A		:					Optional[int]						=			False if not self.vocab_file else True


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase		,      _UpperCAmelCase = None):

          '''simple docstring'''






          if token_ids_a is None:
               return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          __A		:					Optional[Any]						=			[self.cls_token_id]
          __A		:					Optional[int]						=			[self.sep_token_id]
          return cls + token_ids_a + sep + sep + token_ids_a + sep


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase		,      _UpperCAmelCase = None):

          '''simple docstring'''






          __A		:					Optional[int]						=			[self.sep_token_id]
          __A		:					List[str]						=			[self.cls_token_id]

          if token_ids_a is None:
               return len(cls + token_ids_a + sep) * [0]
          return len(cls + token_ids_a + sep + sep + token_ids_a + sep) * [0]


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase		,      _UpperCAmelCase = None):

          '''simple docstring'''






          if not self.can_save_slow_tokenizer:
               raise ValueError(
                   'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
                   'tokenizer.')

          if not os.path.isdir(_UpperCAmelCase):
               logger.error(F'Vocabulary path ({save_directory}) should be a directory')
               return
          __A		:					List[Any]						=			os.path.join(
              _UpperCAmelCase		,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])

          if os.path.abspath(self.vocab_file) != os.path.abspath(_UpperCAmelCase):
               copyfile(self.vocab_file		,      _UpperCAmelCase)

          return (out_vocab_file,)