




'''simple docstring'''




import re

from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P


# Sentinels
a_ :						List[str]				 =			object()

# For specifying empty leaf dict `{}`
a_ :						str				 =			object()





def 	a_				( __snake_case				:     Any  ,			__snake_case				:     Dict  )				->		Optional[Any]:



       """simple docstring"""
       lowerCamelCase_				=tuple((re.compile(x + '''$'''  ) for x in qs)  )
       for i in range(len(__snake_case  ) - len(__snake_case  ) + 1  ):
              lowerCamelCase_				=[x.match(__snake_case  ) for x, y in zip(__snake_case  ,			ks[i:]  )]
              if matches and all(__snake_case  ):
                     return True
       return False





def 	a_				( __snake_case				:     Tuple  )				->		Optional[Any]:



       """simple docstring"""
       def replace(__snake_case				:     int  ,			__snake_case				:     Optional[Any]  ):
              for rule, replacement in rules:
                     if _match(__snake_case  ,			__snake_case  ):
                            return replacement
              return val

       return replace





def 	a_				( )				->		Dict:



       """simple docstring"""
       return [
           # embeddings
           (("transformer", "wpe", "embedding"), P('''mp'''  ,			__snake_case  )),
           (("transformer", "wte", "embedding"), P('''mp'''  ,			__snake_case  )),
           # atention
           (("attention", "(q_proj|k_proj|v_proj)", "kernel"), P(__snake_case  ,			'''mp'''  )),
           (("attention", "out_proj", "kernel"), P('''mp'''  ,			__snake_case  )),
           (("attention", "out_proj", "bias"), None),
           # mlp
           (("mlp", "c_fc", "kernel"), P(__snake_case  ,			'''mp'''  )),
           (("mlp", "c_fc", "bias"), P('''mp'''  )),
           (("mlp", "c_proj", "kernel"), P('''mp'''  ,			__snake_case  )),
           (("mlp", "c_proj", "bias"), None),
           # layer norms
           ((r"ln_\d+", "bias"), None),
           ((r"\d+", r"ln_\d+", "scale"), None),
           (("ln_f", "bias"), None),
           (("ln_f", "scale"), None),
       ]





def 	a_				( __snake_case				:     str  )				->		Tuple:



       """simple docstring"""
       lowerCamelCase_				=_get_partition_rules()
       lowerCamelCase_				=_replacement_rules(__snake_case  )
       lowerCamelCase_				={k: _unmatched for k in flatten_dict(__snake_case  )}
       lowerCamelCase_				={k: replace(__snake_case  ,			__snake_case  ) for k, v in initd.items()}
       assert _unmatched not in result.values(), "Incomplete partition spec."
       return freeze(unflatten_dict(__snake_case  )  )











'''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,)