


'''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_barthez import BarthezTokenizer
else:
   A				:					Any     =			None

A				:					Optional[int]     =			logging.get_logger(__name__)

A				:					List[str]     =			{"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

A				:					List[Any]     =			{
    """vocab_file""": {
        """moussaKam/mbarthez""": """https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model""",
        """moussaKam/barthez""": """https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model""",
        """moussaKam/barthez-orangesum-title""": (
            """https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model"""
        ),
    },
    """tokenizer_file""": {
        """moussaKam/mbarthez""": """https://huggingface.co/moussaKam/mbarthez/resolve/main/tokenizer.json""",
        """moussaKam/barthez""": """https://huggingface.co/moussaKam/barthez/resolve/main/tokenizer.json""",
        """moussaKam/barthez-orangesum-title""": (
            """https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/tokenizer.json"""
        ),
    },
}

A				:					Any     =			{
    """moussaKam/mbarthez""": 1024,
    """moussaKam/barthez""": 1024,
    """moussaKam/barthez-orangesum-title""": 1024,
}

A				:					Union[str, Any]     =			"""▁"""


class 			__lowerCamelCase			(	lowerCAmelCase__	):
    """simple docstring"""
    a													=   VOCAB_FILES_NAMES
    a													=   PRETRAINED_VOCAB_FILES_MAP
    a													=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a													=   ["input_ids", "attention_mask"]
    a													=   BarthezTokenizer


    def __init__(  self      :							Optional[int]				,							SCREAMING_SNAKE_CASE      :							Optional[Any]=None				,							SCREAMING_SNAKE_CASE      :							Tuple=None				,							SCREAMING_SNAKE_CASE      :							Optional[int]="<s>"				,							SCREAMING_SNAKE_CASE      :							List[str]="</s>"				,							SCREAMING_SNAKE_CASE      :							int="</s>"				,							SCREAMING_SNAKE_CASE      :							Tuple="<s>"				,							SCREAMING_SNAKE_CASE      :							Optional[int]="<unk>"				,							SCREAMING_SNAKE_CASE      :							List[Any]="<pad>"				,							SCREAMING_SNAKE_CASE      :							Any="<mask>"				,							**SCREAMING_SNAKE_CASE      :							List[str]				,							):
           # Mask token behave like a normal word, i.e. include the space before it
           _A					:     Union[str, Any]     = AddedToken(a__				,							lstrip=a__				,							rstrip=a__) if isinstance(a__				,							a__) else mask_token

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

           _A					:     List[Any]     = vocab_file
           _A					:     List[Any]     = False if not self.vocab_file else True


    def        A   (  self      :							Dict				,							SCREAMING_SNAKE_CASE      :							Optional[int]				,							SCREAMING_SNAKE_CASE      :							Tuple = None):

           if token_ids_a is None:
                  return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
           _A					:     int     = [self.cls_token_id]
           _A					:     List[str]     = [self.sep_token_id]
           return cls + token_ids_a + sep + sep + token_ids_a + sep


    def        A   (  self      :							Any				,							SCREAMING_SNAKE_CASE      :							Optional[Any]				,							SCREAMING_SNAKE_CASE      :							Union[str, Any] = None):
           _A					:     List[Any]     = [self.sep_token_id]
           _A					:     Optional[Any]     = [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        A   (  self      :							Tuple				,							SCREAMING_SNAKE_CASE      :							List[Any]				,							SCREAMING_SNAKE_CASE      :							Any = None):
           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(a__):
                  logger.error(F'Vocabulary path ({save_directory}) should be a directory')
                  return
           _A					:     Dict     = os.path.join(
               a__				,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])

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

           return (out_vocab_file,)










'''simple docstring'''







class 			__lowerCamelCase			:  # Public class to implement a graph
    """simple docstring"""


    def __init__(  self      :							Optional[Any]				,							SCREAMING_SNAKE_CASE      :							int				,							SCREAMING_SNAKE_CASE      :							int				,							SCREAMING_SNAKE_CASE      :							list[list[bool]]):
           _A					:     List[Any]     = row
           _A					:     Union[str, Any]     = col
           _A					:     List[str]     = graph


    def        A   (  self      :							Any				,							SCREAMING_SNAKE_CASE      :							int				,							SCREAMING_SNAKE_CASE      :							int				,							SCREAMING_SNAKE_CASE      :							list[list[bool]]):
           return (
               0 <= i < self.ROW
               and 0 <= j < self.COL
               and not visited[i][j]
               and self.graph[i][j]
           )


    def        A   (  self      :							Tuple				,							SCREAMING_SNAKE_CASE      :							int				,							SCREAMING_SNAKE_CASE      :							int				,							SCREAMING_SNAKE_CASE      :							list[list[bool]]):
           # Checking all 8 elements surrounding nth element
           _A					:     Tuple     = [-1, -1, -1, 0, 0, 1, 1, 1]  # Coordinate order
           _A					:     Dict     = [-1, 0, 1, -1, 1, -1, 0, 1]
           _A					:     List[Any]     = True  # Make those cells visited
           for k in range(8):
                  if self.is_safe(i + row_nbr[k]				,							j + col_nbr[k]				,							SCREAMING_SNAKE_CASE):
                         self.diffs(i + row_nbr[k]				,							j + col_nbr[k]				,							SCREAMING_SNAKE_CASE)


    def        A   (  self      :							int):  # And finally, count all islands.
           _A					:     Dict     = [[False for j in range(self.COL)] for i in range(self.ROW)]
           _A					:     Union[str, Any]     = 0
           for i in range(self.ROW):
                  for j in range(self.COL):
                         if visited[i][j] is False and self.graph[i][j] == 1:
                                self.diffs(SCREAMING_SNAKE_CASE				,							SCREAMING_SNAKE_CASE				,							SCREAMING_SNAKE_CASE)
                                count += 1
           return count






