



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:
     SCREAMING_SNAKE_CASE_:Dict					=						None

SCREAMING_SNAKE_CASE_:Tuple					=						logging.get_logger(__name__)

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

SCREAMING_SNAKE_CASE_:str					=						{
    """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"""
        ),
    },
}

SCREAMING_SNAKE_CASE_:Optional[int]					=						{
    """moussaKam/mbarthez""": 1_024,
    """moussaKam/barthez""": 1_024,
    """moussaKam/barthez-orangesum-title""": 1_024,
}

SCREAMING_SNAKE_CASE_:List[str]					=						"""▁"""






class SCREAMING_SNAKE_CASE__					(		SCREAMING_SNAKE_CASE__   ):




    '''simple docstring'''






    __lowerCamelCase      :			Optional[Any] =				VOCAB_FILES_NAMES
    __lowerCamelCase      :			Optional[int] =				PRETRAINED_VOCAB_FILES_MAP
    __lowerCamelCase      :			Optional[Any] =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __lowerCamelCase      :			Union[str, Any] =				["input_ids", "attention_mask"]
    __lowerCamelCase      :			int =				BarthezTokenizer






    def __init__(	self,		lowerCamelCase__=None,		lowerCamelCase__=None,		lowerCamelCase__="<s>",		lowerCamelCase__="</s>",		lowerCamelCase__="</s>",		lowerCamelCase__="<s>",		lowerCamelCase__="<unk>",		lowerCamelCase__="<pad>",		lowerCamelCase__="<mask>",		**lowerCamelCase__,		):
        # Mask token behave like a normal word, i.e. include the space before it
        A			:	int										=       AddedToken(lowerCamelCase__,		lstrip=lowerCamelCase__,		rstrip=lowerCamelCase__		) if isinstance(lowerCamelCase__,		lowerCamelCase__		) else mask_token

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

        A			:	str										=       vocab_file
        A			:	Any										=       False if not self.vocab_file else True






    def       _lowerCAmelCase (	self,		lowerCamelCase__,		lowerCamelCase__ = None		):

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






    def       _lowerCAmelCase (	self,		lowerCamelCase__,		lowerCamelCase__ = None		):
        A			:	List[str]										=       [self.sep_token_id]
        A			:	Dict										=       [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       _lowerCAmelCase (	self,		lowerCamelCase__,		lowerCamelCase__ = 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(lowerCamelCase__		):
            logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''		)
            return
        A			:	Any										=       os.path.join(
            lowerCamelCase__,		(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]		)

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

        return (out_vocab_file,)







import socket




def      __UpperCamelCase     (  )	->  Optional[int]:



    """simple docstring"""






    A			:	str										=       socket.socket(socket.AF_INET				,					socket.SOCK_STREAM		)
    A			:	Union[str, Any]										=       socket.gethostname()
    A			:	Dict										=       1_2312

    sock.connect((host, port)		)
    sock.send(B"""Hello server!"""		)

    with open("""Received_file"""				,					"""wb"""		) as out_file:
        print("""File opened"""		)
        print("""Receiving data..."""		)
        while True:
            A			:	Optional[int]										=       sock.recv(1024		)
            if not data:
                break
            out_file.write(_lowerCAmelCase		)

    print("""Successfully received the file"""		)
    sock.close()
    print("""Connection closed"""		)


if __name__ == "__main__":
     main()


