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:
    lowerCAmelCase__     						=			None

lowerCAmelCase__     						=			logging.get_logger(__name__)

lowerCAmelCase__     						=			{'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

lowerCAmelCase__     						=			{
    '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'
        ),
    },
}

lowerCAmelCase__     						=			{
    'moussaKam/mbarthez': 1024,
    'moussaKam/barthez': 1024,
    'moussaKam/barthez-orangesum-title': 1024,
}

lowerCAmelCase__     						=			'▁'
class     a_			(						SCREAMING_SNAKE_CASE						):






 '''simple docstring'''






 UpperCAmelCase_     			= VOCAB_FILES_NAMES
 UpperCAmelCase_     			= PRETRAINED_VOCAB_FILES_MAP
 UpperCAmelCase_     			= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 UpperCAmelCase_     			= ['input_ids', 'attention_mask']
 UpperCAmelCase_     			= BarthezTokenizer




 def __init__(      self :  int      ,   lowercase__ :  List[str]=None      ,   lowercase__ :  Any=None      ,   lowercase__ :  List[str]="<s>"      ,   lowercase__ :  Any="</s>"      ,   lowercase__ :  int="</s>"      ,   lowercase__ :  List[Any]="<s>"      ,   lowercase__ :  Dict="<unk>"      ,   lowercase__ :  Union[str, Any]="<pad>"      ,   lowercase__ :  Any="<mask>"      ,   **lowercase__ :  Union[str, Any]      ,   ):







        '''simple docstring'''



        lowerCAmelCase__					     = AddedToken(lowercase__      ,   lstrip=lowercase__      ,   rstrip=lowercase__) if isinstance(lowercase__      ,   lowercase__) else mask_token

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

        lowerCAmelCase__					     = vocab_file
        lowerCAmelCase__					     = False if not self.vocab_file else True




 def 		__snake_case						(      self :  Optional[int]      ,   lowercase__ :  List[int]      ,   lowercase__ :  Optional[List[int]] = None):







        '''simple docstring'''



        if token_ids_a is None:
               return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
        lowerCAmelCase__					     = [self.cls_token_id]
        lowerCAmelCase__					     = [self.sep_token_id]
        return cls + token_ids_a + sep + sep + token_ids_a + sep




 def 		__snake_case						(      self :  Any      ,   lowercase__ :  List[int]      ,   lowercase__ :  Optional[List[int]] = None):







        '''simple docstring'''



        lowerCAmelCase__					     = [self.sep_token_id]
        lowerCAmelCase__					     = [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 		__snake_case						(      self :  Union[str, Any]      ,   lowercase__ :  str      ,   lowercase__ :  Optional[str] = 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(lowercase__):
               logger.error(F"""Vocabulary path ({save_directory}) should be a directory""")
               return
        lowerCAmelCase__					     = os.path.join(
            lowercase__      ,   (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])

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

        return (out_vocab_file,)

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


if is_sentencepiece_available():
    from ..ta.tokenization_ta import TaTokenizer
else:
    from ...utils.dummy_sentencepiece_objects import TaTokenizer

lowerCAmelCase__     						=			TaTokenizer

if is_tokenizers_available():
    from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
    from ...utils.dummy_tokenizers_objects import TaTokenizerFast

lowerCAmelCase__     						=			TaTokenizerFast

lowerCAmelCase__     						=			{'configuration_mt5': ['MT5Config', 'MT5OnnxConfig']}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__     						=			[
        'MT5EncoderModel',
        'MT5ForConditionalGeneration',
        'MT5ForQuestionAnswering',
        'MT5Model',
        'MT5PreTrainedModel',
        'MT5Stack',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__     						=			['TFMT5EncoderModel', 'TFMT5ForConditionalGeneration', 'TFMT5Model']

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__     						=			['FlaxMT5EncoderModel', 'FlaxMT5ForConditionalGeneration', 'FlaxMT5Model']


if TYPE_CHECKING:
    from .configuration_mta import MTaConfig, MTaOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mta import (
            MTaEncoderModel,
            MTaForConditionalGeneration,
            MTaForQuestionAnswering,
            MTaModel,
            MTaPreTrainedModel,
            MTaStack,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
    import sys

    lowerCAmelCase__     						=			_LazyModule(
        __name__,
        globals()['__file__'],
        _import_structure,
        extra_objects={'MT5Tokenizer': MTaTokenizer, 'MT5TokenizerFast': MTaTokenizerFast},
        module_spec=__spec__,
    )
