



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


a__    =	logging.get_logger(__name__)

a__    =	{
    """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/config.json""",
    """umberto-commoncrawl-cased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"""
    ),
    """umberto-wikipedia-uncased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"""
    ),
}







class 		snake_case						(	_snake_case  ):



   '''simple docstring'''






   snake_case_					: Tuple          =		'camembert'

   def __init__(					self							:			int				,		lowerCAmelCase							:			List[Any]=3_0522				,		lowerCAmelCase							:			List[Any]=768				,		lowerCAmelCase							:			str=12				,		lowerCAmelCase							:			List[str]=12				,		lowerCAmelCase							:			Optional[Any]=3072				,		lowerCAmelCase							:			Tuple="gelu"				,		lowerCAmelCase							:			List[str]=0.1				,		lowerCAmelCase							:			Tuple=0.1				,		lowerCAmelCase							:			Union[str, Any]=512				,		lowerCAmelCase							:			Dict=2				,		lowerCAmelCase							:			Tuple=0.02				,		lowerCAmelCase							:			List[Any]=1E-12				,		lowerCAmelCase							:			Union[str, Any]=1				,		lowerCAmelCase							:			Optional[Any]=0				,		lowerCAmelCase							:			List[Any]=2				,		lowerCAmelCase							:			List[str]="absolute"				,		lowerCAmelCase							:			int=True				,		lowerCAmelCase							:			Any=None				,		**lowerCAmelCase							:			Optional[Any]				,		)				->				Optional[int]:

    """simple docstring"""







    super().__init__(pad_token_id=lowerCAmelCase				,		bos_token_id=lowerCAmelCase				,		eos_token_id=lowerCAmelCase				,		**lowerCAmelCase)

    _snake_case    :  Optional[Any]					=					vocab_size
    _snake_case    :  List[str]					=					hidden_size
    _snake_case    :  List[str]					=					num_hidden_layers
    _snake_case    :  int					=					num_attention_heads
    _snake_case    :  str					=					hidden_act
    _snake_case    :  str					=					intermediate_size
    _snake_case    :  Optional[int]					=					hidden_dropout_prob
    _snake_case    :  Optional[int]					=					attention_probs_dropout_prob
    _snake_case    :  int					=					max_position_embeddings
    _snake_case    :  Dict					=					type_vocab_size
    _snake_case    :  Dict					=					initializer_range
    _snake_case    :  Optional[Any]					=					layer_norm_eps
    _snake_case    :  Optional[int]					=					position_embedding_type
    _snake_case    :  Any					=					use_cache
    _snake_case    :  Tuple					=					classifier_dropout







class 		snake_case						(	_snake_case  ):



   '''simple docstring'''






   @property
   def      UpperCamelCase_  (					self							:			Optional[Any])				->				Any:

    """simple docstring"""







    if self.task == "multiple-choice":
     _snake_case    :  Dict					=					{0: """batch""", 1: """choice""", 2: """sequence"""}
    else:
     _snake_case    :  Tuple					=					{0: """batch""", 1: """sequence"""}
    return OrderedDict(
        [
            ("""input_ids""", dynamic_axis),
            ("""attention_mask""", dynamic_axis),
        ])





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:
  a__    =	None


a__    =	logging.get_logger(__name__)

a__    =	{"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

a__    =	{
    """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""",
    },
}

a__    =	{
    """camembert-base""": 5_12,
}

a__    =	"""▁"""







class 		snake_case						(	SCREAMING_SNAKE_CASE_  ):



   '''simple docstring'''






   snake_case_					: List[str]          =		VOCAB_FILES_NAMES
   snake_case_					: str          =		PRETRAINED_VOCAB_FILES_MAP
   snake_case_					: Optional[Any]          =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   snake_case_					: List[Any]          =		["""input_ids""", """attention_mask"""]
   snake_case_					: int          =		CamembertTokenizer

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

    """simple docstring"""







    _snake_case    :  Dict					=					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				,		sep_token=lowerCAmelCase				,		cls_token=lowerCAmelCase				,		unk_token=lowerCAmelCase				,		pad_token=lowerCAmelCase				,		mask_token=lowerCAmelCase				,		additional_special_tokens=lowerCAmelCase				,		**lowerCAmelCase				,		)

    _snake_case    :  List[str]					=					vocab_file
    _snake_case    :  Optional[Any]					=					False if not self.vocab_file else True

   def      UpperCamelCase_  (					self							:			Optional[int]				,		lowerCAmelCase							:			List[int]				,		lowerCAmelCase							:			Optional[List[int]] = None)				->				List[int]:

    """simple docstring"""







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

   def      UpperCamelCase_  (					self							:			str				,		lowerCAmelCase							:			List[int]				,		lowerCAmelCase							:			Optional[List[int]] = None)				->				List[int]:

    """simple docstring"""







    _snake_case    :  str					=					[self.sep_token_id]
    _snake_case    :  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      UpperCamelCase_  (					self							:			str				,		lowerCAmelCase							:			str				,		lowerCAmelCase							:			Optional[str] = None)				->				Tuple[str]:

    """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(lowerCAmelCase):
     logger.error(F'''Vocabulary path ({save_directory}) should be a directory''')
     return
    _snake_case    :  Optional[int]					=					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,)
