





from collections import OrderedDict
from typing import Mapping

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


snake_case								=							logging.get_logger(__name__)

snake_case								=							{
    """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 					A_					(   UpperCAmelCase						):







       """simple docstring"""





       SCREAMING_SNAKE_CASE_   :			Optional[Any]  			=	'''camembert'''







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

         _lowercase						    =			vocab_size
         _lowercase						    =			hidden_size
         _lowercase						    =			num_hidden_layers
         _lowercase						    =			num_attention_heads
         _lowercase						    =			hidden_act
         _lowercase						    =			intermediate_size
         _lowercase						    =			hidden_dropout_prob
         _lowercase						    =			attention_probs_dropout_prob
         _lowercase						    =			max_position_embeddings
         _lowercase						    =			type_vocab_size
         _lowercase						    =			initializer_range
         _lowercase						    =			layer_norm_eps
         _lowercase						    =			position_embedding_type
         _lowercase						    =			use_cache
         _lowercase						    =			classifier_dropout





class 					A_					(   UpperCAmelCase						):







       """simple docstring"""





       @property
       def  __UpperCAmelCase			(     self						:						Any	)    ->       Mapping[str, Mapping[int, str]]:
         if self.task == "multiple-choice":
           _lowercase						    =			{0: 'batch', 1: 'choice', 2: 'sequence'}
         else:
           _lowercase						    =			{0: 'batch', 1: 'sequence'}
         return OrderedDict(
             [
                 ('input_ids', dynamic_axis),
                 ('attention_mask', dynamic_axis),
             ]	)





'''simple docstring'''



import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer


UpperCamelCase_    	=				logging.get_logger(__name__)

UpperCamelCase_    	=				{"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

UpperCamelCase_    	=				{
    "vocab_file": {
        "distilbert-base-uncased": "https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt",
        "distilbert-base-uncased-distilled-squad": (
            "https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/vocab.txt"
        ),
        "distilbert-base-cased": "https://huggingface.co/distilbert-base-cased/resolve/main/vocab.txt",
        "distilbert-base-cased-distilled-squad": (
            "https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/vocab.txt"
        ),
        "distilbert-base-german-cased": "https://huggingface.co/distilbert-base-german-cased/resolve/main/vocab.txt",
        "distilbert-base-multilingual-cased": (
            "https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/vocab.txt"
        ),
    },
    "tokenizer_file": {
        "distilbert-base-uncased": "https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json",
        "distilbert-base-uncased-distilled-squad": (
            "https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/tokenizer.json"
        ),
        "distilbert-base-cased": "https://huggingface.co/distilbert-base-cased/resolve/main/tokenizer.json",
        "distilbert-base-cased-distilled-squad": (
            "https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/tokenizer.json"
        ),
        "distilbert-base-german-cased": (
            "https://huggingface.co/distilbert-base-german-cased/resolve/main/tokenizer.json"
        ),
        "distilbert-base-multilingual-cased": (
            "https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/tokenizer.json"
        ),
    },
}

UpperCamelCase_    	=				{
    "distilbert-base-uncased": 5_1_2,
    "distilbert-base-uncased-distilled-squad": 5_1_2,
    "distilbert-base-cased": 5_1_2,
    "distilbert-base-cased-distilled-squad": 5_1_2,
    "distilbert-base-german-cased": 5_1_2,
    "distilbert-base-multilingual-cased": 5_1_2,
}


UpperCamelCase_    	=				{
    "distilbert-base-uncased": {"do_lower_case": True},
    "distilbert-base-uncased-distilled-squad": {"do_lower_case": True},
    "distilbert-base-cased": {"do_lower_case": False},
    "distilbert-base-cased-distilled-squad": {"do_lower_case": False},
    "distilbert-base-german-cased": {"do_lower_case": False},
    "distilbert-base-multilingual-cased": {"do_lower_case": False},
}






class 							_a				(			SCREAMING_SNAKE_CASE ):





       '''simple docstring'''






       A						:				List[Any]        =						VOCAB_FILES_NAMES
       A						:				Dict        =						PRETRAINED_VOCAB_FILES_MAP
       A						:				Optional[int]        =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       A						:				Optional[Any]        =						PRETRAINED_INIT_CONFIGURATION
       A						:				Optional[int]        =						['''input_ids''', '''attention_mask''']
       A						:				List[Any]        =						DistilBertTokenizer







       def __init__(      self,							A=None,							A=None,							A=True,							A="[UNK]",							A="[SEP]",							A="[PAD]",							A="[CLS]",							A="[MASK]",							A=True,							A=None,							**A,							):







             '''simple docstring'''







             super().__init__(
                 A,							tokenizer_file=A,							do_lower_case=A,							unk_token=A,							sep_token=A,							pad_token=A,							cls_token=A,							mask_token=A,							tokenize_chinese_chars=A,							strip_accents=A,							**A,							)

             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						json.loads(self.backend_tokenizer.normalizer.__getstate__()  )
             if (
                 normalizer_state.get('lowercase',							A  ) != do_lower_case
                 or normalizer_state.get('strip_accents',							A  ) != strip_accents
                 or normalizer_state.get('handle_chinese_chars',							A  ) != tokenize_chinese_chars
             ):
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						getattr(A,							normalizer_state.pop('type'  )  )
                   SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						do_lower_case
                   SCREAMING_SNAKE_CASE   :      List[str]    					=						strip_accents
                   SCREAMING_SNAKE_CASE   :      List[str]    					=						tokenize_chinese_chars
                   SCREAMING_SNAKE_CASE   :      Dict    					=						normalizer_class(**A  )

             SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						do_lower_case







       def        UpperCamelCase_							(      self,							A,							A=None  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Any    					=						[self.cls_token_id] + token_ids_a + [self.sep_token_id]

             if token_ids_a:
                   output += token_ids_a + [self.sep_token_id]

             return output







       def        UpperCamelCase_							(      self,							A,							A = None  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      List[str]    					=						[self.sep_token_id]
             SCREAMING_SNAKE_CASE   :      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  ) * [0] + len(token_ids_a + sep  ) * [1]







       def        UpperCamelCase_							(      self,							A,							A = None  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      List[str]    					=						self._tokenizer.model.save(A,							name=A  )
             return tuple(A  )


