

import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer


snake_case_			  = logging.get_logger(__name__)

snake_case_			  = {'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

snake_case_			  = {
    '''vocab_file''': {
        '''yjernite/retribert-base-uncased''': (
            '''https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/vocab.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''yjernite/retribert-base-uncased''': (
            '''https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/tokenizer.json'''
        ),
    },
}

snake_case_			  = {
    '''yjernite/retribert-base-uncased''': 512,
}


snake_case_			  = {
    '''yjernite/retribert-base-uncased''': {'''do_lower_case''': True},
}


class       SCREAMING_SNAKE_CASE__					(__snake_case     ):
    __lowerCamelCase						:       Optional[Any]														=     VOCAB_FILES_NAMES
    __lowerCamelCase						:       Any														=     PRETRAINED_VOCAB_FILES_MAP
    __lowerCamelCase						:       Tuple														=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __lowerCamelCase						:       Dict														=     PRETRAINED_INIT_CONFIGURATION
    __lowerCamelCase						:       Optional[int]														=     RetriBertTokenizer
    __lowerCamelCase						:       List[Any]														=     ["""input_ids""", """attention_mask"""]





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

         lowercase__    :   Dict      =       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
         ):
              lowercase__    :   Optional[Any]      =       getattr(a						,   normalizer_state.pop('type'))
              lowercase__    :   Union[str, Any]      =       do_lower_case
              lowercase__    :   int      =       strip_accents
              lowercase__    :   int      =       tokenize_chinese_chars
              lowercase__    :   str      =       normalizer_class(**a)

         lowercase__    :   Any      =       do_lower_case





    def       snake_case_				(      self						,   a						,   a=None):
         lowercase__    :   Optional[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       snake_case_				(      self						,   a						,   a = None):
         lowercase__    :   List[Any]      =       [self.sep_token_id]
         lowercase__    :   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) * [0] + len(token_ids_a + sep) * [1]





    def       snake_case_				(      self						,   a						,   a = None):
         lowercase__    :   List[str]      =       self._tokenizer.model.save(a						,   name=a)
         return tuple(a)




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_			  = {
    '''distilbert-base-uncased''': '''https://huggingface.co/distilbert-base-uncased/resolve/main/config.json''',
    '''distilbert-base-uncased-distilled-squad''': (
        '''https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/config.json'''
    ),
    '''distilbert-base-cased''': '''https://huggingface.co/distilbert-base-cased/resolve/main/config.json''',
    '''distilbert-base-cased-distilled-squad''': (
        '''https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/config.json'''
    ),
    '''distilbert-base-german-cased''': '''https://huggingface.co/distilbert-base-german-cased/resolve/main/config.json''',
    '''distilbert-base-multilingual-cased''': (
        '''https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/config.json'''
    ),
    '''distilbert-base-uncased-finetuned-sst-2-english''': (
        '''https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/resolve/main/config.json'''
    ),
}


class       SCREAMING_SNAKE_CASE__					(__snake_case     ):
    __lowerCamelCase						:       Any														=     """distilbert"""
    __lowerCamelCase						:       List[Any]														=     {
        """hidden_size""": """dim""",
        """num_attention_heads""": """n_heads""",
        """num_hidden_layers""": """n_layers""",
    }





    def __init__(      self						,   a=3_0522						,   a=512						,   a=False						,   a=6						,   a=12						,   a=768						,   a=4 * 768						,   a=0.1						,   a=0.1						,   a="gelu"						,   a=0.02						,   a=0.1						,   a=0.2						,   a=0						,   **a						,   ):
         lowercase__    :   int      =       vocab_size
         lowercase__    :   int      =       max_position_embeddings
         lowercase__    :   List[str]      =       sinusoidal_pos_embds
         lowercase__    :   Tuple      =       n_layers
         lowercase__    :   Optional[int]      =       n_heads
         lowercase__    :   List[Any]      =       dim
         lowercase__    :   Any      =       hidden_dim
         lowercase__    :   Union[str, Any]      =       dropout
         lowercase__    :   Optional[int]      =       attention_dropout
         lowercase__    :   List[Any]      =       activation
         lowercase__    :   Union[str, Any]      =       initializer_range
         lowercase__    :   Dict      =       qa_dropout
         lowercase__    :   Tuple      =       seq_classif_dropout
         super().__init__(**a						,   pad_token_id=a)



class       SCREAMING_SNAKE_CASE__					(__snake_case     ):





    @property
    def       snake_case_				(      self):
         if self.task == "multiple-choice":
              lowercase__    :   List[str]      =       {0: 'batch', 1: 'choice', 2: 'sequence'}
         else:
              lowercase__    :   Tuple      =       {0: 'batch', 1: 'sequence'}
         return OrderedDict(
             [
                 ('input_ids', dynamic_axis),
                 ('attention_mask', dynamic_axis),
             ])

