class  __lowerCAmelCase	:



 '''simple docstring'''

 def __init__(      self							:		List[str]	)			->				None:
        # numbermap keys are the number and its values are lists of indexes sorted
        # in ascending order
        _UpperCamelCase  :							dict[int, list[int]]	    =	{}
        # indexmap keys are an index and it's values are the number at that index
        _UpperCamelCase  :							dict[int, int]	    =	{}

 def        __snake_case       (      self							:		Optional[Any]							,      lowerCamelCase							:		list | str | range							,      lowerCamelCase							:		int	)			->				list[int]:
        if isinstance(lowerCamelCase							,      (range, str)	):
               _UpperCamelCase  :							int	    =	list(lowerCamelCase	)
        elif not isinstance(lowerCamelCase							,      lowerCamelCase	):
               raise TypeError(
                   'binary_search_delete() only accepts either a list, range or str'	)

        _UpperCamelCase  :							Optional[int]	    =	0
        _UpperCamelCase  :							List[str]	    =	len(lowerCamelCase	) - 1

        while low <= high:
               _UpperCamelCase  :							List[Any]	    =	(low + high) // 2
               if array[mid] == item:
                      array.pop(lowerCamelCase	)
                      return array
               elif array[mid] < item:
                      _UpperCamelCase  :							Any	    =	mid + 1
               else:
                      _UpperCamelCase  :							List[str]	    =	mid - 1
        raise ValueError(
            'Either the item is not in the array or the array was unsorted'	)

 def        __snake_case       (      self							:		Optional[Any]							,      lowerCamelCase							:		list | str | range							,      lowerCamelCase							:		int	)			->				list[int]:
        if isinstance(lowerCamelCase							,      (range, str)	):
               _UpperCamelCase  :							Tuple	    =	list(lowerCamelCase	)
        elif not isinstance(lowerCamelCase							,      lowerCamelCase	):
               raise TypeError(
                   'binary_search_insert() only accepts either a list, range or str'	)

        _UpperCamelCase  :							Optional[Any]	    =	0
        _UpperCamelCase  :							Any	    =	len(lowerCamelCase	) - 1

        while low <= high:
               _UpperCamelCase  :							Optional[int]	    =	(low + high) // 2
               if array[mid] == index:
                      # If the item already exists in the array,
                      # insert it after the existing item
                      array.insert(mid + 1							,      lowerCamelCase	)
                      return array
               elif array[mid] < index:
                      _UpperCamelCase  :							int	    =	mid + 1
               else:
                      _UpperCamelCase  :							int	    =	mid - 1

        # If the item doesn't exist in the array, insert it at the appropriate position
        array.insert(lowerCamelCase							,      lowerCamelCase	)
        return array

 def        __snake_case       (      self							:		int							,      lowerCamelCase							:		int							,      lowerCamelCase							:		int	)			->				None:
        # Remove previous index
        if index in self.indexmap:
               _UpperCamelCase  :							List[Any]	    =	self.indexmap[index]
               if len(self.numbermap[n]	) == 1:
                      del self.numbermap[n]
               else:
                      _UpperCamelCase  :							Optional[Any]	    =	self.binary_search_delete(self.numbermap[n]							,      lowerCamelCase	)

        # Set new index
        _UpperCamelCase  :							int	    =	number

        # Number not seen before or empty so insert number value
        if number not in self.numbermap:
               _UpperCamelCase  :							Optional[Any]	    =	[index]

        # Here we need to perform a binary search insertion in order to insert
        # The item in the correct place
        else:
               _UpperCamelCase  :							Dict	    =	self.binary_search_insert(
                   self.numbermap[number]							,      lowerCamelCase	)

 def        __snake_case       (      self							:		Any							,      lowerCamelCase							:		int	)			->				int:
        return self.numbermap.get(lowerCamelCase							,      [-1]	)[0]


if __name__ == "__main__":
 import doctest

 doctest.testmod()




from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase      		=					logging.get_logger(__name__)

UpperCAmelCase      		=					{
    '''flaubert/flaubert_small_cased''': '''https://huggingface.co/flaubert/flaubert_small_cased/resolve/main/config.json''',
    '''flaubert/flaubert_base_uncased''': '''https://huggingface.co/flaubert/flaubert_base_uncased/resolve/main/config.json''',
    '''flaubert/flaubert_base_cased''': '''https://huggingface.co/flaubert/flaubert_base_cased/resolve/main/config.json''',
    '''flaubert/flaubert_large_cased''': '''https://huggingface.co/flaubert/flaubert_large_cased/resolve/main/config.json''',
}




class  __lowerCAmelCase	(							a_    ):



 '''simple docstring'''
 _lowerCamelCase    :						List[Any]					     =			'flaubert'
 _lowerCamelCase    :						List[str]					     =			{
     'hidden_size': 'emb_dim',
     'num_attention_heads': 'n_heads',
     'num_hidden_layers': 'n_layers',
     'n_words': 'vocab_size',  # For backward compatibility
 }

 def __init__(      self							:		List[Any]							,      lowerCamelCase							:		Tuple=False							,      lowerCamelCase							:		str=0.0							,      lowerCamelCase							:		int=3_0_1_4_5							,      lowerCamelCase							:		List[str]=2_0_4_8							,      lowerCamelCase							:		List[str]=1_2							,      lowerCamelCase							:		Dict=1_6							,      lowerCamelCase							:		Any=0.1							,      lowerCamelCase							:		List[str]=0.1							,      lowerCamelCase							:		List[str]=True							,      lowerCamelCase							:		Any=False							,      lowerCamelCase							:		Optional[int]=False							,      lowerCamelCase							:		int=False							,      lowerCamelCase							:		Optional[Any]=1							,      lowerCamelCase							:		int=True							,      lowerCamelCase							:		str=5_1_2							,      lowerCamelCase							:		Tuple=2_0_4_8**-0.5							,      lowerCamelCase							:		str=1e-12							,      lowerCamelCase							:		Any=0.0_2							,      lowerCamelCase							:		Dict=0							,      lowerCamelCase							:		Union[str, Any]=1							,      lowerCamelCase							:		List[Any]=2							,      lowerCamelCase							:		Union[str, Any]=3							,      lowerCamelCase							:		List[Any]=5							,      lowerCamelCase							:		int=True							,      lowerCamelCase							:		Dict="first"							,      lowerCamelCase							:		Optional[int]=True							,      lowerCamelCase							:		Any=None							,      lowerCamelCase							:		Optional[int]=True							,      lowerCamelCase							:		List[str]=0.1							,      lowerCamelCase							:		List[Any]=5							,      lowerCamelCase							:		Optional[Any]=5							,      lowerCamelCase							:		str=0							,      lowerCamelCase							:		Optional[int]=0							,      lowerCamelCase							:		List[str]=2							,      lowerCamelCase							:		Any=0							,      **lowerCamelCase							:		Tuple							,      )			->				Any:
        _UpperCamelCase  :							Optional[Any]	    =	pre_norm
        _UpperCamelCase  :							Optional[int]	    =	layerdrop
        _UpperCamelCase  :							Dict	    =	vocab_size
        _UpperCamelCase  :							Dict	    =	emb_dim
        _UpperCamelCase  :							int	    =	n_layers
        _UpperCamelCase  :							Tuple	    =	n_heads
        _UpperCamelCase  :							Tuple	    =	dropout
        _UpperCamelCase  :							Any	    =	attention_dropout
        _UpperCamelCase  :							Union[str, Any]	    =	gelu_activation
        _UpperCamelCase  :							Dict	    =	sinusoidal_embeddings
        _UpperCamelCase  :							str	    =	causal
        _UpperCamelCase  :							str	    =	asm
        _UpperCamelCase  :							Tuple	    =	n_langs
        _UpperCamelCase  :							Optional[int]	    =	use_lang_emb
        _UpperCamelCase  :							Optional[Any]	    =	layer_norm_eps
        _UpperCamelCase  :							Optional[Any]	    =	bos_index
        _UpperCamelCase  :							Dict	    =	eos_index
        _UpperCamelCase  :							Union[str, Any]	    =	pad_index
        _UpperCamelCase  :							Union[str, Any]	    =	unk_index
        _UpperCamelCase  :							Optional[Any]	    =	mask_index
        _UpperCamelCase  :							Any	    =	is_encoder
        _UpperCamelCase  :							List[str]	    =	max_position_embeddings
        _UpperCamelCase  :							Union[str, Any]	    =	embed_init_std
        _UpperCamelCase  :							Optional[int]	    =	init_std
        _UpperCamelCase  :							Any	    =	summary_type
        _UpperCamelCase  :							Any	    =	summary_use_proj
        _UpperCamelCase  :							Optional[int]	    =	summary_activation
        _UpperCamelCase  :							Union[str, Any]	    =	summary_proj_to_labels
        _UpperCamelCase  :							Dict	    =	summary_first_dropout
        _UpperCamelCase  :							Union[str, Any]	    =	start_n_top
        _UpperCamelCase  :							Any	    =	end_n_top
        _UpperCamelCase  :							List[Any]	    =	mask_token_id
        _UpperCamelCase  :							str	    =	lang_id

        if "n_words" in kwargs:
               _UpperCamelCase  :							Tuple	    =	kwargs['n_words']

        super().__init__(pad_token_id=lowerCamelCase							,      bos_token_id=lowerCamelCase							,      **lowerCamelCase	)







class  __lowerCAmelCase	(							a_    ):



 '''simple docstring'''

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



