code: 
  
  
  
  
  
  
  from collections import OrderedDict
  from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
  
  from ...configuration_utils import PretrainedConfig
  from ...onnx import OnnxConfig
  from ...utils import logging
  
  
  if TYPE_CHECKING:
   from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType
  
  
  lowerCamelCase			:							Any       =logging.get_logger(__name__)
  
  lowerCamelCase			:							Optional[int]       ={
      '''microsoft/deberta-base''': '''https://huggingface.co/microsoft/deberta-base/resolve/main/config.json''',
      '''microsoft/deberta-large''': '''https://huggingface.co/microsoft/deberta-large/resolve/main/config.json''',
      '''microsoft/deberta-xlarge''': '''https://huggingface.co/microsoft/deberta-xlarge/resolve/main/config.json''',
      '''microsoft/deberta-base-mnli''': '''https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/config.json''',
      '''microsoft/deberta-large-mnli''': '''https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/config.json''',
      '''microsoft/deberta-xlarge-mnli''': '''https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/config.json''',
  }
  
  
  
  
  
  class     __a						(					A__ ):
   _lowerCAmelCase : Optional[int] 				=				'''deberta'''
  
  
  
  
  
  
  
   def __init__(	self      :     Tuple							,     SCREAMING_SNAKE_CASE      :     Any=5_02_65							,     SCREAMING_SNAKE_CASE      :     Optional[int]=7_68							,     SCREAMING_SNAKE_CASE      :     str=12							,     SCREAMING_SNAKE_CASE      :     Dict=12							,     SCREAMING_SNAKE_CASE      :     Dict=30_72							,     SCREAMING_SNAKE_CASE      :     List[str]="gelu"							,     SCREAMING_SNAKE_CASE      :     List[Any]=0.1							,     SCREAMING_SNAKE_CASE      :     List[str]=0.1							,     SCREAMING_SNAKE_CASE      :     str=5_12							,     SCREAMING_SNAKE_CASE      :     Any=0							,     SCREAMING_SNAKE_CASE      :     List[str]=0.0_2							,     SCREAMING_SNAKE_CASE      :     List[Any]=1e-7							,     SCREAMING_SNAKE_CASE      :     Union[str, Any]=False							,     SCREAMING_SNAKE_CASE      :     str=-1							,     SCREAMING_SNAKE_CASE      :     List[str]=0							,     SCREAMING_SNAKE_CASE      :     List[str]=True							,     SCREAMING_SNAKE_CASE      :     int=None							,     SCREAMING_SNAKE_CASE      :     Optional[int]=0							,     SCREAMING_SNAKE_CASE      :     Optional[Any]="gelu"							,     **SCREAMING_SNAKE_CASE      :     Union[str, Any]							,     ):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        super().__init__(**SCREAMING_SNAKE_CASE		)
  
        UpperCamelCase__    :     Optional[int]        = hidden_size
        UpperCamelCase__    :     Tuple        = num_hidden_layers
        UpperCamelCase__    :     Optional[int]        = num_attention_heads
        UpperCamelCase__    :     Dict        = intermediate_size
        UpperCamelCase__    :     Optional[Any]        = hidden_act
        UpperCamelCase__    :     List[Any]        = hidden_dropout_prob
        UpperCamelCase__    :     Union[str, Any]        = attention_probs_dropout_prob
        UpperCamelCase__    :     List[str]        = max_position_embeddings
        UpperCamelCase__    :     Optional[Any]        = type_vocab_size
        UpperCamelCase__    :     Any        = initializer_range
        UpperCamelCase__    :     Tuple        = relative_attention
        UpperCamelCase__    :     Optional[int]        = max_relative_positions
        UpperCamelCase__    :     List[Any]        = pad_token_id
        UpperCamelCase__    :     Optional[int]        = position_biased_input
  
        # Backwards compatibility
        if type(SCREAMING_SNAKE_CASE		) == str:
             UpperCamelCase__    :     List[Any]        = [x.strip() for x in pos_att_type.lower().split("|"		)]
  
        UpperCamelCase__    :     Dict        = pos_att_type
        UpperCamelCase__    :     Optional[Any]        = vocab_size
        UpperCamelCase__    :     List[str]        = layer_norm_eps
  
        UpperCamelCase__    :     List[Any]        = kwargs.get("pooler_hidden_size"							,     SCREAMING_SNAKE_CASE		)
        UpperCamelCase__    :     str        = pooler_dropout
        UpperCamelCase__    :     Optional[int]        = pooler_hidden_act
  
  
  
  
  
  
  
  class     __a						(					A__ ):
  
  
  
  
  
  
  
   @property
   def       __lowercase      (	self      :     List[str]		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        if self.task == "multiple-choice":
             UpperCamelCase__    :     Tuple        = {0: "batch", 1: "choice", 2: "sequence"}
        else:
             UpperCamelCase__    :     List[str]        = {0: "batch", 1: "sequence"}
        if self._config.type_vocab_size > 0:
             return OrderedDict(
                 [("input_ids", dynamic_axis), ("attention_mask", dynamic_axis), ("token_type_ids", dynamic_axis)]		)
        else:
             return OrderedDict([("input_ids", dynamic_axis), ("attention_mask", dynamic_axis)]		)
  
  
  
  
  
  
  
   @property
   def       __lowercase      (	self      :     Tuple		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        return 12
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     str							,     SCREAMING_SNAKE_CASE      :     Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"]							,     SCREAMING_SNAKE_CASE      :     int = -1							,     SCREAMING_SNAKE_CASE      :     int = -1							,     SCREAMING_SNAKE_CASE      :     int = -1							,     SCREAMING_SNAKE_CASE      :     bool = False							,     SCREAMING_SNAKE_CASE      :     Optional["TensorType"] = None							,     SCREAMING_SNAKE_CASE      :     int = 3							,     SCREAMING_SNAKE_CASE      :     int = 40							,     SCREAMING_SNAKE_CASE      :     int = 40							,     SCREAMING_SNAKE_CASE      :     "PreTrainedTokenizerBase" = None							,     ):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        UpperCamelCase__    :     Optional[int]        = super().generate_dummy_inputs(preprocessor=SCREAMING_SNAKE_CASE							,     framework=SCREAMING_SNAKE_CASE		)
        if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
             del dummy_inputs["token_type_ids"]
        return dummy_inputs
style_context: 
  
  
  
  
  
  
  from __future__ import annotations
  
  
  
  
  
  
  
  def 	SCREAMING_SNAKE_CASE							(      __lowerCAmelCase    )				->			list[int]:
       if not list_of_ints:
            return []
  
       if min(__lowerCAmelCase    ) < 0:
            raise ValueError("All numbers must be positive"    )
  
       UpperCamelCase__    :     Dict        =						max(len(bin(__lowerCAmelCase    )[2:]    ) for x in list_of_ints    )
       return _msd_radix_sort(__lowerCAmelCase      ,					__lowerCAmelCase    )
  
  
  
  
  
  
  
  def 	SCREAMING_SNAKE_CASE							(      __lowerCAmelCase      ,					__lowerCAmelCase    )				->			list[int]:
       if bit_position == 0 or len(__lowerCAmelCase    ) in [0, 1]:
            return list_of_ints
  
       UpperCamelCase__    :     Union[str, Any]        =						[]
       UpperCamelCase__    :     Dict        =						[]
       # Split numbers based on bit at bit_position from the right
       for number in list_of_ints:
            if (number >> (bit_position - 1)) & 1:
                 # number has a one at bit bit_position
                 ones.append(__lowerCAmelCase    )
            else:
                 # number has a zero at bit bit_position
                 zeros.append(__lowerCAmelCase    )
  
      # recursively split both lists further
       UpperCamelCase__    :     str        =						_msd_radix_sort(__lowerCAmelCase      ,					bit_position - 1    )
       UpperCamelCase__    :     Optional[Any]        =						_msd_radix_sort(__lowerCAmelCase      ,					bit_position - 1    )
  
       # recombine lists
       UpperCamelCase__    :     Optional[int]        =						zeros
       res.extend(__lowerCAmelCase    )
  
       return res
  
  
  
  
  
  
  
  def 	SCREAMING_SNAKE_CASE							(      __lowerCAmelCase    )				->			Dict:
       UpperCamelCase__    :     Optional[int]        =						len(__lowerCAmelCase    )
       if not list_of_ints or length == 1:
            return
  
       if min(__lowerCAmelCase    ) < 0:
            raise ValueError("All numbers must be positive"    )
  
       UpperCamelCase__    :     int        =						max(len(bin(__lowerCAmelCase    )[2:]    ) for x in list_of_ints    )
       _msd_radix_sort_inplace(__lowerCAmelCase      ,					__lowerCAmelCase      ,					0      ,					__lowerCAmelCase    )
  
  
  
  
  
  
  
  def 	SCREAMING_SNAKE_CASE							(      __lowerCAmelCase      ,					__lowerCAmelCase      ,					__lowerCAmelCase      ,					__lowerCAmelCase    )				->			List[str]:
       if bit_position == 0 or end_index - begin_index <= 1:
            return
  
       bit_position -= 1
  
       UpperCamelCase__    :     Any        =						begin_index
       UpperCamelCase__    :     List[str]        =						end_index - 1
       while i <= j:
            UpperCamelCase__    :     Tuple        =						False
            if not (list_of_ints[i] >> bit_position) & 1:
                 # found zero at the beginning
                 i += 1
                 UpperCamelCase__    :     Any        =						True
            if (list_of_ints[j] >> bit_position) & 1:
                 # found one at the end
                 j -= 1
                 UpperCamelCase__    :     Dict        =						True
  
            if changed:
                 continue
  
            UpperCamelCase__       ,  UpperCamelCase__    :     Any        =						list_of_ints[j], list_of_ints[i]
            j -= 1
            if j != i:
                 i += 1
  
       _msd_radix_sort_inplace(__lowerCAmelCase      ,					__lowerCAmelCase      ,					__lowerCAmelCase      ,					__lowerCAmelCase    )
       _msd_radix_sort_inplace(__lowerCAmelCase      ,					__lowerCAmelCase      ,					__lowerCAmelCase      ,					__lowerCAmelCase    )
  
  
  if __name__ == "__main__":
   import doctest
  
   doctest.testmod()