






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







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()