






"""simple docstring"""



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     :     Optional[int]            =	logging.get_logger(__name__)

_lowerCAmelCase     :     List[Any]            =	{
    """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        lowerCAmelCase__       (  __magic_name__					):
   SCREAMING_SNAKE_CASE_					      ='''deberta'''
   def __init__(						self	:     List[Any]				,       snake_case__	:     str=5_0_2_6_5				,       snake_case__	:     Optional[int]=7_6_8				,       snake_case__	:     Dict=1_2				,       snake_case__	:     List[Any]=1_2				,       snake_case__	:     int=3_0_7_2				,       snake_case__	:     List[Any]="gelu"				,       snake_case__	:     Optional[Any]=0.1				,       snake_case__	:     Optional[int]=0.1				,       snake_case__	:     List[str]=5_1_2				,       snake_case__	:     Optional[int]=0				,       snake_case__	:     List[Any]=0.02				,       snake_case__	:     List[str]=1e-7				,       snake_case__	:     Tuple=False				,       snake_case__	:     Tuple=-1				,       snake_case__	:     Any=0				,       snake_case__	:     Optional[Any]=True				,       snake_case__	:     Dict=None				,       snake_case__	:     Dict=0				,       snake_case__	:     Any="gelu"				,       **snake_case__	:     Tuple				,       ):


        '''simple docstring'''
        super().__init__(**snake_case__				)

        UpperCAmelCase__		:  List[str]				=				hidden_size
        UpperCAmelCase__		:  Optional[Any]				=				num_hidden_layers
        UpperCAmelCase__		:  List[str]				=				num_attention_heads
        UpperCAmelCase__		:  List[Any]				=				intermediate_size
        UpperCAmelCase__		:  int				=				hidden_act
        UpperCAmelCase__		:  List[Any]				=				hidden_dropout_prob
        UpperCAmelCase__		:  Any				=				attention_probs_dropout_prob
        UpperCAmelCase__		:  int				=				max_position_embeddings
        UpperCAmelCase__		:  List[str]				=				type_vocab_size
        UpperCAmelCase__		:  Union[str, Any]				=				initializer_range
        UpperCAmelCase__		:  Union[str, Any]				=				relative_attention
        UpperCAmelCase__		:  str				=				max_relative_positions
        UpperCAmelCase__		:  Optional[Any]				=				pad_token_id
        UpperCAmelCase__		:  Any				=				position_biased_input

        # Backwards compatibility
        if type(snake_case__				) == str:
             UpperCAmelCase__		:  Dict				=				[x.strip() for x in pos_att_type.lower().split("|"				)]

        UpperCAmelCase__		:  int				=				pos_att_type
        UpperCAmelCase__		:  List[str]				=				vocab_size
        UpperCAmelCase__		:  Dict				=				layer_norm_eps

        UpperCAmelCase__		:  Optional[int]				=				kwargs.get("pooler_hidden_size"				,       snake_case__				)
        UpperCAmelCase__		:  Tuple				=				pooler_dropout
        UpperCAmelCase__		:  Tuple				=				pooler_hidden_act




class        lowerCAmelCase__       (  __magic_name__					):
   @property
   def 	__a				(						self	:     Tuple				):


        '''simple docstring'''
        if self.task == "multiple-choice":
             UpperCAmelCase__		:  Optional[int]				=				{0: "batch", 1: "choice", 2: "sequence"}
        else:
             UpperCAmelCase__		:  List[Any]				=				{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 	__a				(						self	:     str				):


        '''simple docstring'''
        return 1_2




   def 	__a				(						self	:     str				,       snake_case__	:     Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"]				,       snake_case__	:     int = -1				,       snake_case__	:     int = -1				,       snake_case__	:     int = -1				,       snake_case__	:     bool = False				,       snake_case__	:     Optional["TensorType"] = None				,       snake_case__	:     int = 3				,       snake_case__	:     int = 4_0				,       snake_case__	:     int = 4_0				,       snake_case__	:     "PreTrainedTokenizerBase" = None				,       ):


        '''simple docstring'''
        UpperCAmelCase__		:  Union[str, Any]				=				super().generate_dummy_inputs(preprocessor=snake_case__				,       framework=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










"""simple docstring"""



def      SCREAMING_SNAKE_CASE__    (   snake_case    :      list       , snake_case    :      int       , snake_case    :      int							)->						None:






     '''simple docstring'''



     if right <= left:
          return
     UpperCAmelCase__		:  str				=				left
     UpperCAmelCase__		:  List[str]				=				right
     UpperCAmelCase__		:  List[Any]				=				sorting[left]
     while i <= b:
          if sorting[i] < pivot:
               UpperCAmelCase__				,							UpperCAmelCase__		:  List[str]				=				sorting[i], sorting[a]
               a += 1
               i += 1
          elif sorting[i] > pivot:
               UpperCAmelCase__				,							UpperCAmelCase__		:  Optional[int]				=				sorting[i], sorting[b]
               b -= 1
          else:
               i += 1
     quick_sort_apartition(snake_case       , snake_case       , a - 1							)
     quick_sort_apartition(snake_case       , b + 1       , snake_case							)


def      SCREAMING_SNAKE_CASE__    (   snake_case    :      list       , snake_case    :      int       , snake_case    :      int							)->						None:






     '''simple docstring'''



     if left < right:
          UpperCAmelCase__		:  int				=				lomuto_partition(snake_case       , snake_case       , snake_case							)
          quick_sort_lomuto_partition(snake_case       , snake_case       , pivot_index - 1							)
          quick_sort_lomuto_partition(snake_case       , pivot_index + 1       , snake_case							)


def      SCREAMING_SNAKE_CASE__    (   snake_case    :      list       , snake_case    :      int       , snake_case    :      int							)->						int:






     '''simple docstring'''



     UpperCAmelCase__		:  Union[str, Any]				=				sorting[right]
     UpperCAmelCase__		:  Optional[Any]				=				left
     for i in range(snake_case       , snake_case							):
          if sorting[i] < pivot:
               UpperCAmelCase__				,							UpperCAmelCase__		:  List[Any]				=				sorting[i], sorting[store_index]
               store_index += 1
     UpperCAmelCase__				,							UpperCAmelCase__		:  List[Any]				=				sorting[store_index], sorting[right]
     return store_index


def      SCREAMING_SNAKE_CASE__    (   snake_case    :      list							)->						list:






     '''simple docstring'''



     if len(snake_case							) <= 1:
          return sorting
     return (
         three_way_radix_quicksort([i for i in sorting if i < sorting[0]]							)
         + [i for i in sorting if i == sorting[0]]
         + three_way_radix_quicksort([i for i in sorting if i > sorting[0]]							)
     )


if __name__ == "__main__":
 import doctest

 doctest.testmod(verbose=True)

 _lowerCAmelCase     :     Optional[int]            =	input("""Enter numbers separated by a comma:\n""").strip()
 _lowerCAmelCase     :     str            =	[int(item) for item in user_input.split(""",""")]
 quick_sort_apartition(unsorted, 0, len(unsorted) - 1)
 print(unsorted)


