'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

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


snake_case__	:     List[Any]      =    logging.get_logger(__name__)

snake_case__	:     Tuple      =    {
    '''google/electra-small-generator''': '''https://huggingface.co/google/electra-small-generator/resolve/main/config.json''',
    '''google/electra-base-generator''': '''https://huggingface.co/google/electra-base-generator/resolve/main/config.json''',
    '''google/electra-large-generator''': '''https://huggingface.co/google/electra-large-generator/resolve/main/config.json''',
    '''google/electra-small-discriminator''': (
        '''https://huggingface.co/google/electra-small-discriminator/resolve/main/config.json'''
    ),
    '''google/electra-base-discriminator''': (
        '''https://huggingface.co/google/electra-base-discriminator/resolve/main/config.json'''
    ),
    '''google/electra-large-discriminator''': (
        '''https://huggingface.co/google/electra-large-discriminator/resolve/main/config.json'''
    ),
}






class 	__SCREAMING_SNAKE_CASE		(			snake_case_			):







  '''simple docstring'''






  lowerCamelCase_						:Any		       =						'''electra'''


  def __init__(					self ,						snake_case_=3_0_5_2_2 ,						snake_case_=1_2_8 ,						snake_case_=2_5_6 ,						snake_case_=1_2 ,						snake_case_=4 ,						snake_case_=1_0_2_4 ,						snake_case_="gelu" ,						snake_case_=0.1 ,						snake_case_=0.1 ,						snake_case_=5_1_2 ,						snake_case_=2 ,						snake_case_=0.02 ,						snake_case_=1E-12 ,						snake_case_="first" ,						snake_case_=True ,						snake_case_="gelu" ,						snake_case_=0.1 ,						snake_case_=0 ,						snake_case_="absolute" ,						snake_case_=True ,						snake_case_=None ,						**snake_case_ ,						):




       '''simple docstring'''

       super().__init__(pad_token_id=_lowerCAmelCase ,						**_lowerCAmelCase		)

       UpperCAmelCase_				:  Any  = vocab_size
       UpperCAmelCase_				:  Tuple  = embedding_size
       UpperCAmelCase_				:  Any  = hidden_size
       UpperCAmelCase_				:  List[str]  = num_hidden_layers
       UpperCAmelCase_				:  int  = num_attention_heads
       UpperCAmelCase_				:  Optional[Any]  = intermediate_size
       UpperCAmelCase_				:  Union[str, Any]  = hidden_act
       UpperCAmelCase_				:  str  = hidden_dropout_prob
       UpperCAmelCase_				:  Optional[int]  = attention_probs_dropout_prob
       UpperCAmelCase_				:  Optional[Any]  = max_position_embeddings
       UpperCAmelCase_				:  str  = type_vocab_size
       UpperCAmelCase_				:  Optional[int]  = initializer_range
       UpperCAmelCase_				:  Any  = layer_norm_eps

       UpperCAmelCase_				:  Union[str, Any]  = summary_type
       UpperCAmelCase_				:  Any  = summary_use_proj
       UpperCAmelCase_				:  Optional[int]  = summary_activation
       UpperCAmelCase_				:  Any  = summary_last_dropout
       UpperCAmelCase_				:  Dict  = position_embedding_type
       UpperCAmelCase_				:  Union[str, Any]  = use_cache
       UpperCAmelCase_				:  Any  = classifier_dropout







class 	__SCREAMING_SNAKE_CASE		(			snake_case_			):







  '''simple docstring'''






  @property
  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       if self.task == "multiple-choice":
            UpperCAmelCase_				:  int  = {0: 'batch', 1: 'choice', 2: 'sequence'}
       else:
            UpperCAmelCase_				:  List[Any]  = {0: 'batch', 1: 'sequence'}
       return OrderedDict(
           [
               ('input_ids', dynamic_axis),
               ('attention_mask', dynamic_axis),
               ('token_type_ids', dynamic_axis),
           ]		)











from __future__ import annotations

from random import randrange
def 				UpperCAmelCase__		(					_SCREAMING_SNAKE_CASE :						list					)->list:
      if len(_SCREAMING_SNAKE_CASE					) < 2:
            return collection
      _lowerCAmelCase			      =	randrange(len(_SCREAMING_SNAKE_CASE					)					)  # Use random element as pivot
      _lowerCAmelCase			      =	collection[pivot_index]
      _lowerCAmelCase			      =	[]  # All elements greater than pivot
      _lowerCAmelCase			      =	[]  # All elements less than or equal to pivot

      for element in collection[:pivot_index]:
            (greater if element > pivot else lesser).append(_SCREAMING_SNAKE_CASE					)

      for element in collection[pivot_index + 1 :]:
            (greater if element > pivot else lesser).append(_SCREAMING_SNAKE_CASE					)

      return [*quick_sort(_SCREAMING_SNAKE_CASE					), pivot, *quick_sort(_SCREAMING_SNAKE_CASE					)]


if __name__ == "__main__":
    UpperCAmelCase_          =				input("Enter numbers separated by a comma:\n").strip()
    UpperCAmelCase_          =				[int(item) for item in user_input.split(",")]
    print(quick_sort(unsorted))