






def       a__						(  A		,				A		,				A					):
   if right <= left:
      return
   lowercase__						:	Any         = left
   lowercase__						:	Any         = right
   lowercase__						:	List[Any]         = sorting[left]
   while i <= b:
      if sorting[i] < pivot:
         lowercase__     ,					lowercase__						:	Optional[Any]         = sorting[i], sorting[a]
         a += 1
         i += 1
      elif sorting[i] > pivot:
         lowercase__     ,					lowercase__						:	Tuple         = sorting[i], sorting[b]
         b -= 1
      else:
         i += 1
   quick_sort_apartition(A		,				A		,				a - 1					)
   quick_sort_apartition(A		,				b + 1		,				A					)
def       a__						(  A		,				A		,				A					):
   if left < right:
      lowercase__						:	str         = lomuto_partition(A		,				A		,				A					)
      quick_sort_lomuto_partition(A		,				A		,				pivot_index - 1					)
      quick_sort_lomuto_partition(A		,				pivot_index + 1		,				A					)
def       a__						(  A		,				A		,				A					):
   lowercase__						:	List[Any]         = sorting[right]
   lowercase__						:	int         = left
   for i in range(A		,				A					):
      if sorting[i] < pivot:
         lowercase__     ,					lowercase__						:	List[Any]         = sorting[i], sorting[store_index]
         store_index += 1
   lowercase__     ,					lowercase__						:	Tuple         = sorting[store_index], sorting[right]
   return store_index
def       a__						(  A					):
   if len(A					) <= 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)

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










from collections import OrderedDict
from typing import Mapping

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


a    =       logging.get_logger(__name__)

a    =       {
    'nghuyong/ernie-1.0-base-zh': 'https://huggingface.co/nghuyong/ernie-1.0-base-zh/resolve/main/config.json',
    'nghuyong/ernie-2.0-base-en': 'https://huggingface.co/nghuyong/ernie-2.0-base-en/resolve/main/config.json',
    'nghuyong/ernie-2.0-large-en': 'https://huggingface.co/nghuyong/ernie-2.0-large-en/resolve/main/config.json',
    'nghuyong/ernie-3.0-base-zh': 'https://huggingface.co/nghuyong/ernie-3.0-base-zh/resolve/main/config.json',
    'nghuyong/ernie-3.0-medium-zh': 'https://huggingface.co/nghuyong/ernie-3.0-medium-zh/resolve/main/config.json',
    'nghuyong/ernie-3.0-mini-zh': 'https://huggingface.co/nghuyong/ernie-3.0-mini-zh/resolve/main/config.json',
    'nghuyong/ernie-3.0-micro-zh': 'https://huggingface.co/nghuyong/ernie-3.0-micro-zh/resolve/main/config.json',
    'nghuyong/ernie-3.0-nano-zh': 'https://huggingface.co/nghuyong/ernie-3.0-nano-zh/resolve/main/config.json',
    'nghuyong/ernie-gram-zh': 'https://huggingface.co/nghuyong/ernie-gram-zh/resolve/main/config.json',
    'nghuyong/ernie-health-zh': 'https://huggingface.co/nghuyong/ernie-health-zh/resolve/main/config.json',
}
class        __snake_case(					__UpperCamelCase      ):
 lowercase :       Dict		      =		'''ernie'''



 def __init__(	self   :   Tuple ,		UpperCAmelCase__   :   int=30_522 ,		UpperCAmelCase__   :   List[str]=768 ,		UpperCAmelCase__   :   Tuple=12 ,		UpperCAmelCase__   :   Optional[int]=12 ,		UpperCAmelCase__   :   Any=3_072 ,		UpperCAmelCase__   :   Tuple="gelu" ,		UpperCAmelCase__   :   Union[str, Any]=0.1 ,		UpperCAmelCase__   :   str=0.1 ,		UpperCAmelCase__   :   List[str]=512 ,		UpperCAmelCase__   :   str=2 ,		UpperCAmelCase__   :   Optional[int]=3 ,		UpperCAmelCase__   :   Dict=False ,		UpperCAmelCase__   :   Any=0.02 ,		UpperCAmelCase__   :   Any=1e-12 ,		UpperCAmelCase__   :   str=0 ,		UpperCAmelCase__   :   Any="absolute" ,		UpperCAmelCase__   :   List[str]=True ,		UpperCAmelCase__   :   Tuple=None ,		**UpperCAmelCase__   :   Dict ,		):

    """simple docstring"""






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

    lowercase__						:	List[str]         = vocab_size
    lowercase__						:	Optional[int]         = hidden_size
    lowercase__						:	Union[str, Any]         = num_hidden_layers
    lowercase__						:	Any         = num_attention_heads
    lowercase__						:	Optional[int]         = hidden_act
    lowercase__						:	str         = intermediate_size
    lowercase__						:	Tuple         = hidden_dropout_prob
    lowercase__						:	Tuple         = attention_probs_dropout_prob
    lowercase__						:	str         = max_position_embeddings
    lowercase__						:	List[Any]         = type_vocab_size
    lowercase__						:	Any         = task_type_vocab_size
    lowercase__						:	Optional[Any]         = use_task_id
    lowercase__						:	Optional[Any]         = initializer_range
    lowercase__						:	Union[str, Any]         = layer_norm_eps
    lowercase__						:	Dict         = position_embedding_type
    lowercase__						:	Union[str, Any]         = use_cache
    lowercase__						:	int         = classifier_dropout
class        __snake_case(					__UpperCamelCase      ):



 @property
 def 						UpperCAmelCase    (	self   :   List[Any]	):

    """simple docstring"""






    if self.task == "multiple-choice":
       lowercase__						:	Dict         = {0: """batch""", 1: """choice""", 2: """sequence"""}
    else:
       lowercase__						:	Dict         = {0: """batch""", 1: """sequence"""}
    return OrderedDict(
        [
            ("""input_ids""", dynamic_axis),
            ("""attention_mask""", dynamic_axis),
            ("""token_type_ids""", dynamic_axis),
            ("""task_type_ids""", dynamic_axis),
        ]	)


