
'''simple docstring'''
def 					_UpperCamelCase		(    SCREAMING_SNAKE_CASE__      ,    SCREAMING_SNAKE_CASE__      ,    SCREAMING_SNAKE_CASE__       )   ->				None:


		'''simple docstring'''


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




def 					_UpperCamelCase		(    SCREAMING_SNAKE_CASE__      ,    SCREAMING_SNAKE_CASE__      ,    SCREAMING_SNAKE_CASE__       )   ->				None:


		'''simple docstring'''


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




def 					_UpperCamelCase		(    SCREAMING_SNAKE_CASE__      ,    SCREAMING_SNAKE_CASE__      ,    SCREAMING_SNAKE_CASE__       )   ->				int:


		'''simple docstring'''


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




def 					_UpperCamelCase		(    SCREAMING_SNAKE_CASE__       )   ->				list:


		'''simple docstring'''


		if len(SCREAMING_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)

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





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


SCREAMING_SNAKE_CASE_						=					{'configuration_hubert': ['HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'HubertConfig']}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE_						=					[
					    'HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'HubertForCTC',
					    'HubertForSequenceClassification',
					    'HubertModel',
					    'HubertPreTrainedModel',
					]


try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE_						=					[
					    'TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'TFHubertForCTC',
					    'TFHubertModel',
					    'TFHubertPreTrainedModel',
					]

if TYPE_CHECKING:
					from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_hubert import (
										    HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    HubertForCTC,
										    HubertForSequenceClassification,
										    HubertModel,
										    HubertPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_hubert import (
										    TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFHubertForCTC,
										    TFHubertModel,
										    TFHubertPreTrainedModel,
										)


else:
					import sys

					SCREAMING_SNAKE_CASE_						=					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


