


'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_UpperCAmelCase :       List[Any]										= {
    'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertConfig'],
    'tokenization_lxmert': ['LxmertTokenizer'],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase :       int										= ['LxmertTokenizerFast']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase :       Optional[int]										= [
	    'LxmertEncoder',
	    'LxmertForPreTraining',
	    'LxmertForQuestionAnswering',
	    'LxmertModel',
	    'LxmertPreTrainedModel',
	    'LxmertVisualFeatureEncoder',
	    'LxmertXLayer',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase :       List[Any]										= [
	    'TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'TFLxmertForPreTraining',
	    'TFLxmertMainLayer',
	    'TFLxmertModel',
	    'TFLxmertPreTrainedModel',
	    'TFLxmertVisualFeatureEncoder',
	]


if TYPE_CHECKING:
	from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
	from .tokenization_lxmert import LxmertTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_lxmert_fast import LxmertTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_lxmert import (
		    LxmertEncoder,
		    LxmertForPreTraining,
		    LxmertForQuestionAnswering,
		    LxmertModel,
		    LxmertPreTrainedModel,
		    LxmertVisualFeatureEncoder,
		    LxmertXLayer,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_lxmert import (
		    TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFLxmertForPreTraining,
		    TFLxmertMainLayer,
		    TFLxmertModel,
		    TFLxmertPreTrainedModel,
		    TFLxmertVisualFeatureEncoder,
		)

else:
	import sys

	_UpperCAmelCase :       Any										= _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



import math


def 						UpperCAmelCase			(	a_		,   a_ = 0		,   a_ = 0						)		->	list:







				"""simple docstring"""



				__A   			= end or len(a_						)
				for i in range(a_		,   a_						):
								__A   			= i
								__A   			= array[i]
								while temp_index != start and temp_index_value < array[temp_index - 1]:
												__A   			= array[temp_index - 1]
												temp_index -= 1
								__A   			= temp_index_value
				return array


def 						UpperCAmelCase			(	a_		,   a_		,   a_						)		->	None:  # Max Heap







				"""simple docstring"""



				__A   			= index
				__A   			= 2 * index + 1  # Left Node
				__A   			= 2 * index + 2  # Right Node

				if left_index < heap_size and array[largest] < array[left_index]:
								__A   			= left_index

				if right_index < heap_size and array[largest] < array[right_index]:
								__A   			= right_index

				if largest != index:
								__A			,							__A   			= array[largest], array[index]
								heapify(a_		,   a_		,   a_						)


def 						UpperCAmelCase			(	a_						)		->	list:







				"""simple docstring"""



				__A   			= len(a_						)

				for i in range(n // 2		,   -1		,   -1						):
								heapify(a_		,   a_		,   a_						)

				for i in range(n - 1		,   0		,   -1						):
								__A			,							__A   			= array[0], array[i]
								heapify(a_		,   0		,   a_						)

				return array


def 						UpperCAmelCase			(	a_		,   a_		,   a_		,   a_						)		->	int:







				"""simple docstring"""



				if (array[first_index] > array[middle_index]) != (
				    array[first_index] > array[last_index]
				):
								return array[first_index]
				elif (array[middle_index] > array[first_index]) != (
				    array[middle_index] > array[last_index]
				):
								return array[middle_index]
				else:
								return array[last_index]


def 						UpperCAmelCase			(	a_		,   a_		,   a_		,   a_						)		->	int:







				"""simple docstring"""



				__A   			= low
				__A   			= high
				while True:
								while array[i] < pivot:
												i += 1
								j -= 1
								while pivot < array[j]:
												j -= 1
								if i >= j:
												return i
								__A			,							__A   			= array[j], array[i]
								i += 1


def 						UpperCAmelCase			(	a_						)		->	list:







				"""simple docstring"""



				if len(a_						) == 0:
								return array
				__A   			= 2 * math.ceil(math.loga(len(a_						)						)						)
				__A   			= 1_6
				return intro_sort(a_		,   0		,   len(a_						)		,   a_		,   a_						)


def 						UpperCAmelCase			(	a_		,   a_		,   a_		,   a_		,   a_						)		->	list:







				"""simple docstring"""



				while end - start > size_threshold:
								if max_depth == 0:
												return heap_sort(a_						)
								max_depth -= 1
								__A   			= median_of_a(a_		,   a_		,   start + ((end - start) // 2) + 1		,   end - 1						)
								__A   			= partition(a_		,   a_		,   a_		,   a_						)
								intro_sort(a_		,   a_		,   a_		,   a_		,   a_						)
								__A   			= p
				return insertion_sort(a_		,   a_		,   a_						)


if __name__ == "__main__":
					import doctest

					doctest.testmod()

					SCREAMING_SNAKE_CASE							:List[Any]							 =				input('Enter numbers separated by a comma : ').strip()
					SCREAMING_SNAKE_CASE							:str							 =				[float(item) for item in user_input.split(',')]
					print(sort(unsorted))
