

import math



def   __UpperCAmelCase					(      __a :     list						,__a :     int = 0						,__a :     int = 0      )     ->	list:

					"""simple docstring"""

					_a      :       int   =						end or len(__a      )
					for i in range(__a						,__a      ):
										_a      :       Optional[Any]   =						i
										_a      :       str   =						array[i]
										while temp_index != start and temp_index_value < array[temp_index - 1]:
															_a      :       Union[str, Any]   =						array[temp_index - 1]
															temp_index -= 1
										_a      :       Optional[Any]   =						temp_index_value
					return array



def   __UpperCAmelCase					(      __a :     list						,__a :     int						,__a :     int      )     ->	None:  # Max Heap

					"""simple docstring"""

					_a      :       Any   =						index
					_a      :       Any   =						2 * index + 1  # Left Node
					_a      :       Optional[int]   =						2 * index + 2  # Right Node

					if left_index < heap_size and array[largest] < array[left_index]:
										_a      :       Union[str, Any]   =						left_index

					if right_index < heap_size and array[largest] < array[right_index]:
										_a      :       str   =						right_index

					if largest != index:
										_a ,   _a      :       Tuple   =						array[largest], array[index]
										heapify(__a						,__a						,__a      )



def   __UpperCAmelCase					(      __a :     list      )     ->	list:

					"""simple docstring"""

					_a      :       Dict   =						len(__a      )

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

					for i in range(n - 1						,0						,-1      ):
										_a ,   _a      :       List[str]   =						array[0], array[i]
										heapify(__a						,0						,__a      )

					return array



def   __UpperCAmelCase					(      __a :     list						,__a :     int						,__a :     int						,__a :     int      )     ->	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 :     list						,__a :     int						,__a :     int						,__a :     int      )     ->	int:

					"""simple docstring"""

					_a      :       List[str]   =						low
					_a      :       List[Any]   =						high
					while True:
										while array[i] < pivot:
															i += 1
										j -= 1
										while pivot < array[j]:
															j -= 1
										if i >= j:
															return i
										_a ,   _a      :       int   =						array[j], array[i]
										i += 1



def   __UpperCAmelCase					(      __a :     list      )     ->	list:

					"""simple docstring"""

					if len(__a      ) == 0:
										return array
					_a      :       int   =						2 * math.ceil(math.loga(len(__a      )      )      )
					_a      :       Tuple   =						16
					return intro_sort(__a						,0						,len(__a      )						,__a						,__a      )



def   __UpperCAmelCase					(      __a :     list						,__a :     int						,__a :     int						,__a :     int						,__a :     int      )     ->	list:

					"""simple docstring"""

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


if __name__ == "__main__":
			import doctest

			doctest.testmod()

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





"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE_            =    {
    '''configuration_speecht5''': [
        '''SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP''',
        '''SpeechT5Config''',
        '''SpeechT5HifiGanConfig''',
    ],
    '''feature_extraction_speecht5''': ['''SpeechT5FeatureExtractor'''],
    '''processing_speecht5''': ['''SpeechT5Processor'''],
}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE_            =    ['''SpeechT5Tokenizer''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE_            =    [
       '''SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''SpeechT5ForSpeechToText''',
       '''SpeechT5ForSpeechToSpeech''',
       '''SpeechT5ForTextToSpeech''',
       '''SpeechT5Model''',
       '''SpeechT5PreTrainedModel''',
       '''SpeechT5HifiGan''',
   ]

if TYPE_CHECKING:
   from .configuration_speechta import (
       SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
       SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
       SpeechTaConfig,
       SpeechTaHifiGanConfig,
   )
   from .feature_extraction_speechta import SpeechTaFeatureExtractor
   from .processing_speechta import SpeechTaProcessor

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_speechta import SpeechTaTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_speechta import (
          SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
          SpeechTaForSpeechToSpeech,
          SpeechTaForSpeechToText,
          SpeechTaForTextToSpeech,
          SpeechTaHifiGan,
          SpeechTaModel,
          SpeechTaPreTrainedModel,
      )

else:
   import sys

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



