



"""simple docstring"""






import math






def      snake_case__   (		__lowerCamelCase				:    list							,		__lowerCamelCase				:    int = 0							,		__lowerCamelCase				:    int = 0	):
			"""simple docstring"""
			lowerCamelCase__		:		List[str]			=end or len(__lowerCamelCase	)
			for i in range(__lowerCamelCase							,		__lowerCamelCase	):
						lowerCamelCase__		:		Tuple			=i
						lowerCamelCase__		:		Optional[int]			=array[i]
						while temp_index != start and temp_index_value < array[temp_index - 1]:
									lowerCamelCase__		:		Tuple			=array[temp_index - 1]
									temp_index -= 1
						lowerCamelCase__		:		Dict			=temp_index_value
			return array






def      snake_case__   (		__lowerCamelCase				:    list							,		__lowerCamelCase				:    int							,		__lowerCamelCase				:    int	):  # Max Heap
			"""simple docstring"""
			lowerCamelCase__		:		Union[str, Any]			=index
			lowerCamelCase__		:		Any			=2 * index + 1  # Left Node
			lowerCamelCase__		:		Any			=2 * index + 2  # Right Node

			if left_index < heap_size and array[largest] < array[left_index]:
						lowerCamelCase__		:		Dict			=left_index

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

			if largest != index:
						lowerCamelCase__		:		Any			=array[largest], array[index]
						heapify(__lowerCamelCase							,		__lowerCamelCase							,		__lowerCamelCase	)






def      snake_case__   (		__lowerCamelCase				:    list	):
			"""simple docstring"""
			lowerCamelCase__		:		Optional[int]			=len(__lowerCamelCase	)

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

			for i in range(n - 1							,		0							,		-1	):
						lowerCamelCase__		:		Any			=array[0], array[i]
						heapify(__lowerCamelCase							,		0							,		__lowerCamelCase	)

			return array






def      snake_case__   (		__lowerCamelCase				:    list							,		__lowerCamelCase				:    int							,		__lowerCamelCase				:    int							,		__lowerCamelCase				:    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      snake_case__   (		__lowerCamelCase				:    list							,		__lowerCamelCase				:    int							,		__lowerCamelCase				:    int							,		__lowerCamelCase				:    int	):
			"""simple docstring"""
			lowerCamelCase__		:		Tuple			=low
			lowerCamelCase__		:		List[str]			=high
			while True:
						while array[i] < pivot:
									i += 1
						j -= 1
						while pivot < array[j]:
									j -= 1
						if i >= j:
									return i
						lowerCamelCase__		:		List[Any]			=array[j], array[i]
						i += 1






def      snake_case__   (		__lowerCamelCase				:    list	):
			"""simple docstring"""
			if len(__lowerCamelCase	) == 0:
						return array
			lowerCamelCase__		:		Tuple			=2 * math.ceil(math.loga(len(__lowerCamelCase	)	)	)
			lowerCamelCase__		:		Optional[int]			=16
			return intro_sort(__lowerCamelCase							,		0							,		len(__lowerCamelCase	)							,		__lowerCamelCase							,		__lowerCamelCase	)






def      snake_case__   (		__lowerCamelCase				:    list							,		__lowerCamelCase				:    int							,		__lowerCamelCase				:    int							,		__lowerCamelCase				:    int							,		__lowerCamelCase				:    int	):
			"""simple docstring"""
			while end - start > size_threshold:
						if max_depth == 0:
									return heap_sort(__lowerCamelCase	)
						max_depth -= 1
						lowerCamelCase__		:		Tuple			=median_of_a(__lowerCamelCase							,		__lowerCamelCase							,		start + ((end - start) // 2) + 1							,		end - 1	)
						lowerCamelCase__		:		Optional[int]			=partition(__lowerCamelCase							,		__lowerCamelCase							,		__lowerCamelCase							,		__lowerCamelCase	)
						intro_sort(__lowerCamelCase							,		__lowerCamelCase							,		__lowerCamelCase							,		__lowerCamelCase							,		__lowerCamelCase	)
						lowerCamelCase__		:		Optional[Any]			=p
			return insertion_sort(__lowerCamelCase							,		__lowerCamelCase							,		__lowerCamelCase	)


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		_lowercase : int      						=						input("Enter numbers separated by a comma : ").strip()
		_lowercase : Optional[Any]      						=						[float(item) for item in user_input.split(",")]
		print(sort(unsorted))






from typing import TYPE_CHECKING

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


__lowerCamelCase							=       {"""configuration_xglm""": ["""XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XGLMConfig"""]}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase							=       ["""XGLMTokenizer"""]

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase							=       ["""XGLMTokenizerFast"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase							=       [
       """XGLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """XGLMForCausalLM""",
       """XGLMModel""",
       """XGLMPreTrainedModel""",
   ]


try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase							=       [
       """FlaxXGLMForCausalLM""",
       """FlaxXGLMModel""",
       """FlaxXGLMPreTrainedModel""",
   ]


try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase							=       [
       """TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """TFXGLMForCausalLM""",
       """TFXGLMModel""",
       """TFXGLMPreTrainedModel""",
   ]


if TYPE_CHECKING:
   from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_xglm import XGLMTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_xglm_fast import XGLMTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_xglm import (
          TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFXGLMForCausalLM,
          TFXGLMModel,
          TFXGLMPreTrainedModel,
      )


else:
   import sys

   __lowerCamelCase							=       _LazyModule(__name__, globals()["""__file__"""], _import_structure)





