
def 						A_			(				snake_case				: Optional[int]			,   snake_case				: Optional[int]			,   snake_case				: List[str]			)   ->     int:



						'''simple docstring'''

						__UpperCamelCase  	=      index
						__UpperCamelCase  	=      2 * index + 1
						__UpperCamelCase  	=      2 * index + 2
						if left_index < heap_size and unsorted[left_index] > unsorted[largest]:
												__UpperCamelCase  	=      left_index

						if right_index < heap_size and unsorted[right_index] > unsorted[largest]:
												__UpperCamelCase  	=      right_index

						if largest != index:
												__UpperCamelCase	,				__UpperCamelCase  	=      unsorted[index], unsorted[largest]
												heapify(snake_case			,   snake_case			,   snake_case			)




def 						A_			(				snake_case				: Union[str, Any]			)   ->     Optional[Any]:



						'''simple docstring'''

						__UpperCamelCase  	=      len(snake_case			)
						for i in range(n // 2 - 1			,   -1			,   -1			):
												heapify(snake_case			,   snake_case			,   snake_case			)
						for i in range(n - 1			,   0			,   -1			):
												__UpperCamelCase	,				__UpperCamelCase  	=      unsorted[i], unsorted[0]
												heapify(snake_case			,   0			,   snake_case			)
						return unsorted


if __name__ == "__main__":
				lowercase__				:				Any						=      input("Enter numbers separated by a comma:\n").strip()
				lowercase__				:				Any						=      [int(item) for item in user_input.split(",")]
				print(heap_sort(unsorted))











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCAmelCase			:  Optional[Any]										=				{"configuration_sew_d": ["SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWDConfig"]}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase			:  str										=				[
          "SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST",
          "SEWDForCTC",
          "SEWDForSequenceClassification",
          "SEWDModel",
          "SEWDPreTrainedModel",
      ]

if TYPE_CHECKING:
      from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_sew_d import (
                SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
                SEWDForCTC,
                SEWDForSequenceClassification,
                SEWDModel,
                SEWDPreTrainedModel,
            )


else:
      import sys

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






