






def 						A_					(						lowercase_	,  lowercase_	,  lowercase_			)				->List[Any]:







 """simple docstring"""

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

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

 if largest != index:
  SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE				    =		unsorted[index], unsorted[largest]
  heapify(lowercase_	,  lowercase_	,  lowercase_			)





def 						A_					(						lowercase_			)				->List[str]:







 """simple docstring"""

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


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





"""simple docstring"""
from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__       =	{
    "configuration_open_llama": ["OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "OpenLlamaConfig"],
}

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

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

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__       =	[
					    "OpenLlamaForCausalLM",
					    "OpenLlamaModel",
					    "OpenLlamaPreTrainedModel",
					    "OpenLlamaForSequenceClassification",
					]


if TYPE_CHECKING:
					from .configuration_open_llama import OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenLlamaConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from transformers import LlamaTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from transformers import LlamaTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_open_llama import (
										    OpenLlamaForCausalLM,
										    OpenLlamaForSequenceClassification,
										    OpenLlamaModel,
										    OpenLlamaPreTrainedModel,
										)


else:
					import sys

					SCREAMING_SNAKE_CASE__       =	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


