class 				__lowerCAmelCase					:



 '''simple docstring'''

 def __init__(     self    :						Tuple					)	->							Optional[int]:
        _UpperCamelCase       :    Union[str, Any]					  =					[0]
        _UpperCamelCase       :    Union[str, Any]					  =					0

 def    __snake_case   (     self    :						Tuple    ,     lowerCamelCase    :						int					)	->							None:
        _UpperCamelCase       :    Any					  =					self.__heap[i]
        while i // 2 > 0:
               if self.__heap[i] > self.__heap[i // 2]:
                      _UpperCamelCase       :    int					  =					self.__heap[i // 2]
                      _UpperCamelCase       :    List[str]					  =					temporary
               i //= 2

 def    __snake_case   (     self    :						Dict    ,     lowerCamelCase    :						int					)	->							None:
        self.__heap.append(lowerCamelCase					)
        self.__size += 1
        self.__swap_up(self.__size					)

 def    __snake_case   (     self    :						Dict    ,     lowerCamelCase    :						int					)	->							None:
        while self.__size >= 2 * i:
               if 2 * i + 1 > self.__size:
                      _UpperCamelCase       :    List[Any]					  =					2 * i
               else:
                      if self.__heap[2 * i] > self.__heap[2 * i + 1]:
                             _UpperCamelCase       :    Union[str, Any]					  =					2 * i
                      else:
                             _UpperCamelCase       :    List[Any]					  =					2 * i + 1
               _UpperCamelCase       :    List[Any]					  =					self.__heap[i]
               if self.__heap[i] < self.__heap[bigger_child]:
                      _UpperCamelCase       :    Optional[Any]					  =					self.__heap[bigger_child]
                      _UpperCamelCase       :    Tuple					  =					temporary
               _UpperCamelCase       :    Union[str, Any]					  =					bigger_child

 def    __snake_case   (     self    :						Optional[int]					)	->							int:
        _UpperCamelCase       :    List[Any]					  =					self.__heap[1]
        _UpperCamelCase       :    List[str]					  =					self.__heap[self.__size]
        self.__size -= 1
        self.__heap.pop()
        self.__swap_down(1					)
        return max_value

 @property
 def    __snake_case   (     self    :						str					)	->							int:
        return self.__heap[1:]

 def __len__(     self    :						Tuple					)	->							int:
        return self.__size


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 # create an instance of BinaryHeap
 UpperCAmelCase     						=			BinaryHeap()
 binary_heap.insert(6)
 binary_heap.insert(10)
 binary_heap.insert(15)
 binary_heap.insert(12)
 # pop root(max-values because it is max heap)
 print(binary_heap.pop())  # 15
 print(binary_heap.pop())  # 12
 # get the list and size after operations
 print(binary_heap.get_list)
 print(len(binary_heap))




from typing import TYPE_CHECKING

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


UpperCAmelCase     						=			{
    '''configuration_speech_to_text_2''': ['''SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Speech2Text2Config'''],
    '''processing_speech_to_text_2''': ['''Speech2Text2Processor'''],
    '''tokenization_speech_to_text_2''': ['''Speech2Text2Tokenizer'''],
}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase     						=			[
     '''SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''Speech2Text2ForCausalLM''',
     '''Speech2Text2PreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_speech_to_text_a import SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextaConfig
 from .processing_speech_to_text_a import SpeechaTextaProcessor
 from .tokenization_speech_to_text_a import SpeechaTextaTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_speech_to_text_a import (
      SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST,
      SpeechaTextaForCausalLM,
      SpeechaTextaPreTrainedModel,
  )

else:
 import sys

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



