code: 
  
  
  '''simple docstring'''
  
  from ctypes import c_float, sizeof
  from enum import Enum
  from typing import TYPE_CHECKING, Optional, Union
  
  
  if TYPE_CHECKING:
     from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore
  
  
  
  
  
  
  
  class  UpperCAmelCase (       SCREAMING_SNAKE_CASE__):
   _lowerCamelCase :					Any    					=					c_float
  
   @property
   def 		lowercase_						( self :	int					):
  
  
  
  
  
      """simple docstring"""
  
  
  
      return sizeof(self.value					)
  
  
  
  
  
  
  
  def        SCREAMING_SNAKE_CASE__(		_UpperCamelCase      :				int    ,		_UpperCamelCase      :				int    ,		_UpperCamelCase      :				int = 0   )		->					int:
  
  
  
  
  
     '''simple docstring'''
  
  
  
  
  
  
  
     if dimension <= 0:
        UpperCamelCase__ 						=						fixed_dimension
  
     dimension -= num_token_to_add
     return dimension
  
  
  
  def        SCREAMING_SNAKE_CASE__(		_UpperCamelCase      :				int    ,		_UpperCamelCase      :				ParameterFormat   )		->					int:
  
  
  
  
  
     '''simple docstring'''
  
  
  
  
  
  
  
     return num_parameters * dtype.size
  
  
  
  
  
  
  def        SCREAMING_SNAKE_CASE__(		_UpperCamelCase      :				str   )		->					Optional[Union["AutoTokenizer", "AutoFeatureExtractor", "AutoProcessor"]]:
  
  
  
  
  
     '''simple docstring'''
  
  
  
  
  
  
  
     from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore
  
     try:
        return AutoProcessor.from_pretrained(_UpperCamelCase   )
     except (ValueError, OSError, KeyError):
        UpperCamelCase__						,		UpperCamelCase__ 						=						None, None
        try:
           UpperCamelCase__ 						=						AutoTokenizer.from_pretrained(_UpperCamelCase   )
        except (OSError, KeyError):
           pass
        try:
           UpperCamelCase__ 						=						AutoFeatureExtractor.from_pretrained(_UpperCamelCase   )
        except (OSError, KeyError):
           pass
  
        if tokenizer is not None and feature_extractor is not None:
           raise ValueError(
               F'Couldn\'t auto-detect preprocessor for {model_name}. Found both a tokenizer and a feature extractor.'   )
        elif tokenizer is None and feature_extractor is None:
           return None
        elif tokenizer is not None:
           return tokenizer
        else:
           return feature_extractor
style_context: 
  
  
  '''simple docstring'''
  
  from __future__ import annotations
  
  import random
  from collections.abc import Iterable
  from typing import Any, Generic, TypeVar
  
  __lowercase:		Optional[Any]							=     TypeVar("T", bound=bool)
  
  
  
  
  
  
  
  class  UpperCAmelCase (       Generic[T]):
  
   def __init__( self :	int,					a_ :	T					):
  
  
  
  
  
      """simple docstring"""
  
  
  
      UpperCamelCase__ 						=						value
      UpperCamelCase__ 						=						None
      UpperCamelCase__ 						=						None
  
   @property
   def 		lowercase_						( self :	Dict					):
  
  
  
  
  
      """simple docstring"""
  
  
  
      return self._value
  
   @staticmethod
   def 		lowercase_						( a_ :	RandomizedHeapNode[T] | None,					a_ :	RandomizedHeapNode[T] | None					):
  
  
  
  
  
      """simple docstring"""
  
  
  
      if not roota:
         return roota
  
      if not roota:
         return roota
  
      if roota.value > roota.value:
         UpperCamelCase__						,		UpperCamelCase__ 						=						roota, roota
  
      if random.choice([True, False]					):
         UpperCamelCase__						,		UpperCamelCase__ 						=						roota.right, roota.left
  
      UpperCamelCase__ 						=						RandomizedHeapNode.merge(roota.left,					a_					)
  
      return roota
  
  
  
  
  
  
  
  class  UpperCAmelCase (       Generic[T]):
  
   def __init__( self :	List[Any],					a_ :	Iterable[T] | None = ()					):
  
  
  
  
  
      """simple docstring"""
  
  
  
      UpperCamelCase__ 						=						None
  
      if data:
         for item in data:
            self.insert(a_					)
  
   def 		lowercase_						( self :	Any,					a_ :	T					):
  
  
  
  
  
      """simple docstring"""
  
  
  
      UpperCamelCase__ 						=						RandomizedHeapNode.merge(self._root,					RandomizedHeapNode(a_					)					)
  
   def 		lowercase_						( self :	Any					):
  
  
  
  
  
      """simple docstring"""
  
  
  
      UpperCamelCase__ 						=						self.top()
  
      if self._root is None:
         return None
  
      UpperCamelCase__ 						=						RandomizedHeapNode.merge(self._root.left,					self._root.right					)
  
      return result
  
   def 		lowercase_						( self :	Union[str, Any]					):
  
  
  
  
  
      """simple docstring"""
  
  
  
      if not self._root:
         raise IndexError("Can't get top element for the empty heap."					)
      return self._root.value
  
   def 		lowercase_						( self :	Tuple					):
  
  
  
  
  
      """simple docstring"""
  
  
  
      UpperCamelCase__ 						=						None
  
   def 		lowercase_						( self :	int					):
  
  
  
  
  
      """simple docstring"""
  
  
  
      UpperCamelCase__ 						=						[]
      while self:
         result.append(self.pop()					)
  
      return result
  
   def __bool__( self :	List[Any]					):
  
  
  
  
  
      """simple docstring"""
  
  
  
      return self._root is not None
  
  
  if __name__ == "__main__":
         import doctest
  
         doctest.testmod()