






from __future__ import annotations

import random
from collections.abc import Iterable
from typing import Any, Generic, TypeVar

__UpperCAmelCase      =				TypeVar("T", bound=bool)
class 	a_(		Generic[T]	):



     """simple docstring"""



     def __init__(		self					:	Tuple  ,  lowerCAmelCase__					:	T)							->	None:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		value
      SCREAMING_SNAKE_CASE				    =		None
      SCREAMING_SNAKE_CASE				    =		None





     @property
     def     __UpperCamelCase						(		self					:	int)							->	T:

      """simple docstring"""
      return self._value





     @staticmethod
     def     __UpperCamelCase						(		lowerCAmelCase__					:	RandomizedHeapNode[T] | None  ,  lowerCAmelCase__					:	RandomizedHeapNode[T] | None)							->	RandomizedHeapNode[T] | None:

      """simple docstring"""
      if not roota:
       return roota

      if not roota:
       return roota

      if roota.value > roota.value:
       SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE				    =		roota, roota

      if random.choice([True, False]):
       SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE				    =		roota.right, roota.left

      SCREAMING_SNAKE_CASE				    =		RandomizedHeapNode.merge(roota.left  ,  lowerCAmelCase__)

      return roota

class 	a_(		Generic[T]	):



     """simple docstring"""



     def __init__(		self					:	Union[str, Any]  ,  lowerCAmelCase__					:	Iterable[T] | None = ())							->	None:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		None

      if data:
       for item in data:
        self.insert(lowerCAmelCase__)





     def     __UpperCamelCase						(		self					:	Optional[int]  ,  lowerCAmelCase__					:	T)							->	None:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		RandomizedHeapNode.merge(self._root  ,  RandomizedHeapNode(lowerCAmelCase__))





     def     __UpperCamelCase						(		self					:	Optional[int])							->	T | None:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		self.top()

      if self._root is None:
       return None

      SCREAMING_SNAKE_CASE				    =		RandomizedHeapNode.merge(self._root.left  ,  self._root.right)

      return result





     def     __UpperCamelCase						(		self					:	Tuple)							->	T:

      """simple docstring"""
      if not self._root:
       raise IndexError('Can\'t get top element for the empty heap.')
      return self._root.value





     def     __UpperCamelCase						(		self					:	Optional[int])							->	None:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		None





     def     __UpperCamelCase						(		self					:	List[str])							->	list[Any]:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		[]
      while self:
       result.append(self.pop())

      return result





     def __bool__(		self					:	Optional[int])							->	bool:

      """simple docstring"""
      return self._root is not None


if __name__ == "__main__":
      import doctest

      doctest.testmod()












import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


__UpperCAmelCase      =				logging.get_logger(__name__)
class 	a_(		lowercase__	):



     """simple docstring"""



     __snake_case		:				Union[str, Any]  					='''speech-encoder-decoder'''
     __snake_case		:				List[Any]  					=True





     def __init__(		self					:	Any  ,  **lowerCAmelCase__					:	List[Any])							->	Tuple:

      """simple docstring"""
      super().__init__(**lowerCAmelCase__)
      if "encoder" not in kwargs or "decoder" not in kwargs:
       raise ValueError(
           f'''A configuraton of type {self.model_type} cannot be instantiated because not both `encoder` and'''
           f''' `decoder` sub-configurations are passed, but only {kwargs}''')

      SCREAMING_SNAKE_CASE				    =		kwargs.pop('encoder')
      SCREAMING_SNAKE_CASE				    =		encoder_config.pop('model_type')
      SCREAMING_SNAKE_CASE				    =		kwargs.pop('decoder')
      SCREAMING_SNAKE_CASE				    =		decoder_config.pop('model_type')

      SCREAMING_SNAKE_CASE				    =		AutoConfig.for_model(lowerCAmelCase__  ,  **lowerCAmelCase__)
      SCREAMING_SNAKE_CASE				    =		AutoConfig.for_model(lowerCAmelCase__  ,  **lowerCAmelCase__)
      SCREAMING_SNAKE_CASE				    =		True





     @classmethod
     def     __UpperCamelCase						(		cls					:	str  ,  lowerCAmelCase__					:	PretrainedConfig  ,  lowerCAmelCase__					:	PretrainedConfig  ,  **lowerCAmelCase__					:	List[str])							->	PretrainedConfig:

      """simple docstring"""
      logger.info('Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config')
      SCREAMING_SNAKE_CASE				    =		True
      SCREAMING_SNAKE_CASE				    =		True

      return cls(encoder=encoder_config.to_dict()  ,  decoder=decoder_config.to_dict()  ,  **lowerCAmelCase__)





     def     __UpperCamelCase						(		self					:	str)							->	Union[str, Any]:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		copy.deepcopy(self.__dict__)
      SCREAMING_SNAKE_CASE				    =		self.encoder.to_dict()
      SCREAMING_SNAKE_CASE				    =		self.decoder.to_dict()
      SCREAMING_SNAKE_CASE				    =		self.__class__.model_type
      return output




