



"""simple docstring"""
from __future__ import annotations

from random import random


class 							lowerCamelCase_:





					'''simple docstring'''



					def __init__(    self				,       lowerCamelCase__ = None   ):
									_lowerCamelCase        =				value
									_lowerCamelCase        =				random()
									_lowerCamelCase        =				None
									_lowerCamelCase        =				None

					def __repr__(    self   ):
									from pprint import pformat

									if self.left is None and self.right is None:
													return F"""'{self.value}: {self.prior:.5}'"""
									else:
													return pformat(
													    {F"""{self.value}: {self.prior:.5}""": (self.left, self.right)}				,       indent=1   )





					def __str__(    self   ):
									_lowerCamelCase        =				str(self.value   ) + ''' '''
									_lowerCamelCase        =				str(self.left or ''''''   )
									_lowerCamelCase        =				str(self.right or ''''''   )
									return value + left + right



def        lowerCAmelCase_(   lowercase_     :							Node | None						,   lowercase_     :							int							)	->       tuple[Node | None, Node | None]:
				if root is None:  # None tree is split into 2 Nones
								return None, None
				elif root.value is None:
								return None, None
				else:
								if value < root.value:
												_lowerCamelCase  ,     _lowerCamelCase        =				split(root.left						,   lowercase_							)
												return left, root
								else:
												_lowerCamelCase  ,     _lowerCamelCase        =				split(root.right						,   lowercase_							)
												return root, right



def        lowerCAmelCase_(   lowercase_     :							Node | None						,   lowercase_     :							Node | None							)	->       Node | None:
				if (not left) or (not right):  # If one node is None, return the other
								return left or right
				elif left.prior < right.prior:
								_lowerCamelCase        =				merge(left.right						,   lowercase_							)
								return left
				else:
								_lowerCamelCase        =				merge(lowercase_						,   right.left							)
								return right



def        lowerCAmelCase_(   lowercase_     :							Node | None						,   lowercase_     :							int							)	->       Node | None:
				_lowerCamelCase        =				Node(lowercase_							)
				_lowerCamelCase  ,     _lowerCamelCase        =				split(lowercase_						,   lowercase_							)
				return merge(merge(lowercase_						,   lowercase_							)						,   lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Node | None						,   lowercase_     :							int							)	->       Node | None:
				_lowerCamelCase  ,     _lowerCamelCase        =				split(lowercase_						,   value - 1							)
				_lowerCamelCase  ,     _lowerCamelCase        =				split(lowercase_						,   lowercase_							)
				return merge(lowercase_						,   lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Node | None							)	->       None:
				if not root:  # None
								return
				else:
								inorder(root.left							)
								print(root.value						,   end=''','''							)
								inorder(root.right							)



def        lowerCAmelCase_(   lowercase_     :							Node | None						,   lowercase_     :							str							)	->       Node | None:
				for arg in args.split():
								if arg[0] == "+":
												_lowerCamelCase        =				insert(lowercase_						,   int(arg[1:]							)							)

								elif arg[0] == "-":
												_lowerCamelCase        =				erase(lowercase_						,   int(arg[1:]							)							)

								else:
												print('''Unknown command'''							)

				return root



def        lowerCAmelCase_(   )	->       None:
				_lowerCamelCase        =				None
				print(
				    '''enter numbers to create a tree, + value to add value into treap, '''
				    '''- value to erase all nodes with value. \'q\' to quit. '''							)

				_lowerCamelCase        =				input()
				while args != "q":
								_lowerCamelCase        =				interact_treap(lowercase_						,   lowercase_							)
								print(lowercase_							)
								_lowerCamelCase        =				input()

				print('''good by!'''							)


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							main()





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

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


__SCREAMING_SNAKE_CASE  :						Union[str, Any]    							=      {
    '''configuration_speecht5''': [
        '''SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP''',
        '''SpeechT5Config''',
        '''SpeechT5HifiGanConfig''',
    ],
    '''feature_extraction_speecht5''': ['''SpeechT5FeatureExtractor'''],
    '''processing_speecht5''': ['''SpeechT5Processor'''],
}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__SCREAMING_SNAKE_CASE  :						Tuple    							=      ['''SpeechT5Tokenizer''']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__SCREAMING_SNAKE_CASE  :						Any    							=      [
			    '''SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''SpeechT5ForSpeechToText''',
			    '''SpeechT5ForSpeechToSpeech''',
			    '''SpeechT5ForTextToSpeech''',
			    '''SpeechT5Model''',
			    '''SpeechT5PreTrainedModel''',
			    '''SpeechT5HifiGan''',
			]

if TYPE_CHECKING:
			from .configuration_speechta import (
			    SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
			    SpeechTaConfig,
			    SpeechTaHifiGanConfig,
			)
			from .feature_extraction_speechta import SpeechTaFeatureExtractor
			from .processing_speechta import SpeechTaProcessor

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_speechta import SpeechTaTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_speechta import (
						    SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
						    SpeechTaForSpeechToSpeech,
						    SpeechTaForSpeechToText,
						    SpeechTaForTextToSpeech,
						    SpeechTaHifiGan,
						    SpeechTaModel,
						    SpeechTaPreTrainedModel,
						)

else:
			import sys

			__SCREAMING_SNAKE_CASE  :						int    							=      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
