





"""simple docstring"""


from math import sqrt

def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):

						if 1 < number < 4:
												# 2 and 3 are primes
												return True
						elif number < 2 or number % 2 == 0 or number % 3 == 0:
												# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
												return False

						# All primes number are in format of 6k +/- 1
						for i in range(5							,     int(sqrt(SCREAMING_SNAKE_CASE     ) + 1     )							,     6     ):
												if number % i == 0 or number % (i + 2) == 0:
																		return False
						return True

def      UpperCamelCase							(SCREAMING_SNAKE_CASE = 1_0001     ):
						UpperCamelCase				:		Any				   =			0
						UpperCamelCase				:		Optional[int]				   =			1
						while count != nth and number < 3:
												number += 1
												if is_prime(SCREAMING_SNAKE_CASE     ):
																		count += 1
						while count != nth:
												number += 2
												if is_prime(SCREAMING_SNAKE_CASE     ):
																		count += 1
						return number


if __name__ == "__main__":
		print(f'''{solution() = }''')





"""simple docstring"""

from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_            =    {
    '''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_            =    ['''SpeechT5Tokenizer''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE_            =    [
       '''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_            =    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



