'''simple docstring'''






from typing import TYPE_CHECKING

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


__a									=   {
    '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:
     __a									=   ['SpeechT5Tokenizer']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __a									=   [
         '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

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






"""simple docstring"""



from collections import defaultdict
from math import gcd







def 						__lowercase	(  snake_case_    :    int = 1500000		)  ->int:



    '''simple docstring'''







    __A       :		defaultdict							=	defaultdict(snake_case_		)
    __A       :		Any							=	2
    while 2 * euclid_m * (euclid_m + 1) <= limit:
        for euclid_n in range((euclid_m % 2) + 1							,snake_case_							,2		):
            if gcd(snake_case_							,snake_case_		) > 1:
                continue
            __A       :		List[Any]							=	2 * euclid_m * (euclid_m + euclid_n)
            for perimeter in range(snake_case_							,limit + 1							,snake_case_		):
                frequencies[perimeter] += 1
        euclid_m += 1
    return sum(1 for frequency in frequencies.values() if frequency == 1		)


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




