
'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCAmelCase__      		=			{
    '''configuration_roc_bert''': ['''ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RoCBertConfig'''],
    '''tokenization_roc_bert''': ['''RoCBertTokenizer'''],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 pass

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase__      		=			[
     '''ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''RoCBertForCausalLM''',
     '''RoCBertForMaskedLM''',
     '''RoCBertForMultipleChoice''',
     '''RoCBertForPreTraining''',
     '''RoCBertForQuestionAnswering''',
     '''RoCBertForSequenceClassification''',
     '''RoCBertForTokenClassification''',
     '''RoCBertLayer''',
     '''RoCBertModel''',
     '''RoCBertPreTrainedModel''',
     '''load_tf_weights_in_roc_bert''',
 ]

if TYPE_CHECKING:
 from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
 from .tokenization_roc_bert import RoCBertTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  raise OptionalDependencyNotAvailable()

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_roc_bert import (
      ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      RoCBertForCausalLM,
      RoCBertForMaskedLM,
      RoCBertForMultipleChoice,
      RoCBertForPreTraining,
      RoCBertForQuestionAnswering,
      RoCBertForSequenceClassification,
      RoCBertForTokenClassification,
      RoCBertLayer,
      RoCBertModel,
      RoCBertPreTrainedModel,
      load_tf_weights_in_roc_bert,
  )


else:
 import sys

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




'''simple docstring'''






def 	_A  (					):






 """simple docstring"""



 for n in range(1  ,       1000000   ):
  yield n * (n + 1) // 2


def 	_A  (					A__   ):






 """simple docstring"""



 __lowercase													=				1
 __lowercase													=				2
 while i * i <= n:
  __lowercase													=				0
  while n % i == 0:
   n //= i
   multiplicity += 1
  divisors_count *= multiplicity + 1
  i += 1
 if n > 1:
  divisors_count *= 2
 return divisors_count


def 	_A  (					):






 """simple docstring"""



 return next(i for i in triangle_number_generator() if count_divisors(A__   ) > 500   )


if __name__ == "__main__":
 print(solution())

