
'''simple docstring'''






import math







def     UpperCamelCase_      (   A__ :       Union[str, Any] ):
  '''simple docstring'''





  lowerCAmelCase_      :				int      =       math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )

  return exponent == int(SCREAMING_SNAKE_CASE_ )







def     UpperCamelCase_      (   A__ :       Dict = 1 / 1_23_45 ):
  '''simple docstring'''





  lowerCAmelCase_      :				Any      =       0
  lowerCAmelCase_      :				Optional[int]      =       0

  lowerCAmelCase_      :				Dict      =       3
  while True:
    lowerCAmelCase_      :				Optional[int]      =       (integer**2 - 1) / 4
    # if candidate is an integer, then there is a partition for k
    if partition_candidate == int(SCREAMING_SNAKE_CASE_ ):
      lowerCAmelCase_      :				Union[str, Any]      =       int(SCREAMING_SNAKE_CASE_ )
      total_partitions += 1
      if check_partition_perfect(SCREAMING_SNAKE_CASE_ ):
        perfect_partitions += 1
    if perfect_partitions > 0:
      if perfect_partitions / total_partitions < max_proportion:
        return int(SCREAMING_SNAKE_CASE_ )
    integer += 1


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







'''simple docstring'''






from typing import TYPE_CHECKING

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


__A :  List[Any]    							=				{
    "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:
  __A :  Union[str, Any]    							=				[
      "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

  __A :  int    							=				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



