





from math import ceil, sqrt





def      lowerCAmelCase_ (       __a = 1000000		)     ->		int:







  """simple docstring"""





  lowerCamelCase__:      Optional[int]			  =0

  for outer_width in range(3	,    (limit // 4) + 2		):
    if outer_width**2 > limit:
      lowerCamelCase__:      Dict			  =max(ceil(sqrt(outer_width**2 - limit		)		)	,    1		)
    else:
      lowerCamelCase__:      str			  =1
    if (outer_width - hole_width_lower_bound) % 2:
      hole_width_lower_bound += 1

    answer += (outer_width - hole_width_lower_bound - 2) // 2 + 1

  return answer


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








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A									=				{"configuration_ibert": ["IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "IBertConfig", "IBertOnnxConfig"]}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __A									=				[
         "IBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "IBertForMaskedLM",
         "IBertForMultipleChoice",
         "IBertForQuestionAnswering",
         "IBertForSequenceClassification",
         "IBertForTokenClassification",
         "IBertModel",
         "IBertPreTrainedModel",
     ]

if TYPE_CHECKING:
     from .configuration_ibert import IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, IBertConfig, IBertOnnxConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_ibert import (
              IBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              IBertForMaskedLM,
              IBertForMultipleChoice,
              IBertForQuestionAnswering,
              IBertForSequenceClassification,
              IBertForTokenClassification,
              IBertModel,
              IBertPreTrainedModel,
          )

else:
     import sys

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

