






import decimal






def        lowerCamelCase__   (					):
  __UpperCAmelCase							:			str     =						0
  __UpperCAmelCase							:			Tuple     =						decimal.Context(prec=105	)
  for i in range(2						,	100	):
    __UpperCAmelCase							:			Optional[int]     =						decimal.Decimal(__lowerCamelCase	)
    __UpperCAmelCase							:			Any     =						number.sqrt(__lowerCamelCase	)
    if len(str(__lowerCamelCase	)	) > 1:
      answer += int(str(__lowerCamelCase	)[0]	)
      __UpperCAmelCase							:			Optional[Any]     =						str(__lowerCamelCase	)[2:101]
      answer += sum(int(__lowerCamelCase	) for x in sqrt_number_str	)
  return answer


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       print(f"""{solution() = }""")










from typing import TYPE_CHECKING

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


a	: Union[str, Any]      =				{
    "configuration_mobilenet_v1": [
        "MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "MobileNetV1Config",
        "MobileNetV1OnnxConfig",
    ],
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a	: int      =				["MobileNetV1FeatureExtractor"]
       a	: int      =				["MobileNetV1ImageProcessor"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a	: int      =				[
           "MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST",
           "MobileNetV1ForImageClassification",
           "MobileNetV1Model",
           "MobileNetV1PreTrainedModel",
           "load_tf_weights_in_mobilenet_v1",
       ]


if TYPE_CHECKING:
       from .configuration_mobilenet_va import (
           MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP,
           MobileNetVaConfig,
           MobileNetVaOnnxConfig,
       )

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
              from .image_processing_mobilenet_va import MobileNetVaImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_mobilenet_va import (
                  MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST,
                  MobileNetVaForImageClassification,
                  MobileNetVaModel,
                  MobileNetVaPreTrainedModel,
                  load_tf_weights_in_mobilenet_va,
              )


else:
       import sys

       a	: str      =				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


