
'''simple docstring'''





def snake_case_     (					lowercase__ = 1_0_0_0_0_0_0		):
  UpperCAmelCase__      :					Optional[Any]				       =							set(range(3   ,       lowercase__   ,       2		)		)
  primes.add(2		)
  for p in range(3   ,       lowercase__   ,       2		):
    if p not in primes:
      continue
    primes.difference_update(set(range(p * p   ,       lowercase__   ,       lowercase__		)		)		)

  UpperCAmelCase__      :					Optional[int]				       =							[float(lowercase__		) for n in range(limit + 1		)]

  for p in primes:
    for n in range(lowercase__   ,       limit + 1   ,       lowercase__		):
      phi[n] *= 1 - 1 / p

  return int(sum(phi[2:]		)		)


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





'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


SCREAMING_SNAKE_CASE     =       {"""configuration_deit""": ["""DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DeiTConfig""", """DeiTOnnxConfig"""]}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE     =       ["""DeiTFeatureExtractor"""]
      SCREAMING_SNAKE_CASE     =       ["""DeiTImageProcessor"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE     =       [
          """DEIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """DeiTForImageClassification""",
          """DeiTForImageClassificationWithTeacher""",
          """DeiTForMaskedImageModeling""",
          """DeiTModel""",
          """DeiTPreTrainedModel""",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE     =       [
          """TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """TFDeiTForImageClassification""",
          """TFDeiTForImageClassificationWithTeacher""",
          """TFDeiTForMaskedImageModeling""",
          """TFDeiTModel""",
          """TFDeiTPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_deit import DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, DeiTConfig, DeiTOnnxConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_deit import DeiTFeatureExtractor
            from .image_processing_deit import DeiTImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_deit import (
                DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                DeiTForImageClassification,
                DeiTForImageClassificationWithTeacher,
                DeiTForMaskedImageModeling,
                DeiTModel,
                DeiTPreTrainedModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_deit import (
                TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFDeiTForImageClassification,
                TFDeiTForImageClassificationWithTeacher,
                TFDeiTForMaskedImageModeling,
                TFDeiTModel,
                TFDeiTPreTrainedModel,
            )


else:
      import sys

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



