'''simple docstring'''




from functools import lru_cache

def _lowercase	(      lowerCamelCase__						)					->       set:





       """simple docstring"""


       __UpperCAmelCase  :				int       				=		2
       __UpperCAmelCase  :				Optional[Any]       				=		set()
       while i * i <= n:
              if n % i:
                     i += 1
              else:
                     n //= i
                     factors.add(lowerCamelCase__						)
       if n > 1:
              factors.add(lowerCamelCase__						)
       return factors

@lru_cache
def _lowercase	(      lowerCamelCase__						)					->       int:





       """simple docstring"""


       return len(unique_prime_factors(lowerCamelCase__						)						)

def _lowercase	(      lowerCamelCase__						)					->       bool:





       """simple docstring"""


       return len(set(lowerCamelCase__						)						) in (0, 1)

def _lowercase	(      lowerCamelCase__						)					->       list:





       """simple docstring"""


       __UpperCAmelCase  :				List[str]       				=		2

       while True:
              # Increment each value of a generated range
              __UpperCAmelCase  :				Tuple       				=		[base + i for i in range(lowerCamelCase__						)]

              # Run elements through out unique_prime_factors function
              # Append our target number to the end.
              __UpperCAmelCase  :				List[Any]       				=		[upf_len(lowerCamelCase__						) for x in group]
              checker.append(lowerCamelCase__						)

              # If all numbers in the list are equal, return the group variable.
              if equality(lowerCamelCase__						):
                     return group

              # Increment our base variable by 1
              base += 1

def _lowercase	(      lowerCamelCase__ = 4						)					->       int:





       """simple docstring"""


       __UpperCAmelCase  :				str       				=		run(lowerCamelCase__						)
       return results[0] if len(lowerCamelCase__						) else None


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







'''simple docstring'''




from typing import TYPE_CHECKING

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


_a   :	str 							=   {"configuration_vit": ["VIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTConfig", "ViTOnnxConfig"]}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	str 							=   ["ViTFeatureExtractor"]
   _a   :	Dict 							=   ["ViTImageProcessor"]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	int 							=   [
       "VIT_PRETRAINED_MODEL_ARCHIVE_LIST",
       "ViTForImageClassification",
       "ViTForMaskedImageModeling",
       "ViTModel",
       "ViTPreTrainedModel",
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	List[str] 							=   [
       "TFViTForImageClassification",
       "TFViTModel",
       "TFViTPreTrainedModel",
   ]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	Dict 							=   [
       "FlaxViTForImageClassification",
       "FlaxViTModel",
       "FlaxViTPreTrainedModel",
   ]

if TYPE_CHECKING:
   from .configuration_vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig, ViTOnnxConfig

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_vit import ViTFeatureExtractor
      from .image_processing_vit import ViTImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_vit import (
          VIT_PRETRAINED_MODEL_ARCHIVE_LIST,
          ViTForImageClassification,
          ViTForMaskedImageModeling,
          ViTModel,
          ViTPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel


else:
   import sys

   _a   :	Dict 							=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






