






"""simple docstring"""


from typing import TYPE_CHECKING

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


_UpperCamelCase   :						Optional[Any]     						= {"""configuration_vilt""": ["""VILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViltConfig"""]}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCamelCase   :						str     						= ["""ViltFeatureExtractor"""]
   _UpperCamelCase   :						Tuple     						= ["""ViltImageProcessor"""]
   _UpperCamelCase   :						str     						= ["""ViltProcessor"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCamelCase   :						Tuple     						= [
       """VILT_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """ViltForImageAndTextRetrieval""",
       """ViltForImagesAndTextClassification""",
       """ViltForTokenClassification""",
       """ViltForMaskedLM""",
       """ViltForQuestionAnswering""",
       """ViltLayer""",
       """ViltModel""",
       """ViltPreTrainedModel""",
   ]


if TYPE_CHECKING:
   from .configuration_vilt import VILT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViltConfig

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_vilt import ViltFeatureExtractor
      from .image_processing_vilt import ViltImageProcessor
      from .processing_vilt import ViltProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_vilt import (
          VILT_PRETRAINED_MODEL_ARCHIVE_LIST,
          ViltForImageAndTextRetrieval,
          ViltForImagesAndTextClassification,
          ViltForMaskedLM,
          ViltForQuestionAnswering,
          ViltForTokenClassification,
          ViltLayer,
          ViltModel,
          ViltPreTrainedModel,
      )


else:
   import sys

   _UpperCamelCase   :						Union[str, Any]     						= _LazyModule(__name__, globals()["""__file__"""], _import_structure)













"""simple docstring"""


import math




def 				a (     UpperCamelCase_							:				int		)  ->		list[int]:
 if not isinstance(UpperCamelCase_     ,	UpperCamelCase_		):
  __A	:       Any       =	F"Input value of [number={number}] must be an integer"
  raise TypeError(UpperCamelCase_		)
 if number < 1:
  __A	:       int       =	F"Input value of [number={number}] must be a positive integer"
  raise ValueError(UpperCamelCase_		)
 __A	:       Optional[Any]       =	[number]
 while number != 1:
  if number % 2 == 0:
   __A	:       Optional[int]       =	math.floor(math.sqrt(UpperCamelCase_		)		)
  else:
   __A	:       List[str]       =	math.floor(
       math.sqrt(UpperCamelCase_		) * math.sqrt(UpperCamelCase_		) * math.sqrt(UpperCamelCase_		)		)
  sequence.append(UpperCamelCase_		)
 return sequence


if __name__ == "__main__":
   import doctest

   doctest.testmod()





