






"""simple docstring"""







from typing import TYPE_CHECKING

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


lowerCAmelCase_		:			Tuple				   =					{'''configuration_detr''': ['''DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DetrConfig''', '''DetrOnnxConfig''']}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_		:			Optional[Any]				   =					['''DetrFeatureExtractor''']
 lowerCAmelCase_		:			Dict				   =					['''DetrImageProcessor''']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_		:			Dict				   =					[
     '''DETR_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''DetrForObjectDetection''',
     '''DetrForSegmentation''',
     '''DetrModel''',
     '''DetrPreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_detr import DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DetrConfig, DetrOnnxConfig

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_detr import DetrFeatureExtractor
  from .image_processing_detr import DetrImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_detr import (
      DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
      DetrForObjectDetection,
      DetrForSegmentation,
      DetrModel,
      DetrPreTrainedModel,
  )

else:
 import sys

 lowerCAmelCase_		:			str				   =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)








"""simple docstring"""


def 			snake_case  (A_      :int = 1_0_0_0      ):







  '''simple docstring'''

  a     :			Union[str, Any]				=   0
  a     :			int				=   (n - 1) // 3
  total += ((terms) * (6 + (terms - 1) * 3)) // 2  # total of an A.P.
  a     :			Tuple				=   (n - 1) // 5
  total += ((terms) * (1_0 + (terms - 1) * 5)) // 2
  a     :			Dict				=   (n - 1) // 1_5
  total -= ((terms) * (3_0 + (terms - 1) * 1_5)) // 2
  return total


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




