'''simple docstring'''


from typing import TYPE_CHECKING

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


snake_case__					:      Dict				      =  {'''configuration_beit''': ['''BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BeitConfig''', '''BeitOnnxConfig''']}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__					:      Tuple				      =  ['''BeitFeatureExtractor''']
 snake_case__					:      List[str]				      =  ['''BeitImageProcessor''']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__					:      Any				      =  [
     '''BEIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''BeitForImageClassification''',
     '''BeitForMaskedImageModeling''',
     '''BeitForSemanticSegmentation''',
     '''BeitModel''',
     '''BeitPreTrainedModel''',
 ]


try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__					:      List[Any]				      =  [
     '''FlaxBeitForImageClassification''',
     '''FlaxBeitForMaskedImageModeling''',
     '''FlaxBeitModel''',
     '''FlaxBeitPreTrainedModel''',
 ]

if TYPE_CHECKING:
 from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_beit import BeitFeatureExtractor
  from .image_processing_beit import BeitImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_beit import (
      BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
      BeitForImageClassification,
      BeitForMaskedImageModeling,
      BeitForSemanticSegmentation,
      BeitModel,
      BeitPreTrainedModel,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_beit import (
      FlaxBeitForImageClassification,
      FlaxBeitForMaskedImageModeling,
      FlaxBeitModel,
      FlaxBeitPreTrainedModel,
  )


else:
 import sys

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







'''simple docstring'''


snake_case__					:      str				      =  '''Tobias Carryer'''

from time import time






class 					__SCREAMING_SNAKE_CASE						:







  '''simple docstring'''






  def __init__(			self				,		snake_case_				,		snake_case_				,		snake_case_				,		snake_case_=int(time()						)						):  # noqa: B008




       '''simple docstring'''

       UpperCAmelCase_							:       str       =				multiplier
       UpperCAmelCase_							:       Dict       =				increment
       UpperCAmelCase_							:       Tuple       =				modulo
       UpperCAmelCase_							:       Dict       =				seed






  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Union[str, Any]       =				(self.multiplier * self.seed + self.increment) % self.modulo
       return self.seed


if __name__ == "__main__":
 # Show the LCG in action.
 snake_case__					:      Any				      =  LinearCongruentialGenerator(166_4525, 10_1390_4223, 2 << 31)
 while True:
  print(lcg.next_number())






