



'''simple docstring'''





from typing import TYPE_CHECKING

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


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

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase										=     ['''BeitFeatureExtractor''']
 _lowerCAmelCase										=     ['''BeitImageProcessor''']

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


try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase										=     [
     '''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

 _lowerCAmelCase										=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)







'''simple docstring'''





def        _SCREAMING_SNAKE_CASE  (	UpperCamelCase      ):



    """simple docstring"""





    if any(not isinstance(UpperCamelCase							,   UpperCamelCase      ) or x < 0 for x in sequence      ):
        raise TypeError("""Sequence must be list of non-negative integers"""      )
    for _ in range(len(UpperCamelCase      )      ):
        for i, (rod_upper, rod_lower) in enumerate(zip(UpperCamelCase							,   sequence[1:]      )      ):
            if rod_upper > rod_lower:
                sequence[i] -= rod_upper - rod_lower
                sequence[i + 1] += rod_upper - rod_lower
    return sequence


if __name__ == "__main__":
 assert bead_sort([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5]
 assert bead_sort([7, 9, 4, 3, 5]) == [3, 4, 5, 7, 9]


