'''simple docstring'''




from __future__ import annotations

__SCREAMING_SNAKE_CASE       :     Optional[int]     =  10

def 	UpperCamelCase_							(					_UpperCAmelCase  :      list[int]    )    ->    list[int]:


       """simple docstring"""







       _UpperCAmelCase     :  Dict							      =    1
       _UpperCAmelCase     :  List[str]							      =    max(_UpperCAmelCase    )
       while placement <= max_digit:
              # declare and initialize empty buckets
              _UpperCAmelCase     :  list[list]							      =    [[] for _ in range(_UpperCAmelCase    )]
              # split list_of_ints between the buckets
              for i in list_of_ints:
                     _UpperCAmelCase     :  List[Any]							      =    int((i / placement) % RADIX    )
                     buckets[tmp].append(_UpperCAmelCase    )
              # put each buckets' contents into list_of_ints
              _UpperCAmelCase     :  List[str]							      =    0
              for b in range(_UpperCAmelCase    ):
                     for i in buckets[b]:
                            _UpperCAmelCase     :  Optional[int]							      =    i
                            a += 1
        # move to next
              placement *= RADIX
       return list_of_ints


if __name__ == "__main__":
  import doctest

  doctest.testmod()







from typing import TYPE_CHECKING

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


_UpperCAmelCase		:  int	=   {"configuration_swin": ["SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwinConfig", "SwinOnnxConfig"]}


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase		:  List[str]	=   [
         "SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
         "SwinForImageClassification",
         "SwinForMaskedImageModeling",
         "SwinModel",
         "SwinPreTrainedModel",
         "SwinBackbone",
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase		:  int	=   [
         "TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
         "TFSwinForImageClassification",
         "TFSwinForMaskedImageModeling",
         "TFSwinModel",
         "TFSwinPreTrainedModel",
     ]

if TYPE_CHECKING:
     from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_swin import (
              SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
              SwinBackbone,
              SwinForImageClassification,
              SwinForMaskedImageModeling,
              SwinModel,
              SwinPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_swin import (
              TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFSwinForImageClassification,
              TFSwinForMaskedImageModeling,
              TFSwinModel,
              TFSwinPreTrainedModel,
          )

else:
     import sys

     _UpperCAmelCase		:  int	=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



