
"""simple docstring"""





from __future__ import annotations

lowerCamelCase      =		10
def      a__			(   lowerCAmelCase__   ):
      UpperCAmelCase_    				=							1
      UpperCAmelCase_    				=							max(lowerCAmelCase__   )
      while placement <= max_digit:
            # declare and initialize empty buckets
            UpperCAmelCase_    				=							[[] for _ in range(lowerCAmelCase__   )]
            # split list_of_ints between the buckets
            for i in list_of_ints:
                  UpperCAmelCase_    				=							int((i / placement) % RADIX   )
                  buckets[tmp].append(lowerCAmelCase__   )
            # put each buckets' contents into list_of_ints
            UpperCAmelCase_    				=							0
            for b in range(lowerCAmelCase__   ):
                  for i in buckets[b]:
                        UpperCAmelCase_    				=							i
                        a += 1
                        # move to next
            placement *= RADIX
      return list_of_ints


if __name__ == "__main__":
  import doctest

  doctest.testmod()









"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase      =		{
    """configuration_swinv2""": ["""SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Swinv2Config"""],
}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase      =		[
      """SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """Swinv2ForImageClassification""",
      """Swinv2ForMaskedImageModeling""",
      """Swinv2Model""",
      """Swinv2PreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_swinva import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinvaConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_swinva import (
        SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST,
        SwinvaForImageClassification,
        SwinvaForMaskedImageModeling,
        SwinvaModel,
        SwinvaPreTrainedModel,
    )


else:
  import sys

  lowerCamelCase      =		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




