






from typing import TYPE_CHECKING

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


__a   :							str						= {
    "configuration_maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig"],
    "configuration_maskformer_swin": ["MaskFormerSwinConfig"],
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a   :							Union[str, Any]						= ["MaskFormerFeatureExtractor"]
  __a   :							Any						= ["MaskFormerImageProcessor"]


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a   :							Union[str, Any]						= [
      "MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
      "MaskFormerForInstanceSegmentation",
      "MaskFormerModel",
      "MaskFormerPreTrainedModel",
  ]
  __a   :							Any						= [
      "MaskFormerSwinBackbone",
      "MaskFormerSwinModel",
      "MaskFormerSwinPreTrainedModel",
  ]

if TYPE_CHECKING:
  from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig
  from .configuration_maskformer_swin import MaskFormerSwinConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_maskformer import MaskFormerFeatureExtractor
    from .image_processing_maskformer import MaskFormerImageProcessor
  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_maskformer import (
        MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        MaskFormerForInstanceSegmentation,
        MaskFormerModel,
        MaskFormerPreTrainedModel,
    )
    from .modeling_maskformer_swin import (
        MaskFormerSwinBackbone,
        MaskFormerSwinModel,
        MaskFormerSwinPreTrainedModel,
    )


else:
  import sys

  __a   :							Dict						= _LazyModule(__name__, globals()["__file__"], _import_structure)












def       _SCREAMING_SNAKE_CASE    (			__lowercase :      List[Any]     )    ->   Any:





    """simple docstring"""

    stooge(__lowercase      ,					0      ,					len(__lowercase     ) - 1     )
    return arr



def       _SCREAMING_SNAKE_CASE    (			__lowercase :      str      ,					__lowercase :      Dict      ,					__lowercase :      Dict     )    ->   int:





    """simple docstring"""

    if i >= h:
        return

    # If first element is smaller than the last then swap them
    if arr[i] > arr[h]:
        __A     ,						__A       =						arr[h], arr[i]

    # If there are more than 2 elements in the array
    if h - i + 1 > 2:
        __A       =						(int)((h - i + 1) / 3     )

        # Recursively sort first 2/3 elements
        stooge(__lowercase      ,					__lowercase      ,					(h - t)     )

        # Recursively sort last 2/3 elements
        stooge(__lowercase      ,					i + t      ,					(__lowercase)     )

        # Recursively sort first 2/3 elements
        stooge(__lowercase      ,					__lowercase      ,					(h - t)     )


if __name__ == "__main__":
  __a   :							List[Any]						= input("Enter numbers separated by a comma:\n").strip()
  __a   :							List[str]						= [int(item) for item in user_input.split(",")]
  print(stooge_sort(unsorted))




