





# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowercase_					     =	{
    """configuration_vivit""": ["""VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """VivitConfig"""],
}
try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase_					     =	["""VivitImageProcessor"""]


try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase_					     =	[
          """VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """VivitModel""",
          """VivitPreTrainedModel""",
          """VivitForVideoClassification""",
      ]


if TYPE_CHECKING:
      from .configuration_vivit import VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, VivitConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .image_processing_vivit import VivitImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_vivit import (
                VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                VivitForVideoClassification,
                VivitModel,
                VivitPreTrainedModel,
            )


else:
      import sys

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









def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	)       ->     List[Any]:
  stooge(_SCREAMING_SNAKE_CASE	,		0	,		len(_SCREAMING_SNAKE_CASE	) - 1	)
  return arr




def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	)       ->     int:
  if i >= h:
    return

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

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

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

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

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


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


