






from __future__ import annotations





def  _lowerCamelCase						(						__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase       ) ->			None:

     '''simple docstring'''
     if (direction == 1 and array[indexa] > array[indexa]) or (
         direction == 0 and array[indexa] < array[indexa]
     ):
          UpperCAmelCase__      ,		UpperCAmelCase__      :  Optional[int]				      =			array[indexa], array[indexa]





def  _lowerCamelCase						(						__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase       ) ->			None:

     '''simple docstring'''
     if length > 1:
          UpperCAmelCase__      :  Optional[int]				      =			int(length / 2       )
          for i in range(__lowerCamelCase ,							low + middle       ):
               comp_and_swap(__lowerCamelCase ,							__lowerCamelCase ,							i + middle ,							__lowerCamelCase       )
          bitonic_merge(__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase       )
          bitonic_merge(__lowerCamelCase ,							low + middle ,							__lowerCamelCase ,							__lowerCamelCase       )





def  _lowerCamelCase						(						__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase       ) ->			None:

     '''simple docstring'''
     if length > 1:
          UpperCAmelCase__      :  Dict				      =			int(length / 2       )
          bitonic_sort(__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase ,							1       )
          bitonic_sort(__lowerCamelCase ,							low + middle ,							__lowerCamelCase ,							0       )
          bitonic_merge(__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase       )


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

      bitonic_sort(unsorted, 0, len(unsorted), 1)
      print("""\nSorted array in ascending order is: """, end="""""")
      print(*unsorted, sep=""", """)

      bitonic_merge(unsorted, 0, len(unsorted), 0)
      print("""Sorted array in descending order is: """, end="""""")
      print(*unsorted, sep=""", """)










'''simple docstring'''






from typing import TYPE_CHECKING

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


__A   :    str											= {
    "configuration_audio_spectrogram_transformer": [
        "AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "ASTConfig",
    ]
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A   :    List[str]											= [
      "AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
      "ASTForAudioClassification",
      "ASTModel",
      "ASTPreTrainedModel",
  ]

try:
  if not is_speech_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A   :    Union[str, Any]											= ["ASTFeatureExtractor"]

if TYPE_CHECKING:
  from .configuration_audio_spectrogram_transformer import (
      AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      ASTConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_audio_spectrogram_transformer import (
        AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        ASTForAudioClassification,
        ASTModel,
        ASTPreTrainedModel,
    )

  try:
    if not is_speech_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor


else:
  import sys

  __A   :    List[Any]											= _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



