




from __future__ import annotations

def    UpperCAmelCase_				( __UpperCAmelCase		:      list[int]     ,     __UpperCAmelCase		:      int     ,     __UpperCAmelCase		:      int     ,     __UpperCAmelCase		:      int				)   ->					None:
      if (direction == 1 and array[indexa] > array[indexa]) or (
          direction == 0 and array[indexa] < array[indexa]
      ):
            SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_      		=     array[indexa], array[indexa]

def    UpperCAmelCase_				( __UpperCAmelCase		:      list[int]     ,     __UpperCAmelCase		:      int     ,     __UpperCAmelCase		:      int     ,     __UpperCAmelCase		:      int				)   ->					None:
      if length > 1:
            SCREAMING_SNAKE_CASE_      		=     int(length / 2				)
            for i in range(__UpperCAmelCase     ,     low + middle				):
                  comp_and_swap(__UpperCAmelCase     ,     __UpperCAmelCase     ,     i + middle     ,     __UpperCAmelCase				)
            bitonic_merge(__UpperCAmelCase     ,     __UpperCAmelCase     ,     __UpperCAmelCase     ,     __UpperCAmelCase				)
            bitonic_merge(__UpperCAmelCase     ,     low + middle     ,     __UpperCAmelCase     ,     __UpperCAmelCase				)

def    UpperCAmelCase_				( __UpperCAmelCase		:      list[int]     ,     __UpperCAmelCase		:      int     ,     __UpperCAmelCase		:      int     ,     __UpperCAmelCase		:      int				)   ->					None:
      if length > 1:
            SCREAMING_SNAKE_CASE_      		=     int(length / 2				)
            bitonic_sort(__UpperCAmelCase     ,     __UpperCAmelCase     ,     __UpperCAmelCase     ,     1				)
            bitonic_sort(__UpperCAmelCase     ,     low + middle     ,     __UpperCAmelCase     ,     0				)
            bitonic_merge(__UpperCAmelCase     ,     __UpperCAmelCase     ,     __UpperCAmelCase     ,     __UpperCAmelCase				)


if __name__ == "__main__":
   lowerCamelCase__					:  Optional[Any]      							=				input('Enter numbers separated by a comma:\n').strip()
   lowerCamelCase__					:  Tuple      							=				[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=', ')





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


if is_sentencepiece_available():
   from ..ta.tokenization_ta import TaTokenizer
else:
   from ...utils.dummy_sentencepiece_objects import TaTokenizer

lowerCamelCase__					:  List[Any]      							=				TaTokenizer

if is_tokenizers_available():
   from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
   from ...utils.dummy_tokenizers_objects import TaTokenizerFast

lowerCamelCase__					:  Union[str, Any]      							=				TaTokenizerFast

lowerCamelCase__					:  Dict      							=				{'configuration_mt5': ['MT5Config', 'MT5OnnxConfig']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__					:  Tuple      							=				[
       'MT5EncoderModel',
       'MT5ForConditionalGeneration',
       'MT5ForQuestionAnswering',
       'MT5Model',
       'MT5PreTrainedModel',
       'MT5Stack',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__					:  Tuple      							=				['TFMT5EncoderModel', 'TFMT5ForConditionalGeneration', 'TFMT5Model']

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__					:  Tuple      							=				['FlaxMT5EncoderModel', 'FlaxMT5ForConditionalGeneration', 'FlaxMT5Model']


if TYPE_CHECKING:
   from .configuration_mta import MTaConfig, MTaOnnxConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_mta import (
          MTaEncoderModel,
          MTaForConditionalGeneration,
          MTaForQuestionAnswering,
          MTaModel,
          MTaPreTrainedModel,
          MTaStack,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
   import sys

   lowerCamelCase__					:  int      							=				_LazyModule(
       __name__,
       globals()['__file__'],
       _import_structure,
       extra_objects={'MT5Tokenizer': MTaTokenizer, 'MT5TokenizerFast': MTaTokenizerFast},
       module_spec=__spec__,
   )