'''simple docstring'''






from multiprocessing import Lock, Pipe, Process

# lock used to ensure that two processes do not access a pipe at the same time
SCREAMING_SNAKE_CASE_	   =			Lock()






def  UpperCamelCase__					(					_lowercase    :				Tuple   ,    _lowercase    :				str   ,    _lowercase    :				List[str]   ,    _lowercase    :				Optional[Any]   ,    _lowercase    :				Tuple   ,    _lowercase    :				int   ,    _lowercase    :				str      )							->	List[Any]:
  global process_lock

  # we perform n swaps since after n swaps we know we are sorted
  # we *could* stop early if we are sorted already, but it takes as long to
  # find out we are sorted as it does to sort the list with this algorithm
  for i in range(0   ,    1_0      ):
    if (i + position) % 2 == 0 and r_send is not None:
      # send your value to your right neighbor
      process_lock.acquire()
      r_send[1].send(_lowercase      )
      process_lock.release()

      # receive your right neighbor's value
      process_lock.acquire()
      __UpperCAmelCase:					Optional[int]		= rr_cv[0].recv()
      process_lock.release()

      # take the lower value since you are on the left
      __UpperCAmelCase:					Optional[int]		= min(_lowercase   ,    _lowercase      )
    elif (i + position) % 2 != 0 and l_send is not None:
      # send your value to your left neighbor
      process_lock.acquire()
      l_send[1].send(_lowercase      )
      process_lock.release()

      # receive your left neighbor's value
      process_lock.acquire()
      __UpperCAmelCase:					List[Any]		= lr_cv[0].recv()
      process_lock.release()

      # take the higher value since you are on the right
      __UpperCAmelCase:					Optional[int]		= max(_lowercase   ,    _lowercase      )
    # after all swaps are performed, send the values back to main
  result_pipe[1].send(_lowercase      )






def  UpperCamelCase__					(					_lowercase    :				Dict      )							->	Any:
  __UpperCAmelCase:					Union[str, Any]		= []
  __UpperCAmelCase:					List[Any]		= []
  # initialize the list of pipes where the values will be retrieved
  for _ in arr:
    result_pipe.append(Pipe()      )
  # creates the processes
  # the first and last process only have one neighbor so they are made outside
  # of the loop
  __UpperCAmelCase:					Any		= Pipe()
  __UpperCAmelCase:					Tuple		= Pipe()
  process_array_.append(
      Process(
          target=_lowercase   ,    args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0])   ,    )      )
  __UpperCAmelCase:					Dict		= temp_rs
  __UpperCAmelCase:					Optional[int]		= temp_rr

  for i in range(1   ,    len(_lowercase      ) - 1      ):
    __UpperCAmelCase:					List[Any]		= Pipe()
    __UpperCAmelCase:					int		= Pipe()
    process_array_.append(
        Process(
            target=_lowercase   ,    args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i])   ,    )      )
    __UpperCAmelCase:					Dict		= temp_rs
    __UpperCAmelCase:					List[str]		= temp_rr

  process_array_.append(
      Process(
          target=_lowercase   ,    args=(
              len(_lowercase      ) - 1,
              arr[len(_lowercase      ) - 1],
              temp_ls,
              None,
              temp_lr,
              None,
              result_pipe[len(_lowercase      ) - 1],
          )   ,    )      )

  # start the processes
  for p in process_array_:
    p.start()

  # wait for the processes to end and write their values to the list
  for p in range(0   ,    len(_lowercase      )      ):
    __UpperCAmelCase:					List[Any]		= result_pipe[p][0].recv()
    process_array_[p].join()
  return arr






def  UpperCamelCase__					(					)							->	str:
  __UpperCAmelCase:					Any		= list(range(1_0   ,    0   ,    -1      )      )
  print("""Initial List"""      )
  print(*_lowercase      )
  __UpperCAmelCase:					List[Any]		= odd_even_transposition(_lowercase      )
  print("""Sorted List\n"""      )
  print(*_lowercase      )


if __name__ == "__main__":
    main()
'''simple docstring'''






import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch




class    a (       unittest.TestCase				):



  """simple docstring"""
  __lowerCAmelCase				      =					JukeboxTokenizer
  __lowerCAmelCase				      =					{
      """artist""": """Zac Brown Band""",
      """genres""": """Country""",
      """lyrics""": """I met a traveller from an antique land,
        Who said \"Two vast and trunkless legs of stone
        Stand in the desert. . . . Near them, on the sand,
        Half sunk a shattered visage lies, whose frown,
        And wrinkled lip, and sneer of cold command,
        Tell that its sculptor well those passions read
        Which yet survive, stamped on these lifeless things,
        The hand that mocked them, and the heart that fed;
        And on the pedestal, these words appear:
        My name is Ozymandias, King of Kings;
        Look on my Works, ye Mighty, and despair!
        Nothing beside remains. Round the decay
        Of that colossal Wreck, boundless and bare
        The lone and level sands stretch far away
        """,
  }







  @require_torch
  def    lowercase_  (							self					):

    '''simple docstring'''







    import torch

    __UpperCAmelCase:					Dict		= JukeboxTokenizer.from_pretrained("""openai/jukebox-1b-lyrics"""					)
    __UpperCAmelCase:					List[str]		= tokenizer(**self.metas					)["""input_ids"""]
    # fmt: off
    __UpperCAmelCase:					int		= [
        torch.tensor([[
            0, 0, 0, 7169, 507, 9, 76, 39, 31, 46, 76, 27,
            76, 46, 44, 27, 48, 31, 38, 38, 31, 44, 76, 32,
            44, 41, 39, 76, 27, 40, 76, 27, 40, 46, 35, 43,
            47, 31, 76, 38, 27, 40, 30, 64, 78, 76, 76, 76,
            76, 76, 76, 76, 76, 23, 34, 41, 76, 45, 27, 35,
            30, 76, 71, 20, 49, 41, 76, 48, 27, 45, 46, 76,
            27, 40, 30, 76, 46, 44, 47, 40, 37, 38, 31, 45,
            45, 76, 38, 31, 33, 45, 76, 41, 32, 76, 45, 46,
            41, 40, 31, 78, 76, 76, 76, 76, 76, 76, 76, 76,
            19, 46, 27, 40, 30, 76, 35, 40, 76, 46, 34, 31,
            76, 30, 31, 45, 31, 44, 46, 63, 76, 63, 76, 63,
            76, 63, 76, 14, 31, 27, 44, 76, 46, 34, 31, 39,
            64, 76, 41, 40, 76, 46, 34, 31, 76, 45, 27, 40,
            30, 64, 78, 76, 76, 76, 76, 76, 76, 76, 76, 8,
            27, 38, 32, 76, 45, 47, 40, 37, 76, 27, 76, 45,
            34, 27, 46, 46, 31, 44, 31, 30, 76, 48, 35, 45,
            27, 33, 31, 76, 38, 35, 31, 45, 64, 76, 49, 34,
            41, 45, 31, 76, 32, 44, 41, 49, 40, 64, 78, 76,
            76, 76, 76, 76, 76, 76, 76, 1, 40, 30, 76, 49,
            44, 35, 40, 37, 38, 31, 30, 76, 38, 35, 42, 64,
            76, 27, 40, 30, 76, 45, 40, 31, 31, 44, 76, 41,
            32, 76, 29, 41, 38, 30, 76, 29, 41, 39, 39, 27,
            40, 30, 64, 78, 76, 76, 76, 76, 76, 76, 76, 76,
            20, 31, 38, 38, 76, 46, 34, 27, 46, 76, 35, 46,
            45, 76, 45, 29, 47, 38, 42, 46, 41, 44, 76, 49,
            31, 38, 38, 76, 46, 34, 41, 45, 31, 76, 42, 27,
            45, 45, 35, 41, 40, 45, 76, 44, 31, 27, 30, 78,
            76, 76, 76, 76, 76, 76, 76, 76, 23, 34, 35, 29,
            34, 76, 51, 31, 46, 76, 45, 47, 44, 48, 35, 48,
            31, 64, 76, 45, 46, 27, 39, 42, 31, 30, 76, 41,
            40, 76, 46, 34, 31, 45, 31, 76, 38, 35, 32, 31,
            38, 31, 45, 45, 76, 46, 34, 35, 40, 33, 45, 64,
            78, 76, 76, 76, 76, 76, 76, 76, 76, 20, 34, 31,
            76, 34, 27, 40, 30, 76, 46, 34, 27, 46, 76, 39,
            41, 29, 37, 31, 30, 76, 46, 34, 31, 39, 64, 76,
            27, 40, 30, 76, 46, 34, 31, 76, 34, 31, 27, 44,
            46, 76, 46, 34, 27, 46, 76, 32, 31, 30, 66, 78,
            76, 76, 76, 76, 76, 76, 76, 76, 1, 40, 30, 76,
            41, 40, 76, 46, 34, 31, 76, 42, 31, 30, 31, 45,
            46, 27, 38, 64, 76, 46, 34, 31, 45, 31, 76, 49,
            41, 44, 30, 45, 76, 27, 42, 42, 31, 27, 44, 65,
            78, 76, 76, 76, 76, 76, 76, 76, 76, 13, 51, 76,
            40, 27, 39, 31, 76, 35, 45, 76, 15, 52, 51, 39,
            27, 40, 30, 35, 27, 45, 64, 76, 11, 35, 40, 33,
            76, 41, 32, 76, 11, 35, 40, 33, 45, 66, 78, 76,
            76, 76, 76, 76, 76, 76, 76, 12, 41, 41, 37, 76,
            41, 40, 76, 39, 51, 76, 23, 41, 44, 37, 45, 64,
            76, 51, 31, 76, 13, 35, 33, 34, 46, 51, 64, 76,
            27, 40, 30, 76, 30, 31, 45, 42, 27, 35, 44, 67,
            78, 76, 76, 76, 76, 76, 76, 76, 76, 14, 41, 46,
            34, 35, 40, 33, 76, 28, 31, 45, 35, 30, 31, 76,
            44, 31, 39, 27, 35, 40, 45, 63, 76, 18, 41, 47,
            40, 30, 76, 46, 34, 31, 76, 30, 31, 29, 27, 51,
            78, 76, 76, 76, 76, 76, 76, 76, 76, 15, 32, 76,
            46, 34, 27, 46, 76, 29, 41, 38, 41, 45, 45, 27,
            38, 76, 23, 44, 31, 29, 37, 64, 76, 28, 41, 47,
            40, 30, 38, 31, 45, 45, 76, 27, 40, 30, 76, 28,
            27, 44, 31, 78, 76, 76, 76, 76, 76, 76, 76, 76,
            20, 34, 31, 76, 38, 41, 40, 31, 76, 27, 40, 30,
            76, 38, 31, 48, 31, 38, 76, 45, 27, 40, 30, 45,
            76, 45, 46, 44, 31, 46, 29, 34, 76, 32, 27, 44,
            76, 27, 49, 27, 51, 78, 76, 76, 76, 76, 76, 76,
            76, 76]]					),
        torch.tensor([[0, 0, 0, 1069, 11]]					),
        torch.tensor([[0, 0, 0, 1069, 11]]					),
    ]
    # fmt: on
    self.assertTrue(torch.allclose(tokens[0]   ,    EXPECTED_OUTPUT[0]					)					)
    self.assertTrue(torch.allclose(tokens[1]   ,    EXPECTED_OUTPUT[1]					)					)
    self.assertTrue(torch.allclose(tokens[2]   ,    EXPECTED_OUTPUT[2]					)					)







  @require_torch
  def    lowercase_  (							self					):

    '''simple docstring'''







    import torch

    __UpperCAmelCase:					Any		= JukeboxTokenizer.from_pretrained("""openai/jukebox-5b-lyrics"""					)
    __UpperCAmelCase:					Tuple		= tokenizer(**self.metas					)["""input_ids"""]
    # fmt: off
    __UpperCAmelCase:					int		= [
        torch.tensor([[
            0, 0, 0, 1069, 11, -1, -1, -1, -1, 9, 77, 39,
            31, 46, 77, 27, 77, 46, 44, 27, 48, 31, 38, 38,
            31, 44, 77, 32, 44, 41, 39, 77, 27, 40, 77, 27,
            40, 46, 35, 43, 47, 31, 77, 38, 27, 40, 30, 64,
            79, 77, 77, 77, 77, 77, 77, 77, 77, 23, 34, 41,
            77, 45, 27, 35, 30, 77, 72, 20, 49, 41, 77, 48,
            27, 45, 46, 77, 27, 40, 30, 77, 46, 44, 47, 40,
            37, 38, 31, 45, 45, 77, 38, 31, 33, 45, 77, 41,
            32, 77, 45, 46, 41, 40, 31, 79, 77, 77, 77, 77,
            77, 77, 77, 77, 19, 46, 27, 40, 30, 77, 35, 40,
            77, 46, 34, 31, 77, 30, 31, 45, 31, 44, 46, 63,
            77, 63, 77, 63, 77, 63, 77, 14, 31, 27, 44, 77,
            46, 34, 31, 39, 64, 77, 41, 40, 77, 46, 34, 31,
            77, 45, 27, 40, 30, 64, 79, 77, 77, 77, 77, 77,
            77, 77, 77, 8, 27, 38, 32, 77, 45, 47, 40, 37,
            77, 27, 77, 45, 34, 27, 46, 46, 31, 44, 31, 30,
            77, 48, 35, 45, 27, 33, 31, 77, 38, 35, 31, 45,
            64, 77, 49, 34, 41, 45, 31, 77, 32, 44, 41, 49,
            40, 64, 79, 77, 77, 77, 77, 77, 77, 77, 77, 1,
            40, 30, 77, 49, 44, 35, 40, 37, 38, 31, 30, 77,
            38, 35, 42, 64, 77, 27, 40, 30, 77, 45, 40, 31,
            31, 44, 77, 41, 32, 77, 29, 41, 38, 30, 77, 29,
            41, 39, 39, 27, 40, 30, 64, 79, 77, 77, 77, 77,
            77, 77, 77, 77, 20, 31, 38, 38, 77, 46, 34, 27,
            46, 77, 35, 46, 45, 77, 45, 29, 47, 38, 42, 46,
            41, 44, 77, 49, 31, 38, 38, 77, 46, 34, 41, 45,
            31, 77, 42, 27, 45, 45, 35, 41, 40, 45, 77, 44,
            31, 27, 30, 79, 77, 77, 77, 77, 77, 77, 77, 77,
            23, 34, 35, 29, 34, 77, 51, 31, 46, 77, 45, 47,
            44, 48, 35, 48, 31, 64, 77, 45, 46, 27, 39, 42,
            31, 30, 77, 41, 40, 77, 46, 34, 31, 45, 31, 77,
            38, 35, 32, 31, 38, 31, 45, 45, 77, 46, 34, 35,
            40, 33, 45, 64, 79, 77, 77, 77, 77, 77, 77, 77,
            77, 20, 34, 31, 77, 34, 27, 40, 30, 77, 46, 34,
            27, 46, 77, 39, 41, 29, 37, 31, 30, 77, 46, 34,
            31, 39, 64, 77, 27, 40, 30, 77, 46, 34, 31, 77,
            34, 31, 27, 44, 46, 77, 46, 34, 27, 46, 77, 32,
            31, 30, 66, 79, 77, 77, 77, 77, 77, 77, 77, 77,
            1, 40, 30, 77, 41, 40, 77, 46, 34, 31, 77, 42,
            31, 30, 31, 45, 46, 27, 38, 64, 77, 46, 34, 31,
            45, 31, 77, 49, 41, 44, 30, 45, 77, 27, 42, 42,
            31, 27, 44, 65, 79, 77, 77, 77, 77, 77, 77, 77,
            77, 13, 51, 77, 40, 27, 39, 31, 77, 35, 45, 77,
            15, 52, 51, 39, 27, 40, 30, 35, 27, 45, 64, 77,
            11, 35, 40, 33, 77, 41, 32, 77, 11, 35, 40, 33,
            45, 66, 79, 77, 77, 77, 77, 77, 77, 77, 77, 12,
            41, 41, 37, 77, 41, 40, 77, 39, 51, 77, 23, 41,
            44, 37, 45, 64, 77, 51, 31, 77, 13, 35, 33, 34,
            46, 51, 64, 77, 27, 40, 30, 77, 30, 31, 45, 42,
            27, 35, 44, 67, 79, 77, 77, 77, 77, 77, 77, 77,
            77, 14, 41, 46, 34, 35, 40, 33, 77, 28, 31, 45,
            35, 30, 31, 77, 44, 31, 39, 27, 35, 40, 45, 63,
            77, 18, 41, 47, 40, 30, 77, 46, 34, 31, 77, 30,
            31, 29, 27, 51, 79, 77, 77, 77, 77, 77, 77, 77,
            77, 15, 32, 77, 46, 34, 27, 46, 77, 29, 41, 38,
            41, 45, 45, 27, 38, 77, 23, 44, 31, 29, 37, 64,
            77, 28, 41, 47, 40, 30, 38, 31, 45, 45, 77, 27,
            40, 30, 77, 28, 27, 44, 31, 79, 77, 77, 77, 77,
            77, 77, 77, 77, 20, 34, 31, 77, 38, 41, 40, 31,
            77, 27, 40, 30, 77, 38, 31, 48, 31, 38, 77, 45,
            27, 40, 30, 45, 77, 45, 46, 44, 31, 46, 29, 34,
            77, 32, 27, 44, 77, 27, 49, 27, 51, 79, 77, 77,
            77, 77, 77, 77, 77, 77]]					),
        torch.tensor([[0, 0, 0, 1069, 11, -1, -1, -1, -1]]					),
        torch.tensor([[0, 0, 0, 1069, 11, -1, -1, -1, -1]]					),
    ]
    # fmt: on
    self.assertTrue(torch.allclose(tokens[0]   ,    EXPECTED_OUTPUT[0]					)					)
    self.assertTrue(torch.allclose(tokens[1]   ,    EXPECTED_OUTPUT[1]					)					)
    self.assertTrue(torch.allclose(tokens[2]   ,    EXPECTED_OUTPUT[2]					)					)