'''simple docstring'''


from multiprocessing import Lock, Pipe, Process

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

def   A_      (       SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)			->Tuple:
  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 ,	10						):
    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(SCREAMING_SNAKE_CASE_						)
      process_lock.release()

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

      # take the lower value since you are on the left
      lowercase_     =       min(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)
    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(SCREAMING_SNAKE_CASE_						)
      process_lock.release()

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

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

def   A_      (       SCREAMING_SNAKE_CASE_						)			->List[str]:
  lowercase_     =       []
  lowercase_     =       []
  # 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
  lowercase_     =       Pipe()
  lowercase_     =       Pipe()
  process_array_.append(
      Process(
          target=SCREAMING_SNAKE_CASE_ ,	args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0]) ,	)						)
  lowercase_     =       temp_rs
  lowercase_     =       temp_rr

  for i in range(1 ,	len(SCREAMING_SNAKE_CASE_						) - 1						):
    lowercase_     =       Pipe()
    lowercase_     =       Pipe()
    process_array_.append(
        Process(
            target=SCREAMING_SNAKE_CASE_ ,	args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i]) ,	)						)
    lowercase_     =       temp_rs
    lowercase_     =       temp_rr

  process_array_.append(
      Process(
          target=SCREAMING_SNAKE_CASE_ ,	args=(
              len(SCREAMING_SNAKE_CASE_						) - 1,
              arr[len(SCREAMING_SNAKE_CASE_						) - 1],
              temp_ls,
              None,
              temp_lr,
              None,
              result_pipe[len(SCREAMING_SNAKE_CASE_						) - 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(SCREAMING_SNAKE_CASE_						)						):
    lowercase_     =       result_pipe[p][0].recv()
    process_array_[p].join()
  return arr

def   A_      (       )			->str:
  lowercase_     =       list(range(10 ,	0 ,	-1						)						)
  print("""Initial List"""						)
  print(*SCREAMING_SNAKE_CASE_						)
  lowercase_     =       odd_even_transposition(SCREAMING_SNAKE_CASE_						)
  print("""Sorted List\n"""						)
  print(*SCREAMING_SNAKE_CASE_						)


if __name__ == "__main__":
       main()


'''simple docstring'''


from typing import TYPE_CHECKING

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


__snake_case						  =		{"""configuration_focalnet""": ["""FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FocalNetConfig"""]}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __snake_case						  =		[
           """FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """FocalNetForImageClassification""",
           """FocalNetForMaskedImageModeling""",
           """FocalNetBackbone""",
           """FocalNetModel""",
           """FocalNetPreTrainedModel""",
       ]

if TYPE_CHECKING:
       from .configuration_focalnet import FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FocalNetConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_focalnet import (
                  FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                  FocalNetBackbone,
                  FocalNetForImageClassification,
                  FocalNetForMaskedImageModeling,
                  FocalNetModel,
                  FocalNetPreTrainedModel,
              )

else:
       import sys

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

