



"""simple docstring"""


from multiprocessing import Lock, Pipe, Process

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







def        lowercase		(					_SCREAMING_SNAKE_CASE      :  Tuple    ,   _SCREAMING_SNAKE_CASE      :  Optional[Any]    ,   _SCREAMING_SNAKE_CASE      :  Optional[int]    ,   _SCREAMING_SNAKE_CASE      :  Optional[int]    ,   _SCREAMING_SNAKE_CASE      :  List[Any]    ,   _SCREAMING_SNAKE_CASE      :  Optional[Any]    ,   _SCREAMING_SNAKE_CASE      :  List[str] ):






				'''simple docstring'''



				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(_lowercase )
												process_lock.release()

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

												# take the lower value since you are on the left
												_UpperCAmelCase							=			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							=			lr_cv[0].recv()
												process_lock.release()

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







def        lowercase		(					_SCREAMING_SNAKE_CASE      :  List[Any] ):






				'''simple docstring'''



				_UpperCAmelCase							=			[]
				_UpperCAmelCase							=			[]
				# 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							=			Pipe()
				_UpperCAmelCase							=			Pipe()
				process_array_.append(
				    Process(
				        target=_lowercase    ,   args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0])    ,   ) )
				_UpperCAmelCase							=			temp_rs
				_UpperCAmelCase							=			temp_rr

				for i in range(1    ,   len(_lowercase ) - 1 ):
								_UpperCAmelCase							=			Pipe()
								_UpperCAmelCase							=			Pipe()
								process_array_.append(
								    Process(
								        target=_lowercase    ,   args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i])    ,   ) )
								_UpperCAmelCase							=			temp_rs
								_UpperCAmelCase							=			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							=			result_pipe[p][0].recv()
								process_array_[p].join()
				return arr







def        lowercase		(					):






				'''simple docstring'''



				_UpperCAmelCase							=			list(range(10    ,   0    ,   -1 ) )
				print('''Initial List''' )
				print(*_lowercase )
				_UpperCAmelCase							=			odd_even_transposition(_lowercase )
				print('''Sorted List\n''' )
				print(*_lowercase )


if __name__ == "__main__":
					main()








"""simple docstring"""
from typing import TYPE_CHECKING

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


__a      =				{"configuration_reformer": ["REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "ReformerConfig"]}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      =				["ReformerTokenizer"]

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      =				["ReformerTokenizerFast"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      =				[
						    "REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "ReformerAttention",
						    "ReformerForMaskedLM",
						    "ReformerForQuestionAnswering",
						    "ReformerForSequenceClassification",
						    "ReformerLayer",
						    "ReformerModel",
						    "ReformerModelWithLMHead",
						    "ReformerPreTrainedModel",
						]


if TYPE_CHECKING:
						from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_reformer import ReformerTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_reformer_fast import ReformerTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_reformer import (
												    REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ReformerAttention,
												    ReformerForMaskedLM,
												    ReformerForQuestionAnswering,
												    ReformerForSequenceClassification,
												    ReformerLayer,
												    ReformerModel,
												    ReformerModelWithLMHead,
												    ReformerPreTrainedModel,
												)

else:
						import sys

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