


"""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__    :							Optional[Any]            =					Lock()




def        UpperCAmelCase__	(lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_       ):




					'''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(lowerCAmelCase_       )
															process_lock.release()

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

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

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

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




def        UpperCAmelCase__	(lowerCAmelCase_       ):




					'''simple docstring'''


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

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

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




def        UpperCAmelCase__	():




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE						       =    list(range(10  ,						0  ,						-1       )       )
					print("Initial List"       )
					print(*lowerCAmelCase_       )
					__SCREAMING_SNAKE_CASE						       =    odd_even_transposition(lowerCAmelCase_       )
					print("Sorted List\n"       )
					print(*lowerCAmelCase_       )


if __name__ == "__main__":
		main()




"""simple docstring"""







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

a__    :							Dict            =					TaTokenizer

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

a__    :							Any            =					TaTokenizerFast

a__    :							Tuple            =					{'''configuration_mt5''': ['''MT5Config''', '''MT5OnnxConfig''']}

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

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

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a__    :							Union[str, Any]            =					['''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

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