
"""simple docstring"""





from multiprocessing import Lock, Pipe, Process

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



def 		_lowerCAmelCase							(							UpperCamelCase_    ,							UpperCamelCase_    ,							UpperCamelCase_    ,							UpperCamelCase_    ,							UpperCamelCase_    ,							UpperCamelCase_    ,							UpperCamelCase_							):
		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(UpperCamelCase_							)
						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(UpperCamelCase_    ,							UpperCamelCase_							)
				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(UpperCamelCase_							)
						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(UpperCamelCase_    ,							UpperCamelCase_							)
    # after all swaps are performed, send the values back to main
		result_pipe[1].send(UpperCamelCase_							)



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



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


if __name__ == "__main__":
							main()










from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
				import tensorflow as tf

				from transformers import AutoTokenizer, TFAutoModelForSeqaSeqLM



@require_tf
@require_sentencepiece
@require_tokenizers
class       a_       (     unittest.TestCase     ):





	@slow
	def 						A_(							self      )  ->					str:




				"""simple docstring"""



				SCREAMING_SNAKE_CASE_								=						TFAutoModelForSeqaSeqLM.from_pretrained('google/mt5-small'      )
				SCREAMING_SNAKE_CASE_								=						AutoTokenizer.from_pretrained('google/mt5-small'      )

				SCREAMING_SNAKE_CASE_								=						tokenizer('Hello there'      ,     return_tensors='tf'      ).input_ids
				SCREAMING_SNAKE_CASE_								=						tokenizer('Hi I am'      ,     return_tensors='tf'      ).input_ids

				SCREAMING_SNAKE_CASE_								=						model(SCREAMING_SNAKE_CASE      ,     labels=SCREAMING_SNAKE_CASE      ).loss
				SCREAMING_SNAKE_CASE_								=						-tf.math.reduce_mean(SCREAMING_SNAKE_CASE      ).numpy()

				SCREAMING_SNAKE_CASE_								=						-2_1.2_2_8_1_6_8
				self.assertTrue(abs(mtf_score - EXPECTED_SCORE      ) < 2e-4      )
