





from multiprocessing import Lock, Pipe, Process

# lock used to ensure that two processes do not access a pipe at the same time
__lowercase	: List[Any]       =Lock()




def      a__			(       lowercase__	,     lowercase__	,     lowercase__	,     lowercase__	,     lowercase__	,     lowercase__	,     lowercase__	):






   '''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	,     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_           =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      a__			(       lowercase__	):






   '''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      a__			(       ):






   '''simple docstring'''






   UpperCAmelCase_           =list(range(1_0	,     0	,     -1	)	)
   print("Initial List"	)
   print(*lowercase__	)
   UpperCAmelCase_           =odd_even_transposition(lowercase__	)
   print("Sorted List\n"	)
   print(*lowercase__	)


if __name__ == "__main__":
     main()








'''simple docstring'''





import numpy as np

from transformers import Pipeline






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: Any ):






			"""simple docstring"""




			__A=	np.max(_SCREAMING_SNAKE_CASE,axis=-1,keepdims=_SCREAMING_SNAKE_CASE )
			__A=	np.exp(outputs - maxes )
			return shifted_exp / shifted_exp.sum(axis=-1,keepdims=_SCREAMING_SNAKE_CASE )






class 						a__					(					a_   ):





			'''simple docstring'''

			def 					lowerCAmelCase     (  self							:			Optional[Any]			,    **lowerCAmelCase_							:			List[str]	)      ->		List[str]:
						__A=	{}
						if "second_text" in kwargs:
									__A=	kwargs['second_text']
						return preprocess_kwargs, {}, {}
			def 					lowerCAmelCase     (  self							:			str			,    lowerCAmelCase_							:			Union[str, Any]			,    lowerCAmelCase_							:			Optional[int]=None	)      ->		int:
						return self.tokenizer(lowerCAmelCase_			,    text_pair=lowerCAmelCase_			,    return_tensors=self.framework	)
			def 					lowerCAmelCase     (  self							:			Dict			,    lowerCAmelCase_							:			List[str]	)      ->		Tuple:
						return self.model(**lowerCAmelCase_	)

			def 					lowerCAmelCase     (  self							:			str			,    lowerCAmelCase_							:			Dict	)      ->		Optional[int]:
						__A=	model_outputs.logits[0].numpy()
						__A=	softmax(lowerCAmelCase_	)

						__A=	np.argmax(lowerCAmelCase_	)
						__A=	self.model.config.idalabel[best_class]
						__A=	probabilities[best_class].item()
						__A=	logits.tolist()
						return {"label": label, "score": score, "logits": logits}



