

'''simple docstring'''




from multiprocessing import Lock, Pipe, Process

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




def 						UpperCamelCase	(			a		,						a		,						a		,						a		,						a		,						a		,						a			)				->     int:






     '''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(a			)
               process_lock.release()

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

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

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

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




def 						UpperCamelCase	(			a			)				->     int:






     '''simple docstring'''
     __magic_name__						       =[]
     __magic_name__						       =[]
     # 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
     __magic_name__						       =Pipe()
     __magic_name__						       =Pipe()
     process_array_.append(
         Process(
             target=a		,						args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0])		,						)			)
     __magic_name__						       =temp_rs
     __magic_name__						       =temp_rr

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

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




def 						UpperCamelCase	(			)				->     List[Any]:






     '''simple docstring'''
     __magic_name__						       =list(range(10		,						0		,						-1			)			)
     print('''Initial List'''			)
     print(*a			)
     __magic_name__						       =odd_even_transposition(a			)
     print('''Sorted List\n'''			)
     print(*a			)


if __name__ == "__main__":
      main()









'''simple docstring'''




from pathlib import Path

import fire
from tqdm import tqdm




def 						UpperCamelCase	(			a="ro"		,						a="en"		,						a="wmt16"		,						a=None			)				->     None:






     '''simple docstring'''
     try:
          import datasets
     except (ModuleNotFoundError, ImportError):
          raise ImportError('''run pip install datasets'''			)
     __magic_name__						       =    F'''{src_lang}-{tgt_lang}'''
     print(F'''Converting {dataset}-{pair}'''			)
     __magic_name__						       =    datasets.load_dataset(a		,						a			)
     if save_dir is None:
          __magic_name__						       =    F'''{dataset}-{pair}'''
     __magic_name__						       =    Path(a			)
     save_dir.mkdir(exist_ok=a			)

     for split in ds.keys():
          print(F'''Splitting {split} with {ds[split].num_rows} records'''			)

          # to save to val.source, val.target like summary datasets
          __magic_name__						       =    '''val''' if split == '''validation''' else split
          __magic_name__						       =    save_dir.joinpath(F'''{fn}.source'''			)
          __magic_name__						       =    save_dir.joinpath(F'''{fn}.target'''			)
          __magic_name__						       =    src_path.open('''w+'''			)
          __magic_name__						       =    tgt_path.open('''w+'''			)

          # reader is the bottleneck so writing one record at a time doesn't slow things down
          for x in tqdm(ds[split]			):
               __magic_name__						       =    x['''translation''']
               src_fp.write(ex[src_lang] + '''\n'''			)
               tgt_fp.write(ex[tgt_lang] + '''\n'''			)

     print(F'''Saved {dataset} dataset to {save_dir}'''			)


if __name__ == "__main__":
      fire.Fire(download_wmt_dataset)






