


import warnings

from ...utils import is_sklearn_available, requires_backends


if is_sklearn_available():
    from scipy.stats import pearsonr, spearmanr
    from sklearn.metrics import fa_score, matthews_corrcoef


__snake_case   							=						(
    '''This metric will be removed from the library soon, metrics should be handled with the 🤗 Evaluate '''
    '''library. You can have a look at this example script for pointers: '''
    '''https://github.com/huggingface/transformers/blob/main/examples/pytorch/text-classification/run_glue.py'''
)






def 		_A		(		_lowercase					,  _lowercase )					-> str:


     """simple docstring"""


     warnings.warn(_lowercase					,  _lowercase )
     requires_backends(_lowercase					,  'sklearn' )
     return (preds == labels).mean()






def 		_A		(		_lowercase					,  _lowercase )					-> Optional[int]:


     """simple docstring"""


     warnings.warn(_lowercase					,  _lowercase )
     requires_backends(_lowercase					,  'sklearn' )
     __UpperCamelCase =			simple_accuracy(_lowercase					,  _lowercase )
     __UpperCamelCase =			fa_score(y_true=_lowercase					,  y_pred=_lowercase )
     return {
         "acc": acc,
         "f1": fa,
         "acc_and_f1": (acc + fa) / 2,
     }






def 		_A		(		_lowercase					,  _lowercase )					-> List[str]:


     """simple docstring"""


     warnings.warn(_lowercase					,  _lowercase )
     requires_backends(_lowercase					,  'sklearn' )
     __UpperCamelCase =			pearsonr(_lowercase					,  _lowercase )[0]
     __UpperCamelCase =			spearmanr(_lowercase					,  _lowercase )[0]
     return {
         "pearson": pearson_corr,
         "spearmanr": spearman_corr,
         "corr": (pearson_corr + spearman_corr) / 2,
     }






def 		_A		(		_lowercase					,  _lowercase					,  _lowercase )					-> Dict:


     """simple docstring"""


     warnings.warn(_lowercase					,  _lowercase )
     requires_backends(_lowercase					,  'sklearn' )
     assert len(_lowercase ) == len(_lowercase ), f'''Predictions and labels have mismatched lengths {len(_lowercase )} and {len(_lowercase )}'''
     if task_name == "cola":
          return {"mcc": matthews_corrcoef(_lowercase					,  _lowercase )}
     elif task_name == "sst-2":
          return {"acc": simple_accuracy(_lowercase					,  _lowercase )}
     elif task_name == "mrpc":
          return acc_and_fa(_lowercase					,  _lowercase )
     elif task_name == "sts-b":
          return pearson_and_spearman(_lowercase					,  _lowercase )
     elif task_name == "qqp":
          return acc_and_fa(_lowercase					,  _lowercase )
     elif task_name == "mnli":
          return {"mnli/acc": simple_accuracy(_lowercase					,  _lowercase )}
     elif task_name == "mnli-mm":
          return {"mnli-mm/acc": simple_accuracy(_lowercase					,  _lowercase )}
     elif task_name == "qnli":
          return {"acc": simple_accuracy(_lowercase					,  _lowercase )}
     elif task_name == "rte":
          return {"acc": simple_accuracy(_lowercase					,  _lowercase )}
     elif task_name == "wnli":
          return {"acc": simple_accuracy(_lowercase					,  _lowercase )}
     elif task_name == "hans":
          return {"acc": simple_accuracy(_lowercase					,  _lowercase )}
     else:
          raise KeyError(_lowercase )






def 		_A		(		_lowercase					,  _lowercase					,  _lowercase )					-> Union[str, Any]:


     """simple docstring"""


     warnings.warn(_lowercase					,  _lowercase )
     requires_backends(_lowercase					,  'sklearn' )
     if len(_lowercase ) != len(_lowercase ):
          raise ValueError(f'''Predictions and labels have mismatched lengths {len(_lowercase )} and {len(_lowercase )}''' )
     if task_name == "xnli":
          return {"acc": simple_accuracy(_lowercase					,  _lowercase )}
     else:
          raise KeyError(_lowercase )






from multiprocessing import Lock, Pipe, Process

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


def     lowercase	(    a     , a     , a     , a     , a     , a     , a ):



		'''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()
						SCREAMING_SNAKE_CASE_				:str				     =						rr_cv[0].recv()
						process_lock.release()

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

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


def     lowercase	(    a ):



		'''simple docstring'''




		SCREAMING_SNAKE_CASE_				:Tuple				     =						[]
		SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						[]
		# 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_				:str				     =						Pipe()
		SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						Pipe()
		process_array_.append(
		    Process(
		        target=a     , args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0])     , ) )
		SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						temp_rs
		SCREAMING_SNAKE_CASE_				:Any				     =						temp_rr

		for i in range(1     , len(a ) - 1 ):
				SCREAMING_SNAKE_CASE_				:int				     =						Pipe()
				SCREAMING_SNAKE_CASE_				:Dict				     =						Pipe()
				process_array_.append(
				    Process(
				        target=a     , args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i])     , ) )
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						temp_rs
				SCREAMING_SNAKE_CASE_				:int				     =						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 ) ):
				SCREAMING_SNAKE_CASE_				:Tuple				     =						result_pipe[p][0].recv()
				process_array_[p].join()
		return arr


def     lowercase	(    ):



		'''simple docstring'''




		SCREAMING_SNAKE_CASE_				:List[str]				     =						list(range(10     , 0     , -1 ) )
		print("Initial List" )
		print(*a )
		SCREAMING_SNAKE_CASE_				:int				     =						odd_even_transposition(a )
		print("Sorted List\n" )
		print(*a )


if __name__ == "__main__":
		main()






