

from ...processing_utils import ProcessorMixin






class 	__magic_name__    (			lowerCAmelCase_      ):
			SCREAMING_SNAKE_CASE							   =						'SpeechT5FeatureExtractor'
			SCREAMING_SNAKE_CASE							   =						'SpeechT5Tokenizer'





			def __init__(		self					,  __snake_case					,  __snake_case					)   -> int:




						'''simple docstring'''
						super().__init__(__snake_case					,  __snake_case					)





			def __call__(		self					,  *__snake_case					,  **__snake_case					)   -> List[Any]:




						'''simple docstring'''
						__a        =kwargs.pop('audio'					,  __snake_case					)
						__a        =kwargs.pop('text'					,  __snake_case					)
						__a        =kwargs.pop('text_target'					,  __snake_case					)
						__a        =kwargs.pop('audio_target'					,  __snake_case					)
						__a        =kwargs.pop('sampling_rate'					,  __snake_case					)

						if audio is not None and text is not None:
									raise ValueError(
									    'Cannot process both `audio` and `text` inputs. Did you mean `audio_target` or `text_target`?'					)
						if audio_target is not None and text_target is not None:
									raise ValueError(
									    'Cannot process both `audio_target` and `text_target` inputs. Did you mean `audio` or `text`?'					)
						if audio is None and audio_target is None and text is None and text_target is None:
									raise ValueError(
									    'You need to specify either an `audio`, `audio_target`, `text`, or `text_target` input to process.'					)

						if audio is not None:
									__a        =self.feature_extractor(__snake_case					,  *__snake_case					,  sampling_rate=__snake_case					,  **__snake_case					)
						elif text is not None:
									__a        =self.tokenizer(__snake_case					,  **__snake_case					)
						else:
									__a        =None

						if audio_target is not None:
									__a        =self.feature_extractor(audio_target=__snake_case					,  *__snake_case					,  sampling_rate=__snake_case					,  **__snake_case					)
									__a        =targets['input_values']
						elif text_target is not None:
									__a        =self.tokenizer(__snake_case					,  **__snake_case					)
									__a        =targets['input_ids']
						else:
									__a        =None

						if inputs is None:
									return targets

						if targets is not None:
									__a        =labels

									__a        =targets.get('attention_mask'					)
									if decoder_attention_mask is not None:
												__a        =decoder_attention_mask

						return inputs





			def 		__magic_name__    (		self					,  *__snake_case					,  **__snake_case					)   -> Dict:




						'''simple docstring'''
						__a        =kwargs.pop('input_values'					,  __snake_case					)
						__a        =kwargs.pop('input_ids'					,  __snake_case					)
						__a        =kwargs.pop('labels'					,  __snake_case					)

						if input_values is not None and input_ids is not None:
									raise ValueError('Cannot process both `input_values` and `input_ids` inputs.'					)
						if input_values is None and input_ids is None and labels is None:
									raise ValueError(
									    'You need to specify either an `input_values`, `input_ids`, or `labels` input to be padded.'					)

						if input_values is not None:
									__a        =self.feature_extractor.pad(__snake_case					,  *__snake_case					,  **__snake_case					)
						elif input_ids is not None:
									__a        =self.tokenizer.pad(__snake_case					,  **__snake_case					)
						else:
									__a        =None

						if labels is not None:
									if "input_ids" in labels or (isinstance(__snake_case					,  __snake_case					) and "input_ids" in labels[0]):
												__a        =self.tokenizer.pad(__snake_case					,  **__snake_case					)
												__a        =targets['input_ids']
									else:
												__a        =self.feature_extractor.feature_size
												__a        =self.feature_extractor.num_mel_bins
												__a        =self.feature_extractor.pad(__snake_case					,  *__snake_case					,  **__snake_case					)
												__a        =feature_size_hack
												__a        =targets['input_values']
						else:
									__a        =None

						if inputs is None:
									return targets

						if targets is not None:
									__a        =labels

									__a        =targets.get('attention_mask'					)
									if decoder_attention_mask is not None:
												__a        =decoder_attention_mask

						return inputs





			def 		__magic_name__    (		self					,  *__snake_case					,  **__snake_case					)   -> Optional[int]:




						'''simple docstring'''
						return self.tokenizer.batch_decode(*__snake_case					,  **__snake_case					)





			def 		__magic_name__    (		self					,  *__snake_case					,  **__snake_case					)   -> List[str]:




						'''simple docstring'''
						return self.tokenizer.decode(*__snake_case					,  **__snake_case					)









from multiprocessing import Lock, Pipe, Process

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






def        UpperCamelCase_(							_snake_case   :  List[str]       ,     _snake_case   :  Optional[int]       ,     _snake_case   :  Dict       ,     _snake_case   :  Any       ,     _snake_case   :  List[str]       ,     _snake_case   :  Tuple       ,     _snake_case   :  List[str]	):




			"""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(_snake_case	)
									process_lock.release()

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

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

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

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






def        UpperCamelCase_(							_snake_case   :  List[str]	):




			"""simple docstring"""






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

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

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






def        UpperCamelCase_(							):




			"""simple docstring"""






			__a        =list(range(10       ,     0       ,     -1	)	)
			print('Initial List'	)
			print(*_snake_case	)
			__a        =odd_even_transposition(_snake_case	)
			print('Sorted List\n'	)
			print(*_snake_case	)


if __name__ == "__main__":
						main()






