
'''simple docstring'''







from ...processing_utils import ProcessorMixin






class 			lowerCAmelCase__       (  lowerCamelCase_					):
					lowerCAmelCase_					       =					'''SpeechT5FeatureExtractor'''
					lowerCAmelCase_					       =					'''SpeechT5Tokenizer'''






					def __init__(       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											super().__init__(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)






					def __call__(       self    ,							*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											lowercase_     :					Tuple													=	kwargs.pop('''audio'''    ,							__SCREAMING_SNAKE_CASE		)
											lowercase_     :					int													=	kwargs.pop('''text'''    ,							__SCREAMING_SNAKE_CASE		)
											lowercase_     :					List[Any]													=	kwargs.pop('''text_target'''    ,							__SCREAMING_SNAKE_CASE		)
											lowercase_     :					str													=	kwargs.pop('''audio_target'''    ,							__SCREAMING_SNAKE_CASE		)
											lowercase_     :					Union[str, Any]													=	kwargs.pop('''sampling_rate'''    ,							__SCREAMING_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:
																	lowercase_     :					Any													=	self.feature_extractor(__SCREAMING_SNAKE_CASE    ,							*__SCREAMING_SNAKE_CASE    ,							sampling_rate=__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)
											elif text is not None:
																	lowercase_     :					Optional[Any]													=	self.tokenizer(__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)
											else:
																	lowercase_     :					List[str]													=	None

											if audio_target is not None:
																	lowercase_     :					Any													=	self.feature_extractor(audio_target=__SCREAMING_SNAKE_CASE    ,							*__SCREAMING_SNAKE_CASE    ,							sampling_rate=__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)
																	lowercase_     :					Dict													=	targets['''input_values''']
											elif text_target is not None:
																	lowercase_     :					Dict													=	self.tokenizer(__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)
																	lowercase_     :					List[Any]													=	targets['''input_ids''']
											else:
																	lowercase_     :					str													=	None

											if inputs is None:
																	return targets

											if targets is not None:
																	lowercase_     :					Dict													=	labels

																	lowercase_     :					Optional[Any]													=	targets.get('''attention_mask'''		)
																	if decoder_attention_mask is not None:
																							lowercase_     :					Any													=	decoder_attention_mask

											return inputs






					def      _snake_case   (       self    ,							*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											lowercase_     :					int													=	kwargs.pop('''input_values'''    ,							__SCREAMING_SNAKE_CASE		)
											lowercase_     :					List[Any]													=	kwargs.pop('''input_ids'''    ,							__SCREAMING_SNAKE_CASE		)
											lowercase_     :					Optional[int]													=	kwargs.pop('''labels'''    ,							__SCREAMING_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:
																	lowercase_     :					List[str]													=	self.feature_extractor.pad(__SCREAMING_SNAKE_CASE    ,							*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)
											elif input_ids is not None:
																	lowercase_     :					Optional[int]													=	self.tokenizer.pad(__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)
											else:
																	lowercase_     :					str													=	None

											if labels is not None:
																	if "input_ids" in labels or (isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		) and "input_ids" in labels[0]):
																							lowercase_     :					Any													=	self.tokenizer.pad(__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)
																							lowercase_     :					str													=	targets['''input_ids''']
																	else:
																							lowercase_     :					Union[str, Any]													=	self.feature_extractor.feature_size
																							lowercase_     :					List[str]													=	self.feature_extractor.num_mel_bins
																							lowercase_     :					List[Any]													=	self.feature_extractor.pad(__SCREAMING_SNAKE_CASE    ,							*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)
																							lowercase_     :					Dict													=	feature_size_hack
																							lowercase_     :					Union[str, Any]													=	targets['''input_values''']
											else:
																	lowercase_     :					Optional[int]													=	None

											if inputs is None:
																	return targets

											if targets is not None:
																	lowercase_     :					List[str]													=	labels

																	lowercase_     :					List[str]													=	targets.get('''attention_mask'''		)
																	if decoder_attention_mask is not None:
																							lowercase_     :					Dict													=	decoder_attention_mask

											return inputs






					def      _snake_case   (       self    ,							*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											return self.tokenizer.batch_decode(*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)






					def      _snake_case   (       self    ,							*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											return self.tokenizer.decode(*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)





'''simple docstring'''







from __future__ import annotations






class 			lowerCAmelCase__       :






					def __init__(       self    ,							__SCREAMING_SNAKE_CASE = 0		):


											"""simple docstring"""





											lowercase_     :					Any													=	key






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											assert isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		) and isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											lowercase_     :					List[str]													=	key or self.__key or 1

											# make sure key is an appropriate size
											key %= 2_55

											return [chr(ord(__SCREAMING_SNAKE_CASE		) ^ key		) for ch in content]






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											assert isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		) and isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											lowercase_     :					Optional[int]													=	key or self.__key or 1

											# make sure key is an appropriate size
											key %= 2_55

											return [chr(ord(__SCREAMING_SNAKE_CASE		) ^ key		) for ch in content]






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE = 0		):


											"""simple docstring"""





											assert isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		) and isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											lowercase_     :					List[Any]													=	key or self.__key or 1

											# make sure key can be any size
											while key > 2_55:
																	key -= 2_55

											# This will be returned
											lowercase_     :					str													=	''''''

											for ch in content:
																	ans += chr(ord(__SCREAMING_SNAKE_CASE		) ^ key		)

											return ans






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE = 0		):


											"""simple docstring"""





											assert isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		) and isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											lowercase_     :					Any													=	key or self.__key or 1

											# make sure key can be any size
											while key > 2_55:
																	key -= 2_55

											# This will be returned
											lowercase_     :					Dict													=	''''''

											for ch in content:
																	ans += chr(ord(__SCREAMING_SNAKE_CASE		) ^ key		)

											return ans






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE = 0		):


											"""simple docstring"""





											assert isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		) and isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											try:
																	with open(__SCREAMING_SNAKE_CASE		) as fin, open('''encrypt.out'''    ,							'''w+'''		) as fout:
																							# actual encrypt-process
																							for line in fin:
																													fout.write(self.encrypt_string(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)		)

											except OSError:
																	return False

											return True






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											assert isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		) and isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											try:
																	with open(__SCREAMING_SNAKE_CASE		) as fin, open('''decrypt.out'''    ,							'''w+'''		) as fout:
																							# actual encrypt-process
																							for line in fin:
																													fout.write(self.decrypt_string(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)		)

											except OSError:
																	return False

											return True


# Tests
# crypt = XORCipher()
# key = 67

# # test encrypt
# print(crypt.encrypt("hallo welt",key))
# # test decrypt
# print(crypt.decrypt(crypt.encrypt("hallo welt",key), key))

# # test encrypt_string
# print(crypt.encrypt_string("hallo welt",key))

# # test decrypt_string
# print(crypt.decrypt_string(crypt.encrypt_string("hallo welt",key),key))

# if (crypt.encrypt_file("test.txt",key)):
#       print("encrypt successful")
# else:
#       print("encrypt unsuccessful")

# if (crypt.decrypt_file("encrypt.out",key)):
#       print("decrypt successful")
# else:
#       print("decrypt unsuccessful")



