




"""simple docstring"""

import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer





class 							lowercase_			(	__UpperCAmelCase				):



 '''simple docstring'''
 UpperCAmelCase       :	Any     =      '''Wav2Vec2FeatureExtractor'''
 UpperCAmelCase       :	List[str]     =      '''AutoTokenizer'''

 def __init__(					self			:			int       ,				_UpperCAmelCase			:			Union[str, Any]       ,				_UpperCAmelCase			:			int						):
       super().__init__(lowerCamelCase__       ,				lowerCamelCase__						)
       _A     =  self.feature_extractor
       _A     =  False

 @classmethod
 def      lowerCAmelCase_				(					cls			:			List[str]       ,				_UpperCAmelCase			:			Any       ,				**_UpperCAmelCase			:			int						):
       try:
             return super().from_pretrained(lowerCamelCase__       ,				**lowerCamelCase__						)
       except OSError:
             warnings.warn(
                 F'''Loading a tokenizer inside {cls.__name__} from a config that does not'''
                 ' include a `tokenizer_class` attribute is deprecated and will be '
                 'removed in v5. Please add `\'tokenizer_class\': \'Wav2Vec2CTCTokenizer\'`'
                 ' attribute to either your `config.json` or `tokenizer_config.json` '
                 'file to suppress this warning: '       ,				lowerCamelCase__       ,				)

             _A     =  WavaVecaFeatureExtractor.from_pretrained(lowerCamelCase__       ,				**lowerCamelCase__						)
             _A     =  WavaVecaCTCTokenizer.from_pretrained(lowerCamelCase__       ,				**lowerCamelCase__						)

             return cls(feature_extractor=lowerCamelCase__       ,				tokenizer=lowerCamelCase__						)

 def __call__(					self			:			Union[str, Any]       ,				*_UpperCAmelCase			:			List[Any]       ,				**_UpperCAmelCase			:			str						):
       # For backward compatibility
       if self._in_target_context_manager:
             return self.current_processor(*lowerCamelCase__       ,				**lowerCamelCase__						)

       if "raw_speech" in kwargs:
             warnings.warn('Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead.'						)
             _A     =  kwargs.pop('raw_speech'						)
       else:
             _A     =  kwargs.pop('audio'       ,				lowerCamelCase__						)
       _A     =  kwargs.pop('sampling_rate'       ,				lowerCamelCase__						)
       _A     =  kwargs.pop('text'       ,				lowerCamelCase__						)
       if len(lowerCamelCase__						) > 0:
             _A     =  args[0]
             _A     =  args[1:]

       if audio is None and text is None:
             raise ValueError('You need to specify either an `audio` or `text` input to process.'						)

       if audio is not None:
             _A     =  self.feature_extractor(lowerCamelCase__       ,				*lowerCamelCase__       ,				sampling_rate=lowerCamelCase__       ,				**lowerCamelCase__						)
       if text is not None:
             _A     =  self.tokenizer(lowerCamelCase__       ,				**lowerCamelCase__						)

       if text is None:
             return inputs
       elif audio is None:
             return encodings
       else:
             _A     =  encodings["""input_ids"""]
             return inputs

 def      lowerCAmelCase_				(					self			:			int       ,				*_UpperCAmelCase			:			Dict       ,				**_UpperCAmelCase			:			Optional[int]						):
       # For backward compatibility
       if self._in_target_context_manager:
             return self.current_processor.pad(*lowerCamelCase__       ,				**lowerCamelCase__						)

       _A     =  kwargs.pop('input_features'       ,				lowerCamelCase__						)
       _A     =  kwargs.pop('labels'       ,				lowerCamelCase__						)
       if len(lowerCamelCase__						) > 0:
             _A     =  args[0]
             _A     =  args[1:]

       if input_features is not None:
             _A     =  self.feature_extractor.pad(lowerCamelCase__       ,				*lowerCamelCase__       ,				**lowerCamelCase__						)
       if labels is not None:
             _A     =  self.tokenizer.pad(lowerCamelCase__       ,				**lowerCamelCase__						)

       if labels is None:
             return input_features
       elif input_features is None:
             return labels
       else:
             _A     =  labels["""input_ids"""]
             return input_features

 def      lowerCAmelCase_				(					self			:			Optional[int]       ,				*_UpperCAmelCase			:			List[Any]       ,				**_UpperCAmelCase			:			Tuple						):
       return self.tokenizer.batch_decode(*lowerCamelCase__       ,				**lowerCamelCase__						)

 def      lowerCAmelCase_				(					self			:			Any       ,				*_UpperCAmelCase			:			List[str]       ,				**_UpperCAmelCase			:			Tuple						):
       return self.tokenizer.decode(*lowerCamelCase__       ,				**lowerCamelCase__						)



 @contextmanager
 def      lowerCAmelCase_				(					self			:			Any						):
       warnings.warn(
           '`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your '
           'labels by using the argument `text` of the regular `__call__` method (either in the same call as '
           'your audio inputs, or in a separate call.'						)
       _A     =  True
       _A     =  self.tokenizer
       yield
       _A     =  self.feature_extractor
       _A     =  False





"""simple docstring"""


from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter


def    _lowerCamelCase   (     lowerCamelCase__	:							int       ,		lowerCamelCase__	:							int       ,		lowerCamelCase__	:							float = 1 / sqrt(2  )  ):
 lowercase__       :       str				=						tau * frequency / samplerate
 lowercase__       :       Union[str, Any]				=						sin(lowerCamelCase__  )
 lowercase__       :       int				=						cos(lowerCamelCase__  )
 lowercase__       :       Union[str, Any]				=						_sin / (2 * q_factor)

 lowercase__       :       str				=						(1 - _cos) / 2
 lowercase__       :       Optional[Any]				=						1 - _cos

 lowercase__       :       List[Any]				=						1 + alpha
 lowercase__       :       Dict				=						-2 * _cos
 lowercase__       :       List[str]				=						1 - alpha

 lowercase__       :       int				=						IIRFilter(2  )
 filt.set_coefficients([aa, aa, aa]       ,		[ba, ba, ba]  )
 return filt


def    _lowerCamelCase   (     lowerCamelCase__	:							int       ,		lowerCamelCase__	:							int       ,		lowerCamelCase__	:							float = 1 / sqrt(2  )  ):
 lowercase__       :       Optional[int]				=						tau * frequency / samplerate
 lowercase__       :       Any				=						sin(lowerCamelCase__  )
 lowercase__       :       Any				=						cos(lowerCamelCase__  )
 lowercase__       :       Tuple				=						_sin / (2 * q_factor)

 lowercase__       :       Tuple				=						(1 + _cos) / 2
 lowercase__       :       str				=						-1 - _cos

 lowercase__       :       Dict				=						1 + alpha
 lowercase__       :       Dict				=						-2 * _cos
 lowercase__       :       int				=						1 - alpha

 lowercase__       :       str				=						IIRFilter(2  )
 filt.set_coefficients([aa, aa, aa]       ,		[ba, ba, ba]  )
 return filt


def    _lowerCamelCase   (     lowerCamelCase__	:							int       ,		lowerCamelCase__	:							int       ,		lowerCamelCase__	:							float = 1 / sqrt(2  )  ):
 lowercase__       :       Optional[int]				=						tau * frequency / samplerate
 lowercase__       :       str				=						sin(lowerCamelCase__  )
 lowercase__       :       int				=						cos(lowerCamelCase__  )
 lowercase__       :       Dict				=						_sin / (2 * q_factor)

 lowercase__       :       Dict				=						_sin / 2
 lowercase__       :       Union[str, Any]				=						0
 lowercase__       :       int				=						-ba

 lowercase__       :       List[Any]				=						1 + alpha
 lowercase__       :       Tuple				=						-2 * _cos
 lowercase__       :       List[str]				=						1 - alpha

 lowercase__       :       Dict				=						IIRFilter(2  )
 filt.set_coefficients([aa, aa, aa]       ,		[ba, ba, ba]  )
 return filt


def    _lowerCamelCase   (     lowerCamelCase__	:							int       ,		lowerCamelCase__	:							int       ,		lowerCamelCase__	:							float = 1 / sqrt(2  )  ):
 lowercase__       :       str				=						tau * frequency / samplerate
 lowercase__       :       Dict				=						sin(lowerCamelCase__  )
 lowercase__       :       Union[str, Any]				=						cos(lowerCamelCase__  )
 lowercase__       :       Tuple				=						_sin / (2 * q_factor)

 lowercase__       :       List[Any]				=						1 - alpha
 lowercase__       :       Any				=						-2 * _cos
 lowercase__       :       Optional[Any]				=						1 + alpha

 lowercase__       :       List[Any]				=						IIRFilter(2  )
 filt.set_coefficients([ba, ba, ba]       ,		[ba, ba, ba]  )
 return filt


def    _lowerCamelCase   (     lowerCamelCase__	:							int       ,		lowerCamelCase__	:							int       ,		lowerCamelCase__	:							float       ,		lowerCamelCase__	:							float = 1 / sqrt(2  )       ,		):
 lowercase__       :       Tuple				=						tau * frequency / samplerate
 lowercase__       :       str				=						sin(lowerCamelCase__  )
 lowercase__       :       List[str]				=						cos(lowerCamelCase__  )
 lowercase__       :       Optional[int]				=						_sin / (2 * q_factor)
 lowercase__       :       Optional[Any]				=						10 ** (gain_db / 40)

 lowercase__       :       Optional[Any]				=						1 + alpha * big_a
 lowercase__       :       Dict				=						-2 * _cos
 lowercase__       :       Tuple				=						1 - alpha * big_a
 lowercase__       :       List[str]				=						1 + alpha / big_a
 lowercase__       :       List[Any]				=						-2 * _cos
 lowercase__       :       Optional[int]				=						1 - alpha / big_a

 lowercase__       :       Union[str, Any]				=						IIRFilter(2  )
 filt.set_coefficients([aa, aa, aa]       ,		[ba, ba, ba]  )
 return filt


def    _lowerCamelCase   (     lowerCamelCase__	:							int       ,		lowerCamelCase__	:							int       ,		lowerCamelCase__	:							float       ,		lowerCamelCase__	:							float = 1 / sqrt(2  )       ,		):
 lowercase__       :       Optional[int]				=						tau * frequency / samplerate
 lowercase__       :       Dict				=						sin(lowerCamelCase__  )
 lowercase__       :       Union[str, Any]				=						cos(lowerCamelCase__  )
 lowercase__       :       int				=						_sin / (2 * q_factor)
 lowercase__       :       Union[str, Any]				=						10 ** (gain_db / 40)
 lowercase__       :       Dict				=						(big_a + 1) - (big_a - 1) * _cos
 lowercase__       :       Union[str, Any]				=						(big_a + 1) + (big_a - 1) * _cos
 lowercase__       :       List[Any]				=						(big_a - 1) - (big_a + 1) * _cos
 lowercase__       :       Dict				=						(big_a - 1) + (big_a + 1) * _cos
 lowercase__       :       Optional[int]				=						2 * sqrt(lowerCamelCase__  ) * alpha

 lowercase__       :       str				=						big_a * (pmc + aaa)
 lowercase__       :       Optional[Any]				=						2 * big_a * mpc
 lowercase__       :       str				=						big_a * (pmc - aaa)
 lowercase__       :       Dict				=						ppmc + aaa
 lowercase__       :       List[Any]				=						-2 * pmpc
 lowercase__       :       List[Any]				=						ppmc - aaa

 lowercase__       :       Optional[int]				=						IIRFilter(2  )
 filt.set_coefficients([aa, aa, aa]       ,		[ba, ba, ba]  )
 return filt






def    _lowerCamelCase   (     lowerCamelCase__	:							int       ,		lowerCamelCase__	:							int       ,		lowerCamelCase__	:							float       ,		lowerCamelCase__	:							float = 1 / sqrt(2  )       ,		):
 lowercase__       :       int				=						tau * frequency / samplerate
 lowercase__       :       List[Any]				=						sin(lowerCamelCase__  )
 lowercase__       :       List[Any]				=						cos(lowerCamelCase__  )
 lowercase__       :       List[str]				=						_sin / (2 * q_factor)
 lowercase__       :       int				=						10 ** (gain_db / 40)
 lowercase__       :       str				=						(big_a + 1) - (big_a - 1) * _cos
 lowercase__       :       Optional[Any]				=						(big_a + 1) + (big_a - 1) * _cos
 lowercase__       :       Optional[int]				=						(big_a - 1) - (big_a + 1) * _cos
 lowercase__       :       int				=						(big_a - 1) + (big_a + 1) * _cos
 lowercase__       :       Optional[Any]				=						2 * sqrt(lowerCamelCase__  ) * alpha

 lowercase__       :       str				=						big_a * (ppmc + aaa)
 lowercase__       :       Union[str, Any]				=						-2 * big_a * pmpc
 lowercase__       :       List[Any]				=						big_a * (ppmc - aaa)
 lowercase__       :       str				=						pmc + aaa
 lowercase__       :       int				=						2 * mpc
 lowercase__       :       Any				=						pmc - aaa

 lowercase__       :       int				=						IIRFilter(2  )
 filt.set_coefficients([aa, aa, aa]       ,		[ba, ba, ba]  )
 return filt