






import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin


class 						_a       (  UpperCAmelCase__    ):






  """simple docstring"""





  A_						=   """Speech2TextFeatureExtractor"""
  A_						=   """Speech2TextTokenizer"""




  def __init__(     self		,		_UpperCAmelCase		,		_UpperCAmelCase )			-> Optional[Any]:
     super().__init__(_UpperCAmelCase		,		_UpperCAmelCase )
     UpperCamelCase_									=     self.feature_extractor
     UpperCamelCase_									=     False




  def __call__(     self		,		*_UpperCAmelCase		,		**_UpperCAmelCase )			-> Tuple:
     # For backward compatibility
     if self._in_target_context_manager:
        return self.current_processor(*_UpperCAmelCase		,		**_UpperCAmelCase )

     if "raw_speech" in kwargs:
        warnings.warn('Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead.' )
        UpperCamelCase_									=     kwargs.pop('raw_speech' )
     else:
        UpperCamelCase_									=     kwargs.pop('audio'		,		_UpperCAmelCase )
     UpperCamelCase_									=     kwargs.pop('sampling_rate'		,		_UpperCAmelCase )
     UpperCamelCase_									=     kwargs.pop('text'		,		_UpperCAmelCase )
     if len(_UpperCAmelCase ) > 0:
        UpperCamelCase_									=     args[0]
        UpperCamelCase_									=     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:
        UpperCamelCase_									=     self.feature_extractor(_UpperCAmelCase		,		*_UpperCAmelCase		,		sampling_rate=_UpperCAmelCase		,		**_UpperCAmelCase )
     if text is not None:
        UpperCamelCase_									=     self.tokenizer(_UpperCAmelCase		,		**_UpperCAmelCase )

     if text is None:
        return inputs
     elif audio is None:
        return encodings
     else:
        UpperCamelCase_									=     encodings['input_ids']
        return inputs




  def    _UpperCAmelCase     (     self		,		*_UpperCAmelCase		,		**_UpperCAmelCase )			-> Union[str, Any]:
     return self.tokenizer.batch_decode(*_UpperCAmelCase		,		**_UpperCAmelCase )




  def    _UpperCAmelCase     (     self		,		*_UpperCAmelCase		,		**_UpperCAmelCase )			-> List[Any]:
     return self.tokenizer.decode(*_UpperCAmelCase		,		**_UpperCAmelCase )




  @contextmanager
  def    _UpperCAmelCase     (     self )			-> int:
     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.' )
     UpperCamelCase_									=     True
     UpperCamelCase_									=     self.tokenizer
     yield
     UpperCamelCase_									=     self.feature_extractor
     UpperCamelCase_									=     False













from sympy import diff, lambdify, symbols
from sympy.functions import *  # noqa: F403






def     _snake_case    (__lowercase    ,      __lowercase    ,      __lowercase = "x"    ,      __lowercase = 10**-10    ,      __lowercase = 1    ,      ):
   UpperCamelCase_									=     symbols(__lowercase)
   UpperCamelCase_									=     lambdify(__lowercase    ,      __lowercase)
   UpperCamelCase_									=     lambdify(__lowercase    ,      diff(__lowercase    ,      __lowercase))

   UpperCamelCase_									=     starting_point

   while True:
      if diff_function(__lowercase) != 0:
         UpperCamelCase_									=     prev_guess - multiplicity * func(__lowercase) / diff_function(
             __lowercase)
      else:
         raise ZeroDivisionError('Could not find root') from None

      # Precision is checked by comparing the difference of consecutive guesses
      if abs(next_guess - prev_guess) < precision:
         return next_guess

      UpperCamelCase_									=     next_guess


# Let's Execute
if __name__ == "__main__":
 # Find root of trigonometric function
 # Find value of pi
 print(f'The root of sin(x) = 0 is {newton_raphson("sin(x)", 2)}')

 # Find root of polynomial
 # Find fourth Root of 5
 print(f'The root of x**4 - 5 = 0 is {newton_raphson("x**4 -5", 0.4 +5J)}')

 # Find value of e
 print(
     """The root of log(y) - 1 = 0 is """,
     f'{newton_raphson("log(y) - 1", 2, variable="y")}',
 )

 # Exponential Roots
 print(
     """The root of exp(x) - 1 = 0 is""",
     f'{newton_raphson("exp(x) - 1", 1_0, precision=0.005)}',
 )

 # Find root of cos(x)
 print(f'The root of cos(x) = 0 is {newton_raphson("cos(x)", 0)}')





