'''simple docstring'''
import warnings
from contextlib import contextmanager

from ....processing_utils import ProcessorMixin






class 			__lowercase		(						a__						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						"""MCTCTFeatureExtractor"""
     SCREAMING_SNAKE_CASE__		   =						"""AutoTokenizer"""







     def __init__(		self     ,			_lowerCamelCase     ,			_lowerCamelCase    ):
         super().__init__(lowercase__     ,			lowercase__    )
         __UpperCamelCase	:	List[str]		    =  self.feature_extractor
         __UpperCamelCase	:	Any		    =  False







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





         if self._in_target_context_manager:
             return self.current_processor(*lowercase__     ,			**lowercase__    )

         if "raw_speech" in kwargs:
             warnings.warn('Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead.'    )
             __UpperCamelCase	:	List[str]		    =  kwargs.pop('raw_speech'    )
         else:
             __UpperCamelCase	:	str		    =  kwargs.pop('audio'     ,			lowercase__    )
         __UpperCamelCase	:	Dict		    =  kwargs.pop('sampling_rate'     ,			lowercase__    )
         __UpperCamelCase	:	Optional[int]		    =  kwargs.pop('text'     ,			lowercase__    )
         if len(lowercase__    ) > 0:
             __UpperCamelCase	:	Any		    =  args[0]
             __UpperCamelCase	:	List[str]		    =  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	:	Tuple		    =  self.feature_extractor(lowercase__     ,			*lowercase__     ,			sampling_rate=lowercase__     ,			**lowercase__    )
         if text is not None:
             __UpperCamelCase	:	str		    =  self.tokenizer(lowercase__     ,			**lowercase__    )

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







     def lowerCAmelCase     (		self     ,			*_lowerCamelCase     ,			**_lowerCamelCase    ):
         return self.tokenizer.batch_decode(*lowercase__     ,			**lowercase__    )







     def lowerCAmelCase     (		self     ,			*_lowerCamelCase     ,			**_lowerCamelCase    ):





         if self._in_target_context_manager:
             return self.current_processor.pad(*lowercase__     ,			**lowercase__    )

         __UpperCamelCase	:	int		    =  kwargs.pop('input_features'     ,			lowercase__    )
         __UpperCamelCase	:	Tuple		    =  kwargs.pop('labels'     ,			lowercase__    )
         if len(lowercase__    ) > 0:
             __UpperCamelCase	:	Union[str, Any]		    =  args[0]
             __UpperCamelCase	:	List[Any]		    =  args[1:]

         if input_features is not None:
             __UpperCamelCase	:	Union[str, Any]		    =  self.feature_extractor.pad(lowercase__     ,			*lowercase__     ,			**lowercase__    )
         if labels is not None:
             __UpperCamelCase	:	Union[str, Any]		    =  self.tokenizer.pad(lowercase__     ,			**lowercase__    )

         if labels is None:
             return input_features
         elif input_features is None:
             return labels
         else:
             __UpperCamelCase	:	List[Any]		    =  labels['''input_ids''']
             return input_features







     def lowerCAmelCase     (		self     ,			*_lowerCamelCase     ,			**_lowerCamelCase    ):
         return self.tokenizer.decode(*lowercase__     ,			**lowercase__    )







     @contextmanager
     def lowerCAmelCase     (		self    ):
         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	:	List[str]		    =  True
         __UpperCamelCase	:	Union[str, Any]		    =  self.tokenizer
         yield
         __UpperCamelCase	:	Optional[int]		    =  self.feature_extractor
         __UpperCamelCase	:	Union[str, Any]		    =  False




'''simple docstring'''
from timeit import timeit

a=  {
    '''MALAYALAM''': True,
    '''String''': False,
    '''rotor''': True,
    '''level''': True,
    '''A''': True,
    '''BB''': True,
    '''ABC''': False,
    '''amanaplanacanalpanama''': True,  # "a man a plan a canal panama"
}
# Ensure our test data is valid
assert all((key == key[::-1]) is value for key, value in test_data.items())







def  _UpperCamelCase (     _a	:	str			):




    """simple docstring"""



    __UpperCamelCase	:	int		    =  0
    __UpperCamelCase	:	str		    =  len(_a			) - 1
    while start_i < end_i:
        if s[start_i] == s[end_i]:
            start_i += 1
            end_i -= 1
        else:
            return False
    return True







def  _UpperCamelCase (     _a	:	str			):




    """simple docstring"""



    __UpperCamelCase	:	Optional[Any]		    =  len(_a			) // 2
    __UpperCamelCase	:	Tuple		    =  len(_a			)

    # We need to traverse till half of the length of string
    # as we can get access of the i'th last element from
    # i'th index.
    # eg: [0,1,2,3,4,5] => 4th index can be accessed
    # with the help of 1st index (i==n-i-1)
    # where n is length of string
    return all(s[i] == s[n - i - 1] for i in range(_a			)			)







def  _UpperCamelCase (     _a	:	str			):




    """simple docstring"""



    if len(_a			) <= 2:
        return True
    if s[0] == s[len(_a			) - 1]:
        return is_palindrome_recursive(s[1:-1]			)
    else:
        return False







def  _UpperCamelCase (     _a	:	str			):




    """simple docstring"""



    return s == s[::-1]







def  _UpperCamelCase (     _a	:	str			):




    """simple docstring"""



    __UpperCamelCase	:	int		    =  f"""all({name}(key) is value for key, value in test_data.items())"""
    __UpperCamelCase	:	Union[str, Any]		    =  f"""from __main__ import test_data, {name}"""
    __UpperCamelCase	:	Any		    =  5_0_0_0_0_0
    __UpperCamelCase	:	Tuple		    =  timeit(stmt=_a				,     setup=_a				,     number=_a			)
    print(f"""{name:<35} finished {number:,} runs in {result:.5f} seconds"""			)


if __name__ == "__main__":
  for key, value in test_data.items():
    assert is_palindrome(key) is is_palindrome_recursive(key)
    assert is_palindrome(key) is is_palindrome_slice(key)
    print(F"""{key:21} {value}""")
  print('''a man a plan a canal panama''')

  # finished 500,000 runs in 0.46793 seconds
  benchmark_function('''is_palindrome_slice''')
  # finished 500,000 runs in 0.85234 seconds
  benchmark_function('''is_palindrome''')
  # finished 500,000 runs in 1.32028 seconds
  benchmark_function('''is_palindrome_recursive''')
  # finished 500,000 runs in 2.08679 seconds
  benchmark_function('''is_palindrome_traversal''')



