





"""simple docstring"""



import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin






class 	__snake_case      (	SCREAMING_SNAKE_CASE__  ):





	"""simple docstring"""


	_lowerCamelCase				 =  "AutoFeatureExtractor"
	_lowerCamelCase				 =  "Speech2Text2Tokenizer"

	def __init__(					self      ,		__lowerCamelCase      ,		__lowerCamelCase						):



					'''simple docstring'''




					super().__init__(UpperCAmelCase_      ,		UpperCAmelCase_						)
					__A					:		Union[str, Any]						=  self.feature_extractor
					__A					:		int						=  False

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



					'''simple docstring'''




					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.'''						)
									__A					:		List[Any]						=  kwargs.pop('''raw_speech'''						)
					else:
									__A					:		Tuple						=  kwargs.pop('''audio'''      ,		UpperCAmelCase_						)
					__A					:		Any						=  kwargs.pop('''sampling_rate'''      ,		UpperCAmelCase_						)
					__A					:		Any						=  kwargs.pop('''text'''      ,		UpperCAmelCase_						)
					if len(UpperCAmelCase_						) > 0:
									__A					:		Union[str, Any]						=  args[0]
									__A					:		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:
									__A					:		Optional[int]						=  self.feature_extractor(UpperCAmelCase_      ,		*UpperCAmelCase_      ,		sampling_rate=UpperCAmelCase_      ,		**UpperCAmelCase_						)
					if text is not None:
									__A					:		str						=  self.tokenizer(UpperCAmelCase_      ,		**UpperCAmelCase_						)

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

	def       UpperCamelCase__(					self      ,		*__lowerCamelCase      ,		**__lowerCamelCase						):



					'''simple docstring'''




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

	def       UpperCamelCase__(					self      ,		*__lowerCamelCase      ,		**__lowerCamelCase						):



					'''simple docstring'''




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







	@contextmanager
	def       UpperCamelCase__(					self						):



					'''simple docstring'''




					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					:		List[str]						=  True
					__A					:		Dict						=  self.tokenizer
					yield
					__A					:		Optional[int]						=  self.feature_extractor
					__A					:		Dict						=  False











"""simple docstring"""



def 	__lowercase  (     snake_case_						:						Union[str, Any]		)     ->Optional[int]:



    '''simple docstring'''







    __A					:		Dict						=  [701, 301, 132, 57, 23, 10, 4, 1]
    for gap in gaps:
        for i in range(snake_case_       ,len(snake_case_		)		):
            __A					:		Tuple						=  collection[i]
            __A					:		Union[str, Any]						=  i
            while j >= gap and collection[j - gap] > insert_value:
                __A					:		Optional[int]						=  collection[j - gap]
                j -= gap
            if j != i:
                __A					:		Optional[int]						=  insert_value
    return collection


if __name__ == "__main__":
       from doctest import testmod

       testmod()
       a_				=    input("""Enter numbers separated by a comma:\n""").strip()
       a_				=    [int(item) for item in user_input.split(""",""")]
       print(shell_sort(unsorted))




