





"""simple docstring"""






from ...processing_utils import ProcessorMixin




class 				__lowercase			(			_UpperCamelCase							):







					'''simple docstring'''




					__lowerCAmelCase  =  '''WhisperFeatureExtractor'''
					__lowerCAmelCase  =  '''WhisperTokenizer'''







					def __init__(						self	,			_UpperCAmelCase	,			_UpperCAmelCase     ):
									super().__init__(_UpperCAmelCase	,			_UpperCAmelCase     )
									__a :						Dict			       =  self.feature_extractor
									__a :						Optional[Any]			       =  False







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase=None	,			_UpperCAmelCase=None	,			_UpperCAmelCase=True     ):
									return self.tokenizer.get_decoder_prompt_ids(task=_UpperCAmelCase	,			language=_UpperCAmelCase	,			no_timestamps=_UpperCAmelCase     )







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

									__a :						int			       =  kwargs.pop('''audio'''	,			_UpperCAmelCase     )
									__a :						Union[str, Any]			       =  kwargs.pop('''sampling_rate'''	,			_UpperCAmelCase     )
									__a :						List[str]			       =  kwargs.pop('''text'''	,			_UpperCAmelCase     )
									if len(_UpperCAmelCase     ) > 0:
													__a :						int			       =  args[0]
													__a :						List[Any]			       =  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 :						int			       =  self.feature_extractor(_UpperCAmelCase	,			*_UpperCAmelCase	,			sampling_rate=_UpperCAmelCase	,			**_UpperCAmelCase     )
									if text is not None:
													__a :						Any			       =  self.tokenizer(_UpperCAmelCase	,			**_UpperCAmelCase     )

									if text is None:
													return inputs

									elif audio is None:
													return encodings
									else:
													__a :						str			       =  encodings['''input_ids''']
													return inputs







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







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







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase	,			_UpperCAmelCase="np"     ):
									return self.tokenizer.get_prompt_ids(_UpperCAmelCase	,			return_tensors=_UpperCAmelCase     )






"""simple docstring"""






from __future__ import annotations

import typing
from collections import Counter

def     __A      (			a_						:int)		->		typing.Counter[int]:
				__a :						typing.Counter[int]			       =  Counter()
				for base in range(1   ,       max_perimeter + 1):
								for perpendicular in range(a_   ,       max_perimeter + 1):
												__a :						Any			       =  (base * base + perpendicular * perpendicular) ** 0.5
												if hypotenuse == int(a_):
																__a :						List[Any]			       =  int(base + perpendicular + hypotenuse)
																if perimeter > max_perimeter:
																				continue
																triplets[perimeter] += 1
				return triplets

def     __A      (			a_						:int = 10_00)		->		int:
				__a :						Dict			       =  pythagorean_triple(a_)
				return triplets.most_common(1)[0][0]


if __name__ == "__main__":
		print(F'Perimeter {solution()} has maximum solutions')