





"""simple docstring"""






from ..models.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool




class 			__lowercase     (     _UpperCamelCase							):
					__lowerCAmelCase					=					'''openai/whisper-base'''
					__lowerCAmelCase					=					(
					    '''This is a tool that transcribes an audio into text. It takes an input named `audio` and returns the '''
					    '''transcribed text.'''
					)
					__lowerCAmelCase					=					'''transcriber'''
					__lowerCAmelCase					=					WhisperProcessor
					__lowerCAmelCase					=					WhisperForConditionalGeneration

					__lowerCAmelCase					=					['''audio''']
					__lowerCAmelCase					=					['''text''']







					def 	_lowerCamelCase						(  self		,     _UpperCAmelCase       ):
									return self.pre_processor(_UpperCAmelCase		,     return_tensors='''pt'''       ).input_features







					def 	_lowerCamelCase						(  self		,     _UpperCAmelCase       ):
									return self.model.generate(inputs=_UpperCAmelCase       )







					def 	_lowerCamelCase						(  self		,     _UpperCAmelCase       ):
									return self.pre_processor.batch_decode(_UpperCAmelCase		,     skip_special_tokens=_UpperCAmelCase       )[0]






"""simple docstring"""






def       __A (     a_  :float)						->						float:

				if edge <= 0 or not isinstance(a_				,    a_):
								raise ValueError('''Length must be a positive.''')
				return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)

def       __A (     a_  :float)						->						float:

				if edge <= 0 or not isinstance(a_				,    a_):
								raise ValueError('''Length must be a positive.''')
				return ((15 + (7 * (5 ** (1 / 2)))) / 4) * (edge**3)


if __name__ == "__main__":
		import doctest

		doctest.testmod()