# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool





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

						UpperCamelCase_  =	["""audio"""]
						UpperCamelCase_  =	["""text"""]


						def  __A ( self			:       Optional[Any]					,	UpperCamelCase__			:       Any		):





												'''simple docstring'''





												return self.pre_processor(UpperCamelCase__					,	return_tensors='''pt'''		).input_features


						def  __A ( self			:       Any					,	UpperCamelCase__			:       int		):





												'''simple docstring'''





												return self.model.generate(inputs=UpperCamelCase__		)



						def  __A ( self			:       Any					,	UpperCamelCase__			:       Optional[int]		):





												'''simple docstring'''





												return self.pre_processor.batch_decode(UpperCamelCase__					,	skip_special_tokens=UpperCamelCase__		)[0]






import random
def    A			(					_lowercase	,						_lowercase		):
						SCREAMING_SNAKE_CASE       ,						SCREAMING_SNAKE_CASE       ,						SCREAMING_SNAKE_CASE							:					Tuple           =							[], [], []
						for element in data:
												if element < pivot:
																		less.append(_lowercase		)
												elif element > pivot:
																		greater.append(_lowercase		)
												else:
																		equal.append(_lowercase		)
						return less, equal, greater



def    A			(					_lowercase	,						_lowercase		):
						# index = len(items) // 2 when trying to find the median
						#   (value of index when items is sorted)

						# invalid input
						if index >= len(_lowercase		) or index < 0:
												return None

						SCREAMING_SNAKE_CASE							:					Dict           =							items[random.randint(0	,						len(_lowercase		) - 1		)]
						SCREAMING_SNAKE_CASE							:					int           =							0
						SCREAMING_SNAKE_CASE       ,						SCREAMING_SNAKE_CASE       ,						SCREAMING_SNAKE_CASE							:					List[str]           =							_partition(_lowercase	,						_lowercase		)
						SCREAMING_SNAKE_CASE							:					List[Any]           =							len(_lowercase		)
						SCREAMING_SNAKE_CASE							:					Optional[Any]           =							len(_lowercase		)

						# index is the pivot
						if m <= index < m + count:
												return pivot
						# must be in smaller
						elif m > index:
												return quick_select(_lowercase	,						_lowercase		)
						# must be in larger
						else:
												return quick_select(_lowercase	,						index - (m + count)		)





