




'''simple docstring'''

def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase	)		->					bool:

					'''simple docstring'''

					snake_case_									=				len(__UpperCAmelCase	)
					snake_case_									=				len(__UpperCAmelCase	)
					snake_case_									=				[[False for _ in range(m + 1	)] for _ in range(n + 1	)]
					snake_case_									=				True
					for i in range(__UpperCAmelCase	):
										for j in range(m + 1	):
															if dp[i][j]:
																				if j < m and a[i].upper() == b[j]:
																									snake_case_									=				True
																				if a[i].islower():
																									snake_case_									=				True
					return dp[n][m]


if __name__ == "__main__":
							import doctest

							doctest.testmod()





# 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 	UpperCAmelCase_					(					UpperCamelCase    ):

   '''simple docstring'''




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

   __A :      Any     		=		["audio"]
   __A :      List[str]     		=		["text"]






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     return self.pre_processor(__A						,				return_tensors="pt" ).input_features






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     return self.model.generate(inputs=__A )






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





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



