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#
# 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 (							lowercase__):


       """simple docstring"""




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

       A__											=			["audio"]
       A__											=			["text"]





       def 						lowerCAmelCase     (   self							:			Tuple					,      __lowerCamelCase							:			Optional[int]       ):


             '''simple docstring'''



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





       def 						lowerCAmelCase     (   self							:			int					,      __lowerCamelCase							:			Union[str, Any]       ):


             '''simple docstring'''



             return self.model.generate(inputs=__lowerCamelCase       )





       def 						lowerCAmelCase     (   self							:			List[str]					,      __lowerCamelCase							:			List[str]       ):


             '''simple docstring'''



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






import warnings

from ...utils import logging
from .image_processing_beit import BeitImageProcessor


A      :    List[str]		=					logging.get_logger(__name__)







class 			_lowercase (							lowercase__):


       """simple docstring"""




       def __init__(   self							:			Optional[int]					,      *__lowerCamelCase							:			List[str]					,      **__lowerCamelCase							:			str       ):


             '''simple docstring'''



             warnings.warn(
                 "The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
                 " use BeitImageProcessor instead."					,      __lowerCamelCase					,      )
             super().__init__(*__lowerCamelCase					,      **__lowerCamelCase       )


