

'''simple docstring'''






from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding






class 			lowercase_	(lowerCamelCase__      ):




  """simple docstring"""




  SCREAMING_SNAKE_CASE    :  List[str]							=			['image_processor', 'tokenizer']
  SCREAMING_SNAKE_CASE    :  List[Any]							=			'AutoImageProcessor'
  SCREAMING_SNAKE_CASE    :  Union[str, Any]							=			'AutoTokenizer'






  def __init__(      self   :     Dict					,lowercase__   :     int					,lowercase__   :     List[Any]			):
   super().__init__(lowercase__					,lowercase__			)
   __lowercase							  = self.image_processor






  def __call__(      self   :     int					,lowercase__   :     Dict=None					,lowercase__   :     int=None					,lowercase__   :     str=None					,**lowercase__   :     str			):

   if text is None and images is None:
    raise ValueError('''You have to specify either text or images. Both cannot be none.'''			)

   if text is not None:
    __lowercase							  = self.tokenizer(lowercase__					,return_tensors=lowercase__					,**lowercase__			)

   if images is not None:
    __lowercase							  = self.image_processor(lowercase__					,return_tensors=lowercase__					,**lowercase__			)

   if text is not None and images is not None:
    __lowercase							  = image_features.pixel_values
    return encoding
   elif text is not None:
    return encoding
   else:
    return BatchEncoding(data=dict(**lowercase__			)					,tensor_type=lowercase__			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     str					,*lowercase__   :     Union[str, Any]					,**lowercase__   :     Optional[Any]			):
   return self.tokenizer.batch_decode(*lowercase__					,**lowercase__			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Any					,*lowercase__   :     Optional[int]					,**lowercase__   :     Tuple			):
   return self.tokenizer.decode(*lowercase__					,**lowercase__			)






  @property
  def 					SCREAMING_SNAKE_CASE      (      self   :     List[str]			):
   return ["input_ids", "attention_mask", "pixel_values"]




"""simple docstring"""





# 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 					_lowerCAmelCase  (	lowercase   ):







 """simple docstring"""







 __UpperCAmelCase	:					Tuple   		=	"openai/whisper-base"
 __UpperCAmelCase	:					Union[str, Any]   		=	(
     "This is a tool that transcribes an audio into text. It takes an input named `audio` and returns the "
     "transcribed text."
 )
 __UpperCAmelCase	:					List[str]   		=	"transcriber"
 __UpperCAmelCase	:					Optional[Any]   		=	WhisperProcessor
 __UpperCAmelCase	:					str   		=	WhisperForConditionalGeneration

 __UpperCAmelCase	:					List[str]   		=	["audio"]
 __UpperCAmelCase	:					Tuple   		=	["text"]


 def 					_lowercase (			self							:			str,					UpperCAmelCase__							:			int	):
    return self.pre_processor(UpperCAmelCase__,					return_tensors="pt"	).input_features


 def 					_lowercase (			self							:			Union[str, Any],					UpperCAmelCase__							:			Optional[Any]	):
    return self.model.generate(inputs=UpperCAmelCase__	)



 def 					_lowercase (			self							:			Dict,					UpperCAmelCase__							:			Optional[int]	):
    return self.pre_processor.batch_decode(UpperCAmelCase__,					skip_special_tokens=UpperCAmelCase__	)[0]




