




from ..utils import requires_backends


a_										=       None

class 	_lowerCamelCase  :

      """simple docstring"""

      def __init__(       self   :	int	,    *snake_case   :	Dict	,    **snake_case   :	Tuple			):
         requires_backends(self	,    ['''detectron2''']			)







      @classmethod
      def  snake_case		(       cls   :	Optional[Any]	,    *snake_case   :	Union[str, Any]	,    **snake_case   :	Optional[int]			):
         requires_backends(cls	,    ['''detectron2''']			)












# 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.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool


a_										=       "Here is a text containing a lot of information: '''{text}'''.\n\nCan you answer this question about the text: '{question}'"

class 	_lowerCamelCase  (     _SCREAMING_SNAKE_CASE				):

      """simple docstring"""

      lowerCAmelCase__     :	Union[str, Any]      =   "google/flan-t5-base"
      lowerCAmelCase__     :	Union[str, Any]      =   (
          "This is a tool that answers questions related to a text. It takes two arguments named `text`, which is the "
          "text where to find the answer, and `question`, which is the question, and returns the answer to the question."
      )
      lowerCAmelCase__     :	List[Any]      =   "text_qa"
      lowerCAmelCase__     :	int      =   AutoTokenizer
      lowerCAmelCase__     :	Optional[Any]      =   AutoModelForSeqaSeqLM

      lowerCAmelCase__     :	Tuple      =   ["text", "text"]
      lowerCAmelCase__     :	Any      =   ["text"]







      def  snake_case		(       self   :	Union[str, Any]	,    snake_case   :	str	,    snake_case   :	str			):
          __UpperCamelCase											=  QA_PROMPT.format(text=snake_case	,    question=snake_case			)
          return self.pre_processor(snake_case	,    return_tensors='''pt'''			)







      def  snake_case		(       self   :	Any	,    snake_case   :	Optional[int]			):
          __UpperCamelCase											=  self.model.generate(**snake_case			)

          __UpperCamelCase						, __UpperCamelCase											=  inputs['''input_ids'''].shape
          __UpperCamelCase											=  output_ids.shape[0]

          return output_ids.reshape(snake_case	,    out_b // in_b	,    *output_ids.shape[1:]			)[0][0]







      def  snake_case		(       self   :	Tuple	,    snake_case   :	Optional[Any]			):
          return self.pre_processor.decode(snake_case	,    skip_special_tokens=snake_case	,    clean_up_tokenization_spaces=snake_case			)






