




'''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 typing import TYPE_CHECKING

import torch

from ..models.auto import AutoModelForVisualQuestionAnswering, AutoProcessor
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
   from PIL import Image


class     _a						(			__a				):
       __a       :  List[str]            =      """dandelin/vilt-b32-finetuned-vqa"""
       __a       :  Union[str, Any]            =      (
           """This is a tool that answers a question about an image. It takes an input named `image` which should be the """
           """image containing the information, as well as a `question` which should be the question in English. It """
           """returns a text that is the answer to the question."""
       )
       __a       :  Any            =      """image_qa"""
       __a       :  Any            =      AutoProcessor
       __a       :  Tuple            =      AutoModelForVisualQuestionAnswering

       __a       :  List[Any]            =      ["""image""", """text"""]
       __a       :  Any            =      ["""text"""]
       def __init__(			self		:			Optional[int]     ,       *lowercase		:			Any     ,       **lowercase		:			Union[str, Any]       ):



           '''simple docstring'''

           requires_backends(self     ,       ['''vision''']       )
           super().__init__(*lowercase     ,       **lowercase       )
       def 					A   (			self		:			List[Any]     ,       lowercase		:			"Image"     ,       lowercase		:			str       ):



           '''simple docstring'''

           return self.pre_processor(lowercase     ,       lowercase     ,       return_tensors='''pt'''       )
       def 					A   (			self		:			Union[str, Any]     ,       lowercase		:			Union[str, Any]       ):



           '''simple docstring'''

           with torch.no_grad():
               return self.model(**lowercase       ).logits







       def 					A   (			self		:			int     ,       lowercase		:			Any       ):



           '''simple docstring'''

           UpperCAmelCase     =	outputs.argmax(-1       ).item()
           return self.model.config.idalabel[idx]










'''simple docstring'''







from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
    MaskedBertForMultipleChoice,
    MaskedBertForQuestionAnswering,
    MaskedBertForSequenceClassification,
    MaskedBertForTokenClassification,
    MaskedBertModel,
)
from .modules import *




