



'''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       __magic_name__		(       _UpperCamelCase  ):
							lowerCAmelCase			:       List[Any]  							=   'dandelin/vilt-b32-finetuned-vqa'
							lowerCAmelCase			:       Optional[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.'
							)
							lowerCAmelCase			:       List[Any]  							=   'image_qa'
							lowerCAmelCase			:       Optional[int]  							=   AutoProcessor
							lowerCAmelCase			:       Dict  							=   AutoModelForVisualQuestionAnswering

							lowerCAmelCase			:       Optional[Any]  							=   ['image', 'text']
							lowerCAmelCase			:       Any  							=   ['text']







							def __init__(				self   :			List[str]      ,*_UpperCAmelCase   :			Union[str, Any]      ,**_UpperCAmelCase   :			Any						):
									requires_backends(self      ,['vision']						)
									super().__init__(*_UpperCAmelCase      ,**_UpperCAmelCase						)







							def 				__lowercase     (				self   :			Optional[Any]      ,_UpperCAmelCase   :			"Image"      ,_UpperCAmelCase   :			str						):
									return self.pre_processor(_UpperCAmelCase      ,_UpperCAmelCase      ,return_tensors='pt'						)







							def 				__lowercase     (				self   :			Optional[int]      ,_UpperCAmelCase   :			List[Any]						):
									with torch.no_grad():
											return self.model(**_UpperCAmelCase						).logits







							def 				__lowercase     (				self   :			Any      ,_UpperCAmelCase   :			Tuple						):
									_a	: Optional[Any]								=				outputs.argmax(-1						).item()
									return self.model.config.idalabel[idx]









'''simple docstring'''

from abc import ABC, abstractmethod
from argparse import ArgumentParser

class       __magic_name__		(       _UpperCamelCase  ):







							@staticmethod
							@abstractmethod
							def 				__lowercase     (				_UpperCAmelCase   :			ArgumentParser						):
									raise NotImplementedError()







							@abstractmethod
							def 				__lowercase     (				self   :			str						):
									raise NotImplementedError()




