


'''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 		_snake_case					(     a__	):
					lowerCAmelCase      :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      :Union[str, Any]   =					'''image_qa'''
					lowerCAmelCase      :Tuple   =					AutoProcessor
					lowerCAmelCase      :List[Any]   =					AutoModelForVisualQuestionAnswering

					lowerCAmelCase      :Dict   =					['''image''', '''text''']
					lowerCAmelCase      :List[str]   =					['''text''']




					def __init__(      self							,							*_lowerCamelCase							,							**_lowerCamelCase):
								requires_backends(self							,							["""vision"""])
								super().__init__(*_lowerCamelCase							,							**_lowerCamelCase)




					def 				snake_case__						(      self							,							_lowerCamelCase							,							_lowerCamelCase):
								return self.pre_processor(_lowerCamelCase							,							_lowerCamelCase							,							return_tensors="""pt""")




					def 				snake_case__						(      self							,							_lowerCamelCase):
								with torch.no_grad():
											return self.model(**_lowerCamelCase).logits




					def 				snake_case__						(      self							,							_lowerCamelCase):
								UpperCAmelCase__  :					Tuple        =     outputs.argmax(-1).item()
								return self.model.config.idalabel[idx]



'''simple docstring'''



import warnings
from functools import wraps
from typing import Callable







def     _UpperCamelCase      (		UpperCamelCase__					):

			@wraps(UpperCamelCase__					)
			def _inner_fn(*UpperCamelCase__ ,      **UpperCamelCase__					):
						warnings.warn(
						    (f'''\'{fn.__name__}\' is experimental and might be subject to breaking changes in the future.''') ,      UpperCamelCase__ ,      )
						return fn(*UpperCamelCase__ ,      **UpperCamelCase__					)

			return _inner_fn