


'''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        lowercase     (							A__ ):

		"""simple docstring"""

		_a   			=    'dandelin/vilt-b32-finetuned-vqa'
		_a   			=    (
		    '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   			=    'image_qa'
		_a   			=    AutoProcessor
		_a   			=    AutoModelForVisualQuestionAnswering

		_a   			=    ['image', 'text']
		_a   			=    ['text']




		def __init__(		self   ,       *UpperCamelCase_   ,       **UpperCamelCase_							):

							'''simple docstring'''


							requires_backends(self   ,       ['''vision''']							)
							super().__init__(*UpperCamelCase_   ,       **UpperCamelCase_							)




		def    lowerCAmelCase__    (		self   ,       UpperCamelCase_   ,       UpperCamelCase_							):

							'''simple docstring'''


							return self.pre_processor(UpperCamelCase_   ,       UpperCamelCase_   ,       return_tensors='''pt'''							)




		def    lowerCAmelCase__    (		self   ,       UpperCamelCase_							):

							'''simple docstring'''


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




		def    lowerCAmelCase__    (		self   ,       UpperCamelCase_							):

							'''simple docstring'''


							UpperCamelCase__       :Union[str, Any]							 =			outputs.argmax(-1							).item()
							return self.model.config.idalabel[idx]



'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case											=					{'''configuration_vit_msn''': ['''VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMSNConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case											=					[
		    '''VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''ViTMSNModel''',
		    '''ViTMSNForImageClassification''',
		    '''ViTMSNPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_vit_msn import VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMSNConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_vit_msn import (
				    VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ViTMSNForImageClassification,
				    ViTMSNModel,
				    ViTMSNPreTrainedModel,
				)

else:
		import sys

		__snake_case											=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)