





'''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 					SCREAMING_SNAKE_CASE       (a__				):
     lowerCAmelCase						     =			'''dandelin/vilt-b32-finetuned-vqa'''
     lowerCAmelCase						     =			(
         '''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						     =			'''image_qa'''
     lowerCAmelCase						     =			AutoProcessor
     lowerCAmelCase						     =			AutoModelForVisualQuestionAnswering

     lowerCAmelCase						     =			['''image''', '''text''']
     lowerCAmelCase						     =			['''text''']


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

          '''simple docstring'''






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


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase		,      _UpperCAmelCase):

          '''simple docstring'''






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


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase):

          '''simple docstring'''






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


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase):

          '''simple docstring'''






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






'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase__       : List[Any]         =       logging.get_logger(__name__)

lowercase__       : Optional[int]         =       {
    '''unc-nlp/lxmert-base-uncased''': '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json''',
}


class 					SCREAMING_SNAKE_CASE       (a__				):
     lowerCAmelCase						     =			'''lxmert'''
     lowerCAmelCase						     =			{}


     def __init__(		self		,      _UpperCAmelCase=3_0522		,      _UpperCAmelCase=768		,      _UpperCAmelCase=12		,      _UpperCAmelCase=9500		,      _UpperCAmelCase=1600		,      _UpperCAmelCase=400		,      _UpperCAmelCase=3072		,      _UpperCAmelCase="gelu"		,      _UpperCAmelCase=0.1		,      _UpperCAmelCase=0.1		,      _UpperCAmelCase=512		,      _UpperCAmelCase=2		,      _UpperCAmelCase=0.02		,      _UpperCAmelCase=1e-1_2		,      _UpperCAmelCase=9		,      _UpperCAmelCase=5		,      _UpperCAmelCase=5		,      _UpperCAmelCase=2048		,      _UpperCAmelCase=4		,      _UpperCAmelCase=6.67		,      _UpperCAmelCase=True		,      _UpperCAmelCase=True		,      _UpperCAmelCase=True		,      _UpperCAmelCase=True		,      _UpperCAmelCase=True		,      _UpperCAmelCase=True		,      _UpperCAmelCase=True		,      **_UpperCAmelCase		,      ):

          '''simple docstring'''






          __A		:					Tuple						=			vocab_size
          __A		:					int						=			hidden_size
          __A		:					str						=			num_attention_heads
          __A		:					Tuple						=			hidden_act
          __A		:					int						=			intermediate_size
          __A		:					str						=			hidden_dropout_prob
          __A		:					Optional[int]						=			attention_probs_dropout_prob
          __A		:					Optional[Any]						=			max_position_embeddings
          __A		:					Tuple						=			type_vocab_size
          __A		:					Optional[int]						=			initializer_range
          __A		:					Any						=			layer_norm_eps
          __A		:					Optional[Any]						=			num_qa_labels
          __A		:					Optional[int]						=			num_object_labels
          __A		:					Any						=			num_attr_labels
          __A		:					Union[str, Any]						=			l_layers
          __A		:					Optional[int]						=			x_layers
          __A		:					List[Any]						=			r_layers
          __A		:					Tuple						=			visual_feat_dim
          __A		:					Tuple						=			visual_pos_dim
          __A		:					Optional[int]						=			visual_loss_normalizer
          __A		:					int						=			task_matched
          __A		:					List[Any]						=			task_mask_lm
          __A		:					Optional[Any]						=			task_obj_predict
          __A		:					str						=			task_qa
          __A		:					List[Any]						=			visual_obj_loss
          __A		:					Optional[Any]						=			visual_attr_loss
          __A		:					Union[str, Any]						=			visual_feat_loss
          __A		:					Union[str, Any]						=			{'vision': r_layers, 'cross_encoder': x_layers, 'language': l_layers}
          super().__init__(**_UpperCAmelCase)