

'''simple docstring'''






from __future__ import annotations






def 	_A				(lowerCAmelCase__  :str				,						lowerCAmelCase__  :list[str] | None = None		)   ->  Tuple:




     '''simple docstring'''



     _a			      =							word_bank or []
     # create a table
     _a			      =							len(lowerCAmelCase__		) + 1

     _a			      =							[]
     for _ in range(lowerCAmelCase__		):
          table.append([]		)
     # seed value
     _a			      =							[[]]  # because empty string has empty combination

     # iterate through the indices
     for i in range(lowerCAmelCase__		):
          # condition
          if table[i] != []:
               for word in word_bank:
                    # slice condition
                    if target[i : i + len(lowerCAmelCase__		)] == word:
                         _a			      =							[
                             [word, *way] for way in table[i]
                         ]
                         # adds the word to every combination the current position holds
                         # now,push that combination to the table[i+len(word)]
                         table[i + len(lowerCAmelCase__		)] += new_combinations

    # combinations are in reverse order so reverse for better output
     for combination in table[len(lowerCAmelCase__		)]:
          combination.reverse()

     return table[len(lowerCAmelCase__		)]


if __name__ == "__main__":
 print(all_construct("jwajalapa", ["jwa", "j", "w", "a", "la", "lapa"]))
 print(all_construct("rajamati", ["s", "raj", "amat", "raja", "ma", "i", "t"]))
 print(
     all_construct(
         "hexagonosaurus",
         ["h", "ex", "hex", "ag", "ago", "ru", "auru", "rus", "go", "no", "o", "s"],
     )
 )





'''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     (     _SCREAMING_SNAKE_CASE       ):
 _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      ,				*__magic_name__      ,				**__magic_name__						)					->							Tuple:
      requires_backends(self      ,				['vision']						)
      super().__init__(*__magic_name__      ,				**__magic_name__						)
 def 							__UpperCAmelCase		( self      ,				__magic_name__      ,				__magic_name__						)					->							Tuple:
      return self.pre_processor(__magic_name__      ,				__magic_name__      ,				return_tensors='pt'						)
 def 							__UpperCAmelCase		( self      ,				__magic_name__						)					->							Any:
      with torch.no_grad():
           return self.model(**__magic_name__						).logits




 def 							__UpperCAmelCase		( self      ,				__magic_name__						)					->							Optional[int]:
      _a			      =							outputs.argmax(-1						).item()
      return self.model.config.idalabel[idx]

