

'''simple docstring'''






a_					:    List[str]          =    range(2, 2_0 + 1)
a_					:    Optional[Any]          =    [1_0**k for k in range(ks[-1] + 1)]
a_					:    dict[int, dict[int, list[list[int]]]]          =    {}






def 	_A				(lowerCAmelCase__  :Any				,						lowerCAmelCase__  :Dict				,						lowerCAmelCase__  :Any				,						lowerCAmelCase__  :Optional[Any]		)   ->  int:




     '''simple docstring'''



     _a			      =							sum(a_i[j] for j in range(__UpperCamelCase				,						len(__UpperCamelCase		)		)		)
     _a			      =							sum(a_i[j] * base[j] for j in range(min(len(__UpperCamelCase		)				,						__UpperCamelCase		)		)		)

     _a			      =							0, 0
     _a			      =							n - i

     _a			      =							memo.get(__UpperCamelCase		)

     if sub_memo is not None:
          _a			      =							sub_memo.get(__UpperCamelCase		)

          if jumps is not None and len(__UpperCamelCase		) > 0:
               # find and make the largest jump without going over
               _a			      =							-1
               for _k in range(len(__UpperCamelCase		) - 1				,						-1				,						-1		):
                    if jumps[_k][2] <= k and jumps[_k][1] <= max_dn:
                         _a			      =							_k
                         break

               if max_jump >= 0:
                    _a			      =							jumps[max_jump]
                    # since the difference between jumps is cached, add c
                    _a			      =							diff + c
                    for j in range(min(__UpperCamelCase				,						len(__UpperCamelCase		)		)		):
                         _a			      =							divmod(__UpperCamelCase				,						10		)
                    if new_c > 0:
                         add(__UpperCamelCase				,						__UpperCamelCase				,						__UpperCamelCase		)

          else:
               _a			      =							[]
     else:
          _a			      =							{c: []}
          _a			      =							sub_memo

     if dn >= max_dn or c + diff >= base[k]:
          return diff, dn

     if k > ks[0]:
          while True:
               # keep doing smaller jumps
               _a			      =							next_term(__UpperCamelCase				,						k - 1				,						i + dn				,						__UpperCamelCase		)
               diff += _diff
               dn += terms_jumped

               if dn >= max_dn or c + diff >= base[k]:
                    break
     else:
          # would be too small a jump, just compute sequential terms instead
          _a			      =							compute(__UpperCamelCase				,						__UpperCamelCase				,						i + dn				,						__UpperCamelCase		)
          diff += _diff
          dn += terms_jumped

     _a			      =							sub_memo[c]

     # keep jumps sorted by # of terms skipped
     _a			      =							0
     while j < len(__UpperCamelCase		):
          if jumps[j][1] > dn:
               break
          j += 1

     # cache the jump for this value digitsum(b) and c
     sub_memo[c].insert(__UpperCamelCase				,						(diff, dn, k)		)
     return (diff, dn)






def 	_A				(lowerCAmelCase__  :int				,						lowerCAmelCase__  :Optional[int]				,						lowerCAmelCase__  :List[str]				,						lowerCAmelCase__  :int		)   ->  Any:




     '''simple docstring'''



     if i >= n:
          return 0, i
     if k > len(__UpperCamelCase		):
          a_i.extend([0 for _ in range(k - len(__UpperCamelCase		)		)]		)

     # note: a_i -> b * 10^k + c
     # ds_b -> digitsum(b)
     # ds_c -> digitsum(c)
     _a			      =							i
     _a			      =							0, 0, 0
     for j in range(len(__UpperCamelCase		)		):
          if j >= k:
               ds_b += a_i[j]
          else:
               ds_c += a_i[j]

     while i < n:
          i += 1
          _a			      =							ds_c + ds_b
          diff += addend
          _a			      =							0
          for j in range(__UpperCamelCase		):
               _a			      =							a_i[j] + addend
               _a			      =							divmod(__UpperCamelCase				,						10		)

               ds_c += a_i[j]

          if addend > 0:
               break

     if addend > 0:
          add(__UpperCamelCase				,						__UpperCamelCase				,						__UpperCamelCase		)
     return diff, i - start_i






def 	_A				(lowerCAmelCase__  :Dict				,						lowerCAmelCase__  :List[Any]				,						lowerCAmelCase__  :int		)   ->  Tuple:




     '''simple docstring'''



     for j in range(__UpperCamelCase				,						len(__UpperCamelCase		)		):
          _a			      =							digits[j] + addend
          if s >= 10:
               _a			      =							divmod(__UpperCamelCase				,						10		)
               _a			      =							addend // 10 + quotient
          else:
               _a			      =							s
               _a			      =							addend // 10

          if addend == 0:
               break

     while addend > 0:
          _a			      =							divmod(__UpperCamelCase				,						10		)
          digits.append(__UpperCamelCase		)






def 	_A				(lowerCAmelCase__  :int = 10**15		)   ->  int:




     '''simple docstring'''



     _a			      =							[1]
     _a			      =							1
     _a			      =							0
     while True:
          _a			      =							next_term(__UpperCamelCase				,						20				,						i + dn				,						__UpperCamelCase		)
          dn += terms_jumped
          if dn == n - i:
               break

     _a			      =							0
     for j in range(len(__UpperCamelCase		)		):
          a_n += digits[j] * 10**j
     return a_n


if __name__ == "__main__":
 print(f'''{solution() = }''')





'''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]

