



class     _UpperCAmelCase			:




     def __init__(				self ,						a__):
         A__		 =					len(__A)
         A__		 =					[0] * len_array

         if len_array > 0:
             A__		 =					array[0]

         for i in range(1 ,						__A):
             A__		 =					self.prefix_sum[i - 1] + array[i]




     def 		snake_case_		(				self ,						a__ ,						a__):
         if start == 0:
             return self.prefix_sum[end]

         return self.prefix_sum[end] - self.prefix_sum[start - 1]




     def 		snake_case_		(				self ,						a__):
         A__		 =					{0}
         for sum_item in self.prefix_sum:
             if sum_item - target_sum in sums:
                 return True

             sums.add(__A)

         return False


if __name__ == "__main__":
   import doctest

   doctest.testmod()





# 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

from ..models.auto import AutoModelForVisionaSeq
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
   from PIL import Image



class     _UpperCAmelCase			(       A__     ):
     UpperCamelCase__		    =				'''Salesforce/blip-image-captioning-base'''
     UpperCamelCase__		    =				(
         '''This is a tool that generates a description of an image. It takes an input named `image` which should be the '''
         '''image to caption, and returns a text that contains the description in English.'''
     )
     UpperCamelCase__		    =				'''image_captioner'''
     UpperCamelCase__		    =				AutoModelForVisionaSeq

     UpperCamelCase__		    =				['''image''']
     UpperCamelCase__		    =				['''text''']




     def __init__(				self ,						*a__ ,						**a__):
         requires_backends(self ,						['''vision'''])
         super().__init__(*a__ ,						**a__)




     def 		snake_case_		(				self ,						a__):
         return self.pre_processor(images=a__ ,						return_tensors='''pt''')




     def 		snake_case_		(				self ,						a__):
         return self.model.generate(**a__)




     def 		snake_case_		(				self ,						a__):
         return self.pre_processor.batch_decode(a__ ,						skip_special_tokens=a__)[0].strip()
