



from __future__ import annotations

import os
from collections.abc import Mapping

_lowercase						  =		tuple[int, int]



class     _UpperCAmelCase			:




     def __init__(				self ,						a__ ,						a__):
         A__		 =					vertices
         A__		 =					{
             (min(a__), max(a__)): weight for edge, weight in edges.items()
         }




     def 		snake_case_		(				self ,						a__ ,						a__):
         self.vertices.add(edge[0])
         self.vertices.add(edge[1])
         A__		 =					weight




     def 		snake_case_		(				self):
         A__		 =					Graph({min(self.vertices)} ,						{})
         A__		 =					42
         A__		 =					42
         A__		 =					42
         A__		 =					42

         while len(subgraph.vertices) < len(self.vertices):
             A__		 =					max(self.edges.values()) + 1
             for edge, weight in self.edges.items():
                 if (edge[0] in subgraph.vertices) ^ (edge[1] in subgraph.vertices):
                     if weight < min_weight:
                         A__		 =					edge
                         A__		 =					weight

             subgraph.add_edge(a__ ,						a__)

         return subgraph







def 		lowerCAmelCase__    (					UpperCamelCase_				:       str = "p107_network.txt"	)->  int:
    A__		 =					os.path.abspath(os.path.dirname(UpperCamelCase_	)	)
    A__		 =					os.path.join(UpperCamelCase_ ,       UpperCamelCase_	)
    A__		 =					{}
    A__		 =					42
    A__		 =					42
    A__		 =					42

    with open(UpperCamelCase_	) as f:
        A__		 =					f.read().strip().split('''\n'''	)

    A__		 =					[line.split(''','''	) for line in data]

    for edgea in range(1 ,       len(UpperCamelCase_	)	):
        for edgea in range(UpperCamelCase_	):
            if adjaceny_matrix[edgea][edgea] != "-":
                A__		 =					int(adjaceny_matrix[edgea][edgea]	)

    A__		 =					Graph(set(range(len(UpperCamelCase_	)	)	) ,       UpperCamelCase_	)

    A__		 =					graph.prims_algorithm()

    A__		 =					sum(graph.edges.values()	)
    A__		 =					sum(subgraph.edges.values()	)

    return initial_total - optimal_total


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





# 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()
