





'''simple docstring'''






# Author: OMKAR PATHAK, Nwachukwu Chidiebere

# Use a Python dictionary to construct the graph.
from __future__ import annotations

from pprint import pformat
from typing import Generic, TypeVar

A__    :       List[str]              =TypeVar('''T''')




class 			UpperCAmelCase					(      Generic[T]       ):




      def __init__(      self      :			Tuple      ,      __snake_case      :			bool = True  )    ->				None:
            _lowerCAmelCase												=							{}  # dictionary of lists
            _lowerCAmelCase												=							directed




      def     lowercase__   (      self      :			Union[str, Any]      ,      __snake_case      :			T      ,      __snake_case      :			T  )    ->				GraphAdjacencyList[T]:

            if not self.directed:  # For undirected graphs
                  # if both source vertex and destination vertex are both present in the
                  # adjacency list, add destination vertex to source vertex list of adjacent
                  # vertices and add source vertex to destination vertex list of adjacent
                  # vertices.
                  if source_vertex in self.adj_list and destination_vertex in self.adj_list:
                        self.adj_list[source_vertex].append(__snake_case  )
                        self.adj_list[destination_vertex].append(__snake_case  )
                  # if only source vertex is present in adjacency list, add destination vertex
                  # to source vertex list of adjacent vertices, then create a new vertex with
                  # destination vertex as key and assign a list containing the source vertex
                  # as it's first adjacent vertex.
                  elif source_vertex in self.adj_list:
                        self.adj_list[source_vertex].append(__snake_case  )
                        _lowerCAmelCase												=							[source_vertex]
                  # if only destination vertex is present in adjacency list, add source vertex
                  # to destination vertex list of adjacent vertices, then create a new vertex
                  # with source vertex as key and assign a list containing the source vertex
                  # as it's first adjacent vertex.
                  elif destination_vertex in self.adj_list:
                        self.adj_list[destination_vertex].append(__snake_case  )
                        _lowerCAmelCase												=							[destination_vertex]
                  # if both source vertex and destination vertex are not present in adjacency
                  # list, create a new vertex with source vertex as key and assign a list
                  # containing the destination vertex as it's first adjacent vertex also
                  # create a new vertex with destination vertex as key and assign a list
                  # containing the source vertex as it's first adjacent vertex.
                  else:
                        _lowerCAmelCase												=							[destination_vertex]
                        _lowerCAmelCase												=							[source_vertex]
            else:  # For directed graphs
                  # if both source vertex and destination vertex are present in adjacency
                  # list, add destination vertex to source vertex list of adjacent vertices.
                  if source_vertex in self.adj_list and destination_vertex in self.adj_list:
                        self.adj_list[source_vertex].append(__snake_case  )
                  # if only source vertex is present in adjacency list, add destination
                  # vertex to source vertex list of adjacent vertices and create a new vertex
                  # with destination vertex as key, which has no adjacent vertex
                  elif source_vertex in self.adj_list:
                        self.adj_list[source_vertex].append(__snake_case  )
                        _lowerCAmelCase												=							[]
                  # if only destination vertex is present in adjacency list, create a new
                  # vertex with source vertex as key and assign a list containing destination
                  # vertex as first adjacent vertex
                  elif destination_vertex in self.adj_list:
                        _lowerCAmelCase												=							[destination_vertex]
                  # if both source vertex and destination vertex are not present in adjacency
                  # list, create a new vertex with source vertex as key and a list containing
                  # destination vertex as it's first adjacent vertex. Then create a new vertex
                  # with destination vertex as key, which has no adjacent vertex
                  else:
                        _lowerCAmelCase												=							[destination_vertex]
                        _lowerCAmelCase												=							[]

            return self




      def __repr__(      self      :			int  )    ->				str:
            return pformat(self.adj_list  )













'''simple docstring'''






import unittest

from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_torch,
    require_vision,
    slow,
)

from .test_pipelines_common import ANY


if is_vision_available():
      from PIL import Image
else:




      class 			UpperCAmelCase					:




            @staticmethod
            def     lowercase__   (      *__snake_case      :			Optional[Any]      ,      **__snake_case      :			Any  )    ->				Tuple:
                  pass




@is_pipeline_test
@require_torch
@require_vision
class 			UpperCAmelCase					(      unittest.TestCase       ):
      _lowercase:      Union[str, Any]											=       MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING




      def     lowercase__   (      self      :			List[str]      ,      __snake_case      :			Optional[Any]      ,      __snake_case      :			str      ,      __snake_case      :			List[str]  )    ->				int:
            _lowerCAmelCase												=							pipeline("""visual-question-answering"""      ,      model="""hf-internal-testing/tiny-vilt-random-vqa"""  )
            _lowerCAmelCase												=							[
                {
                    """image""": Image.open("""./tests/fixtures/tests_samples/COCO/000000039769.png"""  ),
                    """question""": """How many cats are there?""",
                },
                {
                    """image""": """./tests/fixtures/tests_samples/COCO/000000039769.png""",
                    """question""": """How many cats are there?""",
                },
            ]
            return vqa_pipeline, examples




      def     lowercase__   (      self      :			Any      ,      __snake_case      :			List[Any]      ,      __snake_case      :			List[Any]  )    ->				Union[str, Any]:
            _lowerCAmelCase												=							vqa_pipeline(__snake_case      ,      top_k=1  )
            self.assertEqual(
                __snake_case      ,      [
                    [{"""score""": ANY(__snake_case  ), """answer""": ANY(__snake_case  )}],
                    [{"""score""": ANY(__snake_case  ), """answer""": ANY(__snake_case  )}],
                ]      ,      )




      @require_torch
      def     lowercase__   (      self      :			str  )    ->				int:
            _lowerCAmelCase												=							pipeline("""visual-question-answering"""      ,      model="""hf-internal-testing/tiny-vilt-random-vqa"""  )
            _lowerCAmelCase												=							"""./tests/fixtures/tests_samples/COCO/000000039769.png"""
            _lowerCAmelCase												=							"""How many cats are there?"""

            _lowerCAmelCase												=							vqa_pipeline(image=__snake_case      ,      question="""How many cats are there?"""      ,      top_k=2  )
            self.assertEqual(
                __snake_case      ,      [{"""score""": ANY(__snake_case  ), """answer""": ANY(__snake_case  )}, {"""score""": ANY(__snake_case  ), """answer""": ANY(__snake_case  )}]  )

            _lowerCAmelCase												=							vqa_pipeline({"""image""": image, """question""": question}      ,      top_k=2  )
            self.assertEqual(
                __snake_case      ,      [{"""score""": ANY(__snake_case  ), """answer""": ANY(__snake_case  )}, {"""score""": ANY(__snake_case  ), """answer""": ANY(__snake_case  )}]  )




      @slow
      @require_torch
      def     lowercase__   (      self      :			List[Any]  )    ->				List[str]:
            _lowerCAmelCase												=							pipeline("""visual-question-answering"""      ,      model="""dandelin/vilt-b32-finetuned-vqa"""  )
            _lowerCAmelCase												=							"""./tests/fixtures/tests_samples/COCO/000000039769.png"""
            _lowerCAmelCase												=							"""How many cats are there?"""

            _lowerCAmelCase												=							vqa_pipeline(image=__snake_case      ,      question=__snake_case      ,      top_k=2  )
            self.assertEqual(
                nested_simplify(__snake_case      ,      decimals=4  )      ,      [{"""score""": 0.87_99, """answer""": """2"""}, {"""score""": 0.2_96, """answer""": """1"""}]  )

            _lowerCAmelCase												=							vqa_pipeline({"""image""": image, """question""": question}      ,      top_k=2  )
            self.assertEqual(
                nested_simplify(__snake_case      ,      decimals=4  )      ,      [{"""score""": 0.87_99, """answer""": """2"""}, {"""score""": 0.2_96, """answer""": """1"""}]  )

            _lowerCAmelCase												=							vqa_pipeline(
                [{"""image""": image, """question""": question}, {"""image""": image, """question""": question}]      ,      top_k=2  )
            self.assertEqual(
                nested_simplify(__snake_case      ,      decimals=4  )      ,      [[{"""score""": 0.87_99, """answer""": """2"""}, {"""score""": 0.2_96, """answer""": """1"""}]] * 2      ,      )




      @require_tf
      @unittest.skip("""Visual question answering not implemented in TF"""  )
      def     lowercase__   (      self      :			List[str]  )    ->				Union[str, Any]:
            pass






