"""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    __snake_case       :



       @staticmethod
       def   lowerCamelCase_   (						*lowercase    ,			**lowercase)	->			int:





         '''simple docstring'''





         pass




@is_pipeline_test
@require_torch
@require_vision
class    __snake_case       (     unittest.TestCase				):
      a__        =		MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING



      def   lowerCamelCase_   (						self    ,			lowercase    ,			lowercase    ,			lowercase)	->			Optional[int]:





        '''simple docstring'''





        a__:     Optional[int]										=	pipeline('visual-question-answering'    ,			model='hf-internal-testing/tiny-vilt-random-vqa')
        a__:     Optional[Any]										=	[
            {
                '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   lowerCamelCase_   (						self    ,			lowercase    ,			lowercase)	->			Optional[Any]:





        '''simple docstring'''





        a__:     List[str]										=	vqa_pipeline(lowercase    ,			top_k=1)
        self.assertEqual(
            lowercase    ,			[
                [{'score': ANY(lowercase), 'answer': ANY(lowercase)}],
                [{'score': ANY(lowercase), 'answer': ANY(lowercase)}],
            ]    ,			)



      @require_torch
      def   lowerCamelCase_   (						self)	->			int:





        '''simple docstring'''





        a__:     List[Any]										=	pipeline('visual-question-answering'    ,			model='hf-internal-testing/tiny-vilt-random-vqa')
        a__:     Optional[int]										=	'./tests/fixtures/tests_samples/COCO/000000039769.png'
        a__:     Optional[Any]										=	'How many cats are there?'

        a__:     List[Any]										=	vqa_pipeline(image=lowercase    ,			question='How many cats are there?'    ,			top_k=2)
        self.assertEqual(
            lowercase    ,			[{'score': ANY(lowercase), 'answer': ANY(lowercase)}, {'score': ANY(lowercase), 'answer': ANY(lowercase)}])

        a__:     Tuple										=	vqa_pipeline({'image': image, 'question': question}    ,			top_k=2)
        self.assertEqual(
            lowercase    ,			[{'score': ANY(lowercase), 'answer': ANY(lowercase)}, {'score': ANY(lowercase), 'answer': ANY(lowercase)}])



      @slow
      @require_torch
      def   lowerCamelCase_   (						self)	->			Dict:





        '''simple docstring'''





        a__:     List[Any]										=	pipeline('visual-question-answering'    ,			model='dandelin/vilt-b32-finetuned-vqa')
        a__:     Optional[int]										=	'./tests/fixtures/tests_samples/COCO/000000039769.png'
        a__:     Dict										=	'How many cats are there?'

        a__:     List[Any]										=	vqa_pipeline(image=lowercase    ,			question=lowercase    ,			top_k=2)
        self.assertEqual(
            nested_simplify(lowercase    ,			decimals=4)    ,			[{'score': 0.8799, 'answer': '2'}, {'score': 0.296, 'answer': '1'}])

        a__:     Tuple										=	vqa_pipeline({'image': image, 'question': question}    ,			top_k=2)
        self.assertEqual(
            nested_simplify(lowercase    ,			decimals=4)    ,			[{'score': 0.8799, 'answer': '2'}, {'score': 0.296, 'answer': '1'}])

        a__:     Tuple										=	vqa_pipeline(
            [{'image': image, 'question': question}, {'image': image, 'question': question}]    ,			top_k=2)
        self.assertEqual(
            nested_simplify(lowercase    ,			decimals=4)    ,			[[{'score': 0.8799, 'answer': '2'}, {'score': 0.296, 'answer': '1'}]] * 2    ,			)



      @require_tf
      @unittest.skip('Visual question answering not implemented in TF')
      def   lowerCamelCase_   (						self)	->			Optional[Any]:





        '''simple docstring'''





        pass



"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import _LazyModule


lowercase__					       =	{'processing_wav2vec2_with_lm': ['Wav2Vec2ProcessorWithLM']}


if TYPE_CHECKING:
 from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
 import sys

 lowercase__					       =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


