'''simple docstring'''

import unittest

from huggingface_hub import hf_hub_download

from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_decord,
    require_tf,
    require_torch,
    require_torch_or_tf,
    require_vision,
)

from .test_pipelines_common import ANY



@is_pipeline_test
@require_torch_or_tf
@require_vision
@require_decord
class      UpperCAmelCase    (		unittest.TestCase   ):





       '''simple docstring'''



       SCREAMING_SNAKE_CASE   						=       MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING

       def _lowerCAmelCase(		self      ,  __lowerCAmelCase      ,  __lowerCAmelCase      ,  __lowerCAmelCase					)    ->    int:
        lowercase__							:       Optional[Any]										=   hf_hub_download(
            repo_id='''nateraw/video-demo'''      ,  filename='''archery.mp4'''      ,  repo_type='''dataset'''					)
        lowercase__							:       List[str]										=   VideoClassificationPipeline(model=__lowerCamelCase      ,  image_processor=__lowerCamelCase      ,  top_k=2					)
        lowercase__							:       List[Any]										=   [
            example_video_filepath,
            '''https://huggingface.co/datasets/nateraw/video-demo/resolve/main/archery.mp4''',
        ]
        return video_classifier, examples

       def _lowerCAmelCase(		self      ,  __lowerCAmelCase      ,  __lowerCAmelCase					)    ->    List[Any]:
        for example in examples:
         lowercase__							:       Any										=   video_classifier(__lowerCamelCase					)

         self.assertEqual(
             __lowerCamelCase      ,  [
                 {'''score''': ANY(__lowerCamelCase					), '''label''': ANY(__lowerCamelCase					)},
                 {'''score''': ANY(__lowerCamelCase					), '''label''': ANY(__lowerCamelCase					)},
             ]      ,  )

       @require_torch
       def _lowerCAmelCase(		self					)    ->    Dict:
        lowercase__							:       Tuple										=   '''hf-internal-testing/tiny-random-VideoMAEForVideoClassification'''
        lowercase__							:       Optional[int]										=   VideoMAEFeatureExtractor(
            size={'''shortest_edge''': 10}      ,  crop_size={'''height''': 10, '''width''': 10}					)
        lowercase__							:       Dict										=   pipeline(
            '''video-classification'''      ,  model=__lowerCamelCase      ,  feature_extractor=__lowerCamelCase      ,  frame_sampling_rate=4					)

        lowercase__							:       Dict										=   hf_hub_download(repo_id='''nateraw/video-demo'''      ,  filename='''archery.mp4'''      ,  repo_type='''dataset'''					)
        lowercase__							:       Tuple										=   video_classifier(__lowerCamelCase      ,  top_k=2					)
        self.assertEqual(
            nested_simplify(__lowerCamelCase      ,  decimals=4					)      ,  [{'''score''': 0.5_1_9_9, '''label''': '''LABEL_0'''}, {'''score''': 0.4_8_0_1, '''label''': '''LABEL_1'''}]      ,  )

        lowercase__							:       Union[str, Any]										=   video_classifier(
            [
                video_file_path,
                video_file_path,
            ]      ,  top_k=2      ,  )
        self.assertEqual(
            nested_simplify(__lowerCamelCase      ,  decimals=4					)      ,  [
                [{'''score''': 0.5_1_9_9, '''label''': '''LABEL_0'''}, {'''score''': 0.4_8_0_1, '''label''': '''LABEL_1'''}],
                [{'''score''': 0.5_1_9_9, '''label''': '''LABEL_0'''}, {'''score''': 0.4_8_0_1, '''label''': '''LABEL_1'''}],
            ]      ,  )


       @require_tf
       def _lowerCAmelCase(		self					)    ->    Union[str, Any]:
        pass








import pytest

import datasets


# Import fixture modules as plugins
a__: Dict							   =						['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']


def       UpperCamelCase__(			UpperCamelCase__     :			List[Any]					,	UpperCamelCase__     :			Tuple    )->List[str]:
       # Mark tests as "unit" by default if not marked as "integration" (or already marked as "unit")
       for item in items:
              if any(marker in item.keywords for marker in ['''integration''', '''unit''']    ):
                     continue
              item.add_marker(pytest.mark.unit    )


def       UpperCamelCase__(			UpperCamelCase__     :			Dict    )->List[Any]:
       config.addinivalue_line('''markers'''					,	'''torchaudio_latest: mark test to run with torchaudio>=0.12'''    )


@pytest.fixture(autouse=UpperCamelCase__    )
def       UpperCamelCase__(			UpperCamelCase__     :			Optional[int]					,	UpperCamelCase__     :			int    )->Union[str, Any]:
       # test_hf_cache_home = tmp_path_factory.mktemp("cache")  # TODO: why a cache dir per test function does not work?
       A__		   =		tmp_path_factory.getbasetemp() / '''cache'''
       A__		   =		test_hf_cache_home / '''datasets'''
       A__		   =		test_hf_cache_home / '''metrics'''
       A__		   =		test_hf_cache_home / '''modules'''
       monkeypatch.setattr('''datasets.config.HF_DATASETS_CACHE'''					,	str(UpperCamelCase__    )    )
       monkeypatch.setattr('''datasets.config.HF_METRICS_CACHE'''					,	str(UpperCamelCase__    )    )
       monkeypatch.setattr('''datasets.config.HF_MODULES_CACHE'''					,	str(UpperCamelCase__    )    )
       A__		   =		test_hf_datasets_cache / '''downloads'''
       monkeypatch.setattr('''datasets.config.DOWNLOADED_DATASETS_PATH'''					,	str(UpperCamelCase__    )    )
       A__		   =		test_hf_datasets_cache / '''downloads''' / '''extracted'''
       monkeypatch.setattr('''datasets.config.EXTRACTED_DATASETS_PATH'''					,	str(UpperCamelCase__    )    )


@pytest.fixture(autouse=UpperCamelCase__					,	scope='''session'''    )
def       UpperCamelCase__(			)->int:
       datasets.disable_progress_bar()


@pytest.fixture(autouse=UpperCamelCase__    )
def       UpperCamelCase__(			UpperCamelCase__     :			str    )->Tuple:
       # don't take tests into account when counting downloads
       monkeypatch.setattr('''datasets.config.HF_UPDATE_DOWNLOAD_COUNTS'''					,	UpperCamelCase__    )


@pytest.fixture
def       UpperCamelCase__(			UpperCamelCase__     :			List[Any]    )->Optional[Any]:
       # Required to suppress RemovedIn20Warning when feature(s) are not compatible with SQLAlchemy 2.0
       # To be removed once SQLAlchemy 2.0 supported
       monkeypatch.setattr('''sqlalchemy.util.deprecations.SILENCE_UBER_WARNING'''					,	UpperCamelCase__    )





