





"""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 		__snake_case (		unittest.TestCase					):





 """simple docstring"""


 _lowerCamelCase				=					MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING

 def  UpperCamelCase__(   self ,						__lowerCamelCase ,						__lowerCamelCase ,						__lowerCamelCase  ):



     '''simple docstring'''




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

 def  UpperCamelCase__(   self ,						__lowerCamelCase ,						__lowerCamelCase  ):



     '''simple docstring'''




     for example in examples:
         __A   :						List[Any]									=					video_classifier(__lowerCamelCase  )

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

 @require_torch
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Union[str, Any]									=					'''hf-internal-testing/tiny-random-VideoMAEForVideoClassification'''
     __A   :						Optional[Any]									=					VideoMAEFeatureExtractor(
         size={'''shortest_edge''': 10} ,						crop_size={'''height''': 10, '''width''': 10}  )
     __A   :						Optional[Any]									=					pipeline(
         '''video-classification''' ,						model=__lowerCamelCase ,						feature_extractor=__lowerCamelCase ,						frame_sampling_rate=4  )

     __A   :						Dict									=					hf_hub_download(repo_id='''nateraw/video-demo''' ,						filename='''archery.mp4''' ,						repo_type='''dataset'''  )
     __A   :						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'''}] ,						)

     __A   :						Optional[int]									=					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  UpperCamelCase__(   self  ):



     '''simple docstring'''




     pass











"""simple docstring"""



def 		__lowercase					(       )       ->Tuple:



    '''simple docstring'''







    __A   :						str									=					[]
    __A   :						List[Any]									=					1

    while len(snake_case_						) < 1e6:
        constant.append(str(snake_case_						)						)
        i += 1

    __A   :						Any									=					''''''.join(snake_case_						)

    return (
        int(constant[0]						)
        * int(constant[9]						)
        * int(constant[99]						)
        * int(constant[999]						)
        * int(constant[9999]						)
        * int(constant[99999]						)
        * int(constant[999999]						)
    )


if __name__ == "__main__":
       print(solution())




