





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   A							(						unittest.TestCase    ):
      _snake_case				  =MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING



      def 						lowerCAmelCase__     (						self:    Tuple		,	_lowerCAmelCase:    Union[str, Any]		,	_lowerCAmelCase:    Optional[Any]		,	_lowerCAmelCase:    Any							)    ->     Optional[Any]:
         '''simple docstring'''

         UpperCAmelCase_           =hf_hub_download(
             repo_id="nateraw/video-demo"		,	filename="archery.mp4"		,	repo_type="dataset"							)
         UpperCAmelCase_           =VideoClassificationPipeline(model=_lowerCAmelCase		,	image_processor=_lowerCAmelCase		,	top_k=2							)
         UpperCAmelCase_           =[
             example_video_filepath,
             "https://huggingface.co/datasets/nateraw/video-demo/resolve/main/archery.mp4",
         ]
         return video_classifier, examples



      def 						lowerCAmelCase__     (						self:    Optional[int]		,	_lowerCAmelCase:    Union[str, Any]		,	_lowerCAmelCase:    int							)    ->     Any:
         '''simple docstring'''

         for example in examples:
            UpperCAmelCase_           =video_classifier(_lowerCAmelCase							)

            self.assertEqual(
                _lowerCAmelCase		,	[
                    {"score": ANY(_lowerCAmelCase							), "label": ANY(_lowerCAmelCase							)},
                    {"score": ANY(_lowerCAmelCase							), "label": ANY(_lowerCAmelCase							)},
                ]		,	)



      @require_torch
      def 						lowerCAmelCase__     (						self:    List[str]							)    ->     str:
         '''simple docstring'''

         UpperCAmelCase_           ="hf-internal-testing/tiny-random-VideoMAEForVideoClassification"
         UpperCAmelCase_           =VideoMAEFeatureExtractor(
             size={"shortest_edge": 10}		,	crop_size={"height": 10, "width": 10}							)
         UpperCAmelCase_           =pipeline(
             "video-classification"		,	model=_lowerCAmelCase		,	feature_extractor=_lowerCAmelCase		,	frame_sampling_rate=4							)

         UpperCAmelCase_           =hf_hub_download(repo_id="nateraw/video-demo"		,	filename="archery.mp4"		,	repo_type="dataset"							)
         UpperCAmelCase_           =video_classifier(_lowerCAmelCase		,	top_k=2							)
         self.assertEqual(
             nested_simplify(_lowerCAmelCase		,	decimals=4							)		,	[{"score": 0.51_99, "label": "LABEL_0"}, {"score": 0.48_01, "label": "LABEL_1"}]		,	)

         UpperCAmelCase_           =video_classifier(
             [
                 video_file_path,
                 video_file_path,
             ]		,	top_k=2		,	)
         self.assertEqual(
             nested_simplify(_lowerCAmelCase		,	decimals=4							)		,	[
                 [{"score": 0.51_99, "label": "LABEL_0"}, {"score": 0.48_01, "label": "LABEL_1"}],
                 [{"score": 0.51_99, "label": "LABEL_0"}, {"score": 0.48_01, "label": "LABEL_1"}],
             ]		,	)






      @require_tf
      def 						lowerCAmelCase__     (						self:    Optional[int]							)    ->     List[str]:
         '''simple docstring'''

         pass








'''simple docstring'''

from argparse import ArgumentParser

from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .run import RunCommand
from .serving import ServeCommand
from .user import UserCommands

def _SCREAMING_SNAKE_CASE ()			->			Dict:






       """simple docstring"""







       lowercase__      =					ArgumentParser('''Transformers CLI tool'''    ,					usage='''transformers-cli <command> [<args>]'''			)
       lowercase__      =					parser.add_subparsers(help='''transformers-cli command helpers'''			)

       # Register commands
       ConvertCommand.register_subcommand(A			)
       DownloadCommand.register_subcommand(A			)
       EnvironmentCommand.register_subcommand(A			)
       RunCommand.register_subcommand(A			)
       ServeCommand.register_subcommand(A			)
       UserCommands.register_subcommand(A			)
       AddNewModelCommand.register_subcommand(A			)
       AddNewModelLikeCommand.register_subcommand(A			)
       LfsCommands.register_subcommand(A			)
       PTtoTFCommand.register_subcommand(A			)

       # Let's go
       lowercase__      =					parser.parse_args()

       if not hasattr(A    ,					'''func'''			):
              parser.print_help()
              exit(1			)

       # Run
       lowercase__      =					args.func(A			)
       service.run()


if __name__ == "__main__":
 main()




