





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

from ...utils import _LazyModule


__UpperCamelCase     :						Optional[Any]						       =  {'''processing_wav2vec2_with_lm''': ['''Wav2Vec2ProcessorWithLM''']}


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

       __UpperCamelCase     :						List[Any]						       =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)












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 							__SCREAMING_SNAKE_CASE       (  unittest.TestCase							):
							snake_case  :   List[str]      =							MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	,			__lowerCAmelCase	,			__lowerCAmelCase	):
														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	,			__lowerCAmelCase	,			__lowerCAmelCase	):
														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	):
														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""": 0.5199, """label""": """LABEL_0"""}, {"""score""": 0.4801, """label""": """LABEL_1"""}]	,			)

														UpperCamelCase__					  =      video_classifier(
														    [
														        video_file_path,
														        video_file_path,
														    ]	,			top_k=2	,			)
														self.assertEqual(
														    nested_simplify(__lowerCAmelCase	,			decimals=4	)	,			[
														        [{"""score""": 0.5199, """label""": """LABEL_0"""}, {"""score""": 0.4801, """label""": """LABEL_1"""}],
														        [{"""score""": 0.5199, """label""": """LABEL_0"""}, {"""score""": 0.4801, """label""": """LABEL_1"""}],
														    ]	,			)







							@require_tf
							def 					_lowerCamelCase		(    self	):
														pass




