




class 							__UpperCamelCase			:





    '''simple docstring'''



    def __init__( self						):
           lowerCAmelCase   =		{}  # Mapping from char to TrieNode
           lowerCAmelCase   =		False



    def       __snake_case		( self       , UpperCAmelCase_						):
           for word in words:
                  self.insert(UpperCAmelCase_						)



    def       __snake_case		( self       , UpperCAmelCase_						):
           lowerCAmelCase   =		self
           for char in word:
                  if char not in curr.nodes:
                         lowerCAmelCase   =		TrieNode()
                  lowerCAmelCase   =		curr.nodes[char]
           lowerCAmelCase   =		True



    def       __snake_case		( self       , UpperCAmelCase_						):
           lowerCAmelCase   =		self
           for char in word:
                  if char not in curr.nodes:
                         return False
                  lowerCAmelCase   =		curr.nodes[char]
           return curr.is_leaf






    def       __snake_case		( self       , UpperCAmelCase_						):

           def _delete(UpperCAmelCase_       , UpperCAmelCase_       , UpperCAmelCase_						) -> bool:
                  if index == len(UpperCAmelCase_						):
                         # If word does not exist
                         if not curr.is_leaf:
                                return False
                         lowerCAmelCase   =		False
                         return len(curr.nodes						) == 0
                  lowerCAmelCase   =		word[index]
                  lowerCAmelCase   =		curr.nodes.get(UpperCAmelCase_						)
                  # If char not in current trie node
                  if not char_node:
                         return False
                  # Flag to check if node can be deleted
                  lowerCAmelCase   =		_delete(UpperCAmelCase_       , UpperCAmelCase_       , index + 1						)
                  if delete_curr:
                         del curr.nodes[char]
                         return len(curr.nodes						) == 0
                  return delete_curr

           _delete(self       , UpperCAmelCase_       , 0						)




def       UpperCAmelCase       (     _snake_case						, _snake_case							):
       if node.is_leaf:
              print(_snake_case						, end=''' '''							)

       for key, value in node.nodes.items():
              print_words(_snake_case						, word + key							)



def       UpperCAmelCase       (     ):
       lowerCAmelCase   =		'''banana bananas bandana band apple all beast'''.split()
       lowerCAmelCase   =		TrieNode()
       root.insert_many(_snake_case							)
       # print_words(root, "")
       assert all(root.find(_snake_case							) for word in words							)
       assert root.find('''banana'''							)
       assert not root.find('''bandanas'''							)
       assert not root.find('''apps'''							)
       assert root.find('''apple'''							)
       assert root.find('''all'''							)
       root.delete('''all'''							)
       assert not root.find('''all'''							)
       root.delete('''banana'''							)
       assert not root.find('''banana'''							)
       assert root.find('''bananas'''							)
       return True



def       UpperCAmelCase       (     _snake_case						, _snake_case							):
       print(str(_snake_case							)						, '''works!''' if passes else '''doesn\'t work :('''							)



def       UpperCAmelCase       (     ):
       assert test_trie()



def       UpperCAmelCase       (     ):
       print_results('''Testing trie functionality'''						, test_trie()							)


if __name__ == "__main__":
  main()









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'''



				__a							: str										=MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING



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



				def       __snake_case		( self       , UpperCAmelCase_       , UpperCAmelCase_						):
											for example in examples:
																		lowerCAmelCase   =		video_classifier(UpperCAmelCase_						)

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



				@require_torch
				def       __snake_case		( self						):
											lowerCAmelCase   =		'''hf-internal-testing/tiny-random-VideoMAEForVideoClassification'''
											lowerCAmelCase   =		VideoMAEFeatureExtractor(
											    size={'''shortest_edge''': 10}       , crop_size={'''height''': 10, '''width''': 10}						)
											lowerCAmelCase   =		pipeline(
											    '''video-classification'''       , model=UpperCAmelCase_       , feature_extractor=UpperCAmelCase_       , frame_sampling_rate=4						)

											lowerCAmelCase   =		hf_hub_download(repo_id='''nateraw/video-demo'''       , filename='''archery.mp4'''       , repo_type='''dataset'''						)
											lowerCAmelCase   =		video_classifier(UpperCAmelCase_       , top_k=2						)
											self.assertEqual(
											    nested_simplify(UpperCAmelCase_       , decimals=4						)       , [{'''score''': 0.5199, '''label''': '''LABEL_0'''}, {'''score''': 0.4801, '''label''': '''LABEL_1'''}]       , )

											lowerCAmelCase   =		video_classifier(
											    [
											        video_file_path,
											        video_file_path,
											    ]       , top_k=2       , )
											self.assertEqual(
											    nested_simplify(UpperCAmelCase_       , 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       __snake_case		( self						):
											pass



