





import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch


if is_vision_available():
	from transformers import TvltImageProcessor

if is_speech_available():
	from transformers import TvltFeatureExtractor

from transformers import TvltProcessor




@require_torch
class 	UpperCamelCase_							(  unittest.TestCase     ):


							def   _snake_case	(				self     :Dict		) -> List[Any]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   """ZinengTang/tvlt-base"""
									SCREAMING_SNAKE_CASE__								=   tempfile.mkdtemp()


							def   _snake_case	(				self     :Optional[int]				,					**__A     :List[str]		) -> Union[str, Any]:



									"""simple docstring"""



									return TvltImageProcessor.from_pretrained(self.checkpoint				,					**__A		)


							def   _snake_case	(				self     :Dict				,					**__A     :Union[str, Any]		) -> str:



									"""simple docstring"""



									return TvltFeatureExtractor.from_pretrained(self.checkpoint				,					**__A		)


							def   _snake_case	(				self     :List[Any]		) -> List[Any]:



									"""simple docstring"""



									shutil.rmtree(self.tmpdirname		)


							def   _snake_case	(				self     :Tuple		) -> Optional[int]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   self.get_image_processor()
									SCREAMING_SNAKE_CASE__								=   self.get_feature_extractor()

									SCREAMING_SNAKE_CASE__								=   TvltProcessor(image_processor=__A				,					feature_extractor=__A		)
									processor.save_pretrained(self.tmpdirname		)
									SCREAMING_SNAKE_CASE__								=   TvltProcessor.from_pretrained(self.tmpdirname		)

									self.assertIsInstance(processor.feature_extractor				,					__A		)
									self.assertIsInstance(processor.image_processor				,					__A		)


							def   _snake_case	(				self     :List[Any]		) -> Dict:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   self.get_image_processor()
									SCREAMING_SNAKE_CASE__								=   self.get_feature_extractor()

									SCREAMING_SNAKE_CASE__								=   TvltProcessor(image_processor=__A				,					feature_extractor=__A		)

									SCREAMING_SNAKE_CASE__								=   np.ones([1_2000]		)

									SCREAMING_SNAKE_CASE__								=   feature_extractor(__A				,					return_tensors="""np"""		)
									SCREAMING_SNAKE_CASE__								=   processor(audio=__A				,					return_tensors="""np"""		)

									for key in audio_dict.keys():
											self.assertAlmostEqual(audio_dict[key].sum()				,					input_processor[key].sum()				,					delta=1E-2		)


							def   _snake_case	(				self     :Dict		) -> int:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   self.get_image_processor()
									SCREAMING_SNAKE_CASE__								=   self.get_feature_extractor()

									SCREAMING_SNAKE_CASE__								=   TvltProcessor(image_processor=__A				,					feature_extractor=__A		)

									SCREAMING_SNAKE_CASE__								=   np.ones([3, 224, 224]		)

									SCREAMING_SNAKE_CASE__								=   image_processor(__A				,					return_tensors="""np"""		)
									SCREAMING_SNAKE_CASE__								=   processor(images=__A				,					return_tensors="""np"""		)

									for key in image_dict.keys():
											self.assertAlmostEqual(image_dict[key].sum()				,					input_processor[key].sum()				,					delta=1E-2		)


							def   _snake_case	(				self     :Tuple		) -> int:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   self.get_image_processor()
									SCREAMING_SNAKE_CASE__								=   self.get_feature_extractor()

									SCREAMING_SNAKE_CASE__								=   TvltProcessor(image_processor=__A				,					feature_extractor=__A		)

									SCREAMING_SNAKE_CASE__								=   np.ones([1_2000]		)
									SCREAMING_SNAKE_CASE__								=   np.ones([3, 224, 224]		)

									SCREAMING_SNAKE_CASE__								=   processor(audio=__A				,					images=__A		)

									self.assertListEqual(list(inputs.keys()		)				,					["""audio_values""", """audio_mask""", """pixel_values""", """pixel_mask"""]		)

									# test if it raises when no input is passed
									with pytest.raises(__A		):
											processor()


							def   _snake_case	(				self     :Dict		) -> Optional[int]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   self.get_image_processor()
									SCREAMING_SNAKE_CASE__								=   self.get_feature_extractor()

									SCREAMING_SNAKE_CASE__								=   TvltProcessor(image_processor=__A				,					feature_extractor=__A		)

									self.assertListEqual(
									    processor.model_input_names				,					image_processor.model_input_names + feature_extractor.model_input_names				,					msg="""`processor` and `image_processor`+`feature_extractor` model input names do not match"""				,					)
class 					_lowercase    :






    '''simple docstring'''




    def __init__(    self ):
       lowerCAmelCase_:							dict[str, TrieNode]       =	{}  # Mapping from char to TrieNode
       lowerCAmelCase_:							str       =	False




    def      _a    (    self       ,						lowerCamelCase__ ):
       for word in words:
          self.insert(lowerCamelCase__ )




    def      _a    (    self       ,						lowerCamelCase__ ):
       lowerCAmelCase_:							Union[str, Any]       =	self
       for char in word:
          if char not in curr.nodes:
             lowerCAmelCase_:							List[Any]       =	TrieNode()
          lowerCAmelCase_:							Optional[Any]       =	curr.nodes[char]
       lowerCAmelCase_:							Dict       =	True




    def      _a    (    self       ,						lowerCamelCase__ ):
       lowerCAmelCase_:							Optional[Any]       =	self
       for char in word:
          if char not in curr.nodes:
             return False
          lowerCAmelCase_:							Dict       =	curr.nodes[char]
       return curr.is_leaf




    def      _a    (    self       ,						lowerCamelCase__ ):

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

       _delete(self       ,						lowerCamelCase__       ,						0 )





def 		snake_case__	(		lowercase							,				lowercase					):
   if node.is_leaf:
      print(lowercase							,				end=" "					)

   for key, value in node.nodes.items():
      print_words(lowercase							,				word + key					)
def 		snake_case__	(		):
   lowerCAmelCase_:							Any       =	"banana bananas bandana band apple all beast".split()
   lowerCAmelCase_:							Optional[Any]       =	TrieNode()
   root.insert_many(lowercase					)
   # print_words(root, "")
   assert all(root.find(lowercase					) 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 		snake_case__	(		lowercase							,				lowercase					):
   print(str(lowercase					)							,				"works!" if passes else "doesn't work :("					)
def 		snake_case__	(		):
   assert test_trie()
def 		snake_case__	(		):
   print_results("Testing trie functionality"							,				test_trie()					)


if __name__ == "__main__":
 main()