

class 				__UpperCamelCase				:







	def __init__(   self: Dict      ):

						'''simple docstring'''





						__magic_name__							=    {}  # Mapping from char to TrieNode
						__magic_name__							=    False







	def 	_SCREAMING_SNAKE_CASE							(   self: List[Any]  , __UpperCamelCase: str      ):

						'''simple docstring'''





						for word in words:
											self.insert(_A      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[int]  , __UpperCamelCase: str      ):

						'''simple docstring'''





						__magic_name__							=    self
						for char in word:
											if char not in curr.nodes:
																__magic_name__							=    TrieNode()
											__magic_name__							=    curr.nodes[char]
						__magic_name__							=    True







	def 	_SCREAMING_SNAKE_CASE							(   self: int  , __UpperCamelCase: Tuple      ):

						'''simple docstring'''





						__magic_name__							=    self
						for char in word:
											if char not in curr.nodes:
																return False
											__magic_name__							=    curr.nodes[char]
						return curr.is_leaf







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]  , __UpperCamelCase: List[str]      ):

						'''simple docstring'''





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

						_delete(self  , _A  , 0      )




def 					_lowercase     (				a_				:					Tuple					,a_				:					Optional[Any]				)				->	Tuple:




					'''simple docstring'''







					if node.is_leaf:
										print(UpperCAmelCase__					,end=' '				)

					for key, value in node.nodes.items():
										print_words(UpperCAmelCase__					,word + key				)
def 					_lowercase     (				)				->	Union[str, Any]:




					'''simple docstring'''







					__magic_name__							=    'banana bananas bandana band apple all beast'.split()
					__magic_name__							=    TrieNode()
					root.insert_many(UpperCAmelCase__				)
					# print_words(root, "")
					assert all(root.find(UpperCAmelCase__				) 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 					_lowercase     (				a_				:					Any					,a_				:					int				)				->	List[Any]:




					'''simple docstring'''







					print(str(UpperCAmelCase__				)					,'works!' if passes else 'doesn\'t work :('				)
def 					_lowercase     (				)				->	Optional[Any]:




					'''simple docstring'''







					assert test_trie()
def 					_lowercase     (				)				->	Tuple:




					'''simple docstring'''







					print_results('Testing trie functionality'					,test_trie()				)


if __name__ == "__main__":
						main()







import shutil
import tempfile
import unittest

from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio

from .test_feature_extraction_clap import floats_list

@require_torchaudio
@require_sentencepiece
class 				__UpperCamelCase				(					unittest.TestCase			):







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]      ):

						'''simple docstring'''





						__magic_name__							=    'laion/clap-htsat-unfused'
						__magic_name__							=    tempfile.mkdtemp()







	def 	_SCREAMING_SNAKE_CASE							(   self: Union[str, Any]  , **__UpperCamelCase: List[Any]      ):

						'''simple docstring'''





						return RobertaTokenizer.from_pretrained(self.checkpoint  , **__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: int  , **__UpperCamelCase: Dict      ):

						'''simple docstring'''





						return ClapFeatureExtractor.from_pretrained(self.checkpoint  , **__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[int]      ):

						'''simple docstring'''





						shutil.rmtree(self.tmpdirname      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]      ):

						'''simple docstring'''





						__magic_name__							=    self.get_tokenizer()
						__magic_name__							=    self.get_feature_extractor()

						__magic_name__							=    ClapProcessor(tokenizer=__UpperCamelCase  , feature_extractor=__UpperCamelCase      )

						processor.save_pretrained(self.tmpdirname      )
						__magic_name__							=    ClapProcessor.from_pretrained(self.tmpdirname      )

						self.assertEqual(processor.tokenizer.get_vocab()  , tokenizer.get_vocab()      )
						self.assertIsInstance(processor.tokenizer  , __UpperCamelCase      )

						self.assertEqual(processor.feature_extractor.to_json_string()  , feature_extractor.to_json_string()      )
						self.assertIsInstance(processor.feature_extractor  , __UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Union[str, Any]      ):

						'''simple docstring'''





						__magic_name__							=    ClapProcessor(tokenizer=self.get_tokenizer()  , feature_extractor=self.get_feature_extractor()      )
						processor.save_pretrained(self.tmpdirname      )

						__magic_name__							=    self.get_tokenizer(bos_token='(BOS)'  , eos_token='(EOS)'      )
						__magic_name__							=    self.get_feature_extractor(do_normalize=__UpperCamelCase  , padding_value=1.0      )

						__magic_name__							=    ClapProcessor.from_pretrained(
						    self.tmpdirname  , bos_token='(BOS)'  , eos_token='(EOS)'  , do_normalize=__UpperCamelCase  , padding_value=1.0      )

						self.assertEqual(processor.tokenizer.get_vocab()  , tokenizer_add_kwargs.get_vocab()      )
						self.assertIsInstance(processor.tokenizer  , __UpperCamelCase      )

						self.assertEqual(processor.feature_extractor.to_json_string()  , feature_extractor_add_kwargs.to_json_string()      )
						self.assertIsInstance(processor.feature_extractor  , __UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: List[str]      ):

						'''simple docstring'''





						__magic_name__							=    self.get_feature_extractor()
						__magic_name__							=    self.get_tokenizer()

						__magic_name__							=    ClapProcessor(tokenizer=__UpperCamelCase  , feature_extractor=__UpperCamelCase      )

						__magic_name__							=    floats_list((3, 10_00)      )

						__magic_name__							=    feature_extractor(__UpperCamelCase  , return_tensors='np'      )
						__magic_name__							=    processor(audios=__UpperCamelCase  , return_tensors='np'      )

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







	def 	_SCREAMING_SNAKE_CASE							(   self: List[Any]      ):

						'''simple docstring'''





						__magic_name__							=    self.get_feature_extractor()
						__magic_name__							=    self.get_tokenizer()

						__magic_name__							=    ClapProcessor(tokenizer=__UpperCamelCase  , feature_extractor=__UpperCamelCase      )

						__magic_name__							=    'This is a test string'

						__magic_name__							=    processor(text=__UpperCamelCase      )

						__magic_name__							=    tokenizer(__UpperCamelCase      )

						for key in encoded_tok.keys():
											self.assertListEqual(encoded_tok[key]  , encoded_processor[key]      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]      ):

						'''simple docstring'''





						__magic_name__							=    self.get_feature_extractor()
						__magic_name__							=    self.get_tokenizer()

						__magic_name__							=    ClapProcessor(tokenizer=__UpperCamelCase  , feature_extractor=__UpperCamelCase      )

						__magic_name__							=    [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

						__magic_name__							=    processor.batch_decode(__UpperCamelCase      )
						__magic_name__							=    tokenizer.batch_decode(__UpperCamelCase      )

						self.assertListEqual(__UpperCamelCase  , __UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Any      ):

						'''simple docstring'''





						__magic_name__							=    self.get_feature_extractor()
						__magic_name__							=    self.get_tokenizer()

						__magic_name__							=    ClapProcessor(tokenizer=__UpperCamelCase  , feature_extractor=__UpperCamelCase      )

						self.assertListEqual(
						    processor.model_input_names[2:]  , feature_extractor.model_input_names  , msg='`processor` and `feature_extractor` model input names do not match'  , )




