






class 	SCREAMING_SNAKE_CASE	:




       def __init__(					self      : Any					):


            """simple docstring"""







            __lowerCamelCase						:       dict[str, TrieNode]				   =				{}  # Mapping from char to TrieNode
            __lowerCamelCase						:       Union[str, Any]				   =				False




       def 					a_					(					self      : Union[str, Any]	,    A__      : list[str]					):


            """simple docstring"""







            for word in words:
                 self.insert(A__					)




       def 					a_					(					self      : Optional[int]	,    A__      : str					):


            """simple docstring"""







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




       def 					a_					(					self      : List[str]	,    A__      : str					):


            """simple docstring"""







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




       def 					a_					(					self      : Optional[int]	,    A__      : str					):


            """simple docstring"""







            def _delete(A__      : TrieNode	,    A__      : str	,    A__      : int					) -> bool:
                 if index == len(A__					):
                      # If word does not exist
                      if not curr.is_leaf:
                           return False
                      __lowerCamelCase						:       int				   =				False
                      return len(curr.nodes					) == 0
                 __lowerCamelCase						:       Dict				   =				word[index]
                 __lowerCamelCase						:       Optional[Any]				   =				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
                 __lowerCamelCase						:       Union[str, Any]				   =				_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  (_lowercase,						_lowercase     )   ->     None:


     """simple docstring"""
     if node.is_leaf:
          print(_lowercase,						end=""" """     )

     for key, value in node.nodes.items():
          print_words(_lowercase,						word + key     )
def     __lowercase  ()   ->     bool:


     """simple docstring"""
     __lowerCamelCase						:       Tuple				   =				"""banana bananas bandana band apple all beast""".split()
     __lowerCamelCase						:       Tuple				   =				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     __lowercase  (_lowercase,						_lowercase     )   ->     None:


     """simple docstring"""
     print(str(_lowercase     ),						"""works!""" if passes else """doesn't work :("""     )
def     __lowercase  ()   ->     None:


     """simple docstring"""
     assert test_trie()
def     __lowercase  ()   ->     None:


     """simple docstring"""
     print_results("""Testing trie functionality""",						test_trie()     )


if __name__ == "__main__":
   main()











'''simple docstring'''

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 	SCREAMING_SNAKE_CASE	(      unittest.TestCase  ):




       def 					a_					(					self      : str					):


            """simple docstring"""







            __lowerCamelCase						:       Any				   =				"""laion/clap-htsat-unfused"""
            __lowerCamelCase						:       List[Any]				   =				tempfile.mkdtemp()




       def 					a_					(					self      : Optional[int]	,    **A__      : Union[str, Any]					):


            """simple docstring"""







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




       def 					a_					(					self      : str	,    **A__      : Any					):


            """simple docstring"""







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




       def 					a_					(					self      : List[str]					):


            """simple docstring"""







            shutil.rmtree(self.tmpdirname					)




       def 					a_					(					self      : str					):


            """simple docstring"""







            __lowerCamelCase						:       Dict				   =				self.get_tokenizer()
            __lowerCamelCase						:       Union[str, Any]				   =				self.get_feature_extractor()

            __lowerCamelCase						:       Dict				   =				ClapProcessor(tokenizer=A__	,    feature_extractor=A__					)

            processor.save_pretrained(self.tmpdirname					)
            __lowerCamelCase						:       Optional[Any]				   =				ClapProcessor.from_pretrained(self.tmpdirname					)

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

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




       def 					a_					(					self      : str					):


            """simple docstring"""







            __lowerCamelCase						:       str				   =				ClapProcessor(tokenizer=self.get_tokenizer()	,    feature_extractor=self.get_feature_extractor()					)
            processor.save_pretrained(self.tmpdirname					)

            __lowerCamelCase						:       Tuple				   =				self.get_tokenizer(bos_token="""(BOS)"""	,    eos_token="""(EOS)"""					)
            __lowerCamelCase						:       Any				   =				self.get_feature_extractor(do_normalize=A__	,    padding_value=1.0					)

            __lowerCamelCase						:       List[Any]				   =				ClapProcessor.from_pretrained(
                self.tmpdirname	,    bos_token="""(BOS)"""	,    eos_token="""(EOS)"""	,    do_normalize=A__	,    padding_value=1.0					)

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

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




       def 					a_					(					self      : Optional[int]					):


            """simple docstring"""







            __lowerCamelCase						:       Dict				   =				self.get_feature_extractor()
            __lowerCamelCase						:       Tuple				   =				self.get_tokenizer()

            __lowerCamelCase						:       Optional[int]				   =				ClapProcessor(tokenizer=A__	,    feature_extractor=A__					)

            __lowerCamelCase						:       Dict				   =				floats_list((3, 1000)					)

            __lowerCamelCase						:       str				   =				feature_extractor(A__	,    return_tensors="""np"""					)
            __lowerCamelCase						:       Any				   =				processor(audios=A__	,    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 					a_					(					self      : Any					):


            """simple docstring"""







            __lowerCamelCase						:       Optional[Any]				   =				self.get_feature_extractor()
            __lowerCamelCase						:       int				   =				self.get_tokenizer()

            __lowerCamelCase						:       str				   =				ClapProcessor(tokenizer=A__	,    feature_extractor=A__					)

            __lowerCamelCase						:       int				   =				"""This is a test string"""

            __lowerCamelCase						:       Any				   =				processor(text=A__					)

            __lowerCamelCase						:       Any				   =				tokenizer(A__					)

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




       def 					a_					(					self      : List[Any]					):


            """simple docstring"""







            __lowerCamelCase						:       Optional[int]				   =				self.get_feature_extractor()
            __lowerCamelCase						:       List[str]				   =				self.get_tokenizer()

            __lowerCamelCase						:       int				   =				ClapProcessor(tokenizer=A__	,    feature_extractor=A__					)

            __lowerCamelCase						:       Union[str, Any]				   =				[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

            __lowerCamelCase						:       int				   =				processor.batch_decode(A__					)
            __lowerCamelCase						:       List[Any]				   =				tokenizer.batch_decode(A__					)

            self.assertListEqual(A__	,    A__					)




       def 					a_					(					self      : str					):


            """simple docstring"""







            __lowerCamelCase						:       Any				   =				self.get_feature_extractor()
            __lowerCamelCase						:       List[Any]				   =				self.get_tokenizer()

            __lowerCamelCase						:       Any				   =				ClapProcessor(tokenizer=A__	,    feature_extractor=A__					)

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



