






"""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							):





       """simple docstring"""





       def  lowercase		(   self:     List[Any]    ):

            '''simple docstring'''

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




       def  lowercase		(   self:     Optional[Any]				,		**__A:     Dict    ):

            '''simple docstring'''

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




       def  lowercase		(   self:     Tuple				,		**__A:     Dict    ):

            '''simple docstring'''

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




       def  lowercase		(   self:     Tuple    ):

            '''simple docstring'''

            shutil.rmtree(self.tmpdirname    )




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

            '''simple docstring'''

            a__          =  self.get_tokenizer()
            a__          =  self.get_feature_extractor()

            a__          =  ClapProcessor(tokenizer=__lowerCamelCase				,		feature_extractor=__lowerCamelCase    )

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

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

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




       def  lowercase		(   self:     Any    ):

            '''simple docstring'''

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

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

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

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

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




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

            '''simple docstring'''

            a__          =  self.get_feature_extractor()
            a__          =  self.get_tokenizer()

            a__          =  ClapProcessor(tokenizer=__lowerCamelCase				,		feature_extractor=__lowerCamelCase    )

            a__          =  floats_list((3, 1000)    )

            a__          =  feature_extractor(__lowerCamelCase				,		return_tensors='''np'''    )
            a__          =  processor(audios=__lowerCamelCase				,		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  lowercase		(   self:     Union[str, Any]    ):

            '''simple docstring'''

            a__          =  self.get_feature_extractor()
            a__          =  self.get_tokenizer()

            a__          =  ClapProcessor(tokenizer=__lowerCamelCase				,		feature_extractor=__lowerCamelCase    )

            a__          =  '''This is a test string'''

            a__          =  processor(text=__lowerCamelCase    )

            a__          =  tokenizer(__lowerCamelCase    )

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




       def  lowercase		(   self:     Optional[int]    ):

            '''simple docstring'''

            a__          =  self.get_feature_extractor()
            a__          =  self.get_tokenizer()

            a__          =  ClapProcessor(tokenizer=__lowerCamelCase				,		feature_extractor=__lowerCamelCase    )

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

            a__          =  processor.batch_decode(__lowerCamelCase    )
            a__          =  tokenizer.batch_decode(__lowerCamelCase    )

            self.assertListEqual(__lowerCamelCase				,		__lowerCamelCase    )





       def  lowercase		(   self:     Optional[Any]    ):

            '''simple docstring'''

            a__          =  self.get_feature_extractor()
            a__          =  self.get_tokenizer()

            a__          =  ClapProcessor(tokenizer=__lowerCamelCase				,		feature_extractor=__lowerCamelCase    )

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










"""simple docstring"""







class        _SCREAMING_SNAKE_CASE						:





							"""simple docstring"""





							def __init__(   self:     Any    ):

												'''simple docstring'''

												a__          =  {}




							def  lowercase		(   self:     Optional[int]    ):

												'''simple docstring'''

												print(self.vertex    )
												for i in self.vertex:
																	print(__A				,		''' -> '''				,		''' -> '''.join([str(__A    ) for j in self.vertex[i]]    )    )




							def  lowercase		(   self:     Union[str, Any]				,		__A:     int				,		__A:     int    ):

												'''simple docstring'''

												if from_vertex in self.vertex:
																	self.vertex[from_vertex].append(__A    )
												else:
																	# else make a new vertex
																	a__          =  [to_vertex]




							def  lowercase		(   self:     Dict    ):

												'''simple docstring'''

												a__          =  [False] * len(self.vertex    )

												# call the recursive helper function
												for i in range(len(self.vertex    )    ):
																	if not visited[i]:
																						self.dfs_recursive(__A				,		__A    )





							def  lowercase		(   self:     Optional[int]				,		__A:     int				,		__A:     list    ):

												'''simple docstring'''

												a__          =  True

												print(__A				,		end=''' '''    )

												# Recur for all the vertices that are adjacent to this node
												for i in self.vertex:
																	if not visited[i]:
																						self.dfs_recursive(__A				,		__A    )


if __name__ == "__main__":
	__a       :	Any             = Graph()
	g.add_edge(0, 1)
	g.add_edge(0, 2)
	g.add_edge(1, 2)
	g.add_edge(2, 0)
	g.add_edge(2, 3)
	g.add_edge(3, 3)

	g.print_graph()
	print('DFS:')
	g.dfs()

	# OUTPUT:
	# 0  ->  1 -> 2
	# 1  ->  2
	# 2  ->  0 -> 3
	# 3  ->  3
	# DFS:
	#  0 1 2 3


