






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 						lowerCAmelCase   (       unittest.TestCase	):

					'''simple docstring'''

					def 					lowerCAmelCase (     self :		Optional[Any]							)	->     List[str]:


												"""simple docstring"""

												__lowercase					:							int			=   """laion/clap-htsat-unfused"""
												__lowercase					:							int			=   tempfile.mkdtemp()



					def 					lowerCAmelCase (     self :		Dict						,   **__a :		int							)	->     Union[str, Any]:


												"""simple docstring"""

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



					def 					lowerCAmelCase (     self :		List[Any]						,   **__a :		Optional[int]							)	->     str:


												"""simple docstring"""

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



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


												"""simple docstring"""

												shutil.rmtree(self.tmpdirname							)



					def 					lowerCAmelCase (     self :		Optional[int]							)	->     Any:


												"""simple docstring"""

												__lowercase					:							Optional[Any]			=   self.get_tokenizer()
												__lowercase					:							str			=   self.get_feature_extractor()

												__lowercase					:							List[Any]			=   ClapProcessor(tokenizer=__a						,   feature_extractor=__a							)

												processor.save_pretrained(self.tmpdirname							)
												__lowercase					:							Union[str, 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 					lowerCAmelCase (     self :		Union[str, Any]							)	->     str:


												"""simple docstring"""

												__lowercase					:							Optional[Any]			=   ClapProcessor(tokenizer=self.get_tokenizer()						,   feature_extractor=self.get_feature_extractor()							)
												processor.save_pretrained(self.tmpdirname							)

												__lowercase					:							str			=   self.get_tokenizer(bos_token="""(BOS)"""						,   eos_token="""(EOS)"""							)
												__lowercase					:							List[Any]			=   self.get_feature_extractor(do_normalize=__a						,   padding_value=1.0							)

												__lowercase					:							List[str]			=   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 					lowerCAmelCase (     self :		Any							)	->     List[str]:


												"""simple docstring"""

												__lowercase					:							Tuple			=   self.get_feature_extractor()
												__lowercase					:							Optional[int]			=   self.get_tokenizer()

												__lowercase					:							Union[str, Any]			=   ClapProcessor(tokenizer=__a						,   feature_extractor=__a							)

												__lowercase					:							Optional[Any]			=   floats_list((3, 1000)							)

												__lowercase					:							Any			=   feature_extractor(__a						,   return_tensors="""np"""							)
												__lowercase					:							List[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 					lowerCAmelCase (     self :		Union[str, Any]							)	->     Tuple:


												"""simple docstring"""

												__lowercase					:							str			=   self.get_feature_extractor()
												__lowercase					:							Tuple			=   self.get_tokenizer()

												__lowercase					:							Union[str, Any]			=   ClapProcessor(tokenizer=__a						,   feature_extractor=__a							)

												__lowercase					:							Dict			=   """This is a test string"""

												__lowercase					:							Union[str, Any]			=   processor(text=__a							)

												__lowercase					:							List[Any]			=   tokenizer(__a							)

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



					def 					lowerCAmelCase (     self :		Optional[Any]							)	->     Dict:


												"""simple docstring"""

												__lowercase					:							Tuple			=   self.get_feature_extractor()
												__lowercase					:							Tuple			=   self.get_tokenizer()

												__lowercase					:							Union[str, Any]			=   ClapProcessor(tokenizer=__a						,   feature_extractor=__a							)

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

												__lowercase					:							Optional[Any]			=   processor.batch_decode(__a							)
												__lowercase					:							str			=   tokenizer.batch_decode(__a							)

												self.assertListEqual(__a						,   __a							)



					def 					lowerCAmelCase (     self :		Optional[int]							)	->     int:


												"""simple docstring"""

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

												__lowercase					:							Tuple			=   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"""						,   )







lowerCamelCase       :       Tuple        =				{'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []}
lowerCamelCase       :       int        =				['''a''', '''b''', '''c''', '''d''', '''e''']
def 					snake_case_						(   lowerCAmelCase_				:  Optional[int]				,				lowerCAmelCase_				:  str				,				lowerCAmelCase_				:  List[Any]					):
							__lowercase					:							Dict			=   start
							# add current to visited
							visited.append(lowerCAmelCase_					)
							__lowercase					:							Dict			=   edges[current]
							for neighbor in neighbors:
														# if neighbor not in visited, visit
														if neighbor not in visited:
																					__lowercase					:							List[Any]			=   topological_sort(lowerCAmelCase_				,				lowerCAmelCase_				,				lowerCAmelCase_					)
    # if all neighbors visited add current to sort
							sort.append(lowerCAmelCase_					)
							# if all vertices haven't been visited select a new one to visit
							if len(lowerCAmelCase_					) != len(lowerCAmelCase_					):
														for vertice in vertices:
																					if vertice not in visited:
																												__lowercase					:							Tuple			=   topological_sort(lowerCAmelCase_				,				lowerCAmelCase_				,				lowerCAmelCase_					)
    # return sort
							return sort


if __name__ == "__main__":
	lowerCamelCase       :       Any        =				topological_sort('''a''', [], [])
	print(sort)