


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 	lowerCamelCase_       (    self				:		str    ):







						"""simple docstring"""







						UpperCamelCase								=       """laion/clap-htsat-unfused"""
						UpperCamelCase								=       tempfile.mkdtemp()




			def 	lowerCamelCase_       (    self				:		int							,							**__magic_name__				:		Optional[int]    ):







						"""simple docstring"""







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




			def 	lowerCamelCase_       (    self				:		List[Any]							,							**__magic_name__				:		Any    ):







						"""simple docstring"""







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




			def 	lowerCamelCase_       (    self				:		int    ):







						"""simple docstring"""







						shutil.rmtree(self.tmpdirname    )




			def 	lowerCamelCase_       (    self				:		int    ):







						"""simple docstring"""







						UpperCamelCase								=       self.get_tokenizer()
						UpperCamelCase								=       self.get_feature_extractor()

						UpperCamelCase								=       ClapProcessor(tokenizer=__snake_case							,							feature_extractor=__snake_case    )

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

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

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




			def 	lowerCamelCase_       (    self				:		Dict    ):







						"""simple docstring"""







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

						UpperCamelCase								=       self.get_tokenizer(bos_token="""(BOS)"""							,							eos_token="""(EOS)"""    )
						UpperCamelCase								=       self.get_feature_extractor(do_normalize=__snake_case							,							padding_value=1.0    )

						UpperCamelCase								=       ClapProcessor.from_pretrained(
						    self.tmpdirname							,							bos_token="""(BOS)"""							,							eos_token="""(EOS)"""							,							do_normalize=__snake_case							,							padding_value=1.0    )

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

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




			def 	lowerCamelCase_       (    self				:		Optional[int]    ):







						"""simple docstring"""







						UpperCamelCase								=       self.get_feature_extractor()
						UpperCamelCase								=       self.get_tokenizer()

						UpperCamelCase								=       ClapProcessor(tokenizer=__snake_case							,							feature_extractor=__snake_case    )

						UpperCamelCase								=       floats_list((3, 1_0_0_0)    )

						UpperCamelCase								=       feature_extractor(__snake_case							,							return_tensors="""np"""    )
						UpperCamelCase								=       processor(audios=__snake_case							,							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				:		Tuple    ):







						"""simple docstring"""







						UpperCamelCase								=       self.get_feature_extractor()
						UpperCamelCase								=       self.get_tokenizer()

						UpperCamelCase								=       ClapProcessor(tokenizer=__snake_case							,							feature_extractor=__snake_case    )

						UpperCamelCase								=       """This is a test string"""

						UpperCamelCase								=       processor(text=__snake_case    )

						UpperCamelCase								=       tokenizer(__snake_case    )

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




			def 	lowerCamelCase_       (    self				:		Optional[int]    ):







						"""simple docstring"""







						UpperCamelCase								=       self.get_feature_extractor()
						UpperCamelCase								=       self.get_tokenizer()

						UpperCamelCase								=       ClapProcessor(tokenizer=__snake_case							,							feature_extractor=__snake_case    )

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

						UpperCamelCase								=       processor.batch_decode(__snake_case    )
						UpperCamelCase								=       tokenizer.batch_decode(__snake_case    )

						self.assertListEqual(__snake_case							,							__snake_case    )





			def 	lowerCamelCase_       (    self				:		List[str]    ):







						"""simple docstring"""







						UpperCamelCase								=       self.get_feature_extractor()
						UpperCamelCase								=       self.get_tokenizer()

						UpperCamelCase								=       ClapProcessor(tokenizer=__snake_case							,							feature_extractor=__snake_case    )

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











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 						__UpperCAmelCase     (							self ):



       """simple docstring"""





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


  def 						__UpperCAmelCase     (							self ,**__snake_case ):



       """simple docstring"""





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


  def 						__UpperCAmelCase     (							self ,**__snake_case ):



       """simple docstring"""





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


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       shutil.rmtree(self.tmpdirname )


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       self.get_tokenizer()
       A_          =       self.get_feature_extractor()

       A_          =       ClapProcessor(tokenizer=__snake_case ,feature_extractor=__snake_case )

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

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

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


  def 						__UpperCAmelCase     (							self ):



       """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=__snake_case ,padding_value=1.0 )

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

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

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


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       self.get_feature_extractor()
       A_          =       self.get_tokenizer()

       A_          =       ClapProcessor(tokenizer=__snake_case ,feature_extractor=__snake_case )

       A_          =       floats_list((3, 1_0_0_0) )

       A_          =       feature_extractor(__snake_case ,return_tensors='''np''' )
       A_          =       processor(audios=__snake_case ,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 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       self.get_feature_extractor()
       A_          =       self.get_tokenizer()

       A_          =       ClapProcessor(tokenizer=__snake_case ,feature_extractor=__snake_case )

       A_          =       '''This is a test string'''

       A_          =       processor(text=__snake_case )

       A_          =       tokenizer(__snake_case )

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


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       self.get_feature_extractor()
       A_          =       self.get_tokenizer()

       A_          =       ClapProcessor(tokenizer=__snake_case ,feature_extractor=__snake_case )

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

       A_          =       processor.batch_decode(__snake_case )
       A_          =       tokenizer.batch_decode(__snake_case )

       self.assertListEqual(__snake_case ,__snake_case )




  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       self.get_feature_extractor()
       A_          =       self.get_tokenizer()

       A_          =       ClapProcessor(tokenizer=__snake_case ,feature_extractor=__snake_case )

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



