




"""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 							lowercase_			(	unittest.TestCase				):



 '''simple docstring'''

 def      lowerCAmelCase_				(					self			:			int						):
       _A     =  'laion/clap-htsat-unfused'
       _A     =  tempfile.mkdtemp()

 def      lowerCAmelCase_				(					self			:			Dict       ,				**_UpperCAmelCase			:			List[str]						):
       return RobertaTokenizer.from_pretrained(self.checkpoint       ,				**_UpperCAmelCase						)

 def      lowerCAmelCase_				(					self			:			Optional[Any]       ,				**_UpperCAmelCase			:			str						):
       return ClapFeatureExtractor.from_pretrained(self.checkpoint       ,				**_UpperCAmelCase						)

 def      lowerCAmelCase_				(					self			:			Optional[int]						):
       shutil.rmtree(self.tmpdirname						)

 def      lowerCAmelCase_				(					self			:			Tuple						):
       _A     =  self.get_tokenizer()
       _A     =  self.get_feature_extractor()

       _A     =  ClapProcessor(tokenizer=_UpperCAmelCase       ,				feature_extractor=_UpperCAmelCase						)

       processor.save_pretrained(self.tmpdirname						)
       _A     =  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      lowerCAmelCase_				(					self			:			Union[str, Any]						):
       _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=_UpperCAmelCase       ,				padding_value=1.0						)

       _A     =  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      lowerCAmelCase_				(					self			:			Dict						):
       _A     =  self.get_feature_extractor()
       _A     =  self.get_tokenizer()

       _A     =  ClapProcessor(tokenizer=_UpperCAmelCase       ,				feature_extractor=_UpperCAmelCase						)

       _A     =  floats_list((3, 1_000)						)

       _A     =  feature_extractor(_UpperCAmelCase       ,				return_tensors='np'						)
       _A     =  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      lowerCAmelCase_				(					self			:			Any						):
       _A     =  self.get_feature_extractor()
       _A     =  self.get_tokenizer()

       _A     =  ClapProcessor(tokenizer=_UpperCAmelCase       ,				feature_extractor=_UpperCAmelCase						)

       _A     =  'This is a test string'

       _A     =  processor(text=_UpperCAmelCase						)

       _A     =  tokenizer(_UpperCAmelCase						)

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

 def      lowerCAmelCase_				(					self			:			Union[str, Any]						):
       _A     =  self.get_feature_extractor()
       _A     =  self.get_tokenizer()

       _A     =  ClapProcessor(tokenizer=_UpperCAmelCase       ,				feature_extractor=_UpperCAmelCase						)

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

       _A     =  processor.batch_decode(_UpperCAmelCase						)
       _A     =  tokenizer.batch_decode(_UpperCAmelCase						)

       self.assertListEqual(_UpperCAmelCase       ,				_UpperCAmelCase						)



 def      lowerCAmelCase_				(					self			:			Dict						):
       _A     =  self.get_feature_extractor()
       _A     =  self.get_tokenizer()

       _A     =  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'       ,				)





'''simple docstring'''






from typing import Any

import numpy as np





def lowerCamelCase__     (		__lowerCamelCase			:				np.ndarray				):







   '''simple docstring'''




   return np.array_equal(__lowerCamelCase			,       matrix.conjugate().T				)





def lowerCamelCase__     (		__lowerCamelCase			:				np.ndarray			,       __lowerCamelCase			:				np.ndarray				):







   '''simple docstring'''




   _UpperCAmelCase  :  str				       =v.conjugate().T
   _UpperCAmelCase  :  Optional[int]				       =v_star.dot(__lowerCamelCase				)
   assert isinstance(__lowerCamelCase			,       np.ndarray				)
   return (v_star_dot.dot(__lowerCamelCase				)) / (v_star.dot(__lowerCamelCase				))





def lowerCamelCase__     (		):







   '''simple docstring'''




   _UpperCAmelCase  :  Optional[Any]				       =np.array([[2, 2 + 1J, 4], [2 - 1J, 3, 1J], [4, -1J, 1]]				)
   _UpperCAmelCase  :  List[str]				       =np.array([[1], [2], [3]]				)
   assert is_hermitian(__lowerCamelCase				), f"{a} is not hermitian."
   print(rayleigh_quotient(__lowerCamelCase			,       __lowerCamelCase				)				)

   _UpperCAmelCase  :  List[str]				       =np.array([[1, 2, 4], [2, 3, -1], [4, -1, 1]]				)
   assert is_hermitian(__lowerCamelCase				), f"{a} is not hermitian."
   assert rayleigh_quotient(__lowerCamelCase			,       __lowerCamelCase				) == float(3				)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 tests()

