






'''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 				A      (   self							:						Dict			)							->    Union[str, Any]:

									'''simple docstring'''







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






			def 				A      (   self							:						Optional[int] ,      **lowercase							:						List[str]			)							->    Optional[int]:

									'''simple docstring'''







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






			def 				A      (   self							:						Dict ,      **lowercase							:						Union[str, Any]			)							->    Optional[Any]:

									'''simple docstring'''







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






			def 				A      (   self							:						Tuple			)							->    List[str]:

									'''simple docstring'''







									shutil.rmtree(self.tmpdirname			)






			def 				A      (   self							:						str			)							->    Optional[int]:

									'''simple docstring'''







									UpperCamelCase__         = self.get_tokenizer()
									UpperCamelCase__         = self.get_feature_extractor()

									UpperCamelCase__         = ClapProcessor(tokenizer=UpperCamelCase__ ,      feature_extractor=UpperCamelCase__			)

									processor.save_pretrained(self.tmpdirname			)
									UpperCamelCase__         = 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 				A      (   self							:						List[str]			)							->    Optional[Any]:

									'''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=UpperCamelCase__ ,      padding_value=1.0			)

									UpperCamelCase__         = 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 				A      (   self							:						List[str]			)							->    Dict:

									'''simple docstring'''







									UpperCamelCase__         = self.get_feature_extractor()
									UpperCamelCase__         = self.get_tokenizer()

									UpperCamelCase__         = ClapProcessor(tokenizer=UpperCamelCase__ ,      feature_extractor=UpperCamelCase__			)

									UpperCamelCase__         = floats_list((3, 1_0_0_0)			)

									UpperCamelCase__         = feature_extractor(UpperCamelCase__ ,      return_tensors="""np"""			)
									UpperCamelCase__         = 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 				A      (   self							:						List[str]			)							->    List[str]:

									'''simple docstring'''







									UpperCamelCase__         = self.get_feature_extractor()
									UpperCamelCase__         = self.get_tokenizer()

									UpperCamelCase__         = ClapProcessor(tokenizer=UpperCamelCase__ ,      feature_extractor=UpperCamelCase__			)

									UpperCamelCase__         = """This is a test string"""

									UpperCamelCase__         = processor(text=UpperCamelCase__			)

									UpperCamelCase__         = tokenizer(UpperCamelCase__			)

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






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

									'''simple docstring'''







									UpperCamelCase__         = self.get_feature_extractor()
									UpperCamelCase__         = self.get_tokenizer()

									UpperCamelCase__         = ClapProcessor(tokenizer=UpperCamelCase__ ,      feature_extractor=UpperCamelCase__			)

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

									UpperCamelCase__         = processor.batch_decode(UpperCamelCase__			)
									UpperCamelCase__         = tokenizer.batch_decode(UpperCamelCase__			)

									self.assertListEqual(UpperCamelCase__ ,      UpperCamelCase__			)







			def 				A      (   self							:						List[str]			)							->    str:

									'''simple docstring'''







									UpperCamelCase__         = self.get_feature_extractor()
									UpperCamelCase__         = self.get_tokenizer()

									UpperCamelCase__         = 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'''


import math







def 	__magic_name__( _A					):
						'''simple docstring'''





						assert isinstance(_A						,      _A					) and (
						    number >= 0
						), "'number' must been an int and positive"

						if 1 < number < 4:
												# 2 and 3 are primes
												return True
						elif number < 2 or not number % 2:
												# Negatives, 0, 1 and all even numbers are not primes
												return False

						UpperCamelCase__         = range(3						,      int(math.sqrt(_A					) + 1					)						,      2					)
						return not any(not number % i for i in odd_numbers					)







def 	__magic_name__( _A						,      _A=1						,      **_A					):
						'''simple docstring'''





						UpperCamelCase__         = factor * value
						UpperCamelCase__         = value

						while not is_prime(_A					):
												value += 1 if not ("desc" in kwargs and kwargs["desc"] is True) else -1

						if value == first_value_val:
												return next_prime(value + 1						,      **_A					)
						return value
