


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							):


     """simple docstring"""


     def 	snake_case_  (	self    ):
        __a					=  """laion/clap-htsat-unfused"""
        __a					=  tempfile.mkdtemp()


     def 	snake_case_  (	self  ,       **__A    ):
        return RobertaTokenizer.from_pretrained(self.checkpoint  ,       **__A    )


     def 	snake_case_  (	self  ,       **__A    ):
        return ClapFeatureExtractor.from_pretrained(self.checkpoint  ,       **__A    )


     def 	snake_case_  (	self    ):
        shutil.rmtree(self.tmpdirname    )


     def 	snake_case_  (	self    ):
        __a					=  self.get_tokenizer()
        __a					=  self.get_feature_extractor()

        __a					=  ClapProcessor(tokenizer=__A  ,       feature_extractor=__A    )

        processor.save_pretrained(self.tmpdirname    )
        __a					=  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 	snake_case_  (	self    ):
        __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=__A  ,       padding_value=1.0    )

        __a					=  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 	snake_case_  (	self    ):
        __a					=  self.get_feature_extractor()
        __a					=  self.get_tokenizer()

        __a					=  ClapProcessor(tokenizer=__A  ,       feature_extractor=__A    )

        __a					=  floats_list((3, 1000)    )

        __a					=  feature_extractor(__A  ,       return_tensors="""np"""    )
        __a					=  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 	snake_case_  (	self    ):
        __a					=  self.get_feature_extractor()
        __a					=  self.get_tokenizer()

        __a					=  ClapProcessor(tokenizer=__A  ,       feature_extractor=__A    )

        __a					=  """This is a test string"""

        __a					=  processor(text=__A    )

        __a					=  tokenizer(__A    )

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


     def 	snake_case_  (	self    ):
        __a					=  self.get_feature_extractor()
        __a					=  self.get_tokenizer()

        __a					=  ClapProcessor(tokenizer=__A  ,       feature_extractor=__A    )

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

        __a					=  processor.batch_decode(__A    )
        __a					=  tokenizer.batch_decode(__A    )

        self.assertListEqual(__A  ,       __A    )


     def 	snake_case_  (	self    ):
        __a					=  self.get_feature_extractor()
        __a					=  self.get_tokenizer()

        __a					=  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"""  ,       )





"""simple docstring"""
from __future__ import annotations

def  lowercase     (_lowerCAmelCase						):
						__lowerCAmelCase     =  2
						__lowerCAmelCase     =  []
						while i * i <= n:
												if n % i:
																		i += 1
												else:
																		n //= i
																		factors.append(_lowerCAmelCase						)
						if n > 1:
												factors.append(_lowerCAmelCase						)
						return factors


if __name__ == "__main__":
			import doctest

			doctest.testmod()
