"""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       a_      (     unittest.TestCase			):




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[str]     ):
							lowerCAmelCase__        =   """laion/clap-htsat-unfused"""
							lowerCAmelCase__        =   tempfile.mkdtemp()




					def 						_SCREAMING_SNAKE_CASE						(	self						:     int  ,						**snake_case__						:     Optional[int]     ):
							return RobertaTokenizer.from_pretrained(self.checkpoint  ,						**snake_case__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Optional[int]  ,						**snake_case__						:     Dict     ):
							return ClapFeatureExtractor.from_pretrained(self.checkpoint  ,						**snake_case__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[str]     ):
							shutil.rmtree(self.tmpdirname     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Tuple     ):
							lowerCAmelCase__        =   self.get_tokenizer()
							lowerCAmelCase__        =   self.get_feature_extractor()

							lowerCAmelCase__        =   ClapProcessor(tokenizer=snake_case__  ,						feature_extractor=snake_case__     )

							processor.save_pretrained(self.tmpdirname     )
							lowerCAmelCase__        =   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 						_SCREAMING_SNAKE_CASE						(	self						:     int     ):
							lowerCAmelCase__        =   ClapProcessor(tokenizer=self.get_tokenizer()  ,						feature_extractor=self.get_feature_extractor()     )
							processor.save_pretrained(self.tmpdirname     )

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

							lowerCAmelCase__        =   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 						_SCREAMING_SNAKE_CASE						(	self						:     Optional[Any]     ):
							lowerCAmelCase__        =   self.get_feature_extractor()
							lowerCAmelCase__        =   self.get_tokenizer()

							lowerCAmelCase__        =   ClapProcessor(tokenizer=snake_case__  ,						feature_extractor=snake_case__     )

							lowerCAmelCase__        =   floats_list((3, 1000)     )

							lowerCAmelCase__        =   feature_extractor(snake_case__  ,						return_tensors="""np"""     )
							lowerCAmelCase__        =   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 						_SCREAMING_SNAKE_CASE						(	self						:     str     ):
							lowerCAmelCase__        =   self.get_feature_extractor()
							lowerCAmelCase__        =   self.get_tokenizer()

							lowerCAmelCase__        =   ClapProcessor(tokenizer=snake_case__  ,						feature_extractor=snake_case__     )

							lowerCAmelCase__        =   """This is a test string"""

							lowerCAmelCase__        =   processor(text=snake_case__     )

							lowerCAmelCase__        =   tokenizer(snake_case__     )

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




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Tuple     ):
							lowerCAmelCase__        =   self.get_feature_extractor()
							lowerCAmelCase__        =   self.get_tokenizer()

							lowerCAmelCase__        =   ClapProcessor(tokenizer=snake_case__  ,						feature_extractor=snake_case__     )

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

							lowerCAmelCase__        =   processor.batch_decode(snake_case__     )
							lowerCAmelCase__        =   tokenizer.batch_decode(snake_case__     )

							self.assertListEqual(snake_case__  ,						snake_case__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Optional[int]     ):
							lowerCAmelCase__        =   self.get_feature_extractor()
							lowerCAmelCase__        =   self.get_tokenizer()

							lowerCAmelCase__        =   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"""  ,						)





"""simple docstring"""




import os
from math import logaa







def 							_UpperCAmelCase		(       lowerCamelCase__ = "base_exp.txt"     ):





		"""simple docstring"""




		lowerCAmelCase__        =   0
		lowerCAmelCase__        =   0
		for i, line in enumerate(open(os.path.join(os.path.dirname(lowerCamelCase__     )			,  lowerCamelCase__     )     )     ):
				lowerCAmelCase__   ,					lowerCAmelCase__        =   list(map(lowerCamelCase__			,  line.split(""","""     )     )     )
				if x * logaa(lowerCamelCase__     ) > largest:
						lowerCAmelCase__        =   x * logaa(lowerCamelCase__     )
						lowerCAmelCase__        =   i + 1
		return result


if __name__ == "__main__":
			print(solution())




