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      A_							(		self    :		Dict				):
								UpperCamelCase__					=				"""laion/clap-htsat-unfused"""
								UpperCamelCase__					=				tempfile.mkdtemp()





				def      A_							(		self    :		Any      ,							**_a    :		Tuple				):
								return RobertaTokenizer.from_pretrained(self.checkpoint      ,							**A__				)





				def      A_							(		self    :		str      ,							**_a    :		Tuple				):
								return ClapFeatureExtractor.from_pretrained(self.checkpoint      ,							**A__				)





				def      A_							(		self    :		Tuple				):
								shutil.rmtree(self.tmpdirname				)





				def      A_							(		self    :		Union[str, Any]				):
								UpperCamelCase__					=				self.get_tokenizer()
								UpperCamelCase__					=				self.get_feature_extractor()

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

								processor.save_pretrained(self.tmpdirname				)
								UpperCamelCase__					=				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      A_							(		self    :		List[Any]				):
								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=A__      ,							padding_value=1.0				)

								UpperCamelCase__					=				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      A_							(		self    :		int				):
								UpperCamelCase__					=				self.get_feature_extractor()
								UpperCamelCase__					=				self.get_tokenizer()

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

								UpperCamelCase__					=				floats_list((3, 1_000)				)

								UpperCamelCase__					=				feature_extractor(A__      ,							return_tensors='''np'''				)
								UpperCamelCase__					=				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      A_							(		self    :		Dict				):
								UpperCamelCase__					=				self.get_feature_extractor()
								UpperCamelCase__					=				self.get_tokenizer()

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

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

								UpperCamelCase__					=				processor(text=A__				)

								UpperCamelCase__					=				tokenizer(A__				)

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





				def      A_							(		self    :		Optional[Any]				):
								UpperCamelCase__					=				self.get_feature_extractor()
								UpperCamelCase__					=				self.get_tokenizer()

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

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

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

								self.assertListEqual(A__      ,							A__				)





				def      A_							(		self    :		int				):
								UpperCamelCase__					=				self.get_feature_extractor()
								UpperCamelCase__					=				self.get_tokenizer()

								UpperCamelCase__					=				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'''      ,							)






def 		UpperCamelCase   (lowercase_:					list   )	-> list:
	A__				:       Union[str, Any]	  =						False
	while is_sorted is False:  # Until all the indices are traversed keep looping
		A__				:       Dict	  =						True
		for i in range(0       , len(lowercase_   ) - 1       , 2   ):  # iterating over all even indices
			if input_list[i] > input_list[i + 1]:
				A__  ,  A__				:       Dict	  =						input_list[i + 1], input_list[i]
				# swapping if elements not in order
				A__				:       Optional[Any]	  =						False

		for i in range(1       , len(lowercase_   ) - 1       , 2   ):  # iterating over all odd indices
			if input_list[i] > input_list[i + 1]:
				A__  ,  A__				:       Dict	  =						input_list[i + 1], input_list[i]
				# swapping if elements not in order
				A__				:       Optional[Any]	  =						False
	return input_list


if __name__ == "__main__":
	print('Enter list to be sorted')
	A_			:					Optional[int]    			=     [int(x) for x in input().split()]
	# inputing elements of the list in one line
	A_			:					Optional[int]    			=     odd_even_sort(input_list)
	print('The sorted list is')
	print(sorted_list)



