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





def  _lowerCAmelCase     (  lowerCamelCase__				:				list,    lowerCamelCase__				:				int,    lowerCamelCase__				:				int,    lowerCamelCase__				:				int					)	->     list:
  _SCREAMING_SNAKE_CASE :					Optional[int]				     =			[]
  _SCREAMING_SNAKE_CASE     ,		_SCREAMING_SNAKE_CASE :					Tuple				     =			input_list[low:mid], input_list[mid : high + 1]
  while left and right:
    result.append((left if left[0] <= right[0] else right).pop(0					)					)
  _SCREAMING_SNAKE_CASE :					Tuple				     =			result + left + right
  return input_list





def  _lowerCAmelCase     (  lowerCamelCase__				:				list					)	->     list:
  if len(lowerCamelCase__					) <= 1:
    return input_list
  _SCREAMING_SNAKE_CASE :					Union[str, Any]				     =			list(lowerCamelCase__					)

  # iteration for two-way merging
  _SCREAMING_SNAKE_CASE :					Optional[int]				     =			2
  while p <= len(lowerCamelCase__					):
    # getting low, high and middle value for merge-sort of single list
    for i in range(0,    len(lowerCamelCase__					),    lowerCamelCase__					):
      _SCREAMING_SNAKE_CASE :					Tuple				     =			i
      _SCREAMING_SNAKE_CASE :					Optional[Any]				     =			i + p - 1
      _SCREAMING_SNAKE_CASE :					Union[str, Any]				     =			(low + high + 1) // 2
      _SCREAMING_SNAKE_CASE :					str				     =			merge(lowerCamelCase__,    lowerCamelCase__,    lowerCamelCase__,    lowerCamelCase__					)
    # final merge of last two parts
    if p * 2 >= len(lowerCamelCase__					):
      _SCREAMING_SNAKE_CASE :					Tuple				     =			i
      _SCREAMING_SNAKE_CASE :					List[Any]				     =			merge(lowerCamelCase__,    0,    lowerCamelCase__,    len(lowerCamelCase__					) - 1					)
      break
    p *= 2

  return input_list


if __name__ == "__main__":
      lowercase_							:    int         =						input('''Enter numbers separated by a comma:\n''').strip()
      if user_input == "":
            lowercase_							:    str         =						[]
      else:
            lowercase_							:    List[str]         =						[int(item.strip()) for item in user_input.split(''',''')]
      print(iter_merge_sort(unsorted))





"""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       ):



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







         """simple docstring"""



         a__		=			'laion/clap-htsat-unfused'
         a__		=			tempfile.mkdtemp()



     def 			lowercase__  (							self     ,				**__SCREAMING_SNAKE_CASE   )		->     Optional[Any]:







         """simple docstring"""



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



     def 			lowercase__  (							self     ,				**__SCREAMING_SNAKE_CASE   )		->     Tuple:







         """simple docstring"""



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



     def 			lowercase__  (							self   )		->     Tuple:







         """simple docstring"""



         shutil.rmtree(self.tmpdirname   )



     def 			lowercase__  (							self   )		->     Optional[int]:







         """simple docstring"""



         a__		=			self.get_tokenizer()
         a__		=			self.get_feature_extractor()

         a__		=			ClapProcessor(tokenizer=__SCREAMING_SNAKE_CASE     ,				feature_extractor=__SCREAMING_SNAKE_CASE   )

         processor.save_pretrained(self.tmpdirname   )
         a__		=			ClapProcessor.from_pretrained(self.tmpdirname   )

         self.assertEqual(processor.tokenizer.get_vocab()     ,				tokenizer.get_vocab()   )
         self.assertIsInstance(processor.tokenizer     ,				__SCREAMING_SNAKE_CASE   )

         self.assertEqual(processor.feature_extractor.to_json_string()     ,				feature_extractor.to_json_string()   )
         self.assertIsInstance(processor.feature_extractor     ,				__SCREAMING_SNAKE_CASE   )



     def 			lowercase__  (							self   )		->     Optional[int]:







         """simple docstring"""



         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=__SCREAMING_SNAKE_CASE     ,				padding_value=1.0   )

         a__		=			ClapProcessor.from_pretrained(
             self.tmpdirname     ,				bos_token='(BOS)'     ,				eos_token='(EOS)'     ,				do_normalize=__SCREAMING_SNAKE_CASE     ,				padding_value=1.0   )

         self.assertEqual(processor.tokenizer.get_vocab()     ,				tokenizer_add_kwargs.get_vocab()   )
         self.assertIsInstance(processor.tokenizer     ,				__SCREAMING_SNAKE_CASE   )

         self.assertEqual(processor.feature_extractor.to_json_string()     ,				feature_extractor_add_kwargs.to_json_string()   )
         self.assertIsInstance(processor.feature_extractor     ,				__SCREAMING_SNAKE_CASE   )



     def 			lowercase__  (							self   )		->     Union[str, Any]:







         """simple docstring"""



         a__		=			self.get_feature_extractor()
         a__		=			self.get_tokenizer()

         a__		=			ClapProcessor(tokenizer=__SCREAMING_SNAKE_CASE     ,				feature_extractor=__SCREAMING_SNAKE_CASE   )

         a__		=			floats_list((3, 1_0_0_0)   )

         a__		=			feature_extractor(__SCREAMING_SNAKE_CASE     ,				return_tensors='np'   )
         a__		=			processor(audios=__SCREAMING_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 			lowercase__  (							self   )		->     Tuple:







         """simple docstring"""



         a__		=			self.get_feature_extractor()
         a__		=			self.get_tokenizer()

         a__		=			ClapProcessor(tokenizer=__SCREAMING_SNAKE_CASE     ,				feature_extractor=__SCREAMING_SNAKE_CASE   )

         a__		=			'This is a test string'

         a__		=			processor(text=__SCREAMING_SNAKE_CASE   )

         a__		=			tokenizer(__SCREAMING_SNAKE_CASE   )

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



     def 			lowercase__  (							self   )		->     Dict:







         """simple docstring"""



         a__		=			self.get_feature_extractor()
         a__		=			self.get_tokenizer()

         a__		=			ClapProcessor(tokenizer=__SCREAMING_SNAKE_CASE     ,				feature_extractor=__SCREAMING_SNAKE_CASE   )

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

         a__		=			processor.batch_decode(__SCREAMING_SNAKE_CASE   )
         a__		=			tokenizer.batch_decode(__SCREAMING_SNAKE_CASE   )

         self.assertListEqual(__SCREAMING_SNAKE_CASE     ,				__SCREAMING_SNAKE_CASE   )




     def 			lowercase__  (							self   )		->     List[Any]:







         """simple docstring"""



         a__		=			self.get_feature_extractor()
         a__		=			self.get_tokenizer()

         a__		=			ClapProcessor(tokenizer=__SCREAMING_SNAKE_CASE     ,				feature_extractor=__SCREAMING_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'     ,				)


