






"""simple docstring"""




import random
import shutil
import tempfile
import unittest

import numpy as np

from transformers import TaTokenizer, TaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torch
from transformers.utils.import_utils import is_speech_available, is_torch_available


if is_torch_available():
  pass

if is_speech_available():
  from transformers import EncodecFeatureExtractor, MusicgenProcessor


SCREAMING_SNAKE_CASE								=  random.Random()

def        _lowerCamelCase		(  __A      :							Optional[int]						,						__A      :							Dict=1.0						,						__A      :							Dict=None						,						__A      :							Union[str, Any]=None	) ->   Optional[Any]:
    if rng is None:
        _UpperCAmelCase			: str     					=			global_rng

    _UpperCAmelCase			: List[str]     					=			[]
    for batch_idx in range(shape[0]	):
        values.append([]	)
        for _ in range(shape[1]	):
            values[-1].append(rng.random() * scale	)

    return values


@require_torch
@require_sentencepiece
class 							A_      (  unittest.TestCase     ):






 '''simple docstring'''




 def 	snake_case__			(		self)	->						str:

     """simple docstring"""



     _UpperCAmelCase			: str     					=			'''facebook/musicgen-small'''
     _UpperCAmelCase			: str     					=			tempfile.mkdtemp()


 def 	snake_case__			(		self							,					**_A)	->						Tuple:

     """simple docstring"""



     return TaTokenizer.from_pretrained(self.checkpoint							,					**_A)


 def 	snake_case__			(		self							,					**_A)	->						Tuple:

     """simple docstring"""



     return EncodecFeatureExtractor.from_pretrained(self.checkpoint							,					**_A)


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

     """simple docstring"""



     shutil.rmtree(self.tmpdirname)


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

     """simple docstring"""



     _UpperCAmelCase			: List[str]     					=			self.get_tokenizer()
     _UpperCAmelCase			: Optional[int]     					=			self.get_feature_extractor()

     _UpperCAmelCase			: Optional[Any]     					=			MusicgenProcessor(tokenizer=_A							,					feature_extractor=_A)

     processor.save_pretrained(self.tmpdirname)
     _UpperCAmelCase			: Union[str, Any]     					=			MusicgenProcessor.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)	->						Dict:

     """simple docstring"""



     _UpperCAmelCase			: List[str]     					=			MusicgenProcessor(tokenizer=self.get_tokenizer()							,					feature_extractor=self.get_feature_extractor())
     processor.save_pretrained(self.tmpdirname)

     _UpperCAmelCase			: List[Any]     					=			self.get_tokenizer(bos_token='''(BOS)'''							,					eos_token='''(EOS)''')
     _UpperCAmelCase			: Dict     					=			self.get_feature_extractor(do_normalize=_A							,					padding_value=1.0)

     _UpperCAmelCase			: Dict     					=			MusicgenProcessor.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)	->						Tuple:

     """simple docstring"""



     _UpperCAmelCase			: str     					=			self.get_feature_extractor()
     _UpperCAmelCase			: Union[str, Any]     					=			self.get_tokenizer()

     _UpperCAmelCase			: str     					=			MusicgenProcessor(tokenizer=_A							,					feature_extractor=_A)

     _UpperCAmelCase			: List[Any]     					=			floats_list((3, 1000))

     _UpperCAmelCase			: Any     					=			feature_extractor(_A							,					return_tensors='''np''')
     _UpperCAmelCase			: List[Any]     					=			processor(_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)	->						int:

     """simple docstring"""



     _UpperCAmelCase			: Any     					=			self.get_feature_extractor()
     _UpperCAmelCase			: List[str]     					=			self.get_tokenizer()

     _UpperCAmelCase			: str     					=			MusicgenProcessor(tokenizer=_A							,					feature_extractor=_A)

     _UpperCAmelCase			: str     					=			'''This is a test string'''

     _UpperCAmelCase			: Dict     					=			processor(text=_A)

     _UpperCAmelCase			: List[str]     					=			tokenizer(_A)

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


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

     """simple docstring"""



     _UpperCAmelCase			: Dict     					=			self.get_feature_extractor()
     _UpperCAmelCase			: str     					=			self.get_tokenizer()

     _UpperCAmelCase			: Any     					=			MusicgenProcessor(tokenizer=_A							,					feature_extractor=_A)

     _UpperCAmelCase			: List[Any]     					=			[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

     _UpperCAmelCase			: Tuple     					=			processor.batch_decode(sequences=_A)
     _UpperCAmelCase			: Optional[Any]     					=			tokenizer.batch_decode(_A)

     self.assertListEqual(_A							,					_A)


 def 	snake_case__			(		self)	->						Dict:

     """simple docstring"""



     _UpperCAmelCase			: Tuple     					=			self.get_feature_extractor()
     _UpperCAmelCase			: Any     					=			self.get_tokenizer()

     _UpperCAmelCase			: Optional[int]     					=			MusicgenProcessor(tokenizer=_A							,					feature_extractor=_A)

     self.assertListEqual(
         processor.model_input_names							,					feature_extractor.model_input_names							,					msg='''`processor` and `feature_extractor` model input names do not match'''							,					)


 def 	snake_case__			(		self)	->						Any:

     """simple docstring"""



     _UpperCAmelCase			: Any     					=			self.get_feature_extractor(padding_side='''left''')
     _UpperCAmelCase			: int     					=			self.get_tokenizer()

     _UpperCAmelCase			: Optional[int]     					=			MusicgenProcessor(tokenizer=_A							,					feature_extractor=_A)

     _UpperCAmelCase			: Dict     					=			[floats_list((1, x))[0] for x in range(5							,					20							,					5)]
     _UpperCAmelCase			: Union[str, Any]     					=			processor(_A).padding_mask

     _UpperCAmelCase			: Any     					=			np.asarray(floats_list((3, 20)))[:, None, :]
     _UpperCAmelCase			: Optional[int]     					=			processor.batch_decode(_A							,					padding_mask=_A)

     self.assertIsInstance(_A							,					_A)

     for audio in decoded_audios:
         self.assertIsInstance(_A							,					np.ndarray)

     self.assertTrue(decoded_audios[0].shape == (1, 10))
     self.assertTrue(decoded_audios[1].shape == (1, 15))
     self.assertTrue(decoded_audios[2].shape == (1, 20))












def        _lowerCamelCase		(  __A      :							list	) ->   list:
    _UpperCAmelCase			: Dict     					=			1.3
    _UpperCAmelCase			: Any     					=			len(__A	)
    _UpperCAmelCase			: List[Any]     					=			False

    while not completed:
        # Update the gap value for a next comb
        _UpperCAmelCase			: Optional[Any]     					=			int(gap / shrink_factor	)
        if gap <= 1:
            _UpperCAmelCase			: Any     					=			True

        _UpperCAmelCase			: Optional[Any]     					=			0
        while index + gap < len(__A	):
            if data[index] > data[index + gap]:
                # Swap values
                _UpperCAmelCase					,	_UpperCAmelCase			: Union[str, Any]     					=			data[index + gap], data[index]
                _UpperCAmelCase			: Any     					=			False
            index += 1

    return data


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  SCREAMING_SNAKE_CASE								=  input('Enter numbers separated by a comma:\n').strip()
  SCREAMING_SNAKE_CASE								=  [int(item) for item in user_input.split(',')]
  print(comb_sort(unsorted))




