


def 			_lowerCAmelCase						(							lowerCAmelCase_							:list							)->bool:
   '''simple docstring'''






   if not isinstance(lowerCAmelCase_		,						lowerCAmelCase_							):
      raise ValueError("Input series is not valid, valid series - [1, 2/3, 2]"							)
   if len(lowerCAmelCase_							) == 0:
      raise ValueError("Input list must be a non empty list"							)
   if len(lowerCAmelCase_							) == 1 and series[0] != 0:
      return True
   snake_case_     :   Tuple					    =					[]
   snake_case_     :   Optional[int]					    =					len(lowerCAmelCase_							)
   for i in range(0		,						lowerCAmelCase_							):
      if series[i] == 0:
         raise ValueError("Input series cannot have 0 as an element"							)
      rec_series.append(1 / series[i]							)
   snake_case_     :   int					    =					rec_series[1] - rec_series[0]
   for index in range(2		,						lowerCAmelCase_							):
      if rec_series[index] - rec_series[index - 1] != common_diff:
         return False
   return True



def 			_lowerCAmelCase						(							lowerCAmelCase_							:list							)->float:
   '''simple docstring'''






   if not isinstance(lowerCAmelCase_		,						lowerCAmelCase_							):
      raise ValueError("Input series is not valid, valid series - [2, 4, 6]"							)
   if len(lowerCAmelCase_							) == 0:
      raise ValueError("Input list must be a non empty list"							)
   snake_case_     :   Dict					    =					0
   for val in series:
      answer += 1 / val
   return len(lowerCAmelCase_							) / answer


if __name__ == "__main__":
   import doctest

   doctest.testmod()








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	:Union[str, Any]  		=     random.Random()



def 			_lowerCAmelCase						(							lowerCAmelCase_							:Union[str, Any]		,						lowerCAmelCase_							:Optional[int]=1.0		,						lowerCAmelCase_							:List[str]=None		,						lowerCAmelCase_							:str=None							)->Union[str, Any]:
   '''simple docstring'''






   if rng is None:
      snake_case_					    =					global_rng

   snake_case_					    =					[]
   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     __lowerCAmelCase     ( unittest.TestCase					):






  """simple docstring"""





  def 					lowerCAmelCase__  (     self       :       List[str]  )   -> List[Any]:




     """simple docstring"""
     snake_case_					    =					"facebook/musicgen-small"
     snake_case_					    =					tempfile.mkdtemp()



  def 					lowerCAmelCase__  (     self       :       Tuple    ,				**_lowerCAmelCase       :       Tuple  )   -> Optional[int]:




     """simple docstring"""
     return TaTokenizer.from_pretrained(self.checkpoint    ,				**_lowerCAmelCase  )



  def 					lowerCAmelCase__  (     self       :       Union[str, Any]    ,				**_lowerCAmelCase       :       Union[str, Any]  )   -> int:




     """simple docstring"""
     return EncodecFeatureExtractor.from_pretrained(self.checkpoint    ,				**_lowerCAmelCase  )



  def 					lowerCAmelCase__  (     self       :       Optional[Any]  )   -> Optional[int]:




     """simple docstring"""
     shutil.rmtree(self.tmpdirname  )



  def 					lowerCAmelCase__  (     self       :       int  )   -> List[Any]:




     """simple docstring"""
     snake_case_					    =					self.get_tokenizer()
     snake_case_					    =					self.get_feature_extractor()

     snake_case_					    =					MusicgenProcessor(tokenizer=_lowerCAmelCase    ,				feature_extractor=_lowerCAmelCase  )

     processor.save_pretrained(self.tmpdirname  )
     snake_case_					    =					MusicgenProcessor.from_pretrained(self.tmpdirname  )

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

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



  def 					lowerCAmelCase__  (     self       :       Optional[Any]  )   -> Tuple:




     """simple docstring"""
     snake_case_					    =					MusicgenProcessor(tokenizer=self.get_tokenizer()    ,				feature_extractor=self.get_feature_extractor()  )
     processor.save_pretrained(self.tmpdirname  )

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

     snake_case_					    =					MusicgenProcessor.from_pretrained(
         self.tmpdirname    ,				bos_token="(BOS)"    ,				eos_token="(EOS)"    ,				do_normalize=_lowerCAmelCase    ,				padding_value=1.0  )

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

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



  def 					lowerCAmelCase__  (     self       :       List[str]  )   -> Optional[Any]:




     """simple docstring"""
     snake_case_					    =					self.get_feature_extractor()
     snake_case_					    =					self.get_tokenizer()

     snake_case_					    =					MusicgenProcessor(tokenizer=_lowerCAmelCase    ,				feature_extractor=_lowerCAmelCase  )

     snake_case_					    =					floats_list((3, 1_0_0_0)  )

     snake_case_					    =					feature_extractor(_lowerCAmelCase    ,				return_tensors="np"  )
     snake_case_					    =					processor(_lowerCAmelCase    ,				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 					lowerCAmelCase__  (     self       :       Tuple  )   -> List[Any]:




     """simple docstring"""
     snake_case_					    =					self.get_feature_extractor()
     snake_case_					    =					self.get_tokenizer()

     snake_case_					    =					MusicgenProcessor(tokenizer=_lowerCAmelCase    ,				feature_extractor=_lowerCAmelCase  )

     snake_case_					    =					"This is a test string"

     snake_case_					    =					processor(text=_lowerCAmelCase  )

     snake_case_					    =					tokenizer(_lowerCAmelCase  )

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



  def 					lowerCAmelCase__  (     self       :       Any  )   -> str:




     """simple docstring"""
     snake_case_					    =					self.get_feature_extractor()
     snake_case_					    =					self.get_tokenizer()

     snake_case_					    =					MusicgenProcessor(tokenizer=_lowerCAmelCase    ,				feature_extractor=_lowerCAmelCase  )

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

     snake_case_					    =					processor.batch_decode(sequences=_lowerCAmelCase  )
     snake_case_					    =					tokenizer.batch_decode(_lowerCAmelCase  )

     self.assertListEqual(_lowerCAmelCase    ,				_lowerCAmelCase  )



  def 					lowerCAmelCase__  (     self       :       Optional[int]  )   -> Dict:




     """simple docstring"""
     snake_case_					    =					self.get_feature_extractor()
     snake_case_					    =					self.get_tokenizer()

     snake_case_					    =					MusicgenProcessor(tokenizer=_lowerCAmelCase    ,				feature_extractor=_lowerCAmelCase  )

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



  def 					lowerCAmelCase__  (     self       :       Tuple  )   -> int:




     """simple docstring"""
     snake_case_					    =					self.get_feature_extractor(padding_side="left"  )
     snake_case_					    =					self.get_tokenizer()

     snake_case_					    =					MusicgenProcessor(tokenizer=_lowerCAmelCase    ,				feature_extractor=_lowerCAmelCase  )

     snake_case_					    =					[floats_list((1, x)  )[0] for x in range(5    ,				2_0    ,				5  )]
     snake_case_					    =					processor(_lowerCAmelCase  ).padding_mask

     snake_case_					    =					np.asarray(floats_list((3, 2_0)  )  )[:, None, :]
     snake_case_					    =					processor.batch_decode(_lowerCAmelCase    ,				padding_mask=_lowerCAmelCase  )

     self.assertIsInstance(_lowerCAmelCase    ,				_lowerCAmelCase  )

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

     self.assertTrue(decoded_audios[0].shape == (1, 1_0)  )
     self.assertTrue(decoded_audios[1].shape == (1, 1_5)  )
     self.assertTrue(decoded_audios[2].shape == (1, 2_0)  )




