





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


_UpperCamelCase       :				Tuple           =			random.Random()
def  __UpperCamelCase    (						snake_case							,			snake_case=1.0							,			snake_case=None							,			snake_case=None      )    ->		int:


   '''simple docstring'''







   if rng is None:
      __A    =  global_rng

   __A    =  []
   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 						SCREAMING_SNAKE_CASE__			(   self      )->   List[str]:
     __A    =  """facebook/musicgen-small"""
     __A    =  tempfile.mkdtemp()

  def 						SCREAMING_SNAKE_CASE__			(   self    ,							**UpperCAmelCase      )->   Tuple:
     return TaTokenizer.from_pretrained(self.checkpoint    ,							**_lowercase      )

  def 						SCREAMING_SNAKE_CASE__			(   self    ,							**UpperCAmelCase      )->   List[Any]:
     return EncodecFeatureExtractor.from_pretrained(self.checkpoint    ,							**_lowercase      )

  def 						SCREAMING_SNAKE_CASE__			(   self      )->   List[Any]:
     shutil.rmtree(self.tmpdirname      )

  def 						SCREAMING_SNAKE_CASE__			(   self      )->   int:
     __A    =  self.get_tokenizer()
     __A    =  self.get_feature_extractor()

     __A    =  MusicgenProcessor(tokenizer=_lowercase    ,							feature_extractor=_lowercase      )

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

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

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

  def 						SCREAMING_SNAKE_CASE__			(   self      )->   List[Any]:
     __A    =  MusicgenProcessor(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=_lowercase    ,							padding_value=1.0      )

     __A    =  MusicgenProcessor.from_pretrained(
         self.tmpdirname    ,							bos_token='''(BOS)'''    ,							eos_token='''(EOS)'''    ,							do_normalize=_lowercase    ,							padding_value=1.0      )

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

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

  def 						SCREAMING_SNAKE_CASE__			(   self      )->   str:
     __A    =  self.get_feature_extractor()
     __A    =  self.get_tokenizer()

     __A    =  MusicgenProcessor(tokenizer=_lowercase    ,							feature_extractor=_lowercase      )

     __A    =  floats_list((3, 10_00)      )

     __A    =  feature_extractor(_lowercase    ,							return_tensors='''np'''      )
     __A    =  processor(_lowercase    ,							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      )->   Union[str, Any]:
     __A    =  self.get_feature_extractor()
     __A    =  self.get_tokenizer()

     __A    =  MusicgenProcessor(tokenizer=_lowercase    ,							feature_extractor=_lowercase      )

     __A    =  """This is a test string"""

     __A    =  processor(text=_lowercase      )

     __A    =  tokenizer(_lowercase      )

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

  def 						SCREAMING_SNAKE_CASE__			(   self      )->   str:
     __A    =  self.get_feature_extractor()
     __A    =  self.get_tokenizer()

     __A    =  MusicgenProcessor(tokenizer=_lowercase    ,							feature_extractor=_lowercase      )

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

     __A    =  processor.batch_decode(sequences=_lowercase      )
     __A    =  tokenizer.batch_decode(_lowercase      )

     self.assertListEqual(_lowercase    ,							_lowercase      )

  def 						SCREAMING_SNAKE_CASE__			(   self      )->   int:
     __A    =  self.get_feature_extractor()
     __A    =  self.get_tokenizer()

     __A    =  MusicgenProcessor(tokenizer=_lowercase    ,							feature_extractor=_lowercase      )

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





  def 						SCREAMING_SNAKE_CASE__			(   self      )->   List[Any]:
     __A    =  self.get_feature_extractor(padding_side='''left'''      )
     __A    =  self.get_tokenizer()

     __A    =  MusicgenProcessor(tokenizer=_lowercase    ,							feature_extractor=_lowercase      )

     __A    =  [floats_list((1, x)      )[0] for x in range(5    ,							20    ,							5      )]
     __A    =  processor(_lowercase      ).padding_mask

     __A    =  np.asarray(floats_list((3, 20)      )      )[:, None, :]
     __A    =  processor.batch_decode(_lowercase    ,							padding_mask=_lowercase      )

     self.assertIsInstance(_lowercase    ,							_lowercase      )

     for audio in decoded_audios:
        self.assertIsInstance(_lowercase    ,							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)      )








import math





class   lowercase__     :







  def __init__(						self     ,    _lowercase    ):
       lowerCAmelCase_       :							Optional[Any]			 =		len(_lowercase    )
       lowerCAmelCase_       :							Union[str, Any]			 =		[0] * (
           4 * self.N
       )  # approximate the overall size of segment tree with array N
       self.build(1     ,    0     ,    self.N - 1    )







  def 						UpperCAmelCase__		(						self     ,    _lowercase    ):
       return idx * 2







  def 						UpperCAmelCase__		(						self     ,    _lowercase    ):
       return idx * 2 + 1







  def 						UpperCAmelCase__		(						self     ,    _lowercase     ,    _lowercase     ,    _lowercase    ):  # noqa: E741
       if l == r:
            lowerCAmelCase_       :							Dict			 =		A[l]
       else:
            lowerCAmelCase_       :							List[str]			 =		(l + r) // 2
            self.build(self.left(_lowercase    )     ,    _lowercase     ,    _lowercase    )
            self.build(self.right(_lowercase    )     ,    mid + 1     ,    _lowercase    )
            lowerCAmelCase_       :							Dict			 =		max(self.st[self.left(_lowercase    )]     ,    self.st[self.right(_lowercase    )]    )







  def 						UpperCAmelCase__		(						self     ,    _lowercase     ,    _lowercase     ,    _lowercase    ):
       return self.update_recursive(1     ,    0     ,    self.N - 1     ,    a - 1     ,    b - 1     ,    _lowercase    )







  def 						UpperCAmelCase__		(						self     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase    ):  # noqa: E741
       if r < a or l > b:
            return True
       if l == r:
            lowerCAmelCase_       :							List[str]			 =		val
            return True
       lowerCAmelCase_       :							List[str]			 =		(l + r) // 2
       self.update_recursive(self.left(_lowercase    )     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase    )
       self.update_recursive(self.right(_lowercase    )     ,    mid + 1     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase    )
       lowerCAmelCase_       :							List[Any]			 =		max(self.st[self.left(_lowercase    )]     ,    self.st[self.right(_lowercase    )]    )
       return True







  def 						UpperCAmelCase__		(						self     ,    _lowercase     ,    _lowercase    ):
       return self.query_recursive(1     ,    0     ,    self.N - 1     ,    a - 1     ,    b - 1    )







  def 						UpperCAmelCase__		(						self     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase    ):  # noqa: E741
       if r < a or l > b:
            return -math.inf
       if l >= a and r <= b:
            return self.st[idx]
       lowerCAmelCase_       :							int			 =		(l + r) // 2
       lowerCAmelCase_       :							List[Any]			 =		self.query_recursive(self.left(_lowercase    )     ,    _lowercase     ,    _lowercase     ,    _lowercase     ,    _lowercase    )
       lowerCAmelCase_       :							List[str]			 =		self.query_recursive(self.right(_lowercase    )     ,    mid + 1     ,    _lowercase     ,    _lowercase     ,    _lowercase    )
       return max(_lowercase     ,    _lowercase    )







  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							List[Any]			 =		[]
       for i in range(1     ,    N + 1    ):
            show_list += [self.query(_lowercase     ,    _lowercase    )]
       print(_lowercase    )


if __name__ == "__main__":
      UpperCAmelCase_       : Any							=    [1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
      UpperCAmelCase_       : Optional[Any]							=    15
      UpperCAmelCase_       : List[Any]							=    SegmentTree(A)
      print(segt.query(4, 6))
      print(segt.query(7, 11))
      print(segt.query(7, 12))
      segt.update(1, 3, 1_11)
      print(segt.query(1, 15))
      segt.update(7, 8, 2_35)
      segt.show_data()
