






"""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


_UpperCamelCase		:  List[str]						=		random.Random()
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  Union[str, Any]		, __snake_case      :  Tuple=1.0		, __snake_case      :  Optional[int]=None		, __snake_case      :  Optional[int]=None   ):





  '''simple docstring'''





  if rng is None:
    lowercase							   =	global_rng

  lowercase							   =	[]
  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     ):







    def       UpperCamelCase_				(      self	):
      lowercase							   =	'facebook/musicgen-small'
      lowercase							   =	tempfile.mkdtemp()







    def       UpperCamelCase_				(      self							,		**_lowerCamelCase	):
      return TaTokenizer.from_pretrained(self.checkpoint							,		**_lowerCamelCase	)







    def       UpperCamelCase_				(      self							,		**_lowerCamelCase	):
      return EncodecFeatureExtractor.from_pretrained(self.checkpoint							,		**_lowerCamelCase	)







    def       UpperCamelCase_				(      self	):
      shutil.rmtree(self.tmpdirname	)







    def       UpperCamelCase_				(      self	):
      lowercase							   =	self.get_tokenizer()
      lowercase							   =	self.get_feature_extractor()

      lowercase							   =	MusicgenProcessor(tokenizer=_lowerCamelCase							,		feature_extractor=_lowerCamelCase	)

      processor.save_pretrained(self.tmpdirname	)
      lowercase							   =	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       UpperCamelCase_				(      self	):
      lowercase							   =	MusicgenProcessor(tokenizer=self.get_tokenizer()							,		feature_extractor=self.get_feature_extractor()	)
      processor.save_pretrained(self.tmpdirname	)

      lowercase							   =	self.get_tokenizer(bos_token='(BOS)'							,		eos_token='(EOS)'	)
      lowercase							   =	self.get_feature_extractor(do_normalize=_lowerCamelCase							,		padding_value=1.0	)

      lowercase							   =	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       UpperCamelCase_				(      self	):
      lowercase							   =	self.get_feature_extractor()
      lowercase							   =	self.get_tokenizer()

      lowercase							   =	MusicgenProcessor(tokenizer=_lowerCamelCase							,		feature_extractor=_lowerCamelCase	)

      lowercase							   =	floats_list((3, 1_0_0_0)	)

      lowercase							   =	feature_extractor(_lowerCamelCase							,		return_tensors='np'	)
      lowercase							   =	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       UpperCamelCase_				(      self	):
      lowercase							   =	self.get_feature_extractor()
      lowercase							   =	self.get_tokenizer()

      lowercase							   =	MusicgenProcessor(tokenizer=_lowerCamelCase							,		feature_extractor=_lowerCamelCase	)

      lowercase							   =	'This is a test string'

      lowercase							   =	processor(text=_lowerCamelCase	)

      lowercase							   =	tokenizer(_lowerCamelCase	)

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







    def       UpperCamelCase_				(      self	):
      lowercase							   =	self.get_feature_extractor()
      lowercase							   =	self.get_tokenizer()

      lowercase							   =	MusicgenProcessor(tokenizer=_lowerCamelCase							,		feature_extractor=_lowerCamelCase	)

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

      lowercase							   =	processor.batch_decode(sequences=_lowerCamelCase	)
      lowercase							   =	tokenizer.batch_decode(_lowerCamelCase	)

      self.assertListEqual(_lowerCamelCase							,		_lowerCamelCase	)







    def       UpperCamelCase_				(      self	):
      lowercase							   =	self.get_feature_extractor()
      lowercase							   =	self.get_tokenizer()

      lowercase							   =	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       UpperCamelCase_				(      self	):
      lowercase							   =	self.get_feature_extractor(padding_side='left'	)
      lowercase							   =	self.get_tokenizer()

      lowercase							   =	MusicgenProcessor(tokenizer=_lowerCamelCase							,		feature_extractor=_lowerCamelCase	)

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

      lowercase							   =	np.asarray(floats_list((3, 2_0)	)	)[:, None, :]
      lowercase							   =	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)	)










"""simple docstring"""



def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  Dict		, __snake_case      :  str   ):





  '''simple docstring'''





  lowercase							   =	1
  while b > 0:
    if b & 1:
      res *= a

    a *= a
    b >>= 1

  return res
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  int		, __snake_case      :  List[str]		, __snake_case      :  str   ):





  '''simple docstring'''





  lowercase							   =	1
  while b > 0:
    if b & 1:
      lowercase							   =	((res % c) * (a % c)) % c

    a *= a
    b >>= 1

  return res


