


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


__lowerCAmelCase									=				random.Random()




def   snake_case_	(    snake_case     ,				snake_case=1.0     ,				snake_case=None     ,				snake_case=None	)    ->							Any:
       if rng is None:
              lowercase__:  Dict         =  global_rng

       lowercase__:  List[Any]         =  []
       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 						SCREAMING_SNAKE_CASE__  (  self					)   ->							str:




        '''simple docstring'''
        lowercase__:  Union[str, Any]         =  'facebook/musicgen-small'
        lowercase__:  Union[str, Any]         =  tempfile.mkdtemp()
 def 						SCREAMING_SNAKE_CASE__  (  self							,					**lowerCAmelCase__					)   ->							str:




        '''simple docstring'''
        return TaTokenizer.from_pretrained(self.checkpoint							,					**lowerCAmelCase__					)
 def 						SCREAMING_SNAKE_CASE__  (  self							,					**lowerCAmelCase__					)   ->							Union[str, Any]:




        '''simple docstring'''
        return EncodecFeatureExtractor.from_pretrained(self.checkpoint							,					**lowerCAmelCase__					)
 def 						SCREAMING_SNAKE_CASE__  (  self					)   ->							Any:




        '''simple docstring'''
        shutil.rmtree(self.tmpdirname					)
 def 						SCREAMING_SNAKE_CASE__  (  self					)   ->							str:




        '''simple docstring'''
        lowercase__:  Optional[int]         =  self.get_tokenizer()
        lowercase__:  List[Any]         =  self.get_feature_extractor()

        lowercase__:  Optional[Any]         =  MusicgenProcessor(tokenizer=lowerCAmelCase__							,					feature_extractor=lowerCAmelCase__					)

        processor.save_pretrained(self.tmpdirname					)
        lowercase__:  Union[str, Any]         =  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 						SCREAMING_SNAKE_CASE__  (  self					)   ->							List[Any]:




        '''simple docstring'''
        lowercase__:  Dict         =  MusicgenProcessor(tokenizer=self.get_tokenizer()							,					feature_extractor=self.get_feature_extractor()					)
        processor.save_pretrained(self.tmpdirname					)

        lowercase__:  int         =  self.get_tokenizer(bos_token='(BOS)'							,					eos_token='(EOS)'					)
        lowercase__:  Optional[int]         =  self.get_feature_extractor(do_normalize=lowerCAmelCase__							,					padding_value=1.0					)

        lowercase__:  List[Any]         =  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 						SCREAMING_SNAKE_CASE__  (  self					)   ->							str:




        '''simple docstring'''
        lowercase__:  Any         =  self.get_feature_extractor()
        lowercase__:  List[str]         =  self.get_tokenizer()

        lowercase__:  List[Any]         =  MusicgenProcessor(tokenizer=lowerCAmelCase__							,					feature_extractor=lowerCAmelCase__					)

        lowercase__:  Dict         =  floats_list((3, 1_000)					)

        lowercase__:  Tuple         =  feature_extractor(lowerCAmelCase__							,					return_tensors='np'					)
        lowercase__:  Optional[Any]         =  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 						SCREAMING_SNAKE_CASE__  (  self					)   ->							Dict:




        '''simple docstring'''
        lowercase__:  Tuple         =  self.get_feature_extractor()
        lowercase__:  Union[str, Any]         =  self.get_tokenizer()

        lowercase__:  str         =  MusicgenProcessor(tokenizer=lowerCAmelCase__							,					feature_extractor=lowerCAmelCase__					)

        lowercase__:  str         =  'This is a test string'

        lowercase__:  Optional[int]         =  processor(text=lowerCAmelCase__					)

        lowercase__:  Optional[Any]         =  tokenizer(lowerCAmelCase__					)

        for key in encoded_tok.keys():
               self.assertListEqual(encoded_tok[key]							,					encoded_processor[key]					)
 def 						SCREAMING_SNAKE_CASE__  (  self					)   ->							Optional[int]:




        '''simple docstring'''
        lowercase__:  Optional[Any]         =  self.get_feature_extractor()
        lowercase__:  int         =  self.get_tokenizer()

        lowercase__:  Union[str, Any]         =  MusicgenProcessor(tokenizer=lowerCAmelCase__							,					feature_extractor=lowerCAmelCase__					)

        lowercase__:  Optional[Any]         =  [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        lowercase__:  Dict         =  processor.batch_decode(sequences=lowerCAmelCase__					)
        lowercase__:  Dict         =  tokenizer.batch_decode(lowerCAmelCase__					)

        self.assertListEqual(lowerCAmelCase__							,					lowerCAmelCase__					)
 def 						SCREAMING_SNAKE_CASE__  (  self					)   ->							Union[str, Any]:




        '''simple docstring'''
        lowercase__:  Union[str, Any]         =  self.get_feature_extractor()
        lowercase__:  Any         =  self.get_tokenizer()

        lowercase__:  Optional[int]         =  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 						SCREAMING_SNAKE_CASE__  (  self					)   ->							List[Any]:




        '''simple docstring'''
        lowercase__:  Union[str, Any]         =  self.get_feature_extractor(padding_side='left'					)
        lowercase__:  Tuple         =  self.get_tokenizer()

        lowercase__:  str         =  MusicgenProcessor(tokenizer=lowerCAmelCase__							,					feature_extractor=lowerCAmelCase__					)

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

        lowercase__:  Any         =  np.asarray(floats_list((3, 20)					)					)[:, None, :]
        lowercase__:  List[str]         =  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, 10)					)
        self.assertTrue(decoded_audios[1].shape == (1, 15)					)
        self.assertTrue(decoded_audios[2].shape == (1, 20)					)






from .hash_table import HashTable
from .number_theory.prime_numbers import is_prime, next_prime





class     __a     (       __UpperCamelCase ):
 def __init__(  self							,					*lowerCAmelCase__							,					**lowerCAmelCase__					)   ->							Any:




        '''simple docstring'''
        super().__init__(*lowerCAmelCase__							,					**lowerCAmelCase__					)
 def 						SCREAMING_SNAKE_CASE__  (  self							,					lowerCAmelCase__							,					lowerCAmelCase__					)   ->							Union[str, Any]:




        '''simple docstring'''
        lowercase__:  str         =  (
            next_prime(value % self.size_table					)
            if not is_prime(value % self.size_table					)
            else value % self.size_table
        )  # gt = bigger than
        return next_prime_gt - (data % next_prime_gt)
 def 						SCREAMING_SNAKE_CASE__  (  self							,					lowerCAmelCase__							,					lowerCAmelCase__							,					lowerCAmelCase__					)   ->							Union[str, Any]:




        '''simple docstring'''
        return (increment * self.__hash_function_a(lowerCAmelCase__							,					lowerCAmelCase__					)) % self.size_table
 def 						SCREAMING_SNAKE_CASE__  (  self							,					lowerCAmelCase__							,					lowerCAmelCase__=None					)   ->							str:




        '''simple docstring'''
        lowercase__:  Dict         =  1
        lowercase__:  str         =  self.hash_function(lowerCAmelCase__					)

        while self.values[new_key] is not None and self.values[new_key] != key:
               lowercase__:  List[Any]         =  (
                   self.__hash_double_function(lowerCAmelCase__							,					lowerCAmelCase__							,					lowerCAmelCase__					)
                   if self.balanced_factor() >= self.lim_charge
                   else None
               )
               if new_key is None:
                      break
               else:
                      i += 1

        return new_key


