



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


a_								=   random.Random()





def 						a__     (						_UpperCamelCase     :	Any	,_UpperCamelCase     :	Optional[int]=1.0	,_UpperCamelCase     :	Optional[int]=None	,_UpperCamelCase     :	Optional[Any]=None							):
   if rng is None:
      __lowerCamelCase  							=      global_rng

   __lowerCamelCase  							=      []
   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				):




 def     lowerCamelCase (  self			):



    '''simple docstring'''
    __lowerCamelCase  							=      '''facebook/musicgen-small'''
    __lowerCamelCase  							=      tempfile.mkdtemp()




 def     lowerCamelCase (  self		,			**__UpperCAmelCase			):



    '''simple docstring'''
    return TaTokenizer.from_pretrained(self.checkpoint		,			**__UpperCAmelCase			)




 def     lowerCamelCase (  self		,			**__UpperCAmelCase			):



    '''simple docstring'''
    return EncodecFeatureExtractor.from_pretrained(self.checkpoint		,			**__UpperCAmelCase			)




 def     lowerCamelCase (  self			):



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




 def     lowerCamelCase (  self			):



    '''simple docstring'''
    __lowerCamelCase  							=      self.get_tokenizer()
    __lowerCamelCase  							=      self.get_feature_extractor()

    __lowerCamelCase  							=      MusicgenProcessor(tokenizer=__UpperCAmelCase		,			feature_extractor=__UpperCAmelCase			)

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

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

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




 def     lowerCamelCase (  self			):



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

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

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

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

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




 def     lowerCamelCase (  self			):



    '''simple docstring'''
    __lowerCamelCase  							=      self.get_feature_extractor()
    __lowerCamelCase  							=      self.get_tokenizer()

    __lowerCamelCase  							=      MusicgenProcessor(tokenizer=__UpperCAmelCase		,			feature_extractor=__UpperCAmelCase			)

    __lowerCamelCase  							=      floats_list((3, 1000)			)

    __lowerCamelCase  							=      feature_extractor(__UpperCAmelCase		,			return_tensors='''np'''			)
    __lowerCamelCase  							=      processor(__UpperCAmelCase		,			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			):



    '''simple docstring'''
    __lowerCamelCase  							=      self.get_feature_extractor()
    __lowerCamelCase  							=      self.get_tokenizer()

    __lowerCamelCase  							=      MusicgenProcessor(tokenizer=__UpperCAmelCase		,			feature_extractor=__UpperCAmelCase			)

    __lowerCamelCase  							=      '''This is a test string'''

    __lowerCamelCase  							=      processor(text=__UpperCAmelCase			)

    __lowerCamelCase  							=      tokenizer(__UpperCAmelCase			)

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




 def     lowerCamelCase (  self			):



    '''simple docstring'''
    __lowerCamelCase  							=      self.get_feature_extractor()
    __lowerCamelCase  							=      self.get_tokenizer()

    __lowerCamelCase  							=      MusicgenProcessor(tokenizer=__UpperCAmelCase		,			feature_extractor=__UpperCAmelCase			)

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

    __lowerCamelCase  							=      processor.batch_decode(sequences=__UpperCAmelCase			)
    __lowerCamelCase  							=      tokenizer.batch_decode(__UpperCAmelCase			)

    self.assertListEqual(__UpperCAmelCase		,			__UpperCAmelCase			)




 def     lowerCamelCase (  self			):



    '''simple docstring'''
    __lowerCamelCase  							=      self.get_feature_extractor()
    __lowerCamelCase  							=      self.get_tokenizer()

    __lowerCamelCase  							=      MusicgenProcessor(tokenizer=__UpperCAmelCase		,			feature_extractor=__UpperCAmelCase			)

    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			):



    '''simple docstring'''
    __lowerCamelCase  							=      self.get_feature_extractor(padding_side='''left'''			)
    __lowerCamelCase  							=      self.get_tokenizer()

    __lowerCamelCase  							=      MusicgenProcessor(tokenizer=__UpperCAmelCase		,			feature_extractor=__UpperCAmelCase			)

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

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

    self.assertIsInstance(__UpperCAmelCase		,			__UpperCAmelCase			)

    for audio in decoded_audios:
       self.assertIsInstance(__UpperCAmelCase		,			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 platform
from argparse import ArgumentParser

import huggingface_hub
import pandas
import pyarrow

from datasets import __version__ as version
from datasets.commands import BaseDatasetsCLICommand





def 						a__     (						_UpperCamelCase     :	Optional[Any]							):
   return EnvironmentCommand()





class 	__lowerCAmelCase       (		lowerCAmelCase__				):




 @staticmethod
 def     lowerCamelCase (  __UpperCAmelCase			):



    '''simple docstring'''
    __lowerCamelCase  							=      parser.add_parser('''env'''		,			help='''Print relevant system environment info.'''			)
    download_parser.set_defaults(func=__UpperCAmelCase			)




 def     lowerCamelCase (  self			):



    '''simple docstring'''
    __lowerCamelCase  							=      {
        '''`datasets` version''': version,
        '''Platform''': platform.platform(),
        '''Python version''': platform.python_version(),
        '''Huggingface_hub version''': huggingface_hub.__version__,
        '''PyArrow version''': pyarrow.__version__,
        '''Pandas version''': pandas.__version__,
    }

    print('''\nCopy-and-paste the text below in your GitHub issue.\n'''			)
    print(self.format_dict(__UpperCAmelCase			)			)

    return info




 @staticmethod
 def     lowerCamelCase (  __UpperCAmelCase			):



    '''simple docstring'''
    return "\n".join([F"""- {prop}: {val}""" for prop, val in d.items()]			) + "\n"






