code: 
  
  
  
  
  
  
  import argparse
  import os
  import sys
  import urllib.request
  import zipfile
  
  
  lowerCamelCase										=  ["""CoLA""", """SST""", """MRPC""", """QQP""", """STS""", """MNLI""", """SNLI""", """QNLI""", """RTE""", """WNLI""", """diagnostic"""]
  lowerCamelCase										=  {
      """CoLA""": """https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FCoLA.zip?alt=media&token=46d5e637-3411-4188-bc44-5809b5bfb5f4""",
      """SST""": """https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSST-2.zip?alt=media&token=aabc5f6b-e466-44a2-b9b4-cf6337f84ac8""",
      """MRPC""": """https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2Fmrpc_dev_ids.tsv?alt=media&token=ec5c0836-31d5-48f4-b431-7480817f1adc""",
      """QQP""": """https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FQQP.zip?alt=media&token=700c6acf-160d-4d89-81d1-de4191d02cb5""",
      """STS""": """https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSTS-B.zip?alt=media&token=bddb94a7-8706-4e0d-a694-1109e12273b5""",
      """MNLI""": """https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FMNLI.zip?alt=media&token=50329ea1-e339-40e2-809c-10c40afff3ce""",
      """SNLI""": """https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSNLI.zip?alt=media&token=4afcfbb2-ff0c-4b2d-a09a-dbf07926f4df""",
      """QNLI""": """https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FQNLIv2.zip?alt=media&token=6fdcf570-0fc5-4631-8456-9505272d1601""",
      """RTE""": """https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FRTE.zip?alt=media&token=5efa7e85-a0bb-4f19-8ea2-9e1840f077fb""",
      """WNLI""": """https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FWNLI.zip?alt=media&token=068ad0a0-ded7-4bd7-99a5-5e00222e0faf""",
      """diagnostic""": """https://storage.googleapis.com/mtl-sentence-representations.appspot.com/tsvsWithoutLabels%2FAX.tsv?GoogleAccessId=firebase-adminsdk-0khhl@mtl-sentence-representations.iam.gserviceaccount.com&Expires=2498860800&Signature=DuQ2CSPt2Yfre0C%2BiISrVYrIFaZH1Lc7hBVZDD4ZyR7fZYOMNOUGpi8QxBmTNOrNPjR3z1cggo7WXFfrgECP6FBJSsURv8Ybrue8Ypt%2FTPxbuJ0Xc2FhDi%2BarnecCBFO77RSbfuz%2Bs95hRrYhTnByqu3U%2FYZPaj3tZt5QdfpH2IUROY8LiBXoXS46LE%2FgOQc%2FKN%2BA9SoscRDYsnxHfG0IjXGwHN%2Bf88q6hOmAxeNPx6moDulUF6XMUAaXCSFU%2BnRO2RDL9CapWxj%2BDl7syNyHhB7987hZ80B%2FwFkQ3MEs8auvt5XW1%2Bd4aCU7ytgM69r8JDCwibfhZxpaa4gd50QXQ%3D%3D""",
  }
  
  lowerCamelCase										=  """https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_train.txt"""
  lowerCamelCase										=  """https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_test.txt"""
  def        UpperCAmelCase      (   _lowercase,      _lowercase      ):
  
  
        '''simple docstring'''
  
  
  
        print(f'''Downloading and extracting {task}...'''      )
        _lowercase     =	f'''{task}.zip'''
        urllib.request.urlretrieve(TASKaPATH[task],      _lowercase      )
        with zipfile.ZipFile(_lowercase      ) as zip_ref:
              zip_ref.extractall(_lowercase      )
        os.remove(_lowercase      )
        print('\tCompleted!'      )
  def        UpperCAmelCase      (   _lowercase,      _lowercase      ):
  
  
        '''simple docstring'''
  
  
  
        print('Processing MRPC...'      )
        _lowercase     =	os.path.join(_lowercase,      'MRPC'      )
        if not os.path.isdir(_lowercase      ):
              os.mkdir(_lowercase      )
        if path_to_data:
              _lowercase     =	os.path.join(_lowercase,      'msr_paraphrase_train.txt'      )
              _lowercase     =	os.path.join(_lowercase,      'msr_paraphrase_test.txt'      )
        else:
              print('Local MRPC data not specified, downloading data from %s' % MRPC_TRAIN      )
              _lowercase     =	os.path.join(_lowercase,      'msr_paraphrase_train.txt'      )
              _lowercase     =	os.path.join(_lowercase,      'msr_paraphrase_test.txt'      )
              urllib.request.urlretrieve(_lowercase,      _lowercase      )
              urllib.request.urlretrieve(_lowercase,      _lowercase      )
        if not os.path.isfile(_lowercase      ):
              raise ValueError(f'''Train data not found at {mrpc_train_file}'''      )
        if not os.path.isfile(_lowercase      ):
              raise ValueError(f'''Test data not found at {mrpc_test_file}'''      )
        urllib.request.urlretrieve(TASKaPATH['MRPC'],      os.path.join(_lowercase,      'dev_ids.tsv'      )      )
  
        _lowercase     =	[]
        with open(os.path.join(_lowercase,      'dev_ids.tsv'      ),      encoding='utf8'      ) as ids_fh:
              for row in ids_fh:
                    dev_ids.append(row.strip().split('\t'      )      )
  
        with open(_lowercase,      encoding='utf8'      ) as data_fh, open(
            os.path.join(_lowercase,      'train.tsv'      ),      'w',      encoding='utf8'      ) as train_fh, open(os.path.join(_lowercase,      'dev.tsv'      ),      'w',      encoding='utf8'      ) as dev_fh:
              _lowercase     =	data_fh.readline()
              train_fh.write(_lowercase      )
              dev_fh.write(_lowercase      )
              for row in data_fh:
                    _lowercase     =	row.strip().split('\t'      )
                    if [ida, ida] in dev_ids:
                          dev_fh.write('%s\t%s\t%s\t%s\t%s\n' % (label, ida, ida, sa, sa)      )
                    else:
                          train_fh.write('%s\t%s\t%s\t%s\t%s\n' % (label, ida, ida, sa, sa)      )
  
        with open(_lowercase,      encoding='utf8'      ) as data_fh, open(
            os.path.join(_lowercase,      'test.tsv'      ),      'w',      encoding='utf8'      ) as test_fh:
              _lowercase     =	data_fh.readline()
              test_fh.write('index\t#1 ID\t#2 ID\t#1 String\t#2 String\n'      )
              for idx, row in enumerate(_lowercase      ):
                    _lowercase     =	row.strip().split('\t'      )
                    test_fh.write('%d\t%s\t%s\t%s\t%s\n' % (idx, ida, ida, sa, sa)      )
        print('\tCompleted!'      )
  def        UpperCAmelCase      (   _lowercase      ):
  
  
        '''simple docstring'''
  
  
  
        print('Downloading and extracting diagnostic...'      )
        if not os.path.isdir(os.path.join(_lowercase,      'diagnostic'      )      ):
              os.mkdir(os.path.join(_lowercase,      'diagnostic'      )      )
        _lowercase     =	os.path.join(_lowercase,      'diagnostic',      'diagnostic.tsv'      )
        urllib.request.urlretrieve(TASKaPATH['diagnostic'],      _lowercase      )
        print('\tCompleted!'      )
        return
  def        UpperCAmelCase      (   _lowercase      ):
  
  
        '''simple docstring'''
  
  
  
        _lowercase     =	task_names.split(','      )
        if "all" in task_names:
              _lowercase     =	TASKS
        else:
              _lowercase     =	[]
              for task_name in task_names:
                    if task_name not in TASKS:
                          raise ValueError(f'''Task {task_name} not found!'''      )
                    tasks.append(_lowercase      )
        return tasks
  def        UpperCAmelCase      (   _lowercase      ):
  
  
        '''simple docstring'''
  
  
  
        _lowercase     =	argparse.ArgumentParser()
        parser.add_argument('--data_dir',      help='directory to save data to',      type=_lowercase,      default='glue_data'      )
        parser.add_argument(
            '--tasks',      help='tasks to download data for as a comma separated string',      type=_lowercase,      default='all'      )
        parser.add_argument(
            '--path_to_mrpc',      help='path to directory containing extracted MRPC data, msr_paraphrase_train.txt and msr_paraphrase_text.txt',      type=_lowercase,      default='',      )
        _lowercase     =	parser.parse_args(_lowercase      )
  
        if not os.path.isdir(args.data_dir      ):
              os.mkdir(args.data_dir      )
        _lowercase     =	get_tasks(args.tasks      )
  
        for task in tasks:
              if task == "MRPC":
                    format_mrpc(args.data_dir,      args.path_to_mrpc      )
              elif task == "diagnostic":
                    download_diagnostic(args.data_dir      )
              else:
                    download_and_extract(_lowercase,      args.data_dir      )
  
  
  if __name__ == "__main__":
     sys.exit(main(sys.argv[1:]))
  
style_context: 
  
  
  
  
  
  
  import functools
  import operator
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  lowerCamelCase										=  logging.get_logger(__name__)
  
  lowerCamelCase										=  {
      '''facebook/hubert-base-ls960''': '''https://huggingface.co/facebook/hubert-base-ls960/resolve/main/config.json''',
      # See all Hubert models at https://huggingface.co/models?filter=hubert
  }
  
  class 					snake_case_							(       lowercase_      ):
  
  
  
  
  
  
  
     """simple docstring"""
  
  
  
     __lowerCAmelCase      =						"""hubert"""
  
     def __init__(    self:	Any   ,       snake_case__:	str=32   ,       snake_case__:	int=768   ,       snake_case__:	Dict=12   ,       snake_case__:	Optional[int]=12   ,       snake_case__:	List[str]=3_072   ,       snake_case__:	Optional[Any]="gelu"   ,       snake_case__:	Optional[int]=0.1   ,       snake_case__:	List[str]=0.1   ,       snake_case__:	Optional[int]=0.1   ,       snake_case__:	List[str]=True   ,       snake_case__:	Union[str, Any]=0.0   ,       snake_case__:	Union[str, Any]=0.1   ,       snake_case__:	List[str]=0.1   ,       snake_case__:	List[Any]=0.02   ,       snake_case__:	Dict=1E-5   ,       snake_case__:	Any="group"   ,       snake_case__:	Union[str, Any]="gelu"   ,       snake_case__:	List[str]=(512, 512, 512, 512, 512, 512, 512)   ,       snake_case__:	Union[str, Any]=(5, 2, 2, 2, 2, 2, 2)   ,       snake_case__:	Any=(10, 3, 3, 3, 3, 2, 2)   ,       snake_case__:	int=False   ,       snake_case__:	Any=128   ,       snake_case__:	Dict=16   ,       snake_case__:	Optional[Any]=False   ,       snake_case__:	Tuple=True   ,       snake_case__:	int=0.05   ,       snake_case__:	List[Any]=10   ,       snake_case__:	Tuple=2   ,       snake_case__:	List[Any]=0.0   ,       snake_case__:	Optional[int]=10   ,       snake_case__:	Optional[int]=0   ,       snake_case__:	Union[str, Any]="sum"   ,       snake_case__:	Union[str, Any]=False   ,       snake_case__:	int=False   ,       snake_case__:	Any=256   ,       snake_case__:	Union[str, Any]=0   ,       snake_case__:	Optional[int]=1   ,       snake_case__:	List[str]=2   ,       **snake_case__:	Optional[int]   ,       )  ->		Any:
  
  
         """simple docstring"""
  
  
  
         super().__init__(**snake_case__   ,       pad_token_id=snake_case__   ,       bos_token_id=snake_case__   ,       eos_token_id=snake_case__	)
         _lowercase     =	hidden_size
         _lowercase     =	feat_extract_norm
         _lowercase     =	feat_extract_activation
         _lowercase     =	list(snake_case__	)
         _lowercase     =	list(snake_case__	)
         _lowercase     =	list(snake_case__	)
         _lowercase     =	conv_bias
         _lowercase     =	num_conv_pos_embeddings
         _lowercase     =	num_conv_pos_embedding_groups
         _lowercase     =	len(self.conv_dim	)
         _lowercase     =	num_hidden_layers
         _lowercase     =	intermediate_size
         _lowercase     =	hidden_act
         _lowercase     =	num_attention_heads
         _lowercase     =	hidden_dropout
         _lowercase     =	attention_dropout
         _lowercase     =	activation_dropout
         _lowercase     =	feat_proj_layer_norm
         _lowercase     =	feat_proj_dropout
         _lowercase     =	final_dropout
         _lowercase     =	layerdrop
         _lowercase     =	layer_norm_eps
         _lowercase     =	initializer_range
         _lowercase     =	vocab_size
         _lowercase     =	do_stable_layer_norm
         _lowercase     =	use_weighted_layer_sum
         _lowercase     =	classifier_proj_size
  
         if (
             (len(self.conv_stride	) != self.num_feat_extract_layers)
             or (len(self.conv_kernel	) != self.num_feat_extract_layers)
             or (len(self.conv_dim	) != self.num_feat_extract_layers)
         ):
             raise ValueError(
                 'Configuration for convolutional layers is incorrect. It is required that `len(config.conv_dim)` =='
                 ' `len(config.conv_stride)` == `len(config.conv_kernel)`, but is `len(config.conv_dim) ='
                 f''' {len(self.conv_dim	)}`, `len(config.conv_stride) = {len(self.conv_stride	)}`,'''
                 f''' `len(config.conv_kernel) = {len(self.conv_kernel	)}`.'''	)
  
         # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
         _lowercase     =	apply_spec_augment
         _lowercase     =	mask_time_prob
         _lowercase     =	mask_time_length
         _lowercase     =	mask_time_min_masks
         _lowercase     =	mask_feature_prob
         _lowercase     =	mask_feature_length
         _lowercase     =	mask_feature_min_masks
  
         # ctc loss
         _lowercase     =	ctc_loss_reduction
         _lowercase     =	ctc_zero_infinity
  
     @property
     def 			SCREAMING_SNAKE_CASE__				(    self:	int	)  ->		Optional[int]:
  
  
         """simple docstring"""
  
  
  
         return functools.reduce(operator.mul   ,       self.conv_stride   ,       1	)
  