






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:]))








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	)
