code: 
  
  
  '''simple docstring'''
  
  
  
  
  import functools
  import operator
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  __lowercase  :      Dict      		=				logging.get_logger(__name__)
  
  __lowercase  :      Union[str, Any]      		=				{
      """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   ( a__   ):
  							"""simple docstring"""
  
  
  
  
  
  							__a												=     '''hubert'''
  
  
  
  
  
  
  
  							def __init__(   self			,				__A=32			,				__A=768			,				__A=12			,				__A=12			,				__A=3072			,				__A="gelu"			,				__A=0.1			,				__A=0.1			,				__A=0.1			,				__A=True			,				__A=0.0			,				__A=0.1			,				__A=0.1			,				__A=0.02			,				__A=1E-5			,				__A="group"			,				__A="gelu"			,				__A=(512, 512, 512, 512, 512, 512, 512)			,				__A=(5, 2, 2, 2, 2, 2, 2)			,				__A=(10, 3, 3, 3, 3, 2, 2)			,				__A=False			,				__A=128			,				__A=16			,				__A=False			,				__A=True			,				__A=0.05			,				__A=10			,				__A=2			,				__A=0.0			,				__A=10			,				__A=0			,				__A="sum"			,				__A=False			,				__A=False			,				__A=256			,				__A=0			,				__A=1			,				__A=2			,				**__A			,				)     ->Union[str, Any]:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											super().__init__(**__A			,				pad_token_id=__A			,				bos_token_id=__A			,				eos_token_id=__A	)
  											__lowerCamelCase		:      Tuple											=					hidden_size
  											__lowerCamelCase		:      Any											=					feat_extract_norm
  											__lowerCamelCase		:      Optional[int]											=					feat_extract_activation
  											__lowerCamelCase		:      Dict											=					list(__A	)
  											__lowerCamelCase		:      Tuple											=					list(__A	)
  											__lowerCamelCase		:      Any											=					list(__A	)
  											__lowerCamelCase		:      List[str]											=					conv_bias
  											__lowerCamelCase		:      Tuple											=					num_conv_pos_embeddings
  											__lowerCamelCase		:      Tuple											=					num_conv_pos_embedding_groups
  											__lowerCamelCase		:      Union[str, Any]											=					len(self.conv_dim	)
  											__lowerCamelCase		:      str											=					num_hidden_layers
  											__lowerCamelCase		:      Optional[int]											=					intermediate_size
  											__lowerCamelCase		:      Any											=					hidden_act
  											__lowerCamelCase		:      Optional[Any]											=					num_attention_heads
  											__lowerCamelCase		:      List[Any]											=					hidden_dropout
  											__lowerCamelCase		:      List[str]											=					attention_dropout
  											__lowerCamelCase		:      Optional[Any]											=					activation_dropout
  											__lowerCamelCase		:      str											=					feat_proj_layer_norm
  											__lowerCamelCase		:      Dict											=					feat_proj_dropout
  											__lowerCamelCase		:      str											=					final_dropout
  											__lowerCamelCase		:      Any											=					layerdrop
  											__lowerCamelCase		:      Any											=					layer_norm_eps
  											__lowerCamelCase		:      Optional[int]											=					initializer_range
  											__lowerCamelCase		:      Union[str, Any]											=					vocab_size
  											__lowerCamelCase		:      int											=					do_stable_layer_norm
  											__lowerCamelCase		:      str											=					use_weighted_layer_sum
  											__lowerCamelCase		:      int											=					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
  											__lowerCamelCase		:      Optional[Any]											=					apply_spec_augment
  											__lowerCamelCase		:      Optional[int]											=					mask_time_prob
  											__lowerCamelCase		:      Union[str, Any]											=					mask_time_length
  											__lowerCamelCase		:      str											=					mask_time_min_masks
  											__lowerCamelCase		:      Tuple											=					mask_feature_prob
  											__lowerCamelCase		:      Dict											=					mask_feature_length
  											__lowerCamelCase		:      Tuple											=					mask_feature_min_masks
  
  											# ctc loss
  											__lowerCamelCase		:      Dict											=					ctc_loss_reduction
  											__lowerCamelCase		:      Tuple											=					ctc_zero_infinity
  
  
  
  
  
  
  
  							@property
  							def 		__SCREAMING_SNAKE_CASE(   self	)     ->Optional[Any]:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											return functools.reduce(operator.mul			,				self.conv_stride			,				1	)
  
  
  
  
  
  
style_context: 
  
  
  '''simple docstring'''
  
  
  
  
  def 							a_       (						lowercase    )			->str:
  
  
  
  
  
  
  				'''simple docstring'''
  
  				return " ".join(sorted(set(sentence.split()    )    )    )
  
  
  if __name__ == "__main__":
  				import doctest
  
  				doctest.testmod()
  
  
  
  
  
  