code: import functools
  import operator
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  lowercase__    :       List[Any]						=			logging.get_logger(__name__)
  
  lowercase__    :       Optional[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      lowercase_						(						UpperCamelCase_		):
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  	UpperCAmelCase_						:      Optional[Any]     =       """hubert"""
  
  
  	def __init__(							self	,    __SCREAMING_SNAKE_CASE=32	,    __SCREAMING_SNAKE_CASE=768	,    __SCREAMING_SNAKE_CASE=12	,    __SCREAMING_SNAKE_CASE=12	,    __SCREAMING_SNAKE_CASE=3072	,    __SCREAMING_SNAKE_CASE="gelu"	,    __SCREAMING_SNAKE_CASE=0.1	,    __SCREAMING_SNAKE_CASE=0.1	,    __SCREAMING_SNAKE_CASE=0.1	,    __SCREAMING_SNAKE_CASE=True	,    __SCREAMING_SNAKE_CASE=0.0	,    __SCREAMING_SNAKE_CASE=0.1	,    __SCREAMING_SNAKE_CASE=0.1	,    __SCREAMING_SNAKE_CASE=0.0_2	,    __SCREAMING_SNAKE_CASE=1e-5	,    __SCREAMING_SNAKE_CASE="group"	,    __SCREAMING_SNAKE_CASE="gelu"	,    __SCREAMING_SNAKE_CASE=(512, 512, 512, 512, 512, 512, 512)	,    __SCREAMING_SNAKE_CASE=(5, 2, 2, 2, 2, 2, 2)	,    __SCREAMING_SNAKE_CASE=(10, 3, 3, 3, 3, 2, 2)	,    __SCREAMING_SNAKE_CASE=False	,    __SCREAMING_SNAKE_CASE=128	,    __SCREAMING_SNAKE_CASE=16	,    __SCREAMING_SNAKE_CASE=False	,    __SCREAMING_SNAKE_CASE=True	,    __SCREAMING_SNAKE_CASE=0.0_5	,    __SCREAMING_SNAKE_CASE=10	,    __SCREAMING_SNAKE_CASE=2	,    __SCREAMING_SNAKE_CASE=0.0	,    __SCREAMING_SNAKE_CASE=10	,    __SCREAMING_SNAKE_CASE=0	,    __SCREAMING_SNAKE_CASE="sum"	,    __SCREAMING_SNAKE_CASE=False	,    __SCREAMING_SNAKE_CASE=False	,    __SCREAMING_SNAKE_CASE=256	,    __SCREAMING_SNAKE_CASE=0	,    __SCREAMING_SNAKE_CASE=1	,    __SCREAMING_SNAKE_CASE=2	,    **__SCREAMING_SNAKE_CASE	,    )		->str:
  								super().__init__(**__SCREAMING_SNAKE_CASE	,    pad_token_id=__SCREAMING_SNAKE_CASE	,    bos_token_id=__SCREAMING_SNAKE_CASE	,    eos_token_id=__SCREAMING_SNAKE_CASE       )
  								lowerCAmelCase				=	hidden_size
  								lowerCAmelCase				=	feat_extract_norm
  								lowerCAmelCase				=	feat_extract_activation
  								lowerCAmelCase				=	list(__SCREAMING_SNAKE_CASE       )
  								lowerCAmelCase				=	list(__SCREAMING_SNAKE_CASE       )
  								lowerCAmelCase				=	list(__SCREAMING_SNAKE_CASE       )
  								lowerCAmelCase				=	conv_bias
  								lowerCAmelCase				=	num_conv_pos_embeddings
  								lowerCAmelCase				=	num_conv_pos_embedding_groups
  								lowerCAmelCase				=	len(self.conv_dim       )
  								lowerCAmelCase				=	num_hidden_layers
  								lowerCAmelCase				=	intermediate_size
  								lowerCAmelCase				=	hidden_act
  								lowerCAmelCase				=	num_attention_heads
  								lowerCAmelCase				=	hidden_dropout
  								lowerCAmelCase				=	attention_dropout
  								lowerCAmelCase				=	activation_dropout
  								lowerCAmelCase				=	feat_proj_layer_norm
  								lowerCAmelCase				=	feat_proj_dropout
  								lowerCAmelCase				=	final_dropout
  								lowerCAmelCase				=	layerdrop
  								lowerCAmelCase				=	layer_norm_eps
  								lowerCAmelCase				=	initializer_range
  								lowerCAmelCase				=	vocab_size
  								lowerCAmelCase				=	do_stable_layer_norm
  								lowerCAmelCase				=	use_weighted_layer_sum
  								lowerCAmelCase				=	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				=	apply_spec_augment
  								lowerCAmelCase				=	mask_time_prob
  								lowerCAmelCase				=	mask_time_length
  								lowerCAmelCase				=	mask_time_min_masks
  								lowerCAmelCase				=	mask_feature_prob
  								lowerCAmelCase				=	mask_feature_length
  								lowerCAmelCase				=	mask_feature_min_masks
  
  								# ctc loss
  								lowerCAmelCase				=	ctc_loss_reduction
  								lowerCAmelCase				=	ctc_zero_infinity
  
  
  
  
  	@property
  	def     SCREAMING_SNAKE_CASE_       (							self       )		->Optional[Any]:
  								return functools.reduce(operator.mul	,    self.conv_stride	,    1       )
  
  
  
  
style_context: import glob
  import os
  
  from get_test_info import get_tester_classes
  
  
  if __name__ == "__main__":
  	lowercase__    :       List[Any]						=			[]
  
  	lowercase__    :       Optional[Any]						=			os.path.join('''tests''', '''models''', '''**''', '''test_modeling_*.py''')
  	lowercase__    :       Optional[int]						=			glob.glob(pattern)
  	# TODO: deal with TF/Flax too
  	lowercase__    :       Dict						=			[
  	    x for x in test_files if not (x.startswith('''test_modeling_tf_''') or x.startswith('''test_modeling_flax_'''))
  	]
  
  	for test_file in test_files:
  		lowercase__    :       Tuple						=			get_tester_classes(test_file)
  		for tester_class in tester_classes:
  			# A few tester classes don't have `parent` parameter in `__init__`.
  			# TODO: deal this better
  			try:
  				lowercase__    :       Union[str, Any]						=			tester_class(parent=None)
  			except Exception:
  				continue
  			if hasattr(tester, '''get_config'''):
  				lowercase__    :       Union[str, Any]						=			tester.get_config()
  				for k, v in config.to_dict().items():
  					if isinstance(v, int):
  						lowercase__    :       int						=			None
  						if k in ["vocab_size"]:
  							lowercase__    :       Optional[int]						=			1_0_0
  						elif k in ["max_position_embeddings"]:
  							lowercase__    :       Union[str, Any]						=			1_2_8
  						elif k in ["hidden_size", "d_model"]:
  							lowercase__    :       Optional[Any]						=			4_0
  						elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
  							lowercase__    :       Dict						=			5
  						if target is not None and v > target:
  							failures.append(
  							    f'{tester_class.__name__} will produce a `config` of type `{config.__class__.__name__}`'
  							    f' with config["{k}"] = {v} which is too large for testing! Set its value to be smaller'
  							    f' than {target}.'
  							)
  
  	if len(failures) > 0:
  		raise Exception(f'There were {len(failures)} failures:\n' + '''\n'''.join(failures))
  
  
  
  