




import functools
import operator

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase__				:     Optional[Any]			       =							logging.get_logger(__name__)

lowerCamelCase__				:     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  lowerCamelCase_							(   _SCREAMING_SNAKE_CASE      ):


 '''simple docstring'''







 lowercase_       					=					"hubert"



 def __init__(							self						:	Optional[int]       ,       _lowerCAmelCase						:	Tuple=32       ,       _lowerCAmelCase						:	Optional[Any]=768       ,       _lowerCAmelCase						:	int=12       ,       _lowerCAmelCase						:	Optional[int]=12       ,       _lowerCAmelCase						:	Any=3_072       ,       _lowerCAmelCase						:	Optional[int]="gelu"       ,       _lowerCAmelCase						:	Tuple=0.1       ,       _lowerCAmelCase						:	List[str]=0.1       ,       _lowerCAmelCase						:	Tuple=0.1       ,       _lowerCAmelCase						:	int=True       ,       _lowerCAmelCase						:	List[Any]=0.0       ,       _lowerCAmelCase						:	Optional[int]=0.1       ,       _lowerCAmelCase						:	int=0.1       ,       _lowerCAmelCase						:	List[str]=0.02       ,       _lowerCAmelCase						:	Union[str, Any]=1E-5       ,       _lowerCAmelCase						:	List[str]="group"       ,       _lowerCAmelCase						:	Dict="gelu"       ,       _lowerCAmelCase						:	List[Any]=(512, 512, 512, 512, 512, 512, 512)       ,       _lowerCAmelCase						:	Tuple=(5, 2, 2, 2, 2, 2, 2)       ,       _lowerCAmelCase						:	Union[str, Any]=(10, 3, 3, 3, 3, 2, 2)       ,       _lowerCAmelCase						:	Optional[Any]=False       ,       _lowerCAmelCase						:	List[str]=128       ,       _lowerCAmelCase						:	Optional[Any]=16       ,       _lowerCAmelCase						:	Optional[int]=False       ,       _lowerCAmelCase						:	List[str]=True       ,       _lowerCAmelCase						:	List[Any]=0.05       ,       _lowerCAmelCase						:	List[Any]=10       ,       _lowerCAmelCase						:	Dict=2       ,       _lowerCAmelCase						:	List[str]=0.0       ,       _lowerCAmelCase						:	List[str]=10       ,       _lowerCAmelCase						:	Dict=0       ,       _lowerCAmelCase						:	int="sum"       ,       _lowerCAmelCase						:	List[Any]=False       ,       _lowerCAmelCase						:	List[str]=False       ,       _lowerCAmelCase						:	Any=256       ,       _lowerCAmelCase						:	int=0       ,       _lowerCAmelCase						:	Union[str, Any]=1       ,       _lowerCAmelCase						:	Optional[int]=2       ,       **_lowerCAmelCase						:	List[Any]       ,       ):
       super().__init__(**_lowerCAmelCase       ,       pad_token_id=_lowerCAmelCase       ,       bos_token_id=_lowerCAmelCase       ,       eos_token_id=_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_					=    hidden_size
       SCREAMING_SNAKE_CASE_					=    feat_extract_norm
       SCREAMING_SNAKE_CASE_					=    feat_extract_activation
       SCREAMING_SNAKE_CASE_					=    list(_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_					=    list(_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_					=    list(_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_					=    conv_bias
       SCREAMING_SNAKE_CASE_					=    num_conv_pos_embeddings
       SCREAMING_SNAKE_CASE_					=    num_conv_pos_embedding_groups
       SCREAMING_SNAKE_CASE_					=    len(self.conv_dim		)
       SCREAMING_SNAKE_CASE_					=    num_hidden_layers
       SCREAMING_SNAKE_CASE_					=    intermediate_size
       SCREAMING_SNAKE_CASE_					=    hidden_act
       SCREAMING_SNAKE_CASE_					=    num_attention_heads
       SCREAMING_SNAKE_CASE_					=    hidden_dropout
       SCREAMING_SNAKE_CASE_					=    attention_dropout
       SCREAMING_SNAKE_CASE_					=    activation_dropout
       SCREAMING_SNAKE_CASE_					=    feat_proj_layer_norm
       SCREAMING_SNAKE_CASE_					=    feat_proj_dropout
       SCREAMING_SNAKE_CASE_					=    final_dropout
       SCREAMING_SNAKE_CASE_					=    layerdrop
       SCREAMING_SNAKE_CASE_					=    layer_norm_eps
       SCREAMING_SNAKE_CASE_					=    initializer_range
       SCREAMING_SNAKE_CASE_					=    vocab_size
       SCREAMING_SNAKE_CASE_					=    do_stable_layer_norm
       SCREAMING_SNAKE_CASE_					=    use_weighted_layer_sum
       SCREAMING_SNAKE_CASE_					=    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
       SCREAMING_SNAKE_CASE_					=    apply_spec_augment
       SCREAMING_SNAKE_CASE_					=    mask_time_prob
       SCREAMING_SNAKE_CASE_					=    mask_time_length
       SCREAMING_SNAKE_CASE_					=    mask_time_min_masks
       SCREAMING_SNAKE_CASE_					=    mask_feature_prob
       SCREAMING_SNAKE_CASE_					=    mask_feature_length
       SCREAMING_SNAKE_CASE_					=    mask_feature_min_masks

       # ctc loss
       SCREAMING_SNAKE_CASE_					=    ctc_loss_reduction
       SCREAMING_SNAKE_CASE_					=    ctc_zero_infinity




 @property
 def    lowerCAmelCase_						(							self						:	List[Any]		):
       return functools.reduce(operator.mul       ,       self.conv_stride       ,       1		)





from collections import defaultdict

def       UpperCAmelCase_							(   __UpperCAmelCase		:			int = 5							)      ->				int:
      SCREAMING_SNAKE_CASE_					=    defaultdict(__UpperCAmelCase							)
      SCREAMING_SNAKE_CASE_					=    0

      while True:
            SCREAMING_SNAKE_CASE_					=    get_digits(__UpperCAmelCase							)
            freqs[digits].append(__UpperCAmelCase							)

            if len(freqs[digits]							) == max_base:
                  SCREAMING_SNAKE_CASE_					=    freqs[digits][0] ** 3
                  return base

            num += 1

def       UpperCAmelCase_							(   __UpperCAmelCase		:			int							)      ->				str:
      return "".join(sorted(str(num**3							)							)							)


if __name__ == "__main__":
   print(f'''{solution() = }''')