
import logging

from transformers.configuration_utils import PretrainedConfig


_lowercase											=    logging.getLogger(__name__)


class 			lowercase_		(      A       ):
       __lowerCamelCase				       =						"masked_bert"


       def __init__(    self						,       __A=30_522						,       __A=768						,       __A=12						,       __A=12						,       __A=3_072						,       __A="gelu"						,       __A=0.1						,       __A=0.1						,       __A=512						,       __A=2						,       __A=0.02						,       __A=1e-1_2						,       __A=0						,       __A="topK"						,       __A="constant"						,       __A=0.0						,       **__A						,       )						->    Tuple:
              super().__init__(pad_token_id=__A						,       **__A				)

              SCREAMING_SNAKE_CASE_							:				Dict		=vocab_size
              SCREAMING_SNAKE_CASE_							:				Any		=hidden_size
              SCREAMING_SNAKE_CASE_							:				int		=num_hidden_layers
              SCREAMING_SNAKE_CASE_							:				List[Any]		=num_attention_heads
              SCREAMING_SNAKE_CASE_							:				int		=hidden_act
              SCREAMING_SNAKE_CASE_							:				Optional[Any]		=intermediate_size
              SCREAMING_SNAKE_CASE_							:				Dict		=hidden_dropout_prob
              SCREAMING_SNAKE_CASE_							:				Any		=attention_probs_dropout_prob
              SCREAMING_SNAKE_CASE_							:				Tuple		=max_position_embeddings
              SCREAMING_SNAKE_CASE_							:				str		=type_vocab_size
              SCREAMING_SNAKE_CASE_							:				Optional[int]		=initializer_range
              SCREAMING_SNAKE_CASE_							:				Tuple		=layer_norm_eps
              SCREAMING_SNAKE_CASE_							:				Dict		=pruning_method
              SCREAMING_SNAKE_CASE_							:				List[Any]		=mask_init
              SCREAMING_SNAKE_CASE_							:				List[Any]		=mask_scale


def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     list				)			->						float:
       SCREAMING_SNAKE_CASE_							:				Dict		=0
       while len(UpperCAmelCase_				) > 1:
              SCREAMING_SNAKE_CASE_							:				Tuple		=0
              # Consider two files with minimum cost to be merged
              for _ in range(2				):
                     SCREAMING_SNAKE_CASE_							:				int		=files.index(min(UpperCAmelCase_				)				)
                     temp += files[min_index]
                     files.pop(UpperCAmelCase_				)
              files.append(UpperCAmelCase_				)
              optimal_merge_cost += temp
       return optimal_merge_cost


if __name__ == "__main__":
 import doctest

 doctest.testmod()
