


import os
from collections.abc import Iterator







def     lowerCAmelCase_					( __lowerCamelCase = "."     ):
							for dir_path, dir_names, filenames in os.walk(__lowerCamelCase     ):
														__snake_case		:      Optional[int]										=       [d for d in dir_names if d != "scripts" and d[0] not in "._"]
														for filename in filenames:
																					if filename == "__init__.py":
																												continue
																					if os.path.splitext(__lowerCamelCase     )[1] in (".py", ".ipynb"):
																												yield os.path.join(__lowerCamelCase							,     __lowerCamelCase     ).lstrip("./"     )







def     lowerCAmelCase_					( __lowerCamelCase     ):
							return F'{i * "  "}*' if i else "\n##"







def     lowerCAmelCase_					( __lowerCamelCase							,     __lowerCamelCase     ):
							__snake_case		:      List[Any]										=       old_path.split(os.sep     )
							for i, new_part in enumerate(new_path.split(os.sep     )     ):
														if (i + 1 > len(__lowerCamelCase     ) or old_parts[i] != new_part) and new_part:
																					print(F'{md_prefix(__lowerCamelCase     )} {new_part.replace("_"							,     " "     ).title()}'     )
							return new_path







def     lowerCAmelCase_					( __lowerCamelCase = "."     ):
							__snake_case		:      List[str]										=       ""
							for filepath in sorted(good_file_paths(__lowerCamelCase     )     ):
														__snake_case		:      List[Any]										=       os.path.split(__lowerCamelCase     )
														if filepath != old_path:
																					__snake_case		:      int										=       print_path(__lowerCamelCase							,     __lowerCamelCase     )
														__snake_case		:      Union[str, Any]										=       (filepath.count(os.sep     ) + 1) if filepath else 0
														__snake_case		:      str										=       F'{filepath}/{filename}'.replace(" "							,     "%20"     )
														__snake_case		:      List[Any]										=       os.path.splitext(filename.replace("_"							,     " "     ).title()     )[0]
														print(F'{md_prefix(__lowerCamelCase     )} [{filename}]({url})'     )


if __name__ == "__main__":
			print_directory_md(".")





import logging

from transformers.configuration_utils import PretrainedConfig


_snake_case					:		Optional[Any]      =    logging.getLogger(__name__)

class     a		(_lowerCAmelCase				):




							"""simple docstring"""


							__UpperCAmelCase   :							Tuple					  =  "masked_bert"

							def __init__(							self	:  Optional[int]   ,     lowerCamelCase	:  Any=30522   ,     lowerCamelCase	:  Tuple=768   ,     lowerCamelCase	:  str=12   ,     lowerCamelCase	:  Dict=12   ,     lowerCamelCase	:  List[str]=3072   ,     lowerCamelCase	:  List[str]="gelu"   ,     lowerCamelCase	:  Any=0.1   ,     lowerCamelCase	:  Any=0.1   ,     lowerCamelCase	:  List[Any]=512   ,     lowerCamelCase	:  int=2   ,     lowerCamelCase	:  str=0.02   ,     lowerCamelCase	:  List[str]=1E-12   ,     lowerCamelCase	:  Any=0   ,     lowerCamelCase	:  Dict="topK"   ,     lowerCamelCase	:  List[Any]="constant"   ,     lowerCamelCase	:  Dict=0.0   ,     **lowerCamelCase	:  List[Any]   ,     )     ->   Dict:
														super().__init__(pad_token_id=lowerCamelCase   ,     **lowerCamelCase    )

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

