


"""simple docstring"""
import os
from collections.abc import Iterator







def 				_a			( _SCREAMING_SNAKE_CASE = "."			)      ->			Iterator[str]:
							for dir_path, dir_names, filenames in os.walk(_SCREAMING_SNAKE_CASE			):
														snake_case_          =						[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(_SCREAMING_SNAKE_CASE			)[1] in (".py", ".ipynb"):
																												yield os.path.join(_SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			).lstrip("""./"""			)







def 				_a			( _SCREAMING_SNAKE_CASE			)      ->			List[Any]:
							return f"""{i * "  "}*""" if i else "\n##"







def 				_a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			str:
							snake_case_          =						old_path.split(os.sep			)
							for i, new_part in enumerate(new_path.split(os.sep			)			):
														if (i + 1 > len(_SCREAMING_SNAKE_CASE			) or old_parts[i] != new_part) and new_part:
																					print(f"""{md_prefix(_SCREAMING_SNAKE_CASE			)} {new_part.replace("_"			,	" "			).title()}"""			)
							return new_path







def 				_a			( _SCREAMING_SNAKE_CASE = "."			)      ->			None:
							snake_case_          =						''''''
							for filepath in sorted(good_file_paths(_SCREAMING_SNAKE_CASE			)			):
														snake_case_          =						os.path.split(_SCREAMING_SNAKE_CASE			)
														if filepath != old_path:
																					snake_case_          =						print_path(_SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)
														snake_case_          =						(filepath.count(os.sep			) + 1) if filepath else 0
														snake_case_          =						f"""{filepath}/{filename}""".replace(""" """			,	"""%20"""			)
														snake_case_          =						os.path.splitext(filename.replace("""_"""			,	""" """			).title()			)[0]
														print(f"""{md_prefix(_SCREAMING_SNAKE_CASE			)} [{filename}]({url})"""			)


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







"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


__SCREAMING_SNAKE_CASE							:      Union[str, Any]						=      logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE							:      int						=      {
    'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json',
    # See all CANINE models at https://huggingface.co/models?filter=canine
}





class        __A       (snake_case__):





							'''simple docstring'''

							__lowercase:						List[str]							 =      """canine"""



							def __init__(			self							: Union[str, Any]						,    UpperCAmelCase_							: str=768						,    UpperCAmelCase_							: Union[str, Any]=12						,    UpperCAmelCase_							: Optional[Any]=12						,    UpperCAmelCase_							: Optional[Any]=3_072						,    UpperCAmelCase_							: List[Any]="gelu"						,    UpperCAmelCase_							: int=0.1						,    UpperCAmelCase_							: Any=0.1						,    UpperCAmelCase_							: List[str]=16_384						,    UpperCAmelCase_							: Tuple=16						,    UpperCAmelCase_							: int=0.02						,    UpperCAmelCase_							: Tuple=1E-12						,    UpperCAmelCase_							: str=0						,    UpperCAmelCase_							: int=0XE000						,    UpperCAmelCase_							: Optional[int]=0XE001						,    UpperCAmelCase_							: Dict=4						,    UpperCAmelCase_							: List[Any]=4						,    UpperCAmelCase_							: List[Any]=8						,    UpperCAmelCase_							: Dict=16_384						,    UpperCAmelCase_							: Optional[int]=128						,    **UpperCAmelCase_							: Any						,    )   ->int:



														"""simple docstring"""



														super().__init__(pad_token_id=UpperCAmelCase_						,    bos_token_id=UpperCAmelCase_						,    eos_token_id=UpperCAmelCase_						,    **UpperCAmelCase_    )

														snake_case_          =						max_position_embeddings
														snake_case_          =						hidden_size
														snake_case_          =						num_hidden_layers
														snake_case_          =						num_attention_heads
														snake_case_          =						intermediate_size
														snake_case_          =						hidden_act
														snake_case_          =						hidden_dropout_prob
														snake_case_          =						attention_probs_dropout_prob
														snake_case_          =						initializer_range
														snake_case_          =						type_vocab_size
														snake_case_          =						layer_norm_eps

														# Character config:
														snake_case_          =						downsampling_rate
														snake_case_          =						upsampling_kernel_size
														snake_case_          =						num_hash_functions
														snake_case_          =						num_hash_buckets
														snake_case_          =						local_transformer_stride



