





from typing import Literal

_SCREAMING_SNAKE_CASE   						=		"""ABCDEFGHIJKLMNOPQRSTUVWXYZ"""


def 				SCREAMING_SNAKE_CASE__    (     __a ,			__a ,			__a ):
	snake_case_		:      List[str]           =						LETTERS if mode == 'decrypt' else key
	snake_case_		:      List[Any]           =						key if mode == 'decrypt' else LETTERS
	snake_case_		:      Any           =						''
	# loop through each symbol in the message
	for symbol in message:
		if symbol.upper() in chars_a:
			# encrypt/decrypt the symbol
			snake_case_		:      int           =						chars_a.find(symbol.upper() )
			if symbol.isupper():
				translated += chars_b[sym_index].upper()
			else:
				translated += chars_b[sym_index].lower()
		else:
			# symbol is not in LETTERS, just add it
			translated += symbol
	return translated


def 				SCREAMING_SNAKE_CASE__    (     __a ,			__a ):
	return translate_message(__a ,			__a ,			'encrypt' )


def 				SCREAMING_SNAKE_CASE__    (     __a ,			__a ):
	return translate_message(__a ,			__a ,			'decrypt' )


def 				SCREAMING_SNAKE_CASE__    (     ):
	snake_case_		:      Optional[int]           =						'Hello World'
	snake_case_		:      Dict           =						'QWERTYUIOPASDFGHJKLZXCVBNM'
	snake_case_		:      Optional[Any]           =						'decrypt'  # set to 'encrypt' or 'decrypt'

	if mode == "encrypt":
		snake_case_		:      List[str]           =						encrypt_message(__a ,			__a )
	elif mode == "decrypt":
		snake_case_		:      Optional[Any]           =						decrypt_message(__a ,			__a )
	print(f"""Using the key {key}, the {mode}ed message is: {translated}""" )


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()








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


_SCREAMING_SNAKE_CASE   						=		logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE   						=		{
    """uw-madison/nystromformer-512""": """https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json""",
    # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
}
class SCREAMING_SNAKE_CASE_    (       snake_case_       ):
						__magic_name__:      Optional[Any]			   =							"nystromformer"






						def __init__(   self   :   List[str]		, _A   :   Optional[Any]=30000		, _A   :   str=768		, _A   :   Optional[int]=12		, _A   :   Dict=12		, _A   :   Any=3072		, _A   :   str="gelu_new"		, _A   :   Optional[Any]=0.1		, _A   :   int=0.1		, _A   :   Dict=510		, _A   :   List[Any]=2		, _A   :   Optional[Any]=64		, _A   :   Union[str, Any]=64		, _A   :   List[Any]=65		, _A   :   Dict=False		, _A   :   str=0.0_2		, _A   :   Dict=1E-5		, _A   :   List[Any]=1		, _A   :   Optional[int]=0		, _A   :   List[Any]=2		, **_A   :   int		, )				->     int:







							"""simple docstring"""


							snake_case_		:      Union[str, Any]           =						vocab_size
							snake_case_		:      str           =						max_position_embeddings
							snake_case_		:      Tuple           =						hidden_size
							snake_case_		:      Union[str, Any]           =						num_hidden_layers
							snake_case_		:      str           =						num_attention_heads
							snake_case_		:      Optional[Any]           =						intermediate_size
							snake_case_		:      str           =						hidden_act
							snake_case_		:      str           =						hidden_dropout_prob
							snake_case_		:      Optional[Any]           =						attention_probs_dropout_prob
							snake_case_		:      Union[str, Any]           =						initializer_range
							snake_case_		:      Union[str, Any]           =						type_vocab_size
							snake_case_		:      Dict           =						segment_means_seq_len
							snake_case_		:      Tuple           =						num_landmarks
							snake_case_		:      Any           =						conv_kernel_size
							snake_case_		:      List[str]           =						inv_coeff_init_option
							snake_case_		:      str           =						layer_norm_eps
							super().__init__(pad_token_id=_A		, bos_token_id=_A		, eos_token_id=_A		, **_A						)

