"""simple docstring"""



import itertools
from pathlib import Path

def    _A(		lowerCAmelCase       ):
							A__					:    int														= [tuple(lowerCAmelCase       ) for login in logins]

							A__					:    int														= {char for login in split_logins for char in login}

							for permutation in itertools.permutations(lowerCAmelCase       ):
														A__					:    Optional[int]														= True
														for login in logins:
																					if not (
																					    permutation.index(login[0]       )
																					    < permutation.index(login[1]       )
																					    < permutation.index(login[2]       )
																					):
																												A__					:    str														= False
																												break

														if satisfied:
																					return int("""""".join(lowerCAmelCase       )       )

							raise Exception("""Unable to find the secret passcode"""       )

def    _A(		lowerCAmelCase = "keylog.txt"       ):
							A__					:    Optional[int]														= Path(lowerCAmelCase       ).parent.joinpath(lowerCAmelCase       ).read_text().splitlines()

							return find_secret_passcode(lowerCAmelCase       )


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






"""simple docstring"""



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


_UpperCamelCase         =		logging.get_logger(__name__)

_UpperCamelCase         =		{
    "facebook/opt-125m": "https://huggingface.co/facebook/opt-125m/blob/main/config.json",
    "facebook/opt-350m": "https://huggingface.co/facebook/opt-350m/blob/main/config.json",
    "facebook/opt-1.3b": "https://huggingface.co/facebook/opt-1.3b/blob/main/config.json",
    "facebook/opt-2.7b": "https://huggingface.co/facebook/opt-2.7b/blob/main/config.json",
    "facebook/opt-6.7b": "https://huggingface.co/facebook/opt-6.7b/blob/main/config.json",
    "facebook/opt-13b": "https://huggingface.co/facebook/opt-13b/blob/main/config.json",
}
class 	__UpperCAmelCase						(__A    ):







			'''simple docstring'''
			_UpperCamelCase     :	Dict				    =							'opt'
			_UpperCamelCase     :	Optional[Any]				    =							['past_key_values']





			def __init__( self      ,			snake_case_=50_272      ,			snake_case_=768      ,			snake_case_=12      ,			snake_case_=3_072      ,			snake_case_=2_048      ,			snake_case_=True      ,			snake_case_=False      ,			snake_case_=None      ,			snake_case_=0.1      ,			snake_case_=0.0      ,			snake_case_=12      ,			snake_case_="relu"      ,			snake_case_=0.0      ,			snake_case_=0.02      ,			snake_case_=True      ,			snake_case_=1      ,			snake_case_=2      ,			snake_case_=2      ,			snake_case_=True      ,			snake_case_=True      ,			**snake_case_      ,			):







										'''simple docstring'''


										super().__init__(
										    pad_token_id=snake_case_      ,			bos_token_id=snake_case_      ,			eos_token_id=snake_case_      ,			**snake_case_      ,			)
										A__					:    int														= vocab_size
										A__					:    List[str]														= max_position_embeddings
										A__					:    str														= num_attention_heads
										A__					:    Dict														= word_embed_proj_dim if word_embed_proj_dim is not None else hidden_size
										A__					:    Optional[int]														= ffn_dim
										A__					:    Optional[int]														= hidden_size
										A__					:    int														= num_hidden_layers
										A__					:    str														= dropout
										A__					:    Tuple														= attention_dropout
										A__					:    Optional[Any]														= activation_function
										A__					:    Any														= init_std
										A__					:    Optional[int]														= layerdrop
										A__					:    Optional[int]														= use_cache
										A__					:    int														= do_layer_norm_before
										# We keep these variables at `True` for backward compatibility.
										A__					:    str														= enable_bias
										A__					:    List[str]														= layer_norm_elementwise_affine

										# Note that the only purpose of `_remove_final_layer_norm` is to keep backward compatibility
										# with checkpoints that have been fine-tuned before transformers v4.20.1
										# see https://github.com/facebookresearch/metaseq/pull/164
										A__					:    str														= _remove_final_layer_norm





