






import argparse
import copy

def   __lowercase       (			snake_case			):







				"""simple docstring"""






				__magic_name__		:Union[str, Any]   =   {}

				with open(snake_case			) as f:
								for line in f:
												if line.split()[0] not in dict_of_neighbours:
																__magic_name__		:Tuple   =   []
																_list.append([line.split()[1], line.split()[2]]			)
																__magic_name__		:Dict   =   _list
												else:
																dict_of_neighbours[line.split()[0]].append(
																    [line.split()[1], line.split()[2]]			)
												if line.split()[1] not in dict_of_neighbours:
																__magic_name__		:Optional[Any]   =   []
																_list.append([line.split()[0], line.split()[2]]			)
																__magic_name__		:Optional[Any]   =   _list
												else:
																dict_of_neighbours[line.split()[1]].append(
																    [line.split()[0], line.split()[2]]			)

				return dict_of_neighbours

def   __lowercase       (			snake_case,	snake_case			):







				"""simple docstring"""






				with open(snake_case			) as f:
								__magic_name__		:Optional[Any]   =   f.read(1			)
				__magic_name__		:List[Any]   =   start_node

				__magic_name__		:int   =   []

				__magic_name__		:str   =   start_node

				__magic_name__		:Optional[Any]   =   0
				while visiting not in first_solution:
								__magic_name__		:List[str]   =   1_0_0_0_0
								for k in dict_of_neighbours[visiting]:
												if int(k[1]			) < int(snake_case			) and k[0] not in first_solution:
																__magic_name__		:Optional[Any]   =   k[1]
																__magic_name__		:int   =   k[0]

								first_solution.append(snake_case			)
								__magic_name__		:Dict   =   distance_of_first_solution + int(snake_case			)
								__magic_name__		:int   =   best_node

				first_solution.append(snake_case			)

				__magic_name__		:Tuple   =   0
				for k in dict_of_neighbours[first_solution[-2]]:
								if k[0] == start_node:
												break
								position += 1

				__magic_name__		:Optional[int]   =   (
				    distance_of_first_solution
				    + int(dict_of_neighbours[first_solution[-2]][position][1]			)
				    - 1_0_0_0_0
				)
				return first_solution, distance_of_first_solution

def   __lowercase       (			snake_case,	snake_case			):







				"""simple docstring"""






				__magic_name__		:str   =   []

				for n in solution[1:-1]:
								__magic_name__		:List[str]   =   solution.index(snake_case			)
								for kn in solution[1:-1]:
												__magic_name__		:str   =   solution.index(snake_case			)
												if n == kn:
																continue

												__magic_name__		:Union[str, Any]   =   copy.deepcopy(snake_case			)
												__magic_name__		:List[str]   =   kn
												__magic_name__		:Optional[int]   =   n

												__magic_name__		:Any   =   0

												for k in _tmp[:-1]:
																__magic_name__		:Tuple   =   _tmp[_tmp.index(snake_case			) + 1]
																for i in dict_of_neighbours[k]:
																				if i[0] == next_node:
																								__magic_name__		:List[str]   =   distance + int(i[1]			)
												_tmp.append(snake_case			)

												if _tmp not in neighborhood_of_solution:
																neighborhood_of_solution.append(_tmp			)

				__magic_name__		:Optional[int]   =   len(neighborhood_of_solution[0]			) - 1

				neighborhood_of_solution.sort(key=lambda snake_case			: x[index_of_last_item_in_the_list]			)
				return neighborhood_of_solution

def   __lowercase       (			snake_case,	snake_case,	snake_case,	snake_case,	snake_case			):







				"""simple docstring"""






				__magic_name__		:Union[str, Any]   =   1
				__magic_name__		:Dict   =   first_solution
				__magic_name__		:Optional[Any]   =   []
				__magic_name__		:Optional[Any]   =   distance_of_first_solution
				__magic_name__		:str   =   solution

				while count <= iters:
								__magic_name__		:Dict   =   find_neighborhood(snake_case,	snake_case			)
								__magic_name__		:Any   =   0
								__magic_name__		:Union[str, Any]   =   neighborhood[index_of_best_solution]
								__magic_name__		:Union[str, Any]   =   len(snake_case			) - 1

								__magic_name__		:str   =   False
								while not found:
												__magic_name__		:List[str]   =   0
												while i < len(snake_case			):
																if best_solution[i] != solution[i]:
																				__magic_name__		:List[str]   =   best_solution[i]
																				__magic_name__		:Any   =   solution[i]
																				break
																__magic_name__		:Any   =   i + 1

												if [first_exchange_node, second_exchange_node] not in tabu_list and [
												    second_exchange_node,
												    first_exchange_node,
												] not in tabu_list:
																tabu_list.append([first_exchange_node, second_exchange_node]			)
																__magic_name__		:List[str]   =   True
																__magic_name__		:List[str]   =   best_solution[:-1]
																__magic_name__		:int   =   neighborhood[index_of_best_solution][best_cost_index]
																if cost < best_cost:
																				__magic_name__		:Union[str, Any]   =   cost
																				__magic_name__		:List[str]   =   solution
												else:
																__magic_name__		:Optional[int]   =   index_of_best_solution + 1
																__magic_name__		:Optional[Any]   =   neighborhood[index_of_best_solution]

								if len(snake_case			) >= size:
												tabu_list.pop(0			)

								__magic_name__		:List[Any]   =   count + 1

				return best_solution_ever, best_cost

def   __lowercase       (			snake_case=None			):







				"""simple docstring"""






				__magic_name__		:str   =   generate_neighbours(args.File			)

				__magic_name__  ,					__magic_name__		:List[str]   =   generate_first_solution(
				    args.File,	snake_case			)

				__magic_name__  ,					__magic_name__		:List[Any]   =   tabu_search(
				    snake_case,	snake_case,	snake_case,	args.Iterations,	args.Size,	)

				print(f'''Best solution: {best_sol}, with total distance: {best_cost}.'''			)


if __name__ == "__main__":
					SCREAMING_SNAKE_CASE__   :      List[str]				=		argparse.ArgumentParser(description="""Tabu Search""")
					parser.add_argument(
					    """-f""",
					    """--File""",
					    type=str,
					    help="""Path to the file containing the data""",
					    required=True,
					)
					parser.add_argument(
					    """-i""",
					    """--Iterations""",
					    type=int,
					    help="""How many iterations the algorithm should perform""",
					    required=True,
					)
					parser.add_argument(
					    """-s""", """--Size""", type=int, help="""Size of the tabu list""", required=True
					)

					# Pass the arguments to main method
					main(parser.parse_args())














import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE__   :      str				=		logging.get_logger(__name__)


SCREAMING_SNAKE_CASE__   :      Tuple				=		"""▁"""

SCREAMING_SNAKE_CASE__   :      Union[str, Any]				=		{"""vocab_file""": """spiece.model"""}

SCREAMING_SNAKE_CASE__   :      List[Any]				=		{
    """vocab_file""": {
        """google/reformer-crime-and-punishment""": (
            """https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"""
        )
    }
}

SCREAMING_SNAKE_CASE__   :      Optional[int]				=		{
    """google/reformer-crime-and-punishment""": 52_42_88,
}
class     lowerCamelCase_					(   lowerCamelCase			):
				a__       							=	VOCAB_FILES_NAMES
				a__       							=	PRETRAINED_VOCAB_FILES_MAP
				a__       							=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				a__       							=	['''input_ids''', '''attention_mask''']







				def __init__(    self							,       __lowerCAmelCase							,       __lowerCAmelCase="</s>"							,       __lowerCAmelCase="<unk>"							,       __lowerCAmelCase=[]							,       __lowerCAmelCase = None							,       **__lowerCAmelCase							,       ):
								"""simple docstring"""
								__magic_name__		:int   =   {} if sp_model_kwargs is None else sp_model_kwargs

								super().__init__(
								    eos_token=__lowerCAmelCase							,       unk_token=__lowerCAmelCase							,       additional_special_tokens=__lowerCAmelCase							,       sp_model_kwargs=self.sp_model_kwargs							,       **__lowerCAmelCase							,       )

								__magic_name__		:Optional[Any]   =   vocab_file
								__magic_name__		:int   =   spm.SentencePieceProcessor(**self.sp_model_kwargs  )
								self.sp_model.Load(__lowerCAmelCase  )







				@property
				def       A						(    self  ):
								"""simple docstring"""
								return self.sp_model.get_piece_size()







				def       A						(    self  ):
								"""simple docstring"""
								__magic_name__		:str   =   {self.convert_ids_to_tokens(__lowerCAmelCase  ): i for i in range(self.vocab_size  )}
								vocab.update(self.added_tokens_encoder  )
								return vocab







				def __getstate__(    self  ):
								"""simple docstring"""
								__magic_name__		:Optional[Any]   =   self.__dict__.copy()
								__magic_name__		:Optional[Any]   =   None
								return state







				def __setstate__(    self							,       __lowerCAmelCase  ):
								"""simple docstring"""
								__magic_name__		:Any   =   d

								# for backward compatibility
								if not hasattr(self							,       '''sp_model_kwargs'''  ):
												__magic_name__		:Optional[int]   =   {}

								__magic_name__		:Union[str, Any]   =   spm.SentencePieceProcessor(**self.sp_model_kwargs  )
								self.sp_model.Load(self.vocab_file  )







				def       A						(    self							,       __lowerCAmelCase  ):
								"""simple docstring"""
								return self.sp_model.encode(__lowerCAmelCase							,       out_type=__lowerCAmelCase  )







				def       A						(    self							,       __lowerCAmelCase  ):
								"""simple docstring"""
								return self.sp_model.piece_to_id(__lowerCAmelCase  )







				def       A						(    self							,       __lowerCAmelCase  ):
								"""simple docstring"""
								if index < self.sp_model.get_piece_size():
												__magic_name__		:int   =   self.sp_model.IdToPiece(__lowerCAmelCase  )
								return token







				def       A						(    self							,       __lowerCAmelCase  ):
								"""simple docstring"""
								__magic_name__		:Optional[Any]   =   []
								__magic_name__		:Tuple   =   ''''''
								for token in tokens:
												# make sure that special tokens are not decoded using sentencepiece model
												if token in self.all_special_tokens:
																out_string += self.sp_model.decode(__lowerCAmelCase  ) + token
																__magic_name__		:Optional[Any]   =   []
												else:
																current_sub_tokens.append(__lowerCAmelCase  )
								out_string += self.sp_model.decode(__lowerCAmelCase  )
								return out_string.strip()







				def       A						(    self							,       __lowerCAmelCase							,       __lowerCAmelCase = None  ):
								"""simple docstring"""
								if not os.path.isdir(__lowerCAmelCase  ):
												logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''  )
												return
								__magic_name__		:Optional[int]   =   os.path.join(
								    __lowerCAmelCase							,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']  )

								if os.path.abspath(self.vocab_file  ) != os.path.abspath(__lowerCAmelCase  ) and os.path.isfile(self.vocab_file  ):
												copyfile(self.vocab_file							,       __lowerCAmelCase  )
								elif not os.path.isfile(self.vocab_file  ):
												with open(__lowerCAmelCase							,       '''wb'''  ) as fi:
																__magic_name__		:Dict   =   self.sp_model.serialized_model_proto()
																fi.write(__lowerCAmelCase  )

								return (out_vocab_file,)






