

'''simple docstring'''





import os
import warnings
from typing import List, Optional

from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig


UpperCamelCase_							=					logging.get_logger(__name__)





class 		__SCREAMING_SNAKE_CASE       :







				def __init__(					self    :		Union[str, Any]		,				UpperCAmelCase__    :		Any		,				UpperCAmelCase__    :		str      ):
										'''simple docstring'''
										lowercase   :       List[str]								=question_encoder
										lowercase   :       Tuple								=generator
										lowercase   :       Any								=self.question_encoder







				def    lowerCamelCase_  (					self    :		Optional[Any]		,				UpperCAmelCase__    :		Dict      ):
										'''simple docstring'''
										if os.path.isfile(UpperCAmelCase__      ):
																raise ValueError(F'''Provided path ({save_directory}) should be a directory, not a file'''      )
										os.makedirs(UpperCAmelCase__		,				exist_ok=UpperCAmelCase__      )
										lowercase   :       Any								=os.path.join(UpperCAmelCase__		,				'''question_encoder_tokenizer'''      )
										lowercase   :       Union[str, Any]								=os.path.join(UpperCAmelCase__		,				'''generator_tokenizer'''      )
										self.question_encoder.save_pretrained(UpperCAmelCase__      )
										self.generator.save_pretrained(UpperCAmelCase__      )







				@classmethod
				def    lowerCamelCase_  (					cls    :		Tuple		,				UpperCAmelCase__    :		Optional[int]		,				**UpperCAmelCase__    :		Union[str, Any]      ):
										'''simple docstring'''
										from ..auto.tokenization_auto import AutoTokenizer

										lowercase   :       Optional[Any]								=kwargs.pop('''config'''		,				UpperCAmelCase__      )

										if config is None:
																lowercase   :       Dict								=RagConfig.from_pretrained(UpperCAmelCase__      )

										lowercase   :       Tuple								=AutoTokenizer.from_pretrained(
										    UpperCAmelCase__		,				config=config.question_encoder		,				subfolder='''question_encoder_tokenizer'''      )
										lowercase   :       List[str]								=AutoTokenizer.from_pretrained(
										    UpperCAmelCase__		,				config=config.generator		,				subfolder='''generator_tokenizer'''      )
										return cls(question_encoder=UpperCAmelCase__		,				generator=UpperCAmelCase__      )







				def __call__(					self    :		List[str]		,				*UpperCAmelCase__    :		Any		,				**UpperCAmelCase__    :		Optional[int]      ):
										'''simple docstring'''
										return self.current_tokenizer(*UpperCAmelCase__		,				**UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		List[Any]		,				*UpperCAmelCase__    :		int		,				**UpperCAmelCase__    :		Optional[Any]      ):
										'''simple docstring'''
										return self.generator.batch_decode(*UpperCAmelCase__		,				**UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		Optional[Any]		,				*UpperCAmelCase__    :		int		,				**UpperCAmelCase__    :		List[Any]      ):
										'''simple docstring'''
										return self.generator.decode(*UpperCAmelCase__		,				**UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		Union[str, Any]      ):
										'''simple docstring'''
										lowercase   :       List[Any]								=self.question_encoder







				def    lowerCamelCase_  (					self    :		Dict      ):
										'''simple docstring'''
										lowercase   :       Union[str, Any]								=self.generator







				def    lowerCamelCase_  (					self    :		Optional[int]		,				UpperCAmelCase__    :		List[str]		,				UpperCAmelCase__    :		Optional[List[str]] = None		,				UpperCAmelCase__    :		Optional[int] = None		,				UpperCAmelCase__    :		Optional[int] = None		,				UpperCAmelCase__    :		str = "longest"		,				UpperCAmelCase__    :		str = None		,				UpperCAmelCase__    :		bool = True		,				**UpperCAmelCase__    :		Union[str, Any]		,				):
										'''simple docstring'''
										warnings.warn(
										    '''`prepare_seq2seq_batch` is deprecated and will be removed in version 5 of 🤗 Transformers. Use the '''
										    '''regular `__call__` method to prepare your inputs and the tokenizer under the `with_target_tokenizer` '''
										    '''context manager to prepare your targets. See the documentation of your specific tokenizer for more '''
										    '''details'''		,				UpperCAmelCase__		,				)
										if max_length is None:
																lowercase   :       int								=self.current_tokenizer.model_max_length
										lowercase   :       List[str]								=self(
										    UpperCAmelCase__		,				add_special_tokens=UpperCAmelCase__		,				return_tensors=UpperCAmelCase__		,				max_length=UpperCAmelCase__		,				padding=UpperCAmelCase__		,				truncation=UpperCAmelCase__		,				**UpperCAmelCase__		,				)
										if tgt_texts is None:
																return model_inputs
										# Process tgt_texts
										if max_target_length is None:
																lowercase   :       Any								=self.current_tokenizer.model_max_length
										lowercase   :       int								=self(
										    text_target=UpperCAmelCase__		,				add_special_tokens=UpperCAmelCase__		,				return_tensors=UpperCAmelCase__		,				padding=UpperCAmelCase__		,				max_length=UpperCAmelCase__		,				truncation=UpperCAmelCase__		,				**UpperCAmelCase__		,				)
										lowercase   :       Dict								=labels['''input_ids''']
										return model_inputs








'''simple docstring'''





import argparse
import copy






def 							_lowerCAmelCase (      __magic_name__	:    List[str]	)							->     Union[str, Any]:
						lowercase   :       int								={}

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

						return dict_of_neighbours






def 							_lowerCAmelCase (      __magic_name__	:    Optional[int]      ,   __magic_name__	:    List[Any]	)							->     str:

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

						lowercase   :       List[Any]								=[]

						lowercase   :       str								=start_node

						lowercase   :       str								=0
						while visiting not in first_solution:
												lowercase   :       Optional[int]								=10000
												for k in dict_of_neighbours[visiting]:
																		if int(k[1]	) < int(__magic_name__	) and k[0] not in first_solution:
																								lowercase   :       List[Any]								=k[1]
																								lowercase   :       str								=k[0]

												first_solution.append(__magic_name__	)
												lowercase   :       Any								=distance_of_first_solution + int(__magic_name__	)
												lowercase   :       Optional[int]								=best_node

						first_solution.append(__magic_name__	)

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

						lowercase   :       str								=(
						    distance_of_first_solution
						    + int(dict_of_neighbours[first_solution[-2]][position][1]	)
						    - 10000
						)
						return first_solution, distance_of_first_solution






def 							_lowerCAmelCase (      __magic_name__	:    str      ,   __magic_name__	:    Any	)							->     Tuple:
						lowercase   :       Tuple								=[]

						for n in solution[1:-1]:
												lowercase   :       Dict								=solution.index(__magic_name__	)
												for kn in solution[1:-1]:
																		lowercase   :       Tuple								=solution.index(__magic_name__	)
																		if n == kn:
																								continue

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

																		lowercase   :       List[Any]								=0

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

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

						lowercase   :       Union[str, Any]								=len(neighborhood_of_solution[0]	) - 1

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






def 							_lowerCAmelCase (      __magic_name__	:    Any      ,   __magic_name__	:    str      ,   __magic_name__	:    List[Any]      ,   __magic_name__	:    Tuple      ,   __magic_name__	:    Dict	)							->     Union[str, Any]:
						lowercase   :       str								=1
						lowercase   :       List[Any]								=first_solution
						lowercase   :       Any								=[]
						lowercase   :       str								=distance_of_first_solution
						lowercase   :       str								=solution

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

												lowercase   :       List[Any]								=False
												while not found:
																		lowercase   :       List[Any]								=0
																		while i < len(__magic_name__	):
																								if best_solution[i] != solution[i]:
																														lowercase   :       List[str]								=best_solution[i]
																														lowercase   :       Dict								=solution[i]
																														break
																								lowercase   :       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]	)
																								lowercase   :       str								=True
																								lowercase   :       int								=best_solution[:-1]
																								lowercase   :       Any								=neighborhood[index_of_best_solution][best_cost_index]
																								if cost < best_cost:
																														lowercase   :       Optional[int]								=cost
																														lowercase   :       str								=solution
																		else:
																								lowercase   :       Optional[int]								=index_of_best_solution + 1
																								lowercase   :       List[Any]								=neighborhood[index_of_best_solution]

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

												lowercase   :       Optional[int]								=count + 1

						return best_solution_ever, best_cost






def 							_lowerCAmelCase (      __magic_name__	:    str=None	)							->     Tuple:
						lowercase   :       List[str]								=generate_neighbours(args.File	)

						lowercase		,  lowercase   :       Optional[Any]								=generate_first_solution(
						    args.File      ,   __magic_name__	)

						lowercase		,  lowercase   :       int								=tabu_search(
						    __magic_name__      ,   __magic_name__      ,   __magic_name__      ,   args.Iterations      ,   args.Size      ,   )

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


if __name__ == "__main__":
							UpperCamelCase_							=					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())





