






import argparse
import copy







def 	_UpperCamelCase   (    UpperCamelCase_       :					Any		)  ->   List[str]:

						"""simple docstring"""



						lowerCAmelCase__    						=						{}

						with open(UpperCamelCase_		) as f:
												for line in f:
																		if line.split()[0] not in dict_of_neighbours:
																								lowerCAmelCase__    						=						[]
																								_list.append([line.split()[1], line.split()[2]]		)
																								lowerCAmelCase__    						=						_list
																		else:
																								dict_of_neighbours[line.split()[0]].append(
																								    [line.split()[1], line.split()[2]]		)
																		if line.split()[1] not in dict_of_neighbours:
																								lowerCAmelCase__    						=						[]
																								_list.append([line.split()[0], line.split()[2]]		)
																								lowerCAmelCase__    						=						_list
																		else:
																								dict_of_neighbours[line.split()[1]].append(
																								    [line.split()[0], line.split()[2]]		)

						return dict_of_neighbours







def 	_UpperCamelCase   (    UpperCamelCase_       :					List[str]    ,       UpperCamelCase_       :					int		)  ->   Optional[int]:

						"""simple docstring"""



						with open(UpperCamelCase_		) as f:
												lowerCAmelCase__    						=						f.read(1		)
						lowerCAmelCase__    						=						start_node

						lowerCAmelCase__    						=						[]

						lowerCAmelCase__    						=						start_node

						lowerCAmelCase__    						=						0
						while visiting not in first_solution:
												lowerCAmelCase__    						=						1_0000
												for k in dict_of_neighbours[visiting]:
																		if int(k[1]		) < int(UpperCamelCase_		) and k[0] not in first_solution:
																								lowerCAmelCase__    						=						k[1]
																								lowerCAmelCase__    						=						k[0]

												first_solution.append(UpperCamelCase_		)
												lowerCAmelCase__    						=						distance_of_first_solution + int(UpperCamelCase_		)
												lowerCAmelCase__    						=						best_node

						first_solution.append(UpperCamelCase_		)

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

						lowerCAmelCase__    						=						(
						    distance_of_first_solution
						    + int(dict_of_neighbours[first_solution[-2]][position][1]		)
						    - 1_0000
						)
						return first_solution, distance_of_first_solution







def 	_UpperCamelCase   (    UpperCamelCase_       :					Optional[int]    ,       UpperCamelCase_       :					Dict		)  ->   Any:

						"""simple docstring"""



						lowerCAmelCase__    						=						[]

						for n in solution[1:-1]:
												lowerCAmelCase__    						=						solution.index(UpperCamelCase_		)
												for kn in solution[1:-1]:
																		lowerCAmelCase__    						=						solution.index(UpperCamelCase_		)
																		if n == kn:
																								continue

																		lowerCAmelCase__    						=						copy.deepcopy(UpperCamelCase_		)
																		lowerCAmelCase__    						=						kn
																		lowerCAmelCase__    						=						n

																		lowerCAmelCase__    						=						0

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

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

						lowerCAmelCase__    						=						len(neighborhood_of_solution[0]		) - 1

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







def 	_UpperCamelCase   (    UpperCamelCase_       :					Any    ,       UpperCamelCase_       :					Optional[Any]    ,       UpperCamelCase_       :					str    ,       UpperCamelCase_       :					Optional[Any]    ,       UpperCamelCase_       :					int		)  ->   List[str]:

						"""simple docstring"""



						lowerCAmelCase__    						=						1
						lowerCAmelCase__    						=						first_solution
						lowerCAmelCase__    						=						[]
						lowerCAmelCase__    						=						distance_of_first_solution
						lowerCAmelCase__    						=						solution

						while count <= iters:
												lowerCAmelCase__    						=						find_neighborhood(UpperCamelCase_    ,       UpperCamelCase_		)
												lowerCAmelCase__    						=						0
												lowerCAmelCase__    						=						neighborhood[index_of_best_solution]
												lowerCAmelCase__    						=						len(UpperCamelCase_		) - 1

												lowerCAmelCase__    						=						False
												while not found:
																		lowerCAmelCase__    						=						0
																		while i < len(UpperCamelCase_		):
																								if best_solution[i] != solution[i]:
																														lowerCAmelCase__    						=						best_solution[i]
																														lowerCAmelCase__    						=						solution[i]
																														break
																								lowerCAmelCase__    						=						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]		)
																								lowerCAmelCase__    						=						True
																								lowerCAmelCase__    						=						best_solution[:-1]
																								lowerCAmelCase__    						=						neighborhood[index_of_best_solution][best_cost_index]
																								if cost < best_cost:
																														lowerCAmelCase__    						=						cost
																														lowerCAmelCase__    						=						solution
																		else:
																								lowerCAmelCase__    						=						index_of_best_solution + 1
																								lowerCAmelCase__    						=						neighborhood[index_of_best_solution]

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

												lowerCAmelCase__    						=						count + 1

						return best_solution_ever, best_cost







def 	_UpperCamelCase   (    UpperCamelCase_       :					Tuple=None		)  ->   Union[str, Any]:

						"""simple docstring"""



						lowerCAmelCase__    						=						generate_neighbours(args.File		)

						lowerCAmelCase__						,       lowerCAmelCase__    						=						generate_first_solution(
						    args.File    ,       UpperCamelCase_		)

						lowerCAmelCase__						,       lowerCAmelCase__    						=						tabu_search(
						    UpperCamelCase_    ,       UpperCamelCase_    ,       UpperCamelCase_    ,       args.Iterations    ,       args.Size    ,       )

						print(F"Best solution: {best_sol}, with total distance: {best_cost}."		)


if __name__ == "__main__":
					__snake_case    :    List[Any]         =     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())













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__snake_case    :    Tuple         =     {"""configuration_glpn""": ["""GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GLPNConfig"""]}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__snake_case    :    Dict         =     ["""GLPNFeatureExtractor"""]
					__snake_case    :    Optional[Any]         =     ["""GLPNImageProcessor"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__snake_case    :    Tuple         =     [
					    """GLPN_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """GLPNForDepthEstimation""",
					    """GLPNLayer""",
					    """GLPNModel""",
					    """GLPNPreTrainedModel""",
					]


if TYPE_CHECKING:
					from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_glpn import GLPNFeatureExtractor
										from .image_processing_glpn import GLPNImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_glpn import (
										    GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GLPNForDepthEstimation,
										    GLPNLayer,
										    GLPNModel,
										    GLPNPreTrainedModel,
										)


else:
					import sys

					__snake_case    :    Optional[int]         =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





