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| import os | |
| from tqdm import tqdm | |
| import multiprocessing | |
| import numpy as np | |
| from utils.utils import load_dataset, calc_tour_length | |
| from models.solvers.general_solver import GeneralSolver | |
| from models.classifiers.ground_truth.ground_truth import GroundTruth | |
| def eval_solver(solver, instance): | |
| tour = solver.solve(instance) | |
| tour_length = calc_tour_length(tour[0], instance["coords"]) | |
| return tour_length | |
| def eval(data_path, problem, solver_name, fix_edges, parallel): | |
| dataset = load_dataset(data_path) | |
| num_cpus = os.cpu_count() if parallel else 1 | |
| if fix_edges: | |
| solver = GroundTruth(problem, solver_name) | |
| if parallel: | |
| with multiprocessing.Pool(num_cpus) as pool: | |
| tours = list(tqdm(pool.starmap(solver.solve, [(step, instance["tour"][vehicle_id], instance, f"{i}-{vehicle_id}-{step}") | |
| for i, instance in enumerate(dataset) | |
| for vehicle_id in range(len(instance["tour"])) | |
| for step in range(1, len(instance["tour"][vehicle_id]))]), desc=f"Solving {data_path} with {solver_name}")) | |
| else: | |
| tours = [] | |
| for i, instance in enumerate(dataset): | |
| for vehicle_id in range(len(instance["tour"])): | |
| for step in range(1, len(instance["tour"][vehicle_id])): | |
| tours.append(solver.solve(step, instance["tour"][vehicle_id], instance, f"{i}-{vehicle_id}-{step}")) | |
| tour_length = {key: [] for key in tours[0].keys()} | |
| for tour in tours: | |
| for key, value in tour.items(): | |
| tour_length[key].append(value) | |
| else: | |
| solver = GeneralSolver(problem, solver_name) | |
| with multiprocessing.Pool(num_cpus) as pool: | |
| tour_length = list(tqdm(pool.starmap(eval_solver, [(solver, instance) for instance in dataset]), total=len(dataset), desc="Solving instances")) | |
| feasible_ratio = 0.0 | |
| penalty = 0.0 | |
| avg_tour_length = np.mean(tour_length["tsp"]) | |
| std_tour_length = np.std(tour_length["tsp"]) | |
| return avg_tour_length, std_tour_length, feasible_ratio, penalty | |
| if __name__ == "__main__": | |
| import argparse | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--problem", default="tsptw", type=str, help="Problem type: [tsptw, pctsp, pctsptw, cvrp]") | |
| parser.add_argument("--solver_name", type=str, default="ortools", help="Select from ") | |
| parser.add_argument("--data_path", type=str, help="Path to a dataset", required=True) | |
| parser.add_argument("--parallel", action="store_true") | |
| parser.add_argument("--all", action="store_true") | |
| parser.add_argument("--fix_edges", action="store_true") | |
| args = parser.parse_args() | |
| avg_tour_length, std_tour_length, feasible_ratio, penalty = eval(data_path=args.data_path, | |
| problem=args.problem, | |
| solver_name=args.solver_name, | |
| fix_edges=args.fix_edges, | |
| parallel=args.parallel) | |
| print(f"tour_length: {avg_tour_length} +/- {std_tour_length}") |