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IDToolkit: A Toolkit for Benchmarking and Developing Inverse Design Algorithms in Nanophotonics, KDD'23
First I want to notice that the downloadable dataset Multi_Layer has a different size than the one indicated in the paper. That is main.py
raises a ValueError
.
python experiments/main.py --env multi_layer --dataset_path datasets/multi_layer --eval_method real_target --method cvae --method_config experiments/configs/cvae
The issue is due to the CombineSpace
which is not all_numerical
.
Traceback (most recent call last):
File "IDToolkit/experiments/main.py", line 194, in <module>
main(args)
File "IDToolkit/experiments/main.py", line 105, in main
pred_params = alg.search(num_samples=args.pred_num)
File "IDToolkit/inverse_design_benchmark/algorithms/neural_opt.py", line 101, in search
params = [self.env.parameter_space.from_numpy(p) for p in pred_params]
File "IDToolkit/inverse_design_benchmark/algorithms/neural_opt.py", line 101, in <listcomp>
params = [self.env.parameter_space.from_numpy(p) for p in pred_params]
File "IDToolkit/inverse_design_benchmark/parameter_space/combine.py", line 72, in from_numpy
raise ValueError("Only support converting numerical parameters from numpy")
ValueError: Only support converting numerical parameters from numpy
Are you aware of that ? Is there any workaround ? Thanks
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