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Description
Hi, thank you for your nice work of ElasticViT.
I'm trying to run the codes according to the instruction information, and I met this issue when I run the training command:
$ python -m torch.distributed.launch --nproc_per_node=2 train_eval_supernet.py configs/final_3min_space.yaml
The error occurs due to the lack of "offline_model_dir" and " lib_data_dir" in the yaml file "final_3min_space.yaml", so that the "select_min_arch" method of "class FuseSuperNet" cannot work. I was wondering if it is necessary to use the "offline_model_dir" from you, or should we edit the codes somewhere else? Thanks.
File "train_eval_supernet.py", line 261, in
main()
File "train_eval_supernet.py", line 226, in main
current_bank_id, direction, train_loss = train_one_epoch(
File "/home/jiy1rng/forclone/Moonlit/ElasticViT/process.py", line 205, in train_one_epoch
arch = model_without_ddp.arch_sampling(mode=mode, random_subnet_idx=uniform_idx,
File "/home/jiy1rng/forclone/Moonlit/ElasticViT/models/model.py", line 852, in arch_sampling
arch, _ = self.sample_random_subnet_from_range(
File "/home/jiy1rng/forclone/Moonlit/ElasticViT/models/model.py", line 758, in sample_random_subnet_from_range
min_arch = self.select_min_arch(flops=min_flops)
File "/home/jiy1rng/forclone/Moonlit/ElasticViT/models/model.py", line 735, in select_min_arch
min_archs = self.offline_archs['min']
KeyError: 'min'