Comments (4)
Thanks for your interest in NATS-Bench.
1, Yes, please use 'cifar10' to get the test accuracy.
2, valtest-accuracy
means the accuracy on the joint of validation and test sets. Note that, here the validation set and test set following the split strategy in our paper, which is different from the original CIFAR-100 setting.
3, Possibly because you are using is_random=True, which will randomly select a seed. When we report the Optimal values, we use the average results from all seeds.
from nats-bench.
Hi, thank you for quick reply!
Therefore, I should set is_random=False to get the average results from all seeds. Am I correct?
from nats-bench.
Yes, when you are using is_random=False, you can get the average results.
If you are benchmarking your own NAS algorithm, it is also suggested to use the simulate_train_eval
API as in our examples: https://github.com/D-X-Y/AutoDL-Projects/blob/main/exps/NATS-algos/regularized_ea.py#L144
from nats-bench.
Ok. Thank you so much!
Hope you have a wonderful day!
from nats-bench.
Related Issues (20)
- The reasults of test accuracy HOT 2
- get_cost_info(hp="200") returns weird value for some models in topology search space HOT 4
- Problem recreating api in fastmode HOT 2
- best accuracy find HOT 3
- The code for ImageNet16 is 404 error HOT 4
- How to generate a architecute model with torch HOT 4
- Question regarding the design space for the topology search space in NATS-Bench HOT 1
- api_utils.py invoking get_latency method without passing "hp" parameter HOT 3
- No testset in ImageNet16 HOT 1
- Details about the data structures more_info and cost_info HOT 2
- Question about ImageNet16120 HOT 1
- Is NATS Extension of NAS_201 bench HOT 4
- get_net_param returns empty dictionary HOT 1
- Regarding the checkpoints HOT 3
- What is the seed of subnet training on cifar10, 111 or 777? HOT 3
- Further training of the network obtained from NATS bench
- Regarding inference with pretrained weights.
- get_more_info(): different seed but same 'train-accuracy', 'train-all-time', 'train-all-time'
- Question about the different init model weights of NATS-Bench-tss and NASbench201
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