Comments (4)
Sure, just updated!
from nats-bench.
Thanks! Today, I meet the new challenge:
I download the NATS-tss-v1_0-3ffb9-full.taraa from google drive and unzip it. Unfortunately, I got this:
tar: Unexpected EOF in archive
tar: Unexpected EOF in archive
tar: Error is not recoverable: exiting now
Then I ignore this and move on to the next step, I want to load the pretrained model using these codes:
api = create('/public/ly/.torch/NATS-tss-v1_0-3ffb9-full', 'tss', fast_mode=True, verbose=True)
info = api.get_more_info(12, 'cifar10')
info = api.get_cost_info(12, 'cifar10')
validation_accuracy, latency, time_cost, current_total_time_cost = api.simulate_train_eval(12, dataset='cifar10', hp='12')
config = api.get_net_config(12, 'cifar10')
network = get_cell_based_tiny_net(config)
# Load the pre-trained weights: params is a dict, where the key is the seed and value is the weights.
params = api.get_net_param(12, 'cifar10', None)
network.load_state_dict(next(iter(params.values())))
but I get this error:
FileNotFoundError: [Errno 2] No such file or directory: '/public/ly/.torch/NATS-tss-v1_0-3ffb9-full/meta.pickle.pbz2.pbz2'
Would you please help me how can I have a pretrained network if I just use NATS-tss-v1_0-3ffb9-full.taraa(The whole weights are too big to afford)
from nats-bench.
If you need to use the pre-trained weights, you need to download all NATS-tss-v1_0-3ffb9-full.tara*
and merge them via cat NATS-tss-v1_0-3ffb9-full.tara* > NATS-tss-v1_0-3ffb9-full.tara
. (which is mentioned in step-2 in https://github.com/D-X-Y/NATS-Bench#preparation-and-download).
You can not use NATS-tss-v1_0-3ffb9-full.taraa
as it is just a piece of the whole zip file..
from nats-bench.
Thank you, I will try it again.
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
- The results of validation/test accuracy in NATS-Bench paper HOT 4
- best accuracy find HOT 3
- 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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