How to search smaller flops model？ about atomnas HOT 6 CLOSED

1. Use larger lambda
2. Start from thinner supernet

from atomnas.

1. Use larger lambda
2. Start from thinner supernet

Thank you for your answer.And where can i set the lambda or thinner supernet in the code or yml? How many hours with 8 cards to search and retrain?
Looking forward to your reply. Thank you very much. @meijieru

from atomnas.

1. Check a YAML config of the training example.
2. We didn't run the code for 8 cards and could not guarantee the performance.

from atomnas.

1. Check a YAML config of the training example.
2. We didn't run the code for 8 cards and could not guarantee the performance.

Thank you for your answer. Start from thinner supernet that means to change the channels and numbers of block in the inverted_residual_setting? If i only use larger lambda( like rho: 2.4e-4), can it work? @meijieru Thank you very much.
'inverted_residual_setting': [[1, 16, 1, 1, [3]],
[6, 24, 4, 2, [3, 5, 7]],
[6, 40, 4, 2, [3, 5, 7]],
[6, 80, 4, 2, [3, 5, 7]],
[6, 96, 4, 1, [3, 5, 7]],
[6, 192, 4, 2, [3, 5, 7]],
[6, 320, 1, 1, [3, 5, 7]]]
prune_params: {
method: network_slimming,
bn_prune_filter: expansion_only_skip_expand1,
rho: 1.8e-4,
epoch_free: 0,
epoch_warmup: 25,
scheduler: linear,
stepwise: True,
logging_verbose: False
}

from atomnas.

1. To start from a thinner supernet, you could try the followings:
   • modify the output channels of the blocks
   • use fewer blocks
   • start from smaller expand ratio
2. If the model you want is at the same level computation cost, I recommend a larger lambda. But if you want a much lighter model, I suggest to use a thinner supernet and then adjust the lambda for better performance.

from atomnas.

1. To start from a thinner supernet, you could try the followings:

   • modify the output channels of the blocks
   • use fewer blocks
   • start from smaller expand ratio

2. If the model you want is at the same level computation cost, I recommend a larger lambda. But if you want a much lighter model, I suggest to use a thinner supernet and then adjust the lambda for better performance.

Thank you for your advice. I'll try it out

from atomnas.