Open NoLookDefense opened 2 years ago
Hi. Thanks for your work. I am reading your paper and trying to reimplement, and I feel confused about some details. You mentioned in your paper that the slimming ratio ρ∈[0.35 : 0.05 : 1.25], which have 18 paths. However, in your code, there are only 14 paths ρ∈[0.35 : 0.05 : 1] as mentioned in https://github.com/changlin31/DS-Net/blob/15cd3036970ec27d2c306014344fd50d9e9b888b/dyn_slim/models/dyn_slim_net.py#L36 . And also, when conducting gate training, the gate function only has a 4-dimension output, meaning that there is only 4 paths and the slimming ratio is restricted to ρ∈[0.35 : 0.05 : 0.5]. https://github.com/changlin31/DS-Net/blob/15cd3036970ec27d2c306014344fd50d9e9b888b/dyn_slim/models/dyn_slim_blocks.py#L204 Why the dynamic path for larger network is not used?
Hi, @NoLookDefense We made some explanations on the implementation of the routing space in the Supplementary Material.
Please feel free to ask if you have further questions.
Hi. Thanks for your work. I am reading your paper and trying to reimplement, and I feel confused about some details. You mentioned in your paper that the slimming ratio ρ∈[0.35 : 0.05 : 1.25], which have 18 paths. However, in your code, there are only 14 paths ρ∈[0.35 : 0.05 : 1] as mentioned in https://github.com/changlin31/DS-Net/blob/15cd3036970ec27d2c306014344fd50d9e9b888b/dyn_slim/models/dyn_slim_net.py#L36 . And also, when conducting gate training, the gate function only has a 4-dimension output, meaning that there is only 4 paths and the slimming ratio is restricted to ρ∈[0.35 : 0.05 : 0.5]. https://github.com/changlin31/DS-Net/blob/15cd3036970ec27d2c306014344fd50d9e9b888b/dyn_slim/models/dyn_slim_blocks.py#L204 Why the dynamic path for larger network is not used?