No speed difference between sparsities

[WaterHyacinthInNANHU]

Thanks for your great work!
I have some trouble running tests with your code, but I could not submit any issues so I'm leaving messages here...

Q1: When I ran test.sh on cityscapes dataset, it gave me the warning:

/home/yan/anaconda3/envs/ML3.9/lib/python3.9/site-packages/acosp/inject.py:119: UserWarning: Incorrect number of channels are masked: tensor([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
        1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
        1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
        1., 1., 1., 1., 1., 1., 1., 1., 1., 1.]) for 32 number of remaining elements

what does it mean?

Q2: There is no speed difference between sparsities. I noticed you had implemented soft_to_channel_sparse in inject.py, and I think it is used to convert masked convs to sparse normal ones, which have fewer flops. Could you tell me how to use it to boot inference at runtime?

Thanks in advance.