What's the difference between FcaBottleneck and FcaBasicBlock ?
meiguoofa opened this issue · comments
As in your code, the FcaBottleneck expansion is 4 and FcaBasicBlock is 1, FcaBottleneck has one more layer of convolution than FcaBasicBlock, so how should I choose which module to use ?
and if i want to input a feature dim = 32 or 16, How should I set the wh?
@meiguoofa
The story is:
ResNet has two kinds of blocks, which are Bottleneck
and BasicBlock
. Bottleneck
s are used in large models like Res50, 101, 152. BasicBlocks
are used in Res34 and Res18.
When they are combined with our attention method, it becomes FcaBottleneck
and FcaBasicBlock
. If you want to use our work, just use the defined fcanet34
, fcanet50
functions to get the model.
If you have a feature dim like 32 or 16, just add an item in here:
Line 19 in aa5fb63
like:
c2wh = dict([(64,56), (128,28), (256,14) ,(512,7), (32,112), (16, 224) ])
In this case, I set the size to 112 and 224 for 32 and 16 dim respectively. You can set it as you want.
Thank You! your answer helped me a lot.