Deformable Convolutional Networks V2 with Pytorch 1.X
Build
./make.sh # build
python testcpu.py # run examples and gradient check on cpu
python testcuda.py # run examples and gradient check on gpu
Note
Now the master branch is for pytorch 1.x, you can switch back to pytorch 0.4 with,
git checkout pytorch_0.4
Known Issues:
- Gradient check w.r.t offset (solved)
- Backward is not reentrant (minor)
This is an adaption of the official Deformable-ConvNets.
Update: all gradient check passes with double precision.
Another issue is that it raises RuntimeError: Backward is not reentrant
. However, the error is very small (<1e-7
for
float <1e-15
for double),
so it may not be a serious problem (?)
Please post an issue or PR if you have any comments.