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Deformable Convolutional Networks V2 with Pytorch 1.7

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 1.7.0, configuration:

  1. python3.7.9
  2. cuda11.1( cuda11.0 cannot support RTX30 compute)
  3. gcc 9
  4. g++ 9
  5. Ubuntu2104
  6. pytorch1.7.0

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.

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