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Mukosame / Zooming-Slow-Mo-CVPR-2020

Fast and Accurate One-Stage Space-Time Video Super-Resolution (accepted in CVPR 2020)
GNU General Public License v3.0
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RuntimeError: Jacobian mismatch for output 0 with respect to input 1, #33

Closed dk-liang closed 4 years ago

dk-liang commented 4 years ago

When I run python test.py

torch.Size([2, 64, 128, 128]) torch.Size([20, 32, 7, 7]) torch.Size([20, 32, 7, 7]) torch.Size([20, 32, 7, 7]) 0.971507, 1.943014 0.971507, 1.943014 Zero offset passed /home/dkliang/miniconda3/envs/pytorch1.2/lib/python3.6/site-packages/torch/autograd/gradcheck.py:242: UserWarning: At least one of the inputs that requires gradient is not of double precision floating point. This check will likely fail if all the inputs are not of double precision floating point. 'At least one of the inputs that requires gradient ' check_gradient_dpooling: True Traceback (most recent call last): File "test.py", line 265, in check_gradient_dconv() File "test.py", line 97, in check_gradient_dconv eps=1e-3, atol=1e-4, rtol=1e-2)) File "/home/dkliang/miniconda3/envs/pytorch1.2/lib/python3.6/site-packages/torch/autograd/gradcheck.py", line 289, in gradcheck 'numerical:%s\nanalytical:%s\n' % (i, j, n, a)) File "/home/dkliang/miniconda3/envs/pytorch1.2/lib/python3.6/site-packages/torch/autograd/gradcheck.py", line 227, in fail_test raise RuntimeError(msg) RuntimeError: Jacobian mismatch for output 0 with respect to input 1, numerical:tensor([[-0.0003, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], [ 0.0000, 0.0013, 0.0000, ..., 0.0000, 0.0000, 0.0000], [ 0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], ..., [ 0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], [ 0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], [ 0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000]]) analytical:tensor([[-0.0003, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], [ 0.0000, 0.0013, 0.0000, ..., 0.0000, 0.0000, 0.0000], [ 0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], ..., [ 0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], [ 0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], [ 0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000]])

Mukosame commented 4 years ago

Hi @dk-liang , please refer https://github.com/CharlesShang/DCNv2#known-issues

In summary, it's not a problem.