Comments (4)
ShellyLingling
commented on July 16, 2024
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/zmb/anaconda3/envs/FairMOT/lib/python3.7/site-packages/torch/autograd/gradcheck.py:267: UserWarning: The {}th input requires gradient and is not a double precision floating point or complex. This check will likely fail if all the inputs are not of double precision floating point or complex.
'The {}th input requires gradient and '
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/zmb/anaconda3/envs/FairMOT/lib/python3.7/site-packages/torch/autograd/gradcheck.py", line 318, in gradcheck
'numerical:%s\nanalytical:%s\n' % (i, j, n, a))
File "/home/zmb/anaconda3/envs/FairMOT/lib/python3.7/site-packages/torch/autograd/gradcheck.py", line 254, in fail_test
raise RuntimeError(msg)
RuntimeError: Jacobian mismatch for output 0 with respect to input 1,
numerical:tensor([[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 6.7055e-05, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
...,
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00]])
analytical:tensor([[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 6.7871e-05, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
...,
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00]])
from dcnv2.
huxiaotaostasy
commented on July 16, 2024
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/zmb/anaconda3/envs/FairMOT/lib/python3.7/site-packages/torch/autograd/gradcheck.py:267: UserWarning: The {}th input requires gradient and is not a double precision floating point or complex. This check will likely fail if all the inputs are not of double precision floating point or complex.
'The {}th input requires gradient and '
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/zmb/anaconda3/envs/FairMOT/lib/python3.7/site-packages/torch/autograd/gradcheck.py", line 318, in gradcheck
'numerical:%s\nanalytical:%s\n' % (i, j, n, a))
File "/home/zmb/anaconda3/envs/FairMOT/lib/python3.7/site-packages/torch/autograd/gradcheck.py", line 254, in fail_test
raise RuntimeError(msg)
RuntimeError: Jacobian mismatch for output 0 with respect to input 1,
numerical:tensor([[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 6.7055e-05, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
...,
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00]])
analytical:tensor([[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 6.7871e-05, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
...,
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00],
[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,
0.0000e+00]])
how to solve????????
from dcnv2.
cnexah
commented on July 16, 2024
Maybe you downloaded the wrong version of code
from dcnv2.
TonightGo
commented on July 16, 2024
same error
from dcnv2.
Related Issues (20)
- Thanks,It is useful
- solve: /usr/local/cuda-11.0/bin/nvcc': No such file or directory
- 有用有用，解决问题了，疯狂安利 HOT 3
- Unable to build in pytorch 1.7.0 env.
- How can I add 'groups' into deformable conv?
- 似乎无法进行分布式训练 HOT 2
- python setup.py develop
- raise RuntimeError(message) from e RuntimeError: Error compiling objects for extension
- raise RuntimeError(message) from e RuntimeError: Error compiling objects for extension
- error: command 'g++' failed with exit status 1 HOT 2
- AttributeError: module '_ext' has no attribute 'dcn_v2_forward' HOT 1
- RuntimeError: Error compiling objects for extension HOT 4
- Unable to import .ext file even after successful build
- I love you HOT 1
- run testcuda error
- what is the supported torch version of the master branch? HOT 1
- command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++ HOT 1
- dcn_v2_cuda.obj : error LNK2001: 无法解析的外部符号 cublasSgemv_v2 HOT 1
- RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn HOT 1
- pytorch版本问题 HOT 1
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