CUDA 11 Test: FFT tests failing
See original GitHub issueFailing Tests
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestRfft2_param_0_{axes=None, norm=None, s=None, shape=(3, 4)}::test_irfft2 FAILED [ 82%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestRfft2_param_2_{axes=(-2, -1), norm=None, s=None, shape=(3, 4)}::test_irfft2 FAILED [ 83%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestRfft2_param_5_{axes=None, norm='ortho', s=None, shape=(3, 4)}::test_irfft2 FAILED [ 84%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestRfft2_param_6_{axes=None, norm=None, s=None, shape=(2, 3, 4)}::test_irfft2 FAILED [ 84%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestRfft2_param_8_{axes=(-3, -2, -1), norm=None, s=None, shape=(2, 3, 4)}::test_irfft2 FAILED [ 85%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestRfft2_param_10_{axes=(0, 1), norm=None, s=None, shape=(2, 3, 4)}::test_irfft2 FAILED [ 86%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestRfft2_param_11_{axes=None, norm='ortho', s=None, shape=(2, 3, 4)}::test_irfft2 FAILED [ 86%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestRfftn_param_0_{axes=None, norm=None, s=None, shape=(3, 4)}::test_irfftn FAILED [ 87%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestRfftn_param_2_{axes=(-2, -1), norm=None, s=None, shape=(3, 4)}::test_irfftn FAILED [ 88%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestRfftn_param_5_{axes=None, norm='ortho', s=None, shape=(3, 4)}::test_irfftn FAILED [ 89%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestRfftn_param_6_{axes=None, norm=None, s=None, shape=(2, 3, 4)}::test_irfftn FAILED [ 89%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestRfftn_param_8_{axes=(-3, -2, -1), norm=None, s=None, shape=(2, 3, 4)}::test_irfftn FAILED [ 90%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestRfftn_param_10_{axes=(0, 1), norm=None, s=None, shape=(2, 3, 4)}::test_irfftn FAILED [ 91%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestRfftn_param_11_{axes=None, norm='ortho', s=None, shape=(2, 3, 4)}::test_irfftn FAILED [ 91%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestHfft_param_13_{axis=0, n=15, norm=None, shape=(10, 10)}::test_hfft FAILED [ 95%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestHfft_param_13_{axis=0, n=15, norm=None, shape=(10, 10)}::test_hfft_backend FAILED [ 95%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestHfft_param_13_{axis=0, n=15, norm=None, shape=(10, 10)}::test_hfft_overwrite FAILED [ 95%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestHfft_param_15_{axis=0, n=15, norm='ortho', shape=(10, 10)}::test_hfft FAILED [ 95%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestHfft_param_15_{axis=0, n=15, norm='ortho', shape=(10, 10)}::test_hfft_backend FAILED [ 95%]
tests/cupyx_tests/scipy_tests/fft_tests/test_fft.py::TestHfft_param_15_{axis=0, n=15, norm='ortho', shape=(10, 10)}::test_hfft_overwrite FAILED [ 95%]
It seems there is a precision decrease in CUDA 11.
E AssertionError:
E Not equal to tolerance rtol=0.0001, atol=1e-07
E
E Mismatch: 0.667%
E Max absolute difference: 4.2915344e-06
E Max relative difference: 0.00027141
E x: array([[ 8.750391e+01, 7.829688e+01, 1.021133e+02, 6.904395e+01,
E 4.463257e+01, 5.814697e+01, 5.923633e+01, 6.878809e+01,
E 9.283203e+01, 5.962695e+01],...
E y: array([[ 8.750391e+01, 7.829688e+01, 1.021133e+02, 6.904395e+01,
E 4.463257e+01, 5.814697e+01, 5.923633e+01, 6.878809e+01,
E 9.283203e+01, 5.962695e+01],...
Enviornment
cu>>> cupy.show_config()
CuPy Version : 8.0.0b5
CUDA Root : /usr/local/cuda
CUDA Build Version : 11000
CUDA Driver Version : 11000
CUDA Runtime Version : 11000
cuBLAS Version : 11100
cuFFT Version : 10200
cuRAND Version : 10201
cuSOLVER Version : (10, 5, 0)
cuSPARSE Version : 11100
NVRTC Version : (11, 0)
Thrust Version : 100909
CUB Build Version : 100909
cuDNN Build Version : None
cuDNN Version : None
NCCL Build Version : None
NCCL Runtime Version : None
cuTENSOR Version : None
Issue Analytics
- State:
- Created 3 years ago
- Reactions:2
- Comments:11 (11 by maintainers)
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This is the reply I got from the cuFFT team:
Note that there’s no deadline for that at the moment. Therefore, I see two options:
Any other ideas of what we could do? If not, what’s people’s preference to the two options above?
I just confirmed it works for me with CUDA 10.0 on a V100. I’ve modified the
3_Imaging/convolutionFFT2D
sample to compare the input data before and after executingcufftExecC2R
and indeed in CUDA 11.0 the input gets modified, but CUDA 10.0 the input data stays the same. I’m asking internally whether this is a bug or expected behavior.