<h2 dir="auto">🐛 Bug</h2>
<p dir="auto">Pytorch-1.0-Cuda-10.0 with ONNX-1.2.1 and 1.3.0. Export onnx model core dumps on Ubuntu on GPU instance</p>
<h2 dir="auto">To Reproduce</h2>
<p dir="auto">Steps to reproduce the behavior:</p>
<p dir="auto">Spin up an Ubuntu with GPU instance like EC2 p2 or g3</p>
<ol dir="auto">
<li>install Cuda-10, cudnn-7.4.1, NCCL-2.3.7</li>
<li>anaconda</li>
<li>conda create -n pytorch_p27 python=2.7</li>
<li>conda install pytorch=1.0.0=py2.7_cuda10.0.130_cudnn7.4.1_1 torchvision=0.2.1 cuda100=1.0 -c pytorch</li>
<li>pip install -U onnx==1.2.1 or 1.3.0</li>
</ol>
<p dir="auto">example used to replicate:<br>
<a href="https://github.com/onnx/tutorials/blob/master/tutorials/PytorchOnnxExport.ipynb">https://github.com/onnx/tutorials/blob/master/tutorials/PytorchOnnxExport.ipynb</a></p>
<p dir="auto">Error:<br>
Illegal instruction (core dumped)</p>
<h2 dir="auto">Expected behavior</h2>
<p dir="auto">It should have exported a .onnx file with the model</p>
<h2 dir="auto">Environment</h2>
<p dir="auto">Please copy and paste the output from our<br>
<a href="https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py" rel="nofollow">environment collection script</a><br>
PyTorch version: 1.0.0<br>
Is debug build: No<br>
CUDA used to build PyTorch: 10.0.130</p>
<p dir="auto">OS: Ubuntu 16.04.5 LTS<br>
GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.10) 5.4.0 20160609<br>
CMake version: version 3.5.1</p>
<p dir="auto">Python version: 2.7<br>
Is CUDA available: Yes<br>
CUDA runtime version: 10.0.130<br>
GPU models and configuration:<br>
GPU 0: Tesla M60<br>
GPU 1: Tesla M60<br>
GPU 2: Tesla M60<br>
GPU 3: Tesla M60</p>
<p dir="auto">Nvidia driver version: 410.79<br>
cuDNN version: Probably one of the following:<br>
/usr/local/cuda-10.0/lib64/libcudnn.so.7.4.1<br>
/usr/local/cuda-10.0/lib64/libcudnn_static.a<br>
/usr/local/cuda-8.0/lib64/libcudnn.so.6.0.21<br>
/usr/local/cuda-8.0/lib64/libcudnn_static.a<br>
/usr/local/cuda-9.0/lib64/libcudnn.so.7.3.1<br>
/usr/local/cuda-9.0/lib64/libcudnn_static.a<br>
/usr/local/cuda-9.2/lib64/libcudnn.so.7.3.1<br>
/usr/local/cuda-9.2/lib64/libcudnn_static.a</p>
<p dir="auto">Versions of relevant libraries:<br>
[pip] Could not collect<br>
[conda] blas                      1.0                         mkl<br>
[conda] cuda100                   1.0                           0    pytorch<br>
[conda] mkl                       2018.0.3                      1<br>
[conda] mkl_fft                   1.0.6            py27h7dd41cf_0<br>
[conda] mkl_random                1.0.1            py27h4414c95_1<br>
[conda] pytorch                   1.0.0           py2.7_cuda10.0.130_cudnn7.4.1_1  [cuda100]  pytorch<br>
[conda] torchvision               0.2.1                      py_2    pytorch</p>
<h2 dir="auto">Additional context</h2>
<p dir="auto">complete list of packages<br>
packages in environment:</p>
<p dir="auto">Name                    Version                   Build  Channel<br>
blas                      1.0                         mkl<br>
ca-certificates           2018.03.07                    0<br>
certifi                   2018.10.15               py27_0<br>
cffi                      1.11.5           py27he75722e_1<br>
cuda100                   1.0                           0    pytorch<br>
freetype                  2.9.1                h8a8886c_1<br>
intel-openmp              2019.1                      144<br>
jpeg                      9b                   h024ee3a_2<br>
libedit                   3.1.20170329         h6b74fdf_2<br>
libffi                    3.2.1                hd88cf55_4<br>
libgcc-ng                 8.2.0                hdf63c60_1<br>
libgfortran-ng            7.3.0                hdf63c60_0<br>
libpng                    1.6.35               hbc83047_0<br>
libstdcxx-ng              8.2.0                hdf63c60_1<br>
libtiff                   4.0.9                he85c1e1_2<br>
mkl                       2018.0.3                      1<br>
mkl_fft                   1.0.6            py27h7dd41cf_0<br>
mkl_random                1.0.1            py27h4414c95_1<br>
ncurses                   6.1                  he6710b0_1<br>
ninja                     1.8.2            py27h6bb024c_1<br>
numpy                     1.15.4           py27h1d66e8a_0<br>
numpy-base                1.15.4           py27h81de0dd_0<br>
olefile                   0.46                     py27_0<br>
onnx                      1.3.0                     <br>
openssl                   1.1.1a               h7b6447c_0<br>
pillow                    5.3.0            py27h34e0f95_0<br>
pip                       18.1                     py27_0<br>
protobuf                  3.6.1                     <br>
pycparser                 2.19                     py27_0<br>
python                    2.7.15               h9bab390_4<br>
pytorch                   1.0.0           py2.7_cuda10.0.130_cudnn7.4.1_1  [cuda100]  pytorch<br>
readline                  7.0                  h7b6447c_5<br>
setuptools                40.6.2                   py27_0<br>
six                       1.11.0                   py27_1<br>
sqlite                    3.25.3               h7b6447c_0<br>
tk                        8.6.8                hbc83047_0<br>
torchvision               0.2.1                      py_2    pytorch<br>
typing                    3.6.6                     <br>
typing-extensions         3.6.6                     <br>
wheel                     0.32.3                   py27_0<br>
xz                        5.2.4                h14c3975_4<br>
zlib                      1.2.11               h7b6447c_3</p>
<h2 dir="auto">🐛 Bug</h2>
<p dir="auto">Pytorch-1.0-Cuda-10.0 with ONNX-1.2.1 and 1.3.0. Export onnx model core dumps on Ubuntu on GPU instance</p>
<h2 dir="auto">To Reproduce</h2>
<p dir="auto">Steps to reproduce the behavior:</p>
<p dir="auto">Spin up an Ubuntu with GPU instance like EC2 p2 or g3</p>
<ol dir="auto">
<li>install Cuda-10, cudnn-7.4.1, NCCL-2.3.7</li>
<li>anaconda</li>
<li>conda create -n pytorch_p27 python=2.7</li>
<li>conda install pytorch=1.0.0=py2.7_cuda10.0.130_cudnn7.4.1_1 torchvision=0.2.1 cuda100=1.0 -c pytorch</li>
<li>pip install -U onnx==1.2.1 or 1.3.0</li>
</ol>
<p dir="auto">example used to replicate:<br>
<a href="https://github.com/onnx/tutorials/blob/master/tutorials/PytorchOnnxExport.ipynb">https://github.com/onnx/tutorials/blob/master/tutorials/PytorchOnnxExport.ipynb</a></p>
<p dir="auto">Error:<br>
Illegal instruction (core dumped)</p>
<h2 dir="auto">Expected behavior</h2>
<p dir="auto">It should have exported a .onnx file with the model</p>
<h2 dir="auto">Environment</h2>
<p dir="auto">Please copy and paste the output from our<br>
<a href="https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py" rel="nofollow">environment collection script</a><br>
PyTorch version: 1.0.0<br>
Is debug build: No<br>
CUDA used to build PyTorch: 10.0.130</p>
<p dir="auto">OS: Ubuntu 16.04.5 LTS<br>
GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.10) 5.4.0 20160609<br>
CMake version: version 3.5.1</p>
<p dir="auto">Python version: 2.7<br>
Is CUDA available: Yes<br>
CUDA runtime version: 10.0.130<br>
GPU models and configuration:<br>
GPU 0: Tesla M60<br>
GPU 1: Tesla M60<br>
GPU 2: Tesla M60<br>
GPU 3: Tesla M60</p>
<p dir="auto">Nvidia driver version: 410.79<br>
cuDNN version: Probably one of the following:<br>
/usr/local/cuda-10.0/lib64/libcudnn.so.7.4.1<br>
/usr/local/cuda-10.0/lib64/libcudnn_static.a<br>
/usr/local/cuda-8.0/lib64/libcudnn.so.6.0.21<br>
/usr/local/cuda-8.0/lib64/libcudnn_static.a<br>
/usr/local/cuda-9.0/lib64/libcudnn.so.7.3.1<br>
/usr/local/cuda-9.0/lib64/libcudnn_static.a<br>
/usr/local/cuda-9.2/lib64/libcudnn.so.7.3.1<br>
/usr/local/cuda-9.2/lib64/libcudnn_static.a</p>
<p dir="auto">Versions of relevant libraries:<br>
[pip] Could not collect<br>
[conda] blas                      1.0                         mkl<br>
[conda] cuda100                   1.0                           0    pytorch<br>
[conda] mkl                       2018.0.3                      1<br>
[conda] mkl_fft                   1.0.6            py27h7dd41cf_0<br>
[conda] mkl_random                1.0.1            py27h4414c95_1<br>
[conda] pytorch                   1.0.0           py2.7_cuda10.0.130_cudnn7.4.1_1  [cuda100]  pytorch<br>
[conda] torchvision               0.2.1                      py_2    pytorch</p>
<h2 dir="auto">Additional context</h2>
<p dir="auto">complete list of packages<br>
packages in environment:</p>
<p dir="auto">Name                    Version                   Build  Channel<br>
blas                      1.0                         mkl<br>
ca-certificates           2018.03.07                    0<br>
certifi                   2018.10.15               py27_0<br>
cffi                      1.11.5           py27he75722e_1<br>
cuda100                   1.0                           0    pytorch<br>
freetype                  2.9.1                h8a8886c_1<br>
intel-openmp              2019.1                      144<br>
jpeg                      9b                   h024ee3a_2<br>
libedit                   3.1.20170329         h6b74fdf_2<br>
libffi                    3.2.1                hd88cf55_4<br>
libgcc-ng                 8.2.0                hdf63c60_1<br>
libgfortran-ng            7.3.0                hdf63c60_0<br>
libpng                    1.6.35               hbc83047_0<br>
libstdcxx-ng              8.2.0                hdf63c60_1<br>
libtiff                   4.0.9                he85c1e1_2<br>
mkl                       2018.0.3                      1<br>
mkl_fft                   1.0.6            py27h7dd41cf_0<br>
mkl_random                1.0.1            py27h4414c95_1<br>
ncurses                   6.1                  he6710b0_1<br>
ninja                     1.8.2            py27h6bb024c_1<br>
numpy                     1.15.4           py27h1d66e8a_0<br>
numpy-base                1.15.4           py27h81de0dd_0<br>
olefile                   0.46                     py27_0<br>
onnx                      1.3.0                     <br>
openssl                   1.1.1a               h7b6447c_0<br>
pillow                    5.3.0            py27h34e0f95_0<br>
pip                       18.1                     py27_0<br>
protobuf                  3.6.1                     <br>
pycparser                 2.19                     py27_0<br>
python                    2.7.15               h9bab390_4<br>
pytorch                   1.0.0           py2.7_cuda10.0.130_cudnn7.4.1_1  [cuda100]  pytorch<br>
readline                  7.0                  h7b6447c_5<br>
setuptools                40.6.2                   py27_0<br>
six                       1.11.0                   py27_1<br>
sqlite                    3.25.3               h7b6447c_0<br>
tk                        8.6.8                hbc83047_0<br>
torchvision               0.2.1                      py_2    pytorch<br>
typing                    3.6.6                     <br>
typing-extensions         3.6.6                     <br>
wheel                     0.32.3                   py27_0<br>
xz                        5.2.4                h14c3975_4<br>
zlib                      1.2.11               h7b6447c_3</p>