Hi @user54392, yes this container should have GPU support if you ran it with --runtime nvidia
You can find the example commands to run this container on this page: https://ngc.nvidia.com/catalog/containers/nvidia:l4t-pytorch
Version of JetPack is 4.5-b129, I copied cudnn.h and libcudnn* to /usr/local/cuda/include and /usr/local/cuda/lib64 respectively then chmod +x. It was with SD card image.
Hi @user14194, the SD card image should have already come with cuDNN installed in it’s correct location. My guess is that something got messed up and you may want to try new SD card image. Or you can try the l4t-pytorch container to see if that helps.
Thanks for your reply, I’ll try.
I had run the container with --runtime nvidia. Inside that container I had executed a program but while executing the program it only uses cpu. I need to execute the program with gpu support.
Please suggest me any options to make it possible. Or do I need to add any extra codes in the program.
Was this a PyTorch program? Had you called .cuda() on the model and tensors?
I’m trying to install torchvision in docker container with l4t-base:r32.6.1 as described above There is my commands:
ENV BUILD_VERSION=0.11.1
RUN apt-get update && apt-get install -y libjpeg-dev zlib1g-dev libpython3-dev libavcodec-dev libavformat-dev libswscale-dev && \
git clone --branch v0.11.1 https://github.com/pytorch/vision torchvision && \
cd torchvision && \
python setup.py install
But get the next error:
Hit:1 http://ports.ubuntu.com/ubuntu-ports bionic InRelease
Get:2 http://ports.ubuntu.com/ubuntu-ports bionic-updates InRelease [88.7 kB]
Hit:3 https://repo.download.nvidia.com/jetson/common r32.6 InRelease
Get:4 http://ports.ubuntu.com/ubuntu-ports bionic-backports InRelease [74.6 kB]
Get:5 http://ports.ubuntu.com/ubuntu-ports bionic-security InRelease [88.7 kB]
Hit:6 https://repo.download.nvidia.com/jetson/t194 r32.6 InRelease
Fetched 252 kB in 3s (95.1 kB/s)
Reading package lists...
Reading package lists...
Building dependency tree...
Reading state information...
libpython3-dev is already the newest version (3.6.7-1~18.04).
libpython3-dev set to manually installed.
The following additional packages will be installed:
libavutil-dev libjpeg-turbo8-dev libjpeg8-dev libswresample-dev
The following NEW packages will be installed:
libavcodec-dev libavformat-dev libavutil-dev libjpeg-dev libjpeg-turbo8-dev
libjpeg8-dev libswresample-dev libswscale-dev zlib1g-dev
0 upgraded, 9 newly installed, 0 to remove and 22 not upgraded.
Need to get 6519 kB of archives.
After this operation, 24.2 MB of additional disk space will be used.
Get:1 http://ports.ubuntu.com/ubuntu-ports bionic-updates/universe arm64 libavutil-dev arm64 7:3.4.8-0ubuntu0.2 [297 kB]
Get:2 http://ports.ubuntu.com/ubuntu-ports bionic-updates/universe arm64 libswresample-dev arm64 7:3.4.8-0ubuntu0.2 [57.2 kB]
Get:3 http://ports.ubuntu.com/ubuntu-ports bionic-updates/universe arm64 libavcodec-dev arm64 7:3.4.8-0ubuntu0.2 [4580 kB]
Get:4 http://ports.ubuntu.com/ubuntu-ports bionic-updates/universe arm64 libavformat-dev arm64 7:3.4.8-0ubuntu0.2 [1073 kB]
Get:5 http://ports.ubuntu.com/ubuntu-ports bionic-updates/main arm64 libjpeg-turbo8-dev arm64 1.5.2-0ubuntu5.18.04.4 [203 kB]
Get:6 http://ports.ubuntu.com/ubuntu-ports bionic/main arm64 libjpeg8-dev arm64 8c-2ubuntu8 [1550 B]
Get:7 http://ports.ubuntu.com/ubuntu-ports bionic/main arm64 libjpeg-dev arm64 8c-2ubuntu8 [1546 B]
Get:8 http://ports.ubuntu.com/ubuntu-ports bionic-updates/universe arm64 libswscale-dev arm64 7:3.4.8-0ubuntu0.2 [135 kB]
Get:9 http://ports.ubuntu.com/ubuntu-ports bionic/main arm64 zlib1g-dev arm64 1:1.2.11.dfsg-0ubuntu2 [171 kB]
debconf: delaying package configuration, since apt-utils is not installed
Fetched 6519 kB in 1s (7582 kB/s)
Selecting previously unselected package libavutil-dev:arm64.
(Reading database ... 41829 files and directories currently installed.)
Preparing to unpack .../0-libavutil-dev_7%3a3.4.8-0ubuntu0.2_arm64.deb ...
Unpacking libavutil-dev:arm64 (7:3.4.8-0ubuntu0.2) ...
Selecting previously unselected package libswresample-dev:arm64.
Preparing to unpack .../1-libswresample-dev_7%3a3.4.8-0ubuntu0.2_arm64.deb ...
Unpacking libswresample-dev:arm64 (7:3.4.8-0ubuntu0.2) ...
Selecting previously unselected package libavcodec-dev:arm64.
Preparing to unpack .../2-libavcodec-dev_7%3a3.4.8-0ubuntu0.2_arm64.deb ...
Unpacking libavcodec-dev:arm64 (7:3.4.8-0ubuntu0.2) ...
Selecting previously unselected package libavformat-dev:arm64.
Preparing to unpack .../3-libavformat-dev_7%3a3.4.8-0ubuntu0.2_arm64.deb ...
Unpacking libavformat-dev:arm64 (7:3.4.8-0ubuntu0.2) ...
Selecting previously unselected package libjpeg-turbo8-dev:arm64.
Preparing to unpack .../4-libjpeg-turbo8-dev_1.5.2-0ubuntu5.18.04.4_arm64.deb ...
Unpacking libjpeg-turbo8-dev:arm64 (1.5.2-0ubuntu5.18.04.4) ...
Selecting previously unselected package libjpeg8-dev:arm64.
Preparing to unpack .../5-libjpeg8-dev_8c-2ubuntu8_arm64.deb ...
Unpacking libjpeg8-dev:arm64 (8c-2ubuntu8) ...
Selecting previously unselected package libjpeg-dev:arm64.
Preparing to unpack .../6-libjpeg-dev_8c-2ubuntu8_arm64.deb ...
Unpacking libjpeg-dev:arm64 (8c-2ubuntu8) ...
Selecting previously unselected package libswscale-dev:arm64.
Preparing to unpack .../7-libswscale-dev_7%3a3.4.8-0ubuntu0.2_arm64.deb ...
Unpacking libswscale-dev:arm64 (7:3.4.8-0ubuntu0.2) ...
Selecting previously unselected package zlib1g-dev:arm64.
Preparing to unpack .../8-zlib1g-dev_1%3a1.2.11.dfsg-0ubuntu2_arm64.deb ...
Unpacking zlib1g-dev:arm64 (1:1.2.11.dfsg-0ubuntu2) ...
Setting up libavutil-dev:arm64 (7:3.4.8-0ubuntu0.2) ...
Setting up libswscale-dev:arm64 (7:3.4.8-0ubuntu0.2) ...
Setting up libjpeg-turbo8-dev:arm64 (1.5.2-0ubuntu5.18.04.4) ...
Setting up libjpeg8-dev:arm64 (8c-2ubuntu8) ...
Setting up libjpeg-dev:arm64 (8c-2ubuntu8) ...
Setting up libswresample-dev:arm64 (7:3.4.8-0ubuntu0.2) ...
Setting up zlib1g-dev:arm64 (1:1.2.11.dfsg-0ubuntu2) ...
Setting up libavcodec-dev:arm64 (7:3.4.8-0ubuntu0.2) ...
Setting up libavformat-dev:arm64 (7:3.4.8-0ubuntu0.2) ...
Cloning into 'torchvision'...
Note: checking out 'fa347eb9f38c1759b73677a11b17335191e3f602'.
You are in 'detached HEAD' state. You can look around, make experimental
changes and commit them, and you can discard any commits you make in this
state without impacting any branches by performing another checkout.
If you want to create a new branch to retain commits you create, you may
do so (now or later) by using -b with the checkout command again. Example:
git checkout -b <new-branch-name>
Building wheel torchvision-0.11.1
PNG found: False
Running build on conda-build: False
Running build on conda: False
JPEG found: True
Building torchvision with JPEG image support
NVJPEG found: False
FFmpeg found: True
ffmpeg include path: ['/usr/include', '/usr/include/aarch64-linux-gnu']
ffmpeg library_dir: ['/usr/lib', '/usr/lib/aarch64-linux-gnu']
running install
running bdist_egg
running egg_info
creating torchvision.egg-info
writing torchvision.egg-info/PKG-INFO
writing dependency_links to torchvision.egg-info/dependency_links.txt
writing requirements to torchvision.egg-info/requires.txt
writing top-level names to torchvision.egg-info/top_level.txt
writing manifest file 'torchvision.egg-info/SOURCES.txt'
reading manifest file 'torchvision.egg-info/SOURCES.txt'
reading manifest template 'MANIFEST.in'
/usr/local/lib/python3.6/dist-packages/torch/utils/cpp_extension.py:369: UserWarning: Attempted to use ninja as the BuildExtension backend but we could not find ninja.. Falling back to using the slow distutils backend.
warnings.warn(msg.format('we could not find ninja.'))
warning: no previously-included files matching '__pycache__' found under directory '*'
warning: no previously-included files matching '*.py[co]' found under directory '*'
writing manifest file 'torchvision.egg-info/SOURCES.txt'
installing library code to build/bdist.linux-aarch64/egg
running install_lib
running build_py
creating build
creating build/lib.linux-aarch64-3.6
creating build/lib.linux-aarch64-3.6/torchvision
copying torchvision/extension.py -> build/lib.linux-aarch64-3.6/torchvision
copying torchvision/utils.py -> build/lib.linux-aarch64-3.6/torchvision
copying torchvision/_internally_replaced_utils.py -> build/lib.linux-aarch64-3.6/torchvision
copying torchvision/version.py -> build/lib.linux-aarch64-3.6/torchvision
copying torchvision/__init__.py -> build/lib.linux-aarch64-3.6/torchvision
creating build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/regnet.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/shufflenetv2.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/mnasnet.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/resnet.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/feature_extraction.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/inception.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/mobilenetv2.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/squeezenet.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/mobilenetv3.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/densenet.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/efficientnet.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/vgg.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/_utils.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/alexnet.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/googlenet.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/mobilenet.py -> build/lib.linux-aarch64-3.6/torchvision/models
copying torchvision/models/__init__.py -> build/lib.linux-aarch64-3.6/torchvision/models
creating build/lib.linux-aarch64-3.6/torchvision/io
copying torchvision/io/_video_opt.py -> build/lib.linux-aarch64-3.6/torchvision/io
copying torchvision/io/image.py -> build/lib.linux-aarch64-3.6/torchvision/io
copying torchvision/io/video.py -> build/lib.linux-aarch64-3.6/torchvision/io
copying torchvision/io/__init__.py -> build/lib.linux-aarch64-3.6/torchvision/io
creating build/lib.linux-aarch64-3.6/torchvision/transforms
copying torchvision/transforms/functional.py -> build/lib.linux-aarch64-3.6/torchvision/transforms
copying torchvision/transforms/autoaugment.py -> build/lib.linux-aarch64-3.6/torchvision/transforms
copying torchvision/transforms/functional_pil.py -> build/lib.linux-aarch64-3.6/torchvision/transforms
copying torchvision/transforms/transforms.py -> build/lib.linux-aarch64-3.6/torchvision/transforms
copying torchvision/transforms/_functional_video.py -> build/lib.linux-aarch64-3.6/torchvision/transforms
copying torchvision/transforms/_transforms_video.py -> build/lib.linux-aarch64-3.6/torchvision/transforms
copying torchvision/transforms/functional_tensor.py -> build/lib.linux-aarch64-3.6/torchvision/transforms
copying torchvision/transforms/__init__.py -> build/lib.linux-aarch64-3.6/torchvision/transforms
creating build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/poolers.py -> build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/boxes.py -> build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/roi_align.py -> build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/_box_convert.py -> build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/misc.py -> build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/deform_conv.py -> build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/ps_roi_pool.py -> build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/ps_roi_align.py -> build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/stochastic_depth.py -> build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/focal_loss.py -> build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/feature_pyramid_network.py -> build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/roi_pool.py -> build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/_utils.py -> build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/_register_onnx_ops.py -> build/lib.linux-aarch64-3.6/torchvision/ops
copying torchvision/ops/__init__.py -> build/lib.linux-aarch64-3.6/torchvision/ops
creating build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/folder.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/imagenet.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/caltech.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/svhn.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/inaturalist.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/celeba.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/fakedata.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/ucf101.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/stl10.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/coco.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/sbd.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/hmdb51.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/utils.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/flickr.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/semeion.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/vision.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/cityscapes.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/sbu.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/voc.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/usps.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/kitti.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/video_utils.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/kinetics.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/lsun.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/widerface.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/mnist.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/phototour.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/cifar.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/places365.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/lfw.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/omniglot.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
copying torchvision/datasets/__init__.py -> build/lib.linux-aarch64-3.6/torchvision/datasets
creating build/lib.linux-aarch64-3.6/torchvision/models/quantization
copying torchvision/models/quantization/shufflenetv2.py -> build/lib.linux-aarch64-3.6/torchvision/models/quantization
copying torchvision/models/quantization/resnet.py -> build/lib.linux-aarch64-3.6/torchvision/models/quantization
copying torchvision/models/quantization/inception.py -> build/lib.linux-aarch64-3.6/torchvision/models/quantization
copying torchvision/models/quantization/mobilenetv2.py -> build/lib.linux-aarch64-3.6/torchvision/models/quantization
copying torchvision/models/quantization/utils.py -> build/lib.linux-aarch64-3.6/torchvision/models/quantization
copying torchvision/models/quantization/mobilenetv3.py -> build/lib.linux-aarch64-3.6/torchvision/models/quantization
copying torchvision/models/quantization/googlenet.py -> build/lib.linux-aarch64-3.6/torchvision/models/quantization
copying torchvision/models/quantization/mobilenet.py -> build/lib.linux-aarch64-3.6/torchvision/models/quantization
copying torchvision/models/quantization/__init__.py -> build/lib.linux-aarch64-3.6/torchvision/models/quantization
creating build/lib.linux-aarch64-3.6/torchvision/models/video
copying torchvision/models/video/resnet.py -> build/lib.linux-aarch64-3.6/torchvision/models/video
copying torchvision/models/video/__init__.py -> build/lib.linux-aarch64-3.6/torchvision/models/video
creating build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/backbone_utils.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/generalized_rcnn.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/transform.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/ssdlite.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/mask_rcnn.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/retinanet.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/ssd.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/faster_rcnn.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/image_list.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/anchor_utils.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/rpn.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/roi_heads.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/_utils.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/keypoint_rcnn.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
copying torchvision/models/detection/__init__.py -> build/lib.linux-aarch64-3.6/torchvision/models/detection
creating build/lib.linux-aarch64-3.6/torchvision/models/segmentation
copying torchvision/models/segmentation/segmentation.py -> build/lib.linux-aarch64-3.6/torchvision/models/segmentation
copying torchvision/models/segmentation/fcn.py -> build/lib.linux-aarch64-3.6/torchvision/models/segmentation
copying torchvision/models/segmentation/lraspp.py -> build/lib.linux-aarch64-3.6/torchvision/models/segmentation
copying torchvision/models/segmentation/deeplabv3.py -> build/lib.linux-aarch64-3.6/torchvision/models/segmentation
copying torchvision/models/segmentation/_utils.py -> build/lib.linux-aarch64-3.6/torchvision/models/segmentation
copying torchvision/models/segmentation/__init__.py -> build/lib.linux-aarch64-3.6/torchvision/models/segmentation
creating build/lib.linux-aarch64-3.6/torchvision/datasets/samplers
copying torchvision/datasets/samplers/__init__.py -> build/lib.linux-aarch64-3.6/torchvision/datasets/samplers
copying torchvision/datasets/samplers/clip_sampler.py -> build/lib.linux-aarch64-3.6/torchvision/datasets/samplers
running build_ext
building 'torchvision._C' extension
creating build/temp.linux-aarch64-3.6
creating build/temp.linux-aarch64-3.6/torchvision
creating build/temp.linux-aarch64-3.6/torchvision/torchvision
creating build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc
creating build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc/ops
creating build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc/ops/autocast
creating build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc/ops/autograd
creating build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc/ops/cpu
creating build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc/ops/cuda
creating build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc/ops/quantized
creating build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc/ops/quantized/cpu
aarch64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/torchvision/torchvision/csrc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda-10.2/include -I/usr/include/python3.6m -c /torchvision/torchvision/csrc/ops/autocast/deform_conv2d_kernel.cpp -o build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc/ops/autocast/deform_conv2d_kernel.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE="_gcc" -DPYBIND11_STDLIB="_libstdcpp" -DPYBIND11_BUILD_ABI="_cxxabi1011" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=1 -std=c++14
aarch64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/torchvision/torchvision/csrc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda-10.2/include -I/usr/include/python3.6m -c /torchvision/torchvision/csrc/ops/autocast/nms_kernel.cpp -o build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc/ops/autocast/nms_kernel.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE="_gcc" -DPYBIND11_STDLIB="_libstdcpp" -DPYBIND11_BUILD_ABI="_cxxabi1011" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=1 -std=c++14
aarch64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/torchvision/torchvision/csrc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda-10.2/include -I/usr/include/python3.6m -c /torchvision/torchvision/csrc/ops/autocast/ps_roi_align_kernel.cpp -o build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc/ops/autocast/ps_roi_align_kernel.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE="_gcc" -DPYBIND11_STDLIB="_libstdcpp" -DPYBIND11_BUILD_ABI="_cxxabi1011" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=1 -std=c++14
aarch64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/torchvision/torchvision/csrc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda-10.2/include -I/usr/include/python3.6m -c /torchvision/torchvision/csrc/ops/autocast/ps_roi_pool_kernel.cpp -o build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc/ops/autocast/ps_roi_pool_kernel.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE="_gcc" -DPYBIND11_STDLIB="_libstdcpp" -DPYBIND11_BUILD_ABI="_cxxabi1011" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=1 -std=c++14
aarch64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/torchvision/torchvision/csrc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda-10.2/include -I/usr/include/python3.6m -c /torchvision/torchvision/csrc/ops/autocast/roi_align_kernel.cpp -o build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc/ops/autocast/roi_align_kernel.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE="_gcc" -DPYBIND11_STDLIB="_libstdcpp" -DPYBIND11_BUILD_ABI="_cxxabi1011" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=1 -std=c++14
aarch64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/torchvision/torchvision/csrc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda-10.2/include -I/usr/include/python3.6m -c /torchvision/torchvision/csrc/ops/autocast/roi_pool_kernel.cpp -o build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc/ops/autocast/roi_pool_kernel.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE="_gcc" -DPYBIND11_STDLIB="_libstdcpp" -DPYBIND11_BUILD_ABI="_cxxabi1011" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=1 -std=c++14
aarch64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/torchvision/torchvision/csrc -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda-10.2/include -I/usr/include/python3.6m -c /torchvision/torchvision/csrc/ops/autograd/deform_conv2d_kernel.cpp -o build/temp.linux-aarch64-3.6/torchvision/torchvision/csrc/ops/autograd/deform_conv2d_kernel.o -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE="_gcc" -DPYBIND11_STDLIB="_libstdcpp" -DPYBIND11_BUILD_ABI="_cxxabi1011" -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=1 -std=c++14
/torchvision/torchvision/csrc/ops/autograd/deform_conv2d_kernel.cpp: In static member function 'static torch::autograd::variable_list vision::ops::{anonymous}::DeformConv2dFunction::forward(torch::autograd::AutogradContext*, const Variable&, const Variable&, const Variable&, const Variable&, const Variable&, int64_t, int64_t, int64_t, int64_t, int64_t, int64_t, int64_t, int64_t, bool)':
/torchvision/torchvision/csrc/ops/autograd/deform_conv2d_kernel.cpp:30:9: error: 'AutoDispatchBelowADInplaceOrView' is not a member of 'at'
at::AutoDispatchBelowADInplaceOrView g;
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/torchvision/torchvision/csrc/ops/autograd/deform_conv2d_kernel.cpp: In static member function 'static torch::autograd::variable_list vision::ops::{anonymous}::DeformConv2dBackwardFunction::forward(torch::autograd::AutogradContext*, const Variable&, const Variable&, const Variable&, const Variable&, const Variable&, const Variable&, int64_t, int64_t, int64_t, int64_t, int64_t, int64_t, int64_t, int64_t, bool)':
/torchvision/torchvision/csrc/ops/autograd/deform_conv2d_kernel.cpp:145:9: error: 'AutoDispatchBelowADInplaceOrView' is not a member of 'at'
at::AutoDispatchBelowADInplaceOrView g;
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In file included from /usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include/torch/autograd.h:4:0,
from /torchvision/torchvision/csrc/ops/autograd/deform_conv2d_kernel.cpp:3:
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/custom_function.h: In instantiation of 'torch::autograd::variable_list torch::autograd::CppNode<T>::apply(torch::autograd::variable_list&&) [with T = vision::ops::{anonymous}::DeformConv2dBackwardFunction; torch::autograd::variable_list = std::vector<at::Tensor>]':
/torchvision/torchvision/csrc/ops/autograd/deform_conv2d_kernel.cpp:266:1: required from here
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/custom_function.h:279:19: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
if (num_outputs > num_forward_inputs) {
~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/custom_function.h:290:19: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
if (num_outputs != num_forward_inputs) {
~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/custom_function.h:300:21: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
for (int i = 0; i < num_outputs; ++i) {
~~^~~~~~~~~~~~~
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/custom_function.h: In instantiation of 'torch::autograd::variable_list torch::autograd::CppNode<T>::apply(torch::autograd::variable_list&&) [with T = vision::ops::{anonymous}::DeformConv2dFunction; torch::autograd::variable_list = std::vector<at::Tensor>]':
/torchvision/torchvision/csrc/ops/autograd/deform_conv2d_kernel.cpp:266:1: required from here
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/custom_function.h:279:19: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
if (num_outputs > num_forward_inputs) {
~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/custom_function.h:290:19: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
if (num_outputs != num_forward_inputs) {
~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/custom_function.h:300:21: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
for (int i = 0; i < num_outputs; ++i) {
~~^~~~~~~~~~~~~
error: command 'aarch64-linux-gnu-gcc' failed with exit status 1
I can not understand what is going wrong.
Hi @andhover, which version of PyTorch do you have installed in the container? The torchvision version appears to be mismatched with the PyTorch version.
You may want to check the build scripts and dockerfiles from https://github.com/dusty-nv/jetson-containers
Sorry, I forgot to mention pytorch v1.10.0. It’s mentioned in instruction that with pytorch 1.10.0 comes torchvision v. 0.11.1
OK yes, I am able to use torchvision v0.11.1 with PyTorch 1.10.0. If you try building the container with jetson-containers, you can disable the other configs here:
Hi,I met a trouble installing torchvision.
sudo python3 setup.py install
warning: ignoring #pragma omp parallel [-Wunknown-pragmas]
#pragma omp parallel for if ((end - begin) >= grain_size)
In file included from /home/deeplearn/下载/vision-0.8.0/torchvision/csrc/vision.cpp:14:0:
/home/deeplearn/下载/vision-0.8.0/torchvision/csrc/ROIAlign.h: In function ‘at::Tensor ROIAlign_autocast(const at::Tensor&, const at::Tensor&, double, int64_t, int64_t, int64_t, bool)’:
/home/deeplearn/下载/vision-0.8.0/torchvision/csrc/ROIAlign.h:52:28: error: ‘cached_cast’ is not a member of ‘at::autocast’
at::autocast::cached_cast(at::kFloat, input),
^~~~~~~~~~~
/home/deeplearn/下载/vision-0.8.0/torchvision/csrc/ROIAlign.h:53:28: error: ‘cached_cast’ is not a member of ‘at::autocast’
at::autocast::cached_cast(at::kFloat, rois),
^~~~~~~~~~~
In file included from /home/deeplearn/下载/vision-0.8.0/torchvision/csrc/vision.cpp:17:0:
/home/deeplearn/下载/vision-0.8.0/torchvision/csrc/nms.h: In function ‘at::Tensor nms_autocast(const at::Tensor&, const at::Tensor&, double)’:
/home/deeplearn/下载/vision-0.8.0/torchvision/csrc/nms.h:31:21: error: ‘cached_cast’ is not a member of ‘at::autocast’
at::autocast::cached_cast(at::kFloat, dets),
^~~~~~~~~~~
/home/deeplearn/下载/vision-0.8.0/torchvision/csrc/nms.h:32:21: error: ‘cached_cast’ is not a member of ‘at::autocast’
at::autocast::cached_cast(at::kFloat, scores),
^~~~~~~~~~~
error: command 'aarch64-linux-gnu-gcc' failed with exit status 1
what can I do?Thanks.
Hey I am using the new Jetpack version 5 on the AGX and I tried to install pytorch v1.12.0. During the import of pytorch in python I receive the following error:
OSError: libcurand.so.10: cannot open shared object file: No such file or directory
I used the following commands to install pytorch:
wget https://developer.download.nvidia.com/compute/redist/jp/v50/pytorch/torch-1.12.0a0+2c916ef.nv22.3-cp38-cp38-linux_aarch64.whl -O torch-1.12.0a0+2c916ef.nv22.3-cp38-cp38-linux_aarch64.whl
sudo apt-get install python3-pip libopenblas-base libopenmpi-dev libomp-dev
pip3 install Cython
pip3 install numpy torch-1.12.0a0+2c916ef.nv22.3-cp38-cp38-linux_aarch64.whl
I am actually quite desperate at this point, because I am spending now hours to fix that. Since we need it quite fast, a fast reply would be awesome.
I’m revisiting my Docker process to build PyTorch from source. Are there patches for PyTorch 1.11 and beyond, or have the fixes been migrated into the PyTorch code base?
Hi
Can you tell me how to install MAGMA and its version number? and how to compile it form the source code of pytorch？
Hi @znmeb, I haven’t built PyTorch 1.11, but suffice it to say that my 1.10 patches would be a good starting point. Also, I’m not sure if Python 3.6 is supported past PyTorch 1.10, so you may need JetPack 5.0 (or upgrade Python if you are on Python 4.x) to build it.
Hi @18208947737, I haven’t built MAGMA before, you may want to open a new topic about that.
Hi @robert.scheffler, do you have CUDA Toolkit installed okay? Can you check the following directory:
ls -ll /usr/local/cuda/lib64/
total 3626264
lrwxrwxrwx 1 root root 17 Nov 15 04:07 libcublasLt.so -> libcublasLt.so.11
lrwxrwxrwx 1 root root 24 Nov 15 04:07 libcublasLt.so.11 -> libcublasLt.so.11.6.5.24
-rw-r--r-- 1 root root 371525152 Nov 15 04:07 libcublasLt.so.11.6.5.24
-rw-r--r-- 1 root root 502851542 Nov 15 04:07 libcublasLt_static.a
lrwxrwxrwx 1 root root 15 Nov 15 04:07 libcublas.so -> libcublas.so.11
lrwxrwxrwx 1 root root 22 Nov 15 04:07 libcublas.so.11 -> libcublas.so.11.6.5.24
-rw-r--r-- 1 root root 168021872 Nov 15 04:07 libcublas.so.11.6.5.24
-rw-r--r-- 1 root root 212415888 Nov 15 04:07 libcublas_static.a
-rw-r--r-- 1 root root 796212 Nov 15 02:30 libcudadevrt.a
lrwxrwxrwx 1 root root 17 Nov 15 02:30 libcudart.so -> libcudart.so.11.0
lrwxrwxrwx 1 root root 21 Nov 15 02:30 libcudart.so.11.0 -> libcudart.so.11.4.167
-rw-r--r-- 1 root root 670808 Nov 15 02:30 libcudart.so.11.4.167
-rw-r--r-- 1 root root 1078022 Nov 15 02:30 libcudart_static.a
lrwxrwxrwx 1 root root 13 Nov 17 03:57 libcudla.so -> libcudla.so.1
lrwxrwxrwx 1 root root 17 Nov 17 03:57 libcudla.so.1 -> libcudla.so.1.0.0
-rw-r--r-- 1 root root 159296 Nov 17 03:57 libcudla.so.1.0.0
lrwxrwxrwx 1 root root 14 Nov 15 03:49 libcufft.so -> libcufft.so.10
lrwxrwxrwx 1 root root 21 Nov 15 03:49 libcufft.so.10 -> libcufft.so.10.6.0.71
-rw-r--r-- 1 root root 174702496 Nov 15 03:49 libcufft.so.10.6.0.71
-rw-r--r-- 1 root root 215629292 Nov 15 03:49 libcufft_static.a
-rw-r--r-- 1 root root 187336232 Nov 15 03:49 libcufft_static_nocallback.a
lrwxrwxrwx 1 root root 15 Nov 15 03:49 libcufftw.so -> libcufftw.so.10
lrwxrwxrwx 1 root root 22 Nov 15 03:49 libcufftw.so.10 -> libcufftw.so.10.6.0.71
-rw-r--r-- 1 root root 740776 Nov 15 03:49 libcufftw.so.10.6.0.71
-rw-r--r-- 1 root root 30202 Nov 15 03:49 libcufftw_static.a
-rw-r--r-- 1 root root 1436538 Nov 15 02:22 libcufilt.a
-rw-r--r-- 1 root root 33242 Nov 15 02:30 libculibos.a
lrwxrwxrwx 1 root root 16 Nov 15 03:52 libcupti.so -> libcupti.so.11.4
lrwxrwxrwx 1 root root 20 Nov 15 03:52 libcupti.so.11.4 -> libcupti.so.2021.2.2
-rw-r--r-- 1 root root 5782696 Nov 15 03:52 libcupti.so.2021.2.2
lrwxrwxrwx 1 root root 15 Nov 12 13:45 libcurand.so -> libcurand.so.10
lrwxrwxrwx 1 root root 23 Nov 12 13:45 libcurand.so.10 -> libcurand.so.10.2.5.165
-rw-r--r-- 1 root root 81480832 Nov 12 13:45 libcurand.so.10.2.5.165
-rw-r--r-- 1 root root 81438022 Nov 12 13:45 libcurand_static.a
lrwxrwxrwx 1 root root 19 Nov 12 13:56 libcusolverMg.so -> libcusolverMg.so.11
lrwxrwxrwx 1 root root 27 Nov 12 13:56 libcusolverMg.so.11 -> libcusolverMg.so.11.2.0.165
-rw-r--r-- 1 root root 258827504 Nov 12 13:56 libcusolverMg.so.11.2.0.165
lrwxrwxrwx 1 root root 17 Nov 12 13:56 libcusolver.so -> libcusolver.so.11
lrwxrwxrwx 1 root root 25 Nov 12 13:56 libcusolver.so.11 -> libcusolver.so.11.2.0.165
-rw-r--r-- 1 root root 218556608 Nov 12 13:56 libcusolver.so.11.2.0.165
-rw-r--r-- 1 root root 211452066 Nov 12 13:56 libcusolver_static.a
lrwxrwxrwx 1 root root 17 Nov 12 13:50 libcusparse.so -> libcusparse.so.11
lrwxrwxrwx 1 root root 25 Nov 12 13:50 libcusparse.so.11 -> libcusparse.so.11.6.0.165
-rw-r--r-- 1 root root 230611448 Nov 12 13:50 libcusparse.so.11.6.0.165
-rw-r--r-- 1 root root 256717656 Nov 12 13:50 libcusparse_static.a
-rw-r--r-- 1 root root 15858550 Nov 12 13:56 liblapack_static.a
-rw-r--r-- 1 root root 909274 Nov 12 13:56 libmetis_static.a
lrwxrwxrwx 1 root root 13 Nov 12 14:00 libnppc.so -> libnppc.so.11
lrwxrwxrwx 1 root root 21 Nov 12 14:00 libnppc.so.11 -> libnppc.so.11.4.0.155
-rw-r--r-- 1 root root 1564840 Nov 12 14:00 libnppc.so.11.4.0.155
-rw-r--r-- 1 root root 26846 Nov 12 14:00 libnppc_static.a
lrwxrwxrwx 1 root root 15 Nov 12 14:00 libnppial.so -> libnppial.so.11
lrwxrwxrwx 1 root root 23 Nov 12 14:00 libnppial.so.11 -> libnppial.so.11.4.0.155
-rw-r--r-- 1 root root 13533736 Nov 12 14:00 libnppial.so.11.4.0.155
-rw-r--r-- 1 root root 15378762 Nov 12 14:00 libnppial_static.a
lrwxrwxrwx 1 root root 15 Nov 12 14:00 libnppicc.so -> libnppicc.so.11
lrwxrwxrwx 1 root root 23 Nov 12 14:00 libnppicc.so.11 -> libnppicc.so.11.4.0.155
-rw-r--r-- 1 root root 6509104 Nov 12 14:00 libnppicc.so.11.4.0.155
-rw-r--r-- 1 root root 6291604 Nov 12 14:00 libnppicc_static.a
lrwxrwxrwx 1 root root 16 Nov 12 14:00 libnppidei.so -> libnppidei.so.11
lrwxrwxrwx 1 root root 24 Nov 12 14:00 libnppidei.so.11 -> libnppidei.so.11.4.0.155
-rw-r--r-- 1 root root 9937808 Nov 12 14:00 libnppidei.so.11.4.0.155
-rw-r--r-- 1 root root 11479354 Nov 12 14:00 libnppidei_static.a
lrwxrwxrwx 1 root root 14 Nov 12 14:00 libnppif.so -> libnppif.so.11
lrwxrwxrwx 1 root root 22 Nov 12 14:00 libnppif.so.11 -> libnppif.so.11.4.0.155
-rw-r--r-- 1 root root 79115976 Nov 12 14:00 libnppif.so.11.4.0.155
-rw-r--r-- 1 root root 82495146 Nov 12 14:00 libnppif_static.a
lrwxrwxrwx 1 root root 14 Nov 12 14:00 libnppig.so -> libnppig.so.11
lrwxrwxrwx 1 root root 22 Nov 12 14:00 libnppig.so.11 -> libnppig.so.11.4.0.155
-rw-r--r-- 1 root root 34841224 Nov 12 14:00 libnppig.so.11.4.0.155
-rw-r--r-- 1 root root 36462618 Nov 12 14:00 libnppig_static.a
lrwxrwxrwx 1 root root 14 Nov 12 14:00 libnppim.so -> libnppim.so.11
lrwxrwxrwx 1 root root 22 Nov 12 14:00 libnppim.so.11 -> libnppim.so.11.4.0.155
-rw-r--r-- 1 root root 8880704 Nov 12 14:00 libnppim.so.11.4.0.155
-rw-r--r-- 1 root root 8057652 Nov 12 14:00 libnppim_static.a
lrwxrwxrwx 1 root root 15 Nov 12 14:00 libnppist.so -> libnppist.so.11
lrwxrwxrwx 1 root root 23 Nov 12 14:00 libnppist.so.11 -> libnppist.so.11.4.0.155
-rw-r--r-- 1 root root 34354008 Nov 12 14:00 libnppist.so.11.4.0.155
-rw-r--r-- 1 root root 36021764 Nov 12 14:00 libnppist_static.a
lrwxrwxrwx 1 root root 15 Nov 12 14:00 libnppisu.so -> libnppisu.so.11
lrwxrwxrwx 1 root root 23 Nov 12 14:00 libnppisu.so.11 -> libnppisu.so.11.4.0.155
-rw-r--r-- 1 root root 658520 Nov 12 14:00 libnppisu.so.11.4.0.155
-rw-r--r-- 1 root root 11458 Nov 12 14:00 libnppisu_static.a
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drwxr-xr-x 2 root root 4096 Mar 24 18:02 stubs
Hi! I’ve compiled torch1.10.0 from source with Clang on Xavier NX for python3.8, and the process took 9 hours.
Here’s the Google Drive link：
And here’s the Baidu Net Disk link:
I’m not sure whether the extraction code is necessary when you download through the Baidu link, if needed, the extraction code is:
vhys
I hope it helps you.
1 Like
I have installed Jetpack 5.0 on my Jetson Xavier AGX and I am trying to create a torchscript file from Detectron2 weights. I have used the torch-1.12 provided and torch & torchvision seem to be correctly installed when I open a python shell and print their versions. However when I try to create a torchscript model I get errors about missing torchvision ops, similar as posted here: MIssing torchvision::nms error in the C++ CUDA TorchVision API · Issue #5697 · pytorch/vision · GitHub.
Most things I seem to point to an incompatible torch & torchvision version but according to (torchvision · PyPI) the versions in the 1.12 and 1.10 wheels for pytorch I got from here (jetson-containers/docker_build_ml.sh at master · dusty-nv/jetson-containers · GitHub) are compatible.
The full error I get is:
RuntimeError:
object has no attribute nms:
File "/home/jetsonxavier/.local/lib/python3.8/site-packages/torchvision/ops/boxes.py", line 35
"""
_assert_has_ops()
return torch.ops.torchvision.nms(boxes, scores, iou_threshold)
~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
'nms' is being compiled since it was called from '_batched_nms_vanilla'
File "/home/jetsonxavier/.local/lib/python3.8/site-packages/torchvision/ops/boxes.py", line 102
for class_id in torch.unique(idxs):
curr_indices = torch.where(idxs == class_id)[0]
curr_keep_indices = nms(boxes[curr_indices], scores[curr_indices], iou_threshold)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
keep_mask[curr_indices[curr_keep_indices]] = True
keep_indices = torch.where(keep_mask)[0]
'_batched_nms_vanilla' is being compiled since it was called from 'batched_nms'
File "/home/jetsonxavier/.local/lib/python3.8/site-packages/torchvision/ops/boxes.py", line 66
# Ideally for GPU we'd use a higher threshold
if boxes.numel() > 4_000 and not torchvision._is_tracing():
return _batched_nms_vanilla(boxes, scores, idxs, iou_threshold)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
else:
return _batched_nms_coordinate_trick(boxes, scores, idxs, iou_threshold)
'batched_nms' is being compiled since it was called from 'batched_nms'
File "/home/jetsonxavier/Projects/F3D/detectron2/detectron2/layers/nms.py", line 20
# just call it directly.
# Fp16 does not have enough range for batched NMS, so adding float().
return box_ops.batched_nms(boxes.float(), scores, idxs, iou_threshold)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
'batched_nms' is being compiled since it was called from 'find_top_rpn_proposals'
File "/home/jetsonxavier/Projects/F3D/detectron2/detectron2/modeling/proposal_generator/proposal_utils.py", line 112
boxes, scores_per_img, lvl = boxes[keep], scores_per_img[keep], lvl[keep]
keep = batched_nms(boxes.tensor, scores_per_img, lvl, nms_thresh)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
# In Detectron1, there was different behavior during training vs. testing.
# (https://github.com/facebookresearch/Detectron/issues/459)
'find_top_rpn_proposals' is being compiled since it was called from 'RPN.predict_proposals'
File "/home/jetsonxavier/Projects/F3D/detectron2/detectron2/modeling/proposal_generator/rpn.py", line 503
with torch.no_grad():
pred_proposals = self._decode_proposals(anchors, pred_anchor_deltas)
return find_top_rpn_proposals(
~~~~~~~~~~~~~~~~~~~~~~~
pred_proposals,
~~~~~~~~~~~~~~~
pred_objectness_logits,
~~~~~~~~~~~~~~~~~~~~~~~
image_sizes,
~~~~~~~~~~~~
self.nms_thresh,
~~~~~~~~~~~~~~~~
self.pre_nms_topk[self.training],
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
self.post_nms_topk[self.training],
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
self.min_box_size,
~~~~~~~~~~~~~~~~~~
self.training,
~~~~~~~~~~~~~ <--- HERE
)
'RPN.predict_proposals' is being compiled since it was called from 'RPN.forward'
File "/home/jetsonxavier/Projects/F3D/detectron2/detectron2/modeling/proposal_generator/rpn.py", line 477
else:
losses = {}
proposals = self.predict_proposals(
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
anchors, pred_objectness_logits, pred_anchor_deltas, images.image_sizes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
)
return proposals, losses
This is the error message when I try to create torchscript file. When I try to run a .pth weights file I get the following error message:
RuntimeError: Couldn't load custom C++ ops. This can happen if your PyTorch and torchvision versions are incompatible,
or if you had errors while compiling torchvision from source. For further information on the compatible versions, check https://github.com/pytorch/vision#installation
for the compatibility matrix. Please check your PyTorch version with torch.__version__ and your torchvision version with torchvision.__version__ and
verify if they are compatible, and if not please reinstall torchvision so that it matches your PyTorch install
They both seem to be related to the torch & torchvision compatibility.
Has anybody encountered the same problems?
1 Like
- Python 3.6 - [
torch-1.10.0-cp36-cp36m-linux_aarch64.whl] can not download ， why？