Jetson Nano Jetbot Install "create-sdcard-image-from-scratch" pytorch vision error

Error at :
git clone GitHub - pytorch/vision: Datasets, Transforms and Models specific to Computer Vision
cd vision
#git checkout v0.4.0
sudo -H python3 setup.py install

/home/jetbot/vision/torchvision/csrc/ops/autocast/deform_conv2d_kernel.cpp: In function ‘ at::Tensor vision::ops::
{anonymous}::deform_conv2d_autocast(const at::Tensor&, const at::Tensor&, const at::Tensor&, const at::Tensor&, const at::Tensor&, int64_t, int64_t, int64_t, int64_t, int64_t, int64_t, int64_t, int64_t, bool)
’:
/home/jetbot/vision/torchvision/csrc/ops/autocast/deform_conv2d_kernel.cpp:11:12:

warning:at::Tensor vision::ops::{anonymous}::deform_conv2d_autocast(const at::Tensor&, const at::Tensor&, const at::Tensor&, const at::Tensor&, const at::Tensor&, int64_t, int64_t, int64_t, int64_t, int64_t, int64_t, int64_t, int64_t, bool) ’ defined but not used [ -Wunused-function ]

at::Tensor deform_conv2d_autocast (
**^~~~~~~~~~~~~~~~~~~~~~**
error: command ‘aarch64-linux-gnu-gcc’ failed with exit status 1
jetbot@jetbot-ROS2 : ~/jetbot/scripts $

Thus unable to continue installing Jetbot code, i/e/ torch2RT, tartlets, Jupiter, etc., JetBot services, dependencies

.

Hi Phreddog24,

Thanks for reaching out!

This may be the result of with a mismatch between the version of PyTorch and Torchvision. For using JetBot, the latest validated instructions are located here

https://jetbot.org/v0.4.3/software_setup/sd_card.html

If you’re interested in doing a custom setup and not using these docker containers, I would recommend following this post for installing PyTorch on Jetson

Please let me know if this helps, or if you run into any questions / issues.

Best,
John

Yes, I tried that image on a fresh 64GB SD first which finished ok and JB runs properly but encountered an odd problem regarding displayed SD Card allocations. df -h shows 22 of 24 GB used & several other smaller allocations totaling 7GB, so where is the remaining 35 GB? I tried a Linux command to expand to fill the SD which stated “nothing to do all 64 GB allocated”. I want to also add a ROS2 Foxy Docker to try an additional Jetbot_ros2 project but concerned there will not be sufficient space.

I was able resolve my issue of correctly configuring a fully configured Jetbot 4gb jp45 on a 64gb sd card, with a patch to the Jetbot flash described in another Post. Thus not necessary for me to build Pytorch & torch vision from source. I can now complete my intended installation of a ROS2 Foxy Container on a Jetbot Nano. There may be others who may need to manually configure a Jetson Nano “from scratch”.