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I’d be happy to help you with installing and importing Torch on your Jetson Orin Nano devkit.
Background
The issue you’re facing is due to the fact that the standard PyTorch installation using pip doesn’t work on Jetson devices, as they require custom-built wheels that are compatible with the device’s architecture and CUDA version. NVIDIA provides these custom wheels through their AI Lab repository.
Solution
To install Torch on your Jetson Orin Nano devkit, you’ll need to download the custom wheels from the NVIDIA AI Lab repository. Here are the steps:
- Check your CUDA version: Before downloading the wheels, make sure you have the correct CUDA version installed on your Jetson device. You can check the CUDA version by running
nvcc --version in your terminal.
- Download the custom wheels: Use the following commands to download the custom wheels for Torch and Torchvision:
wget https://pypi.jetson-ai-lab.dev/jp6/cu12/torch-1.12.0-cp310-cp310-linux_aarch64.whl
wget https://pypi.jetson-ai-lab.dev/jp6/cu12/torchvision-0.13.0-cp310-cp310-linux_aarch64.whl
Note that the URLs may vary depending on the CUDA version and PyTorch version you want to install. Make sure to check the NVIDIA AI Lab repository for the latest available wheels.
3. Install the wheels: Once you’ve downloaded the wheels, install them using pip:
pip3 install torch-1.12.0-cp310-cp310-linux_aarch64.whl
pip3 install torchvision-0.13.0-cp310-cp310-linux_aarch64.whl
- Verify the installation: After installation, verify that Torch is working correctly by running a simple Python script:
import torch
print(torch.__version__)
print(torch.cuda.is_available())
This should print the PyTorch version and indicate that CUDA is available.
Comparison with older Jetpack versions
If you’re using an older Jetpack version, you may need to use a different URL or wheel version. For example, if you’re using Jetpack 4.6, you may need to use the following URLs:
wget https://pypi.jetson-ai-lab.dev/jp46/cu10/torch-1.9.0-cp36-cp36-linux_aarch64.whl
wget https://pypi.jetson-ai-lab.dev/jp46/cu10/torchvision-0.10.0-cp36-cp36-linux_aarch64.whl
Make sure to check the NVIDIA AI Lab repository for the correct wheels and URLs for your specific Jetpack version.
Troubleshooting
If you encounter issues during installation, such as “no route to host” or “file not found” errors, try the following:
- Check your internet connection and ensure that you can access the NVIDIA AI Lab repository.
- Verify that you’re using the correct URLs and wheel versions for your Jetpack version and CUDA version.
- Try using a different download method, such as
curl or wget with the --retry option.
I hope this helps you install and import Torch on your Jetson Orin Nano devkit!
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