If you’re looking to run PyTorch on aarch64 (ARMv8 ARM64) devices, you’ve hit the jackpot! With official support introduced in version 1.8.0, installing it has never been simpler. This guide will walk you through the installation process using conda or pip, giving you a solid start for your AI development journey.

Installation Steps

Before you dive in, ensure that you have a compatible aarch64 device. Now, let’s jump into the installation!

Using Conda (Recommended)

Installing PyTorch via conda is straightforward. Here’s how:

• Open your terminal.
• Run the command:

conda install -c kumatea pytorch

Optionally, you may need to install numpy:

conda install -c kumatea pytorch numpy

CPU-only support is provided but not a requirement:

conda install -c kumatea pytorch numpy cpuonly

Using Pip

Although installing with pip is not recommended from this source, you can still go for it. Here’s how:

• Run the command:

pip install torch

• For faster installation, use prebuilt wheels:

pip install torch -f https://torch.kmtea.eu/whl/stable.html

Using Docker (Deprecated)

If you’re a fan of Docker, you can pull the image using:

docker run -it kumateapytorch

To see all available tags, you can check the Docker hub.

Understanding the Code: An Analogy

Imagine you’re assembling furniture from a flat-pack. Each command in the installation process is like a step in the assembly instructions.

• When you run conda install -c kumatea pytorch, it’s like grabbing the main piece of furniture.
• Installing numpy is akin to finding the right screws and dowels to hold everything together.
• The optional cpuonly command is like deciding whether you need an electric drill. It’s handy, but you can still assemble without it!

Just like assembling your furniture step-by-step, following these installation commands will lead to a successful setup of PyTorch on your aarch64 device!

Troubleshooting

If you run into any issues during installation, here are a few troubleshooting tips:

• If you encounter a RuntimeError while importing, it might be due to mismatched API versions. Upgrade numpy with:

pip install -U numpy

• If things still fail, double-check your version compatibility by referring to the releases page.
• Visit the fxis.ai for insights, updates, or to collaborate on AI development projects.

Final Thoughts

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.