We are excited to announce the release of EvoX 1.1, introducing full integration of torch.compile (TorchDynamo) as the backend compiler! This update replaces the previous TorchScript approach, making EvoX more user-friendly and highly compatible with the broader Python ecosystem.
By leveraging torch.compile, EvoX now captures computation graphs dynamically at runtime, eliminating the need for manual tracing while optimizing performance automatically.
🎯 What’s New?
💡 torch.compile: Smarter, More Flexible Compilation
In EvoX 1.1, we fully adopt torch.compile as the new compilation backend. Unlike the previous tracing-based approach, torch.compile—which internally uses TorchDynamo—intercepts Python execution, dynamically extracts computation graphs, and optimizes them in real time.
This means:
✅ No more manual tracing – Just call torch.compile(workflow.step), and EvoX takes care of the rest.
✅ Seamless Python compatibility – Works with native Python functions and external libraries like NumPy and SciPy.
✅ Better performance – Optimized computation graphs result in faster execution and better hardware utilization.
✅ Future-proof design – Aligns with PyTorch’s roadmap, ensuring long-term compatibility and performance improvements.
🤔 Why Move from TorchScript to torch.compile?
In earlier versions, EvoX relied on tracing-based methods:
- Pre-1.0.0 used JAX tracing for computation graph extraction.
- v1.0.0 switched to TorchScript, enhancing PyTorch integration.
However, these methods had several drawbacks:
🔹 Complex to use – Users had to manually trace graphs and handle intricate debugging.
🔹 Limited compatibility – Struggled with dynamic workflows and non-PyTorch functions.
🔹 Restricted flexibility – Loops, conditionals, and other Python constructs were not always correctly captured.
With torch.compile and TorchDynamo, these issues are gone. EvoX now optimizes dynamically, supporting a broader range of workflows with zero extra effort from users.
🔥 How EvoX 1.1 Makes Your Life Easier
🔹 No more hassle with tracing – Everything happens behind the scenes, making your code cleaner and easier to maintain.
🔹 Works with your existing Python code – No need to modify your workflow for compatibility.
🔹 Faster execution, better scaling – Benefit from PyTorch’s latest optimizations for GPUs and TPUs.
🔹 Future-ready – Stay aligned with PyTorch’s long-term evolution, ensuring continuous performance gains.
📌 Upgrade to EvoX 1.1 Now!
EvoX 1.1 is now officially available! Upgrade today to experience a smarter, faster, and more intuitive computational workflow.
🔗 Get EvoX 1.1: GitHub
Have questions or feedback? Open an issue on GitHub or join our community discussion. Let’s push the boundaries of computational intelligence together! 🚀