Ivy is both an ML transpiler and a framework, currently supporting JAX, TensorFlow, PyTorch, and Numpy.
Ivy unifies all ML frameworks 💥 enabling you not only to write code that can be used with any of these frameworks as the backend, but also to convert 🔄 any function, model or library written in any of them to your preferred framework!
You can check out Ivy as a transpiler and Ivy as a framework to learn more about this, try out Ivy straight away going through the Setting up Ivy section, or dive deep into Ivy's Documentation and Examples!
If you would like to contribute, you can join our growing Community 🌍, check out our Contributing guide, and take a look at the open tasks if you'd like to dive straight in 🧑💻
Let's unify.ai together 🦾
🚀 We have recently enabled Pilot Preview for our Compiler and Transpiler in a private setting, so come take a look by joining our waitlist!
Come join us for an Octernship term as we are on our mission to unify AI. We are looking for folks who have experience working in any of the following domains
- Machine Learning framework development such as TensorFlow, PyTorch, JAX, NumPy, and more
- Development of ML Compilers and Deployment Engines such as XLA, ONNX, OpenAI Triton, TensorRT, and more
Our primary development solely happens around Python, and we make use of Docker and DevContainers to configure environments extensively.
- Submission Date (Updated): August 23, 2023
- Length of the Octernship: 12 weeks
- Stipend: $1000
A candidate must have, at minimum, operational knowledge of the tools we use
It is a major plus point to have expertise/experience in any of the following
To participate, you must be:
-
A verified student on Global Campus
-
18 years or older
-
Active contributor on GitHub (monthly)
Contribute to our PaddlePaddle Frontend Functions!
In this task, you will contribute one PaddlePaddle Front-end function that will become a part of the Ivy master branch. This would involve the following steps
- Choose one function from the list of open function tasks
- Set up your environment to start working with Ivy
- Implement the function using the Ivy framework
- Implement the corresponding test for the function (to know where to place each of those files, refer to our documentation!)
- Commit and make a PR to the Main branch for this addition!
Upon approval and subsequent acceptance, your contribution will be attributed to you and added to the Ivy master branch.
Feel free to ask questions on our Discord server!
Please make sure you adhere to the GitHub Octernships Code of Conduct, and follow these rules:
- Complete the project on your own. Feel free to take help from our Discord, but do not copy code or use external code without comprehending the logic.
- Make sure you add sufficient comments and documentation at each step. That will allow us to evaluate your work, as well as make the code more friendly to read!
🚨 Task must be submitting in your private repository assigned after applying via Octernships Dashboard
Your private assignment repository will be named: ivy-octernships-ml-USERNAME
Students are expected to use the GitHub Flow when working on their project.
- Create a new branch
- Making changes on the new branch
- Create a new Pull Request from
new branch->main - Merge the PR changes into
mainbranch on or before the assignment deadline. - Use GitHub Discussions to ask any relevant questions regarding the project
- Public Pull Requests are not accepted for GitHub Octernships. Apply via the official Octernships dashboard.
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