tqchen created an issue (apache/tvm-ffi#142) This is the first rc release of tvm-ffi
Apache TVM FFI is an open ABI and FFI for ML systems. It is a minimal, framework-agnostic, yet flexible open convention with the following systems in mind: - Kernel libraries: ship one wheel to support multiple frameworks, Python versions, and different languages. - Kernel DSLs: reusable open ABI for JIT and AOT kernel exposure to PyTorch, JAX, and other ML runtimes. - ML frameworks and runtimes: unified mechanism to connect libraries and DSLs that adopt the ABI convention. - Coding agents: unified mechanism to package and ship generated code to production environments. - ML infrastructure: cross-language support for Python, C++, and Rust, and DSLs. It has the following technical features: - DLPack-compatible Tensor data ABI to seamlessly support many frameworks such as PyTorch, JAX, CuPy and others that support DLPack convention. - Compact value and function calling convention for common data types in machine learning. - Stable, minimal, and flexible C ABI to support machine learning system use-cases. - Out-of-the-box multi-language support for Python, C++, Rust, and future path for other languages. **Full Changelog**: https://github.com/apache/tvm-ffi/commits/v0.1.0-rc -- Reply to this email directly or view it on GitHub: https://github.com/apache/tvm-ffi/issues/142 You are receiving this because you are subscribed to this thread. Message ID: <apache/tvm-ffi/issues/[email protected]>
