gemini-code-assist[bot] commented on code in PR #182: URL: https://github.com/apache/tvm-ffi/pull/182#discussion_r2446721485
########## README.md: ########## @@ -22,34 +22,30 @@ Apache TVM FFI is an open ABI and FFI for machine learning 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. +- **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 frameworks and runtimes. +- **Frameworks and runtimes** — a uniform extension point for ABI-compliant libraries and DSLs. +- **ML infrastructure** — out-of-the-box bindings and interop for Python, C++, and Rust. +- **Coding agents** — a unified mechanism for shipping generated code in production. -It has the following technical features: +## 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. +* **Stable, minimal C ABI** designed for kernels, DSLs, and runtime extensibility. +* **Zero-copy interop** across PyTorch, JAX, and CuPy using [DLPack protocol](https://data-apis.org/array-api/2024.12/design_topics/data_interchange.html). +* **Compact value & call convention** covering common data types for ultra low-overhead ML applications. Review Comment:  In technical writing, it's generally preferred to write out "and" instead of using an ampersand (`&`) to maintain a more formal tone and improve readability. Consider replacing `&` with `and`. ```suggestion * **Compact value and call convention** covering common data types for ultra low-overhead ML applications. ``` ########## README.md: ########## @@ -22,34 +22,30 @@ Apache TVM FFI is an open ABI and FFI for machine learning 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. +- **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 frameworks and runtimes. +- **Frameworks and runtimes** — a uniform extension point for ABI-compliant libraries and DSLs. +- **ML infrastructure** — out-of-the-box bindings and interop for Python, C++, and Rust. +- **Coding agents** — a unified mechanism for shipping generated code in production. Review Comment:  There's an inconsistent use of separators in this list. The first item uses a hyphen (`-`), while the subsequent items use an em dash (`—`). For better consistency and readability, it would be best to use the same separator for all list items. I suggest using a hyphen throughout. ```suggestion - **Kernel DSLs** - reusable open ABI for JIT and AOT kernel exposure frameworks and runtimes. - **Frameworks and runtimes** - a uniform extension point for ABI-compliant libraries and DSLs. - **ML infrastructure** - out-of-the-box bindings and interop for Python, C++, and Rust. - **Coding agents** - a unified mechanism for shipping generated code in production. ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
