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new be3de4c [DOCS] Minor the to the binding doc (#165)
be3de4c is described below
commit be3de4c075dba71b5bb99c9d64a8a8f21b122c00
Author: Tianqi Chen <[email protected]>
AuthorDate: Fri Oct 17 15:44:55 2025 -0400
[DOCS] Minor the to the binding doc (#165)
This PR does minor updates to the binding doc.
---------
Co-authored-by: gemini-code-assist[bot]
<176961590+gemini-code-assist[bot]@users.noreply.github.com>
---
docs/guides/python_packaging.md | 7 ++++---
1 file changed, 4 insertions(+), 3 deletions(-)
diff --git a/docs/guides/python_packaging.md b/docs/guides/python_packaging.md
index 0c191e9..3934b1f 100644
--- a/docs/guides/python_packaging.md
+++ b/docs/guides/python_packaging.md
@@ -20,7 +20,7 @@ This guide explains how to leverage tvm-ffi to expose C++
functions into Python
At a high level, packaging with tvm-ffi offers several benefits:
- **Ship one wheel** that can be used across Python versions, including
free-threaded Python.
-- **Multi-language access** to functions from Python, C++, Rust and other
languages that connect to the ABI.
+- **Multi-language access** to functions from Python, C++, Rust and other
languages that support the ABI.
- **ML Systems Interop** with ML frameworks, DSLs, and libraries while
maintaining minimal dependency.
## Directly using Exported Library
@@ -54,7 +54,8 @@ def add_one(x):
This approach is like using {py:mod}`ctypes` to load and run DLLs, except we
have more powerful features:
-- We can pass in and return a richer set of data types such as
{py:class}`tvm_ffi.Tensor` and strings.
+- We can pass in `torch.Tensor` (or any other DLPack-compatible arrays).
+- We can pass in a richer set of data structures such as strings, tuples, and
dicts.
- {py:class}`tvm_ffi.Function` enables natural callbacks to Python lambdas or
other languages.
- Exceptions are propagated naturally across language boundaries.
@@ -406,7 +407,7 @@ def raise_error(msg):
return _ffi_api.raise_error(msg)
```
-## Build and Use the Package
+### Build and Use the Package
First, build the wheel: