This crate provides an idiomatic Rust API for TVM runtime, see here for more details.
TVM is an end-to-end deep learning compiler which takes high level machine learning models or tensor computations and lowers them into executable code for a variety of heterogenous devices (e.g., CPU, GPU).
This crate provides access to the APIs for manipulating runtime data structures, as well as TVM's cross-language Object system which functions similarly to systems such as COM, enabling cross-language interoperability.
Please follow TVM installation instructions, export TVM_HOME=/path/to/tvm
and add libtvm_runtime
to your LD_LIBRARY_PATH
.
One can use register!
macro to expose a Rust closure with arguments which implement TryFrom<ArgValue>
and return types which implement Into<RetValue>
. Once registered with TVM these functions can be accessed via Python or C++, or any other language which implements the TVM packed function convention see the offcial documentation for more information.
use tvm_rt::{ArgValue, RetValue}; use tvm_rt::function::{Function, Result, register}; fn sum(x: i64, y: i64, z: i64) -> i64 { x + y + z } fn main() { register(sum, "mysum".to_owned()).unwrap(); let func = Function::get("mysum").unwrap(); let boxed_fn: Box<dyn Fn(i64, i64, i64) -> Result<i64>> = func.into(); let ret = boxed_fn(10, 20, 30).unwrap(); assert_eq!(ret, 60); }