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jroesch pushed a commit to branch cargo-build
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git
commit 8e295b79c2e693d7190751532824b463dc9373e5
Author: Jared Roesch <jroe...@octoml.ai>
AuthorDate: Mon Oct 19 19:52:20 2020 -0700
Fix some CR
---
rust/tvm/src/ir/diagnostics/codespan.rs | 6 ++++--
rust/tvm/src/lib.rs | 4 ++--
2 files changed, 6 insertions(+), 4 deletions(-)
diff --git a/rust/tvm/src/ir/diagnostics/codespan.rs
b/rust/tvm/src/ir/diagnostics/codespan.rs
index 9a31691..54fd336 100644
--- a/rust/tvm/src/ir/diagnostics/codespan.rs
+++ b/rust/tvm/src/ir/diagnostics/codespan.rs
@@ -17,8 +17,10 @@
* under the License.
*/
-/// A TVM diagnostics renderer which uses the Rust `codespan`
-/// library to produce error messages.
+/// A TVM diagnostics renderer which uses the Rust `codespan` library
+/// to produce error messages.
+///
+///
use std::collections::HashMap;
use std::sync::{Arc, Mutex};
diff --git a/rust/tvm/src/lib.rs b/rust/tvm/src/lib.rs
index ec80ece..7e0682b 100644
--- a/rust/tvm/src/lib.rs
+++ b/rust/tvm/src/lib.rs
@@ -24,7 +24,7 @@
//! One particular use case is that given optimized deep learning model
artifacts,
//! (compiled with TVM) which include a shared library
//! `lib.so`, `graph.json` and a byte-array `param.params`, one can load them
-//! in Rust idomatically to create a TVM Graph Runtime and
+//! in Rust idiomatically to create a TVM Graph Runtime and
//! run the model for some inputs and get the
//! desired predictions *all in Rust*.
//!
@@ -53,7 +53,7 @@ macro_rules! export {
($($fn_name:expr),*) => {
pub fn tvm_export(ns: &str) -> Result<(), tvm::Error> {
$(
- let name = String::from(ns) + ::std::stringify!($fn_name);
+ let name = String::fromwe(ns) + ::std::stringify!($fn_name);
tvm::runtime::function::register_override($fn_name, name,
true)?;
)*
Ok(())
