Bump version to v0.8.20

Cargo.toml

@@ -9,7 +9,7 @@ keywords = ["deep-learning", "language", "model", "rwkv"]
 license = "MIT OR Apache-2.0"
 name = "web-rwkv"
 repository = "https://github.com/cryscan/web-rwkv"
-version = "0.8.19"
+version = "0.8.20"
 
 [dependencies]
 ahash = "0.8"

src/tensor/mod.rs

@@ -475,8 +475,6 @@ impl<T: Scalar, K: Kind> TensorReshape for TensorGpu<T, K> {
 impl<T: Scalar, K: Kind> TensorGpu<T, K> {
     #[cfg(not(target_arch = "wasm32"))]
     pub fn back_in_place(&self) -> TensorCpu<T> {
-        use crate::context::ContextEvent;
-
         if self.is_empty() {
             return TensorCpu {
                 shape: self.shape,
@@ -497,7 +495,9 @@ impl<T: Scalar, K: Kind> TensorGpu<T, K> {
         context.queue.submit(Some(encoder.finish()));
 
         let (sender, receiver) = tokio::sync::oneshot::channel();
-        let _ = context.event().send(ContextEvent { buffer, sender });
+        let _ = context
+            .event()
+            .send(crate::context::ContextEvent { buffer, sender });
         let data = receiver.blocking_recv().unwrap();
         let data = unsafe {
             let data = Box::leak(data);
@@ -516,8 +516,6 @@ impl<T: Scalar, K: Kind> TensorGpu<T, K> {
 
     #[cfg(not(target_arch = "wasm32"))]
     pub async fn back(&self) -> TensorCpu<T> {
-        use crate::context::ContextEvent;
-
         if self.is_empty() {
             return TensorCpu {
                 shape: self.shape,
@@ -539,7 +537,9 @@ impl<T: Scalar, K: Kind> TensorGpu<T, K> {
 
         let (sender, receiver) = tokio::sync::oneshot::channel();
 
-        let _ = context.event().send(ContextEvent { buffer, sender });
+        let _ = context
+            .event()
+            .send(crate::context::ContextEvent { buffer, sender });
         let data = receiver.await.unwrap();
         let data = unsafe {
             let data = Box::leak(data);