mosure · mosure · Nov 2, 2025 · Nov 2, 2025 · Nov 2, 2025 · Nov 2, 2025
diff --git a/Cargo.lock b/Cargo.lock
diff --git a/Cargo.toml b/Cargo.toml
@@ -1,7 +1,7 @@
 [package]
 name = "bevy_burn"
 description = "bevy burn bindings"
-version = "0.3.0"
+version = "0.4.0"
 edition = "2021"
 authors = ["mosure <mitchell@mosure.me>"]
 license = "MIT"
@@ -31,14 +31,14 @@ exclude = [
 
 
 [dependencies]
-burn = { version = "0.18", features = ["wgpu"] }
-burn-core = { version = "0.18" }
-burn-cubecl = { version = "0.18" }
-burn-fusion = { version = "0.18" }
-burn-wgpu = { version = "0.18" }
+burn = { version = "0.19", features = ["wgpu"] }
+burn-core = { version = "0.19" }
+burn-cubecl = { version = "0.19" }
+burn-fusion = { version = "0.19" }
+burn-wgpu = { version = "0.19" }
 bytemuck = "1.23"
-cubecl = { version = "0.6", features = ["std", "wgpu"] }
-wgpu = "25.0"
+cubecl = { version = "0.8", features = ["std", "wgpu"] }
+wgpu = "26.0"
 
 
 [target.'cfg(target_arch = "wasm32")'.dependencies]
@@ -48,11 +48,11 @@ wasm-bindgen = "0.2"
 
 
 [dependencies.bevy]
-git = "https://github.com/bevyengine/bevy.git"
-rev = "b79b8133c881942a42bb359f998bd8792c48c1bc"
+version = "0.17"
 default-features = false
 features = [
   "bevy_asset",
+  "bevy_camera",
   "bevy_core_pipeline",
   "bevy_image",
   "bevy_log",
@@ -61,11 +61,13 @@ features = [
   "bevy_sprite",
   "bevy_text",
   "bevy_ui",
+  "bevy_ui_render",
   "bevy_window",
   "bevy_winit",
   "debug",
   "default_font",
   "png",
+  "std",
   "tonemapping_luts",
   "webgpu",
   "x11",
@@ -87,6 +89,7 @@ features = [
 
 [dev-dependencies]
 criterion = { version = "0.7", features = ["html_reports"] }
+futures = "0.3"
 
 
 [profile.dev.package."*"]

diff --git a/README.md b/README.md
@@ -6,9 +6,6 @@
 bevy burn data bridge plugin
 
 
-
-
-
 ## features
 - [ ] bevy texture -> burn tensor
 - [x] burn tensor -> bevy texture
@@ -22,9 +19,9 @@ bevy burn data bridge plugin
 
 ```rust
 use bevy::prelude::*;
-use bevy::render::{
-    render_asset::RenderAssetUsages,
-    render_resource::*,
+use bevy::{
+    asset::RenderAssetUsages,
+    render::render_resource::*,
 };
 use burn_core::tensor::Int;
 use burn_wgpu::Wgpu as BurnWgpu;
@@ -93,6 +90,7 @@ fn setup(
 
 | `bevy_burn` | `bevy`  | `burn` |
 | :--         | :--     | :--    |
+| `0.4`       | `0.17`  | `0.19` |
 | `0.3`       | `0.17-dev*` | `0.18` |
 
 > *`wgpu` version must match

diff --git a/bench/io.rs b/bench/io.rs
@@ -1,35 +1,15 @@
-use criterion::{
-    BenchmarkId,
-    criterion_group,
-    criterion_main,
-    Criterion,
-    Throughput,
-};
-
-use bevy::{
-    prelude::*,
-    render::{
-        render_asset::RenderAssetUsages,
-        render_resource::*,
-    },
-};
+use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
+
+use bevy::{asset::RenderAssetUsages, prelude::*, render::render_resource::*};
 use burn::tensor::Tensor;
 use burn_wgpu::Wgpu;
 
-use bevy_burn::{
-    BevyBurnBridgePlugin,
-    BevyBurnHandle,
-    BindingDirection,
-    TransferKind,
-};
-
+use bevy_burn::{BevyBurnBridgePlugin, BevyBurnHandle, BindingDirection, TransferKind};
 
 type BurnBackend = Wgpu<f32, i32>;
 
-
 const SIZE: u32 = 512;
 
-
 fn default_app() -> App {
     let mut app = App::new();
 
@@ -43,7 +23,6 @@ fn default_app() -> App {
     app
 }
 
-
 fn make_image() -> Image {
     let mut img = Image::new_fill(
         Extent3d {
@@ -60,32 +39,25 @@ fn make_image() -> Image {
     img
 }
 
-
 fn bench_burn_to_bevy_cpu(crit: &mut Criterion) {
     let mut app = default_app();
 
     app.add_systems(
         Startup,
-        |
-                    mut cmds: Commands,
-                    mut images: ResMut<Assets<Image>>,
-                | {
-                    let handle = images.add(make_image());
-                    let tensor = Tensor::<BurnBackend, 3>::zeros([
-                            SIZE as usize,
-                            SIZE as usize,
-                            4,
-                        ],
-                        &Default::default(),
-                    );
-                    cmds.spawn(BevyBurnHandle {
-                        bevy_image: handle,
-                        tensor,
-                        upload: true,
-                        direction: BindingDirection::BurnToBevy,
-                        xfer: TransferKind::Cpu,
-                    });
-                },
+        |mut cmds: Commands, mut images: ResMut<Assets<Image>>| {
+            let handle = images.add(make_image());
+            let tensor = Tensor::<BurnBackend, 3>::zeros(
+                [SIZE as usize, SIZE as usize, 4],
+                &Default::default(),
+            );
+            cmds.spawn(BevyBurnHandle {
+                bevy_image: handle,
+                tensor,
+                upload: true,
+                direction: BindingDirection::BurnToBevy,
+                xfer: TransferKind::Cpu,
+            });
+        },
     );
 
     app.add_systems(
@@ -110,32 +82,25 @@ fn bench_burn_to_bevy_cpu(crit: &mut Criterion) {
     group.finish();
 }
 
-
 fn bench_bevy_to_burn_cpu(crit: &mut Criterion) {
     let mut app = default_app();
 
     app.add_systems(
         Startup,
-        |
-                    mut cmds: Commands,
-                    mut images: ResMut<Assets<Image>>,
-                | {
-                    let handle = images.add(make_image());
-                    let tensor = Tensor::<BurnBackend, 3>::zeros([
-                            SIZE as usize,
-                            SIZE as usize,
-                            4,
-                        ],
-                        &Default::default(),
-                    );
-                    cmds.spawn(BevyBurnHandle {
-                        bevy_image: handle,
-                        tensor,
-                        upload: true,
-                        direction: BindingDirection::BevyToBurn,
-                        xfer: TransferKind::Cpu,
-                    });
-                },
+        |mut cmds: Commands, mut images: ResMut<Assets<Image>>| {
+            let handle = images.add(make_image());
+            let tensor = Tensor::<BurnBackend, 3>::zeros(
+                [SIZE as usize, SIZE as usize, 4],
+                &Default::default(),
+            );
+            cmds.spawn(BevyBurnHandle {
+                bevy_image: handle,
+                tensor,
+                upload: true,
+                direction: BindingDirection::BevyToBurn,
+                xfer: TransferKind::Cpu,
+            });
+        },
     );
 
     app.add_systems(
@@ -160,10 +125,6 @@ fn bench_bevy_to_burn_cpu(crit: &mut Criterion) {
     group.finish();
 }
 
-
-
-
-
 // TODO: fix main thread issues for gpu benchmarking/tests
 // fn bench_burn_to_bevy_gpu(crit: &mut Criterion) {
 //     let mut app = default_app();
@@ -214,7 +175,6 @@ fn bench_bevy_to_burn_cpu(crit: &mut Criterion) {
 //     group.finish();
 // }
 
-
 // fn bench_bevy_to_burn_gpu(crit: &mut Criterion) {
 //     let mut app = default_app();
 
@@ -264,10 +224,7 @@ fn bench_bevy_to_burn_cpu(crit: &mut Criterion) {
 //     group.finish();
 // }
 
-
-
-
-criterion_group!{
+criterion_group! {
     name = io_benches;
     config = Criterion::default().sample_size(10);
     targets = bench_burn_to_bevy_cpu,

diff --git a/example/gpu_interop.rs b/example/gpu_interop.rs
@@ -1,13 +1,10 @@
 #![recursion_limit = "256"]
 
 use bevy::prelude::*;
-use bevy::render::{
-    render_asset::RenderAssetUsages,
-    render_resource::*,
-};
+use bevy::{asset::RenderAssetUsages, render::render_resource::*};
+use bevy_burn::*;
 use burn_core::tensor::{Int, Tensor};
 use burn_wgpu::Wgpu as BurnWgpu;
-use bevy_burn::*;
 
 type BB = BurnWgpu<f32, i32>;
 
@@ -29,11 +26,7 @@ struct Plasma {
     a: Tensor<BB, 2>,
 }
 
-fn setup(
-    mut cmds: Commands,
-    mut images: ResMut<Assets<Image>>,
-    burn: Res<BurnDevice>,
-) {
+fn setup(mut cmds: Commands, mut images: ResMut<Assets<Image>>, burn: Res<BurnDevice>) {
     let size = Extent3d {
         width: SIZE,
         height: SIZE,
@@ -71,13 +64,25 @@ fn setup(
     let x = Tensor::<BB, 2>::zeros([h, 1], &dev) + xs; // [h, w]
     let y = ys + Tensor::<BB, 2>::zeros([1, w], &dev); // [h, w]
     let a1 = Tensor::<BB, 2>::ones([h, w], &dev);
-    let boot_r = x.clone().mul_scalar(8.0).sin().mul_scalar(0.5).add_scalar(0.5);
-    let boot_g = x.clone().add(y.clone())
+    let boot_r = x
+        .clone()
+        .mul_scalar(8.0)
+        .sin()
+        .mul_scalar(0.5)
+        .add_scalar(0.5);
+    let boot_g = x
+        .clone()
+        .add(y.clone())
         .mul_scalar(6.0)
         .sin()
         .mul_scalar(0.5)
         .add_scalar(0.5);
-    let boot_b = y.clone().mul_scalar(8.0).sin().mul_scalar(0.5).add_scalar(0.5);
+    let boot_b = y
+        .clone()
+        .mul_scalar(8.0)
+        .sin()
+        .mul_scalar(0.5)
+        .add_scalar(0.5);
     let rgba = Tensor::<BB, 2>::stack(vec![boot_r, boot_g, boot_b, a1.clone()], 2);
 
     cmds.spawn((
@@ -98,35 +103,31 @@ fn setup(
     cmds.spawn(Camera2d);
 }
 
-
-fn animate_plasma(
-    time: Res<Time>,
-    mut q: Query<(&Plasma, &mut BevyBurnHandle<BB>)>,
-) {
+fn animate_plasma(time: Res<Time>, mut q: Query<(&Plasma, &mut BevyBurnHandle<BB>)>) {
     let t = time.elapsed_secs();
     for (p, mut h) in &mut q {
-        let r = p.x
-            .clone()
-            .mul_scalar(8.0)
-            .add_scalar(t * 1.00)
-            .sin()
-            .mul_scalar(0.5)
-            .add_scalar(0.5);
-        let g = p.x
-            .clone()
-            .add(p.y.clone())
-            .mul_scalar(6.0)
-            .add_scalar(t * 1.37)
-            .sin()
-            .mul_scalar(0.5)
-            .add_scalar(0.5);
-        let b = p.y
-            .clone()
-            .mul_scalar(9.0)
-            .add_scalar(-t * 0.73)
-            .sin()
-            .mul_scalar(0.5)
-            .add_scalar(0.5);
+        let r =
+            p.x.clone()
+                .mul_scalar(8.0)
+                .add_scalar(t * 1.00)
+                .sin()
+                .mul_scalar(0.5)
+                .add_scalar(0.5);
+        let g =
+            p.x.clone()
+                .add(p.y.clone())
+                .mul_scalar(6.0)
+                .add_scalar(t * 1.37)
+                .sin()
+                .mul_scalar(0.5)
+                .add_scalar(0.5);
+        let b =
+            p.y.clone()
+                .mul_scalar(9.0)
+                .add_scalar(-t * 0.73)
+                .sin()
+                .mul_scalar(0.5)
+                .add_scalar(0.5);
         let rgba = Tensor::<BB, 2>::stack(vec![r, g, b, p.a.clone()], 2);
         h.tensor = rgba;
         h.upload = true;