Merge branch 'main' into feat/burn-vision

Cargo.toml

@@ -54,7 +54,7 @@ log = { default-features = false, version = "0.4.25" }
 md5 = "0.7.0"
 paste = "1"
 percent-encoding = "2.3.1"
-polars = { version = "0.44.2", features = ["lazy"] }
+polars = { version = "0.46.0", features = ["lazy"] }
 pretty_assertions = "1.4.1"
 proc-macro2 = "1.0.93"
 protobuf = "3.7.1"

backend-comparison/src/burnbenchapp/base.rs

@@ -62,6 +62,13 @@ enum BackendValues {
     CandleCuda,
     #[strum(to_string = "candle-metal")]
     CandleMetal,
+    #[strum(to_string = "cuda")]
+    Cuda,
+    #[strum(to_string = "cuda-fusion")]
+    CudaFusion,
+    #[cfg(target_os = "linux")]
+    #[strum(to_string = "hip")]
+    Hip,
     #[strum(to_string = "ndarray")]
     Ndarray,
     #[strum(to_string = "ndarray-blas-accelerate")]
@@ -82,13 +89,6 @@ enum BackendValues {
     WgpuSpirv,
     #[strum(to_string = "wgpu-spirv-fusion")]
     WgpuSpirvFusion,
-    #[strum(to_string = "cuda-jit")]
-    CudaJit,
-    #[strum(to_string = "cuda-jit-fusion")]
-    CudaJitFusion,
-    #[cfg(target_os = "linux")]
-    #[strum(to_string = "hip-jit")]
-    HipJit,
 }
 
 #[derive(Debug, Clone, PartialEq, Eq, ValueEnum, Display, EnumIter)]

crates/burn-dataset/src/dataset/dataframe.rs

@@ -269,20 +269,20 @@ mod tests {
     }
 
     fn create_test_dataframe() -> DataFrame {
-        let s0 = Column::Series(Series::new("int32".into(), &[1i32, 2i32, 3i32]));
-        let s1 = Column::Series(Series::new("bool".into(), &[true, false, true]));
-        let s2 = Column::Series(Series::new("float64".into(), &[1.1f64, 2.2f64, 3.3f64]));
-        let s3 = Column::Series(Series::new("string".into(), &["Boo", "Boo2", "Boo3"]));
-        let s6 = Column::Series(Series::new("int16".into(), &[1i16, 2i16, 3i16]));
-        let s8 = Column::Series(Series::new("uint32".into(), &[1u32, 2u32, 3u32]));
-        let s9 = Column::Series(Series::new("uint64".into(), &[1u64, 2u64, 3u64]));
-        let s10 = Column::Series(Series::new("float32".into(), &[1.1f32, 2.2f32, 3.3f32]));
-        let s11 = Column::Series(Series::new("int64".into(), &[1i64, 2i64, 3i64]));
-        let s12 = Column::Series(Series::new("int8".into(), &[1i8, 2i8, 3i8]));
+        let s0 = Column::new("int32".into(), &[1i32, 2i32, 3i32]);
+        let s1 = Column::new("bool".into(), &[true, false, true]);
+        let s2 = Column::new("float64".into(), &[1.1f64, 2.2f64, 3.3f64]);
+        let s3 = Column::new("string".into(), &["Boo", "Boo2", "Boo3"]);
+        let s6 = Column::new("int16".into(), &[1i16, 2i16, 3i16]);
+        let s8 = Column::new("uint32".into(), &[1u32, 2u32, 3u32]);
+        let s9 = Column::new("uint64".into(), &[1u64, 2u64, 3u64]);
+        let s10 = Column::new("float32".into(), &[1.1f32, 2.2f32, 3.3f32]);
+        let s11 = Column::new("int64".into(), &[1i64, 2i64, 3i64]);
+        let s12 = Column::new("int8".into(), &[1i8, 2i8, 3i8]);
 
         let binary_data: Vec<&[u8]> = vec![&[1, 2, 3], &[4, 5, 6], &[7, 8, 9]];
 
-        let s13 = Column::Series(Series::new("binary".into(), binary_data));
+        let s13 = Column::new("binary".into(), binary_data);
         DataFrame::new(vec![s0, s1, s2, s3, s6, s8, s9, s10, s11, s12, s13]).unwrap()
     }
 

crates/burn-remote/src/server/session.rs

@@ -101,12 +101,12 @@ impl<B: ReprBackend> SessionManager<B> {
 
 impl<B: ReprBackend> Session<B> {
     fn new(runner: Runner<B>) -> Self {
-        let (sender, reveiver) = std::sync::mpsc::sync_channel(1);
+        let (sender, receiver) = std::sync::mpsc::sync_channel(1);
         Self {
             runner,
             streams: Default::default(),
             sender,
-            receiver: Some(reveiver),
+            receiver: Some(receiver),
         }
     }
 

crates/burn-tensor/src/tensor/backend/conversion.rs

@@ -188,7 +188,7 @@ mod tests {
     }
 
     #[test]
-    fn should_build_indices_2d_complexe() {
+    fn should_build_indices_2d_complex() {
         let shape = Shape::new([2, 3]);
 
         let indices = build_indices(&shape, Order::Left);
@@ -206,7 +206,7 @@ mod tests {
     }
 
     #[test]
-    fn should_build_indices_3d_complexe() {
+    fn should_build_indices_3d_complex() {
         let shape = Shape::new([2, 5, 3]);
 
         let indices = build_indices(&shape, Order::Left);

examples/wgan/examples/wgan-generate.rs

@@ -11,24 +11,18 @@ pub fn launch<B: Backend>(device: B::Device) {
     feature = "ndarray-blas-accelerate",
 ))]
 mod ndarray {
-    use burn::backend::{
-        ndarray::{NdArray, NdArrayDevice},
-        Autodiff,
-    };
+    use burn::backend::ndarray::{NdArray, NdArrayDevice};
 
     use crate::launch;
 
     pub fn run() {
-        launch::<Autodiff<NdArray>>(NdArrayDevice::Cpu);
+        launch::<NdArray>(NdArrayDevice::Cpu);
     }
 }
 
 #[cfg(feature = "tch-gpu")]
 mod tch_gpu {
-    use burn::backend::{
-        libtorch::{LibTorch, LibTorchDevice},
-        Autodiff,
-    };
+    use burn::backend::libtorch::{LibTorch, LibTorchDevice};
 
     use crate::launch;
 
@@ -38,41 +32,38 @@ mod tch_gpu {
         #[cfg(target_os = "macos")]
         let device = LibTorchDevice::Mps;
 
-        launch::<Autodiff<LibTorch>>(device);
+        launch::<LibTorch>(device);
     }
 }
 
 #[cfg(feature = "tch-cpu")]
 mod tch_cpu {
-    use burn::backend::{
-        libtorch::{LibTorch, LibTorchDevice},
-        Autodiff,
-    };
+    use burn::backend::libtorch::{LibTorch, LibTorchDevice};
 
     use crate::launch;
 
     pub fn run() {
-        launch::<Autodiff<LibTorch>>(LibTorchDevice::Cpu);
+        launch::<LibTorch>(LibTorchDevice::Cpu);
     }
 }
 
 #[cfg(feature = "wgpu")]
 mod wgpu {
     use crate::launch;
-    use burn::backend::{wgpu::Wgpu, Autodiff};
+    use burn::backend::wgpu::Wgpu;
 
     pub fn run() {
-        launch::<Autodiff<Wgpu>>(Default::default());
+        launch::<Wgpu>(Default::default());
     }
 }
 
 #[cfg(feature = "cuda")]
 mod cuda {
     use crate::launch;
-    use burn::backend::{Autodiff, Cuda};
+    use burn::backend::Cuda;
 
     pub fn run() {
-        launch::<Autodiff<Cuda>>(Default::default());
+        launch::<Cuda>(Default::default());
     }
 }
 

examples/wgan/src/model.rs

@@ -83,7 +83,7 @@ impl<B: Backend> Discriminator<B> {
     }
 }
 
-// Use model config to construct a generative and adverserial model
+// Use model config to construct a generative and adversarial model
 #[derive(Config, Debug)]
 pub struct ModelConfig {
     /// Dimensionality of the latent space