Adding Cuda device and skeleton cuda kernel impls

Cargo.toml

@@ -31,14 +31,17 @@ matrixmultiply = { version = "0.3.2", default-features = false }
 zip = { version = "0.6.2", default-features = false, optional = true }
 cblas-sys = { version = "0.1.4", default-features = false, optional = true }
 libc = { version = "0.2", default-features = false, optional = true }
+cudarc = { version = "0.5.0", default-features = false, optional = true }
 
 [features]
 default = ["std", "numpy"]
-std = ["no-std-compat/std", "rand/std", "rand_distr/std"]
+std = ["no-std-compat/std", "rand/std", "rand_distr/std", "cudarc?/std"]
 nightly = []
 numpy = ["dep:zip", "std"]
 cblas = ["dep:cblas-sys", "dep:libc"]
 intel-mkl = ["cblas"]
+cuda = ["dep:cudarc"]
+test-cuda = ["cuda"]
 
 [dev-dependencies]
 rand = "0.8.5"

src/lib.rs

@@ -165,8 +165,12 @@ pub fn keep_denormals() {
 pub(crate) mod tests {
     const TOLERANCE: f32 = 1e-6;
 
+    #[cfg(not(feature = "test-cuda"))]
     pub type TestDevice = crate::tensor::Cpu;
 
+    #[cfg(feature = "test-cuda")]
+    pub type TestDevice = crate::tensor::Cuda;
+
     pub trait AssertClose {
         fn get_far_pair(&self, rhs: &Self, tolerance: f32) -> Option<(f32, f32)>;
         fn assert_close(&self, rhs: &Self, tolerance: f32)

src/nn/add_into.rs

@@ -111,7 +111,7 @@ mod tests {
     #[test]
     fn test_add_into_3() {
         let dev: TestDevice = Default::default();
-        let m: AddInto<(Linear<2, 5>, Linear<3, 5>, Linear<4, 5>)> = dev.build_module();
+        let m: AddInto<(Linear<2, 5, _>, Linear<3, 5, _>, Linear<4, 5, _>)> = dev.build_module();
         let _: Tensor<Rank1<5>, _, _, OwnedTape<_>> = m.forward((
             dev.zeros::<Rank1<2>>().traced(),
             dev.zeros::<Rank1<3>>().traced(),
@@ -127,8 +127,12 @@ mod tests {
     #[test]
     fn test_add_into_4() {
         let dev: TestDevice = Default::default();
-        type Model = AddInto<(Linear<2, 5>, Linear<3, 5>, Linear<4, 5>, Linear<5, 5>)>;
-        let m: Model = dev.build_module();
+        let m: AddInto<(
+            Linear<2, 5, _>,
+            Linear<3, 5, _>,
+            Linear<4, 5, _>,
+            Linear<5, 5, _>,
+        )> = dev.build_module();
         let _: Tensor<Rank1<5>, _, _, OwnedTape<_>> = m.forward((
             dev.zeros::<Rank1<2>>().traced(),
             dev.zeros::<Rank1<3>>().traced(),
@@ -146,14 +150,13 @@ mod tests {
     #[test]
     fn test_add_into_5() {
         let dev: TestDevice = Default::default();
-        type Model = AddInto<(
-            Linear<2, 5>,
-            Linear<3, 5>,
-            Linear<4, 5>,
-            Linear<5, 5>,
-            Linear<6, 5>,
-        )>;
-        let m: Model = dev.build_module();
+        let m: AddInto<(
+            Linear<2, 5, _>,
+            Linear<3, 5, _>,
+            Linear<4, 5, _>,
+            Linear<5, 5, _>,
+            Linear<6, 5, _>,
+        )> = dev.build_module();
         let _: Tensor<Rank1<5>, _, _, OwnedTape<_>> = m.forward((
             dev.zeros::<Rank1<2>>().traced(),
             dev.zeros::<Rank1<3>>().traced(),
@@ -173,15 +176,14 @@ mod tests {
     #[test]
     fn test_add_into_6() {
         let dev: TestDevice = Default::default();
-        type Model = AddInto<(
-            Linear<2, 5>,
-            Linear<3, 5>,
-            Linear<4, 5>,
-            Linear<5, 5>,
-            Linear<6, 5>,
-            Linear<7, 5>,
-        )>;
-        let m: Model = dev.build_module();
+        let m: AddInto<(
+            Linear<2, 5, _>,
+            Linear<3, 5, _>,
+            Linear<4, 5, _>,
+            Linear<5, 5, _>,
+            Linear<6, 5, _>,
+            Linear<7, 5, _>,
+        )> = dev.build_module();
         let _: Tensor<Rank1<5>, _, _, OwnedTape<_>> = m.forward((
             dev.zeros::<Rank1<2>>().traced(),
             dev.zeros::<Rank1<3>>().traced(),

src/nn/batchnorm2d.rs

@@ -201,7 +201,7 @@ mod tests {
     fn test_batchnorm2d_3d_forward_mut() {
         let dev = TestDevice::seed_from_u64(0);
 
-        let x1: Tensor<Rank3<3, 2, 2>> = dev.sample(rand_distr::StandardNormal);
+        let x1: Tensor<Rank3<3, 2, 2>, f32, _> = dev.sample(rand_distr::StandardNormal);
         let mut bn: BatchNorm2D<3, _> = dev.build_module();
 
         let y1 = bn.forward_mut(x1.trace());

src/nn/impl_module_for_tuples.rs

@@ -155,7 +155,7 @@ mod tests {
 
     #[test]
     fn test_set_to_1() {
-        let dev: TestDevice = Default::default();
+        let dev: Cpu = Default::default();
         assert_eq!(
             SetTo1::<0, 5>::default().forward(dev.zeros()).array(),
             [1.0, 0.0, 0.0, 0.0, 0.0]
@@ -184,31 +184,31 @@ mod tests {
 
     #[test]
     fn test_2_tuple_forward() {
-        let dev: TestDevice = Default::default();
+        let dev: Cpu = Default::default();
         let model: (SetTo1<0, 2>, SetTo1<1, 2>) = Default::default();
         let y = model.forward(dev.zeros());
         assert_eq!(y.array(), [1.0, 1.0]);
     }
 
     #[test]
     fn test_3_tuple_forward() {
-        let dev: TestDevice = Default::default();
+        let dev: Cpu = Default::default();
         let model: (SetTo1<0, 3>, SetTo1<1, 3>, SetTo1<2, 3>) = Default::default();
         let y = model.forward(dev.zeros());
         assert_eq!(y.array(), [1.0, 1.0, 1.0]);
     }
 
     #[test]
     fn test_4_tuple_forward() {
-        let dev: TestDevice = Default::default();
+        let dev: Cpu = Default::default();
         let model: (SetTo1<0, 4>, SetTo1<1, 4>, SetTo1<2, 4>, SetTo1<3, 4>) = Default::default();
         let y = model.forward(dev.zeros());
         assert_eq!(y.array(), [1.0, 1.0, 1.0, 1.0]);
     }
 
     #[test]
     fn test_5_tuple_forward() {
-        let dev: TestDevice = Default::default();
+        let dev: Cpu = Default::default();
         let model: (
             SetTo1<0, 5>,
             SetTo1<1, 5>,
@@ -222,7 +222,7 @@ mod tests {
 
     #[test]
     fn test_6_tuple_forward() {
-        let dev: TestDevice = Default::default();
+        let dev: Cpu = Default::default();
         let model: (
             SetTo1<0, 6>,
             SetTo1<1, 6>,

src/nn/npz_impls.rs

@@ -378,8 +378,8 @@ mod tests {
         let x = dev.sample_normal::<Rank3<3, 4, 5>>();
         let file = NamedTempFile::new().expect("failed to create tempfile");
 
-        let mut saved: BatchNorm2D<3> = dev.build_module();
-        let mut loaded: BatchNorm2D<3> = dev.build_module();
+        let mut saved: BatchNorm2D<3, _> = dev.build_module();
+        let mut loaded: BatchNorm2D<3, _> = dev.build_module();
 
         saved.running_mean.fill_with_distr(Standard);
         saved.running_var.fill_with_distr(Standard);

src/nn/split_into.rs

@@ -121,8 +121,7 @@ mod tests {
     #[test]
     fn test_split_into_2() {
         let dev: TestDevice = Default::default();
-        type Model = SplitInto<(Linear<5, 1>, Linear<5, 2>)>;
-        let m: Model = dev.build_module();
+        let m: SplitInto<(Linear<5, 1, _>, Linear<5, 2, _>)> = dev.build_module();
         let _: (Tensor<Rank1<1>, _, _>, Tensor<Rank1<2>, _, _, OwnedTape<_>>) =
             m.forward(dev.zeros::<Rank1<5>>().traced());
         let _: (
@@ -134,8 +133,7 @@ mod tests {
     #[test]
     fn test_split_into_3() {
         let dev: TestDevice = Default::default();
-        type Model = SplitInto<(Linear<5, 1>, Linear<5, 2>, Linear<5, 3>)>;
-        let m: Model = dev.build_module();
+        let m: SplitInto<(Linear<5, 1, _>, Linear<5, 2, _>, Linear<5, 3, _>)> = dev.build_module();
         let _: (
             Tensor<Rank1<1>, _, _>,
             Tensor<Rank1<2>, _, _>,
@@ -150,9 +148,13 @@ mod tests {
 
     #[test]
     fn test_split_into_4() {
-        type Model = SplitInto<(Linear<5, 1>, Linear<5, 2>, Linear<5, 3>, Linear<5, 4>)>;
         let dev: TestDevice = Default::default();
-        let m: Model = dev.build_module();
+        let m: SplitInto<(
+            Linear<5, 1, _>,
+            Linear<5, 2, _>,
+            Linear<5, 3, _>,
+            Linear<5, 4, _>,
+        )> = dev.build_module();
         let _: (
             Tensor<Rank1<1>, _, _>,
             Tensor<Rank1<2>, _, _>,
@@ -169,15 +171,14 @@ mod tests {
 
     #[test]
     fn test_split_into_5() {
-        type Model = SplitInto<(
-            Linear<5, 1>,
-            Linear<5, 2>,
-            Linear<5, 3>,
-            Linear<5, 4>,
-            Linear<5, 5>,
-        )>;
         let dev: TestDevice = Default::default();
-        let m: Model = dev.build_module();
+        let m: SplitInto<(
+            Linear<5, 1, _>,
+            Linear<5, 2, _>,
+            Linear<5, 3, _>,
+            Linear<5, 4, _>,
+            Linear<5, 5, _>,
+        )> = dev.build_module();
         let _: (
             Tensor<Rank1<1>, _, _>,
             Tensor<Rank1<2>, _, _>,
@@ -196,16 +197,15 @@ mod tests {
 
     #[test]
     fn test_split_into_6() {
-        type Model = SplitInto<(
-            Linear<5, 1>,
-            Linear<5, 2>,
-            Linear<5, 3>,
-            Linear<5, 4>,
-            Linear<5, 5>,
-            Linear<5, 6>,
-        )>;
         let dev: TestDevice = Default::default();
-        let m: Model = dev.build_module();
+        let m: SplitInto<(
+            Linear<5, 1, _>,
+            Linear<5, 2, _>,
+            Linear<5, 3, _>,
+            Linear<5, 4, _>,
+            Linear<5, 5, _>,
+            Linear<5, 6, _>,
+        )> = dev.build_module();
         let _: (
             Tensor<Rank1<1>, _, _>,
             Tensor<Rank1<2>, _, _>,

src/optim/adam/cuda_kernel.rs

@@ -0,0 +1,14 @@
+use crate::{shapes::Shape, tensor::Cuda};
+
+impl super::AdamKernel<f32> for Cuda {
+    fn update<S: Shape>(
+        t: i32,
+        cfg: &super::AdamConfig<f32>,
+        param: &mut Self::Storage<S, f32>,
+        moment1: &mut Self::Storage<S, f32>,
+        moment2: &mut Self::Storage<S, f32>,
+        grad: Self::Storage<S, f32>,
+    ) {
+        todo!()
+    }
+}

src/optim/adam/mod.rs

@@ -1,5 +1,8 @@
 mod cpu_kernel;
 
+#[cfg(feature = "cuda")]
+mod cuda_kernel;
+
 use std::marker::PhantomData;
 
 use crate::{

src/optim/rmsprop/cuda_kernel.rs

@@ -0,0 +1,14 @@
+use crate::tensor::Cuda;
+
+impl super::RMSpropKernel<f32> for Cuda {
+    fn update<S: crate::shapes::Shape>(
+        cfg: &super::RMSpropConfig<f32>,
+        param: &mut Self::Storage<S, f32>,
+        momentum: &mut Self::Storage<S, f32>,
+        square_avg: &mut Self::Storage<S, f32>,
+        grad_avg: &mut Self::Storage<S, f32>,
+        grad: Self::Storage<S, f32>,
+    ) {
+        todo!()
+    }
+}

src/optim/rmsprop/mod.rs

@@ -1,5 +1,8 @@
 mod cpu_kernel;
 
+#[cfg(feature = "cuda")]
+mod cuda_kernel;
+
 use std::marker::PhantomData;
 
 use crate::{

src/optim/sgd/cuda_kernel.rs

@@ -0,0 +1,12 @@
+use crate::{shapes::*, tensor::Cuda};
+
+impl<E: Dtype> super::SgdKernel<E> for Cuda {
+    fn update<S: Shape>(
+        cfg: &super::SgdConfig<E>,
+        param: &mut Self::Storage<S, E>,
+        velocity: &mut Self::Storage<S, E>,
+        grad: Self::Storage<S, E>,
+    ) {
+        todo!()
+    }
+}

src/optim/sgd/mod.rs

@@ -1,5 +1,8 @@
 mod cpu_kernel;
 
+#[cfg(feature = "cuda")]
+mod cuda_kernel;
+
 use std::marker::PhantomData;
 
 use crate::gradients::Gradients;

src/shapes/shape.rs

@@ -2,7 +2,7 @@ use super::{axes::*, ReduceShapeTo};
 
 /// Represents a unit type, but no arithmetic.
 pub trait Unit:
-    'static + Copy + Clone + Default + std::fmt::Debug + PartialOrd + Send + Sync
+    'static + Copy + Clone + Default + std::fmt::Debug + PartialOrd + Send + Sync + std::marker::Unpin
 {
 }
 impl Unit for f32 {}