Backends and Tensor redesign

.vscode/settings.json

@@ -1,3 +1,3 @@
 {
-  "rust-analyzer.linkedProjects": ["./Cargo.toml"]
+  "rust-analyzer.linkedProjects": ["./Cargo.toml", "./Cargo.toml"]
 }

Cargo.toml

@@ -1,12 +1,6 @@
-[package]
-name = "phantom"
-version = "0.1.0"
-edition = "2021"
+[workspace]
+resolver = "2"
 
-description = "A forward mode autodiff and deep learning library for Rust"
-license = "MIT"
-readme = "README.md"
-
-[dependencies]
-anyhow = "1.0.75"
-thiserror = "1"
+members = [
+    "phantom-core",
+]

phantom-core/Cargo.toml

@@ -0,0 +1,19 @@
+[package]
+name = "phantom-core"
+version = "0.1.0"
+edition = "2021"
+
+description = "A forward mode autodiff and deep learning library for Rust"
+license = "MIT"
+readme = "README.md"
+
+[dependencies]
+anyhow = { version = "1.0.75", features = ["backtrace"]}
+num-traits = "0.2.16"
+thiserror = "1"
+
+# TODO: Switch back to the official gemm implementation once something similar to
+# https://github.com/sarah-ek/gemm/pull/8 is available.
+gemm = { git = "https://github.com/LaurentMazare/gemm.git", branch = "f16-vectorize-pack" }
+rand = "0.8.5"
+num_cpus = "1.16.0"

phantom-core/src/backend/backend.rs

@@ -0,0 +1,95 @@
+use crate::operation::{BinaryOperation, UnaryOperation};
+use crate::{CPUStorage, DType, Layout, Result, Shape};
+
+pub(crate) trait BackendStorage: Sized {
+    type Device: BackendDevice;
+
+    fn to_cpu(&self) -> Result<CPUStorage>;
+
+    fn dtype(&self) -> DType;
+
+    fn to_dtype(&self, layout: &Layout, dtype: DType) -> Result<Self>;
+
+    fn device(&self) -> &Self::Device;
+
+    fn try_clone(&self, layout: &Layout) -> Result<Self>;
+
+    fn copy_strided_source(
+        &self,
+        destination: &mut Self,
+        destination_offset: usize,
+        source_layout: &Layout,
+    ) -> Result<()>;
+
+    fn unary_operation<T: UnaryOperation>(&self, layout: &Layout) -> Result<Self>;
+
+    fn binary_operation<T: BinaryOperation>(
+        &self,
+        rhs: &Self,
+        lhs_layout: &Layout,
+        rhs_layout: &Layout,
+    ) -> Result<Self>;
+
+    fn affine(&self, layout: &Layout, add: f64, mul: f64) -> Result<Self>;
+
+    fn matmul(
+        &self,
+        rhs: &Self,
+        bmnk: (usize, usize, usize, usize),
+        lhs_layout: &Layout,
+        rhs_layout: &Layout,
+    ) -> Result<Self>;
+
+    fn where_condition(
+        &self,
+        _: &Layout,
+        _: &Self,
+        _: &Layout,
+        _: &Self,
+        _: &Layout,
+    ) -> Result<Self>;
+
+    // fn conv1d(
+    //     &self,
+    //     _l: &Layout,
+    //     _kernel: &Self,
+    //     _kernel_l: &Layout,
+    //     _params: &crate::conv::ParamsConv1D,
+    // ) -> Result<Self>;
+
+    fn embedding(&self, _: &Layout, _: &Self, _: &Layout) -> Result<Self>;
+
+    fn sum(&self, _: &Layout, _: &[usize]) -> Result<Self>;
+}
+
+pub(crate) trait BackendDevice: Sized + std::fmt::Debug + Clone {
+    type Storage: BackendStorage;
+
+    fn new(_: usize) -> Result<Self>;
+
+    fn location(&self) -> crate::device::DeviceLocation;
+
+    fn same_device(&self, _: &Self) -> bool;
+
+    fn zeros_impl(&self, shape: &Shape, dtype: DType) -> Result<Self::Storage>;
+
+    fn ones_impl(&self, shape: &Shape, dtype: DType) -> Result<Self::Storage>;
+
+    fn rand_uniform(
+        &self,
+        shape: &Shape,
+        dtype: DType,
+        lower_bound: f64,
+        upper_bound: f64,
+    ) -> Result<Self::Storage>;
+
+    fn rand_normal(
+        &self,
+        shape: &Shape,
+        dtype: DType,
+        mean: f64,
+        std: f64,
+    ) -> Result<Self::Storage>;
+
+    fn from_cpu(&self, storage: &CPUStorage) -> Result<Self::Storage>;
+}