Optimize the cat operation on contiguous tensors (#1855)

* Add a specialized kernel for copy2d.

* Move the cat operations.

* Avoid transpositions in cat.

* Bugfix.

* Bugfix for the cuda kernel.

* Add a benchmark.

* Add more testing.

* Test fix.

* Faster kernel.

* Add the missing kernel.

* Tweak the test.

* Add a metal kernel.

* Fix for the metal kernel.

* Get the tests to pass on metal.

* Also use this opportunity to fix the metal kernel for ELU.

* Add some bf16 kernels.

* Clippy fixes.

candle-nn/examples/cpu_benchmarks.rs

@@ -238,6 +238,23 @@ impl Benchmark for QMatMul {
     const ITERS: usize = 100;
 }
 
+struct Cat;
+impl Benchmark for Cat {
+    type PreProcessData = (Tensor, Tensor);
+    type RunResult = Tensor;
+    fn preprocess() -> Result<Self::PreProcessData> {
+        let lhs = Tensor::randn(0f32, 1., (1, 32, 2000, 128), &Device::Cpu)?;
+        let rhs = Tensor::randn(0f32, 1., (1, 32, 1, 128), &Device::Cpu)?;
+        Ok((lhs, rhs))
+    }
+
+    fn run_one(d: &Self::PreProcessData) -> Result<Self::RunResult> {
+        Tensor::cat(&[&d.0, &d.1], 2)
+    }
+
+    const ITERS: usize = 1000;
+}
+
 struct Softmax;
 impl Benchmark for Softmax {
     type PreProcessData = Tensor;
@@ -295,6 +312,7 @@ enum Task {
     Qmatmul,
     Softmax,
     SoftmaxLastDim,
+    Cat,
 }
 
 #[derive(Parser, Debug)]
@@ -319,6 +337,7 @@ fn main() -> Result<()> {
         Task::Softmax => run::<Softmax>(args.iters)?,
         Task::SoftmaxLastDim => run::<SoftmaxLastDim>(args.iters)?,
         Task::Qmatmul => run::<QMatMul>(args.iters)?,
+        Task::Cat => run::<Cat>(args.iters)?,
     }
     Ok(())
 }