Files
xserv/crates/xserv-kernels/src/layernorm.rs

73 lines
2.1 KiB
Rust

use std::ffi::c_void;
use xserv_tensor::{DType, Device, Tensor};
unsafe extern "C" {
fn launch_layernorm_f32(
x: *const c_void,
gamma: *const c_void,
beta: *const c_void,
out: *mut c_void,
rows: i32,
hidden_size: i32,
eps: f32,
stream: *mut c_void,
);
fn launch_layernorm_bf16(
x: *const c_void,
gamma: *const c_void,
beta: *const c_void,
out: *mut c_void,
rows: i32,
hidden_size: i32,
eps: f32,
stream: *mut c_void,
);
}
pub fn layernorm(x: &Tensor, gamma: &Tensor, beta: &Tensor, eps: f32) -> Tensor {
assert!(x.ndim() >= 1);
assert!(x.is_contiguous() && gamma.is_contiguous() && beta.is_contiguous());
assert!(matches!(x.device(), Device::Cuda(_)));
let hidden_size = *x.shape().last().unwrap();
assert_eq!(gamma.shape(), &[hidden_size]);
assert_eq!(beta.shape(), &[hidden_size]);
let rows = x.numel() / hidden_size;
assert!(
rows <= i32::MAX as usize,
"too many rows for i32 kernel param"
);
assert!(
hidden_size <= i32::MAX as usize,
"hidden_size too large for i32 kernel param"
);
let out = Tensor::empty(x.shape(), x.dtype(), x.device());
unsafe {
match x.dtype() {
DType::F32 => launch_layernorm_f32(
x.data_ptr() as _,
gamma.data_ptr() as _,
beta.data_ptr() as _,
out.data_ptr() as *mut c_void,
rows as i32,
hidden_size as i32,
eps,
xserv_cuda::current_stream_raw(),
),
DType::BF16 => launch_layernorm_bf16(
x.data_ptr() as _,
gamma.data_ptr() as _,
beta.data_ptr() as _,
out.data_ptr() as *mut c_void,
rows as i32,
hidden_size as i32,
eps,
xserv_cuda::current_stream_raw(),
),
_ => panic!("unsupported dtype for layernorm"),
}
}
out
}