use std::ffi::c_void;
use xserv_tensor::{DType, Device, Tensor};

unsafe extern "C" {
    fn launch_softmax_f32(x: *const c_void, out: *mut c_void, rows: i32, cols: i32, stream: *mut c_void);
    fn launch_softmax_bf16(x: *const c_void, out: *mut c_void, rows: i32, cols: i32, stream: *mut c_void);
}

/// Softmax along the last dimension.
pub fn softmax(x: &Tensor) -> Tensor {
    assert!(x.ndim() >= 1);
    assert!(x.is_contiguous());
    assert!(matches!(x.device(), Device::Cuda(_)));

    let cols = *x.shape().last().unwrap();
    let rows = x.numel() / cols;
    assert!(rows <= i32::MAX as usize, "too many rows for i32 kernel param");
    assert!(cols <= i32::MAX as usize, "cols too large for i32 kernel param");
    let out = Tensor::empty(x.shape(), x.dtype(), x.device());

    unsafe {
        match x.dtype() {
            DType::F32 => launch_softmax_f32(
                x.data_ptr() as _, out.data_ptr() as *mut c_void,
                rows as i32, cols as i32, std::ptr::null_mut(),
            ),
            DType::BF16 => launch_softmax_bf16(
                x.data_ptr() as _, out.data_ptr() as *mut c_void,
                rows as i32, cols as i32, std::ptr::null_mut(),
            ),
            _ => panic!("unsupported dtype for softmax"),
        }
    }
    out
}