use core::ffi::c_void;
use core::marker::PhantomData;
use baracuda_cutlass::{Error, Result};
use baracuda_driver::Stream;
use baracuda_kernels_types::{
ArchSku, BackendKind, Element, ElementKind, KernelSku, MathPrecision, OpCategory,
PlanPreference, PrecisionGuarantee, TensorMut, TensorRef, Workspace,
};
#[derive(Copy, Clone, Debug)]
pub struct WhereBackwardDescriptor<const N: usize> {
pub shape: [i32; N],
pub element: ElementKind,
}
pub struct WhereBackwardArgs<'a, T: Element, const N: usize> {
pub cond: TensorRef<'a, u8, N>,
pub dy: TensorRef<'a, T, N>,
pub da: TensorMut<'a, T, N>,
pub db: TensorMut<'a, T, N>,
}
pub struct WhereBackwardPlan<T: Element, const N: usize> {
desc: WhereBackwardDescriptor<N>,
sku: KernelSku,
_marker: PhantomData<T>,
}
impl<T: Element, const N: usize> WhereBackwardPlan<T, N> {
pub fn select(
_stream: &Stream,
desc: &WhereBackwardDescriptor<N>,
_pref: PlanPreference,
) -> Result<Self> {
if desc.element != T::KIND {
return Err(Error::Unsupported(
"baracuda-kernels::WhereBackwardPlan: descriptor element != type parameter T",
));
}
for &d in desc.shape.iter() {
if d < 0 {
return Err(Error::InvalidProblem(
"baracuda-kernels::WhereBackwardPlan: shape dims must be non-negative",
));
}
}
let supported = matches!(
T::KIND,
ElementKind::F32 | ElementKind::F16 | ElementKind::Bf16 | ElementKind::F64
);
if !supported {
return Err(Error::Unsupported(
"baracuda-kernels::WhereBackwardPlan: value dtype must be one of \
{F32, F16, Bf16, F64}",
));
}
let (math_precision, accumulator) = match T::KIND {
ElementKind::F16 => (MathPrecision::F16, ElementKind::F16),
ElementKind::Bf16 => (MathPrecision::Bf16, ElementKind::Bf16),
ElementKind::F64 => (MathPrecision::F64, ElementKind::F64),
_ => (MathPrecision::F32, ElementKind::F32),
};
let precision_guarantee = PrecisionGuarantee {
math_precision,
accumulator,
bit_stable_on_same_hardware: true,
deterministic: true,
};
let sku = KernelSku {
category: OpCategory::TernaryElementwise,
op: 4,
element: T::KIND,
aux_element: None,
layout: None,
epilogue: None,
arch: ArchSku::Sm80,
backend: BackendKind::Bespoke,
precision_guarantee,
};
Ok(Self {
desc: *desc,
sku,
_marker: PhantomData,
})
}
pub fn can_implement(&self, args: &WhereBackwardArgs<'_, T, N>) -> Result<()> {
if args.dy.shape != self.desc.shape {
return Err(Error::InvalidProblem(
"baracuda-kernels::WhereBackwardPlan: dy shape mismatch with descriptor",
));
}
if args.da.shape != self.desc.shape {
return Err(Error::InvalidProblem(
"baracuda-kernels::WhereBackwardPlan: da shape mismatch with descriptor",
));
}
if args.db.shape != self.desc.shape {
return Err(Error::InvalidProblem(
"baracuda-kernels::WhereBackwardPlan: db shape mismatch with descriptor",
));
}
if args.cond.shape != self.desc.shape {
return Err(Error::InvalidProblem(
"baracuda-kernels::WhereBackwardPlan: cond shape mismatch with descriptor \
(trailblazer requires full-shape cond; stride-0 broadcasting on cond \
lands later)",
));
}
if !args.cond.is_contiguous()
|| !args.dy.is_contiguous()
|| !args.da.is_contiguous()
|| !args.db.is_contiguous()
{
return Err(Error::Unsupported(
"baracuda-kernels::WhereBackwardPlan: trailblazer requires contiguous \
cond / dy / da / db; strided / broadcast fanout lands later",
));
}
if N > 8 {
return Err(Error::Unsupported(
"baracuda-kernels::WhereBackwardPlan: tensor rank > 8 not supported",
));
}
let numel = args.dy.numel();
let cond_len = args.cond.data.len() as i64;
let dy_len = args.dy.data.len() as i64;
let da_len = args.da.data.len() as i64;
let db_len = args.db.data.len() as i64;
if dy_len < numel || da_len < numel || db_len < numel || cond_len < numel {
return Err(Error::BufferTooSmall {
needed: numel as usize,
got: cond_len.min(dy_len).min(da_len).min(db_len) as usize,
});
}
Ok(())
}
#[inline]
pub fn workspace_size(&self) -> usize {
0
}
#[inline]
pub fn sku(&self) -> KernelSku {
self.sku
}
#[inline]
pub fn precision_guarantee(&self) -> PrecisionGuarantee {
self.sku.precision_guarantee
}
pub fn run(
&self,
stream: &Stream,
_workspace: Workspace<'_>,
args: WhereBackwardArgs<'_, T, N>,
) -> Result<()> {
self.can_implement(&args)?;
let numel = args.dy.numel();
if numel == 0 {
return Ok(());
}
let cond_ptr = args.cond.data.as_raw().0 as *const c_void;
let dy_ptr = args.dy.data.as_raw().0 as *const c_void;
let da_ptr = args.da.data.as_raw().0 as *mut c_void;
let db_ptr = args.db.data.as_raw().0 as *mut c_void;
let stream_ptr = stream.as_raw() as *mut c_void;
let status = match T::KIND {
ElementKind::F32 => unsafe {
baracuda_kernels_sys::baracuda_kernels_where_backward_f32_run(
numel,
cond_ptr,
dy_ptr,
da_ptr,
db_ptr,
core::ptr::null_mut(),
0,
stream_ptr,
)
},
ElementKind::F16 => unsafe {
baracuda_kernels_sys::baracuda_kernels_where_backward_f16_run(
numel,
cond_ptr,
dy_ptr,
da_ptr,
db_ptr,
core::ptr::null_mut(),
0,
stream_ptr,
)
},
ElementKind::Bf16 => unsafe {
baracuda_kernels_sys::baracuda_kernels_where_backward_bf16_run(
numel,
cond_ptr,
dy_ptr,
da_ptr,
db_ptr,
core::ptr::null_mut(),
0,
stream_ptr,
)
},
ElementKind::F64 => unsafe {
baracuda_kernels_sys::baracuda_kernels_where_backward_f64_run(
numel,
cond_ptr,
dy_ptr,
da_ptr,
db_ptr,
core::ptr::null_mut(),
0,
stream_ptr,
)
},
_ => {
return Err(Error::Unsupported(
"baracuda-kernels::WhereBackwardPlan::run reached an unimplemented \
dtype — select() should have caught this",
));
}
};
map_status(status)
}
}
fn map_status(code: i32) -> Result<()> {
match code {
0 => Ok(()),
1 => Err(Error::MisalignedOperand),
2 => Err(Error::InvalidProblem(
"baracuda-kernels-sys reported invalid problem",
)),
3 => Err(Error::Unsupported(
"baracuda-kernels-sys reported unsupported configuration",
)),
4 => Err(Error::WorkspaceTooSmall { needed: 0, got: 0 }),
n => Err(Error::CutlassInternal(n)),
}
}