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, ImageKind, KernelSku, MathPrecision, OpCategory,
PlanPreference, PrecisionGuarantee, TensorMut, TensorRef, Workspace,
};
use super::map_status;
#[derive(Copy, Clone, Debug)]
pub struct NmsDescriptor {
pub num_boxes: i32,
pub iou_threshold: f32,
pub element: ElementKind,
}
pub struct NmsArgs<'a, T: Element> {
pub boxes: TensorRef<'a, T, 2>,
pub keep_mask: TensorMut<'a, u8, 1>,
pub count: TensorMut<'a, i32, 1>,
}
pub struct NmsPlan<T: Element> {
desc: NmsDescriptor,
sku: KernelSku,
_marker: PhantomData<T>,
}
impl<T: Element> NmsPlan<T> {
pub fn select(
_stream: &Stream,
desc: &NmsDescriptor,
_pref: PlanPreference,
) -> Result<Self> {
if desc.element != T::KIND {
return Err(Error::Unsupported(
"baracuda-kernels::NmsPlan: descriptor element != T",
));
}
if desc.num_boxes < 0 {
return Err(Error::InvalidProblem(
"baracuda-kernels::NmsPlan: num_boxes must be non-negative",
));
}
if !matches!(T::KIND, ElementKind::F32 | ElementKind::F64) {
return Err(Error::Unsupported(
"baracuda-kernels::NmsPlan: only `f32`, `f64` wired",
));
}
let precision_guarantee = PrecisionGuarantee {
math_precision: if T::KIND == ElementKind::F64 {
MathPrecision::F64
} else {
MathPrecision::F32
},
accumulator: T::KIND,
bit_stable_on_same_hardware: true,
deterministic: true,
};
let sku = KernelSku {
category: OpCategory::Image,
op: ImageKind::Nms as u16,
element: T::KIND,
aux_element: Some(ElementKind::U8),
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: &NmsArgs<'_, T>) -> Result<()> {
if args.boxes.shape != [self.desc.num_boxes, 4] {
return Err(Error::InvalidProblem(
"baracuda-kernels::NmsPlan: boxes must be [num_boxes, 4]",
));
}
if args.keep_mask.shape != [self.desc.num_boxes] {
return Err(Error::InvalidProblem(
"baracuda-kernels::NmsPlan: keep_mask must be [num_boxes]",
));
}
if args.count.shape != [1] {
return Err(Error::InvalidProblem(
"baracuda-kernels::NmsPlan: count must be [1]",
));
}
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: NmsArgs<'_, T>,
) -> Result<()> {
self.can_implement(&args)?;
let boxes_ptr = args.boxes.data.as_raw().0 as *const c_void;
let mask_ptr = args.keep_mask.data.as_raw().0 as *mut c_void;
let count_ptr = args.count.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_nms_f32_run(
self.desc.num_boxes,
self.desc.iou_threshold,
boxes_ptr, mask_ptr, count_ptr,
core::ptr::null_mut(), 0, stream_ptr,
)
},
ElementKind::F64 => unsafe {
baracuda_kernels_sys::baracuda_kernels_nms_f64_run(
self.desc.num_boxes,
self.desc.iou_threshold,
boxes_ptr, mask_ptr, count_ptr,
core::ptr::null_mut(), 0, stream_ptr,
)
},
_ => {
return Err(Error::Unsupported(
"baracuda-kernels::NmsPlan::run reached unimplemented dtype",
));
}
};
map_status(status)
}
}