CPU implementation for upsample-nearest2d. (#339)

This commit is contained in:
Laurent Mazare
2023-08-07 21:07:10 +02:00
committed by GitHub
parent fc265d9dcf
commit d0d7010682
5 changed files with 61 additions and 7 deletions

View File

@ -38,6 +38,7 @@ pub trait BackendStorage: Sized {
) -> Result<Self>;
fn avg_pool2d(&self, _: &Layout, _: (usize, usize), _: (usize, usize)) -> Result<Self>;
fn upsample_nearest2d(&self, _: &Layout, _: usize, _: usize) -> Result<Self>;
fn gather(&self, _: &Layout, _: &Self, _: &Layout, _: usize) -> Result<Self>;
fn scatter_add(

View File

@ -672,6 +672,43 @@ impl Map1 for AvgPool2D {
}
}
struct UpsampleNearest2D(usize, usize);
impl Map1 for UpsampleNearest2D {
fn f<T: WithDType>(&self, src: &[T], layout: &Layout) -> Result<Vec<T>> {
// TODO: Specialized implementation for the case 2*h, 2*w?
let (dst_h, dst_w) = (self.0, self.1);
let (b_sz, c, src_h, src_w) = layout.shape().dims4()?;
let stride = layout.stride();
let (stride_h, stride_w) = (stride[2], stride[3]);
let src_index = layout.start_offset();
let scale_h = src_h as f64 / dst_h as f64;
let scale_w = src_w as f64 / dst_w as f64;
let mut dst = vec![T::zero(); b_sz * c * dst_h * dst_w];
let src_h_idxs = (0..src_h)
.map(|h_idx| usize::min(src_h - 1, (h_idx as f64 * scale_h) as usize))
.collect::<Vec<_>>();
let src_w_idxs = (0..src_w)
.map(|w_idx| usize::min(src_w - 1, (w_idx as f64 * scale_w) as usize))
.collect::<Vec<_>>();
for b_idx in 0..b_sz {
let dst = &mut dst[b_idx * c * dst_h * dst_w..];
let src_index = src_index + b_idx * stride[0];
for c_idx in 0..c {
let dst = &mut dst[c_idx * dst_h * dst_w..];
let src_index = src_index + c_idx * stride[1];
for (h_idx, src_h_idx) in src_h_idxs.iter().enumerate() {
for (w_idx, src_w_idx) in src_w_idxs.iter().enumerate() {
let src_index = src_index + src_h_idx * stride_h + src_w_idx * stride_w;
dst[h_idx * dst_w + w_idx] = src[src_index]
}
}
}
}
Ok(dst)
}
}
struct Gather<'a, I: IntDType> {
ids: &'a [I],
ids_l: &'a Layout,
@ -1577,6 +1614,10 @@ impl BackendStorage for CpuStorage {
AvgPool2D(kernel_size, stride).map(self, layout)
}
fn upsample_nearest2d(&self, layout: &Layout, h: usize, w: usize) -> Result<Self> {
UpsampleNearest2D(h, w).map(self, layout)
}
fn elu(&self, layout: &Layout, alpha: f64) -> Result<Self> {
// TODO: Have some generic map for functions that apply on num_traits::Float elements.
match self {

View File

@ -1385,6 +1385,10 @@ impl BackendStorage for CudaStorage {
todo!()
}
fn upsample_nearest2d(&self, _: &Layout, _: usize, _: usize) -> Result<Self> {
todo!()
}
fn index_select(&self, ids: &Self, l: &Layout, ids_l: &Layout, dim: usize) -> Result<Self> {
let device = self.device().clone();
let slice = IndexSelect(ids, ids_l, dim).map(&self.slice, &device, l)?;

View File

@ -123,6 +123,10 @@ impl crate::backend::BackendStorage for CudaStorage {
fn avg_pool2d(&self, _: &Layout, _: (usize, usize), _: (usize, usize)) -> Result<Self> {
Err(Error::NotCompiledWithCudaSupport)
}
fn upsample_nearest2d(&self, _: &Layout, _: usize, _: usize) -> Result<Self> {
Err(Error::NotCompiledWithCudaSupport)
}
}
impl crate::backend::BackendDevice for CudaDevice {

View File

@ -284,13 +284,17 @@ impl Storage {
}
}
pub(crate) fn upsample_nearest2d(
&self,
_layout: &Layout,
_h: usize,
_w: usize,
) -> Result<Self> {
todo!()
pub(crate) fn upsample_nearest2d(&self, layout: &Layout, h: usize, w: usize) -> Result<Self> {
match self {
Storage::Cpu(storage) => {
let storage = storage.upsample_nearest2d(layout, h, w)?;
Ok(Self::Cpu(storage))
}
Self::Cuda(storage) => {
let storage = storage.upsample_nearest2d(layout, h, w)?;
Ok(Self::Cuda(storage))
}
}
}
pub(crate) fn where_cond(