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Add grads for interpolate1d (#1742)

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* add backprop for interpolate1d

* fix clippy lint

* correct fix clippy lint
This commit is contained in:
Kirpal Grewal
2024-02-22 07:44:01 +00:00
committed by GitHub
parent 45d5322d62
commit 8013b50829
4 changed files with 51 additions and 6 deletions
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17
candle-core/src/backprop.rs
View File

@ -113,7 +113,7 @@ impl Tensor {
| Op::Unary(_node, UnaryOp::Floor)
| Op::Unary(_node, UnaryOp::Round) => nodes,
Op::Reshape(node)
| Op::UpsampleNearest1D(node)
| Op::UpsampleNearest1D { arg: node, .. }
| Op::UpsampleNearest2D { arg: node, .. }
| Op::AvgPool2D { arg: node, .. }
| Op::MaxPool2D { arg: node, .. }
@ -348,9 +348,18 @@ impl Tensor {
let sum_grad = grads.or_insert(arg)?;
*sum_grad = sum_grad.add(&grad_arg)?;
}
Op::UpsampleNearest1D { .. } => Err(Error::BackwardNotSupported {
op: "upsample-nearest1d",
})?,
Op::UpsampleNearest1D { arg, target_size } => {
let (_n, c, size) = arg.dims3()?;
if target_size % size != 0 {
crate::bail!("backward not supported for non integer upscaling factors")
}
let scale = target_size / size;
let kernel = Tensor::ones((c, 1, scale), arg.dtype(), arg.device())?;
let conv_sum = grad.conv1d(&kernel, 0, scale, 1, c)?;
let sum_grad = grads.or_insert(arg)?;
*sum_grad = conv_sum;
}
Op::UpsampleNearest2D {
arg,
target_h,

5
candle-core/src/op.rs
View File

@ -132,7 +132,10 @@ pub enum Op {
stride: (usize, usize),
},
UpsampleNearest1D(Tensor),
UpsampleNearest1D {
arg: Tensor,
target_size: usize,
},
UpsampleNearest2D {
arg: Tensor,
target_h: usize,

2
candle-core/src/tensor.rs
View File

@ -1015,7 +1015,7 @@ impl Tensor {
/// tensor also has three dimensions, `(batch, channels, target_size)`.
pub fn interpolate1d(&self, target_size: usize) -> Result<Self> {
let (n, c, _l) = self.dims3()?;
let op = BackpropOp::new1(self, Op::UpsampleNearest1D);
let op = BackpropOp::new1(self, |arg| Op::UpsampleNearest1D { arg, target_size });
let storage = self
.storage()
.upsample_nearest1d(self.layout(), target_size)?;