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Backprop for conv2d. (#638)

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* Start adding backprop for conv2d.

* Backprop for conv2d.

* Bugfix + start adding a conv2d test.

* Conv2d backprop testing.

* More conv fixes.
This commit is contained in:
Laurent Mazare
2023-08-28 16:08:55 +01:00
committed by GitHub
parent 9137c63175
commit b292047882
4 changed files with 106 additions and 13 deletions
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25
candle-core/src/backprop.rs
View File

@ -192,7 +192,30 @@ impl Tensor {
*f_sum_grad = f_sum_grad.add(&f_grad)?;
}
Op::Conv1D { .. } => Err(Error::BackwardNotSupported { op: "conv1d" })?,
Op::Conv2D { .. } => Err(Error::BackwardNotSupported { op: "conv2d" })?,
Op::Conv2D {
arg,
kernel,
padding,
stride,
} => {
// The output height for conv_transpose2d is:
// (i_h - 1) * stride - 2 * padding + dilation * (k_h - 1) + out_padding + 1
let grad_h = grad.dim(2)?;
let k_h = kernel.dim(2)?;
let out_size = (grad_h - 1) * stride + (k_h - 1) + 1 - 2 * padding;
let out_padding = arg.dim(2)? - out_size;
let grad_arg =
grad.conv_transpose2d(kernel, *padding, out_padding, *stride)?;
let sum_grad = grads.or_insert(arg)?;
*sum_grad = sum_grad.add(&grad_arg)?;
let grad_kernel = arg
.transpose(0, 1)?
.conv2d(&grad.transpose(0, 1)?, *padding, *stride, 1)?
.transpose(0, 1)?;
let sum_grad = grads.or_insert(kernel)?;
*sum_grad = sum_grad.add(&grad_kernel)?;
}
Op::ConvTranspose2D { .. } => Err(Error::BackwardNotSupported {
op: "conv-transpose2d",
})?,

12
candle-core/src/conv.rs
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@ -71,18 +71,14 @@ pub struct ParamsConvTranspose2D {
impl ParamsConvTranspose2D {
pub(crate) fn out_h(&self) -> usize {
let dilation = 1;
(self.i_h - 1) * self.stride - 2 * self.padding
+ dilation * (self.k_h - 1)
+ self.output_padding
+ 1
(self.i_h - 1) * self.stride + dilation * (self.k_h - 1) + self.output_padding + 1
- 2 * self.padding
}
pub(crate) fn out_w(&self) -> usize {
let dilation = 1;
(self.i_w - 1) * self.stride - 2 * self.padding
+ dilation * (self.k_w - 1)
+ self.output_padding
+ 1
(self.i_w - 1) * self.stride + dilation * (self.k_w - 1) + self.output_padding + 1
- 2 * self.padding
}
pub(crate) fn out_dims(&self) -> Vec<usize> {

10
candle-core/src/cpu_backend.rs
View File

@ -1204,7 +1204,7 @@ impl<'a> Map2 for ConvTranspose2D<'a> {
let inp_x = out_x * p.stride as i32 - p.padding as i32;
let inp_y = out_y * p.stride as i32 - p.padding as i32;
for k_y in 0..p.k_h as i32 {
for k_x in 0..p.k_h as i32 {
for k_x in 0..p.k_w as i32 {
let k_index = k_y as usize * k_s2 + k_x as usize * k_s3;
let inp_y = inp_y + k_y;
let inp_x = inp_x + k_x;
@ -1215,9 +1215,11 @@ impl<'a> Map2 for ConvTranspose2D<'a> {
let inp_y = inp_y as usize;
if inp_x < p.i_w && inp_y < p.i_h {
let inp_index = b_idx * inp_s0 + inp_y * inp_s2 + inp_x * inp_s3;
let dst_index = b_idx * dst_s0 + inp_y * dst_s2 + inp_x * dst_s3;
for c_out in 0..k_s0 {
for c_in in 0..k_s1 {
let dst_index = b_idx * dst_s0
+ out_y as usize * dst_s2
+ out_x as usize * dst_s3;
for c_out in 0..p.c_out {
for c_in in 0..p.c_in {
let k_index = k_index + c_out * k_s1 + c_in * k_s0;
let dst_index = dst_index + c_out * dst_s1;
let inp_index = inp_index + c_in * inp_s1;