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Add some group parameter to convolutions. (#566)

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* Add some group parameter to convolutions.

* Avoid some unnecessary groups checks.

* Move the tensor convolution bits.

* Properh handling of groups.

* Bump the crate version.

* And add a changelog.
This commit is contained in:
Laurent Mazare
2023-08-23 12:58:55 +01:00
committed by GitHub
parent 4ee1cf038a
commit aba1e90797
30 changed files with 216 additions and 113 deletions
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14
candle-core/tests/conv_tests.rs
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@ -33,13 +33,13 @@ fn conv1d(dev: &Device) -> Result<()> {
dev,
)?
.reshape((2, 4, 3))?;
let res = t.conv1d(&w, 0, 1)?;
let res = t.conv1d(&w, 0, 1, 1)?;
assert_eq!(res.dims(), [1, 2, 3]);
assert_eq!(
test_utils::to_vec1_round(&res.flatten_all()?, 4)?,
[2.6357, -1.3336, 4.1393, -1.1784, 3.5675, 0.5069]
);
let res = t.conv1d(&w, /*padding*/ 1, 1)?;
let res = t.conv1d(&w, /*padding*/ 1, 1, 1)?;
assert_eq!(res.dims(), [1, 2, 5]);
// Same as pytorch default padding: use zeros.
assert_eq!(
@ -52,13 +52,13 @@ fn conv1d(dev: &Device) -> Result<()> {
fn conv1d_small(dev: &Device) -> Result<()> {
let t = Tensor::new(&[0.4056f32, -0.8689, -0.0773, -1.5630], dev)?.reshape((1, 1, 4))?;
let w = Tensor::new(&[1f32, 0., 0.], dev)?.reshape((1, 1, 3))?;
let res = t.conv1d(&w, 0, 1)?;
let res = t.conv1d(&w, 0, 1, 1)?;
assert_eq!(res.dims(), [1, 1, 2]);
assert_eq!(
test_utils::to_vec1_round(&res.flatten_all()?, 4)?,
[0.4056, -0.8689]
);
let res = t.conv1d(&w, /*padding*/ 1, 1)?;
let res = t.conv1d(&w, /*padding*/ 1, 1, 1)?;
assert_eq!(res.dims(), [1, 1, 4]);
assert_eq!(
test_utils::to_vec1_round(&res.flatten_all()?, 4)?,
@ -109,7 +109,7 @@ fn conv2d(dev: &Device) -> Result<()> {
)?;
let t = t.reshape((1, 4, 5, 5))?;
let w = w.reshape((2, 4, 3, 3))?;
let res = t.conv2d(&w, 0, 1)?;
let res = t.conv2d(&w, 0, 1, 1)?;
assert_eq!(res.dims(), [1, 2, 3, 3]);
assert_eq!(
test_utils::to_vec1_round(&res.flatten_all()?, 4)?,
@ -143,7 +143,7 @@ fn conv2d_small(dev: &Device) -> Result<()> {
let w = Tensor::new(&[-0.9259f32, 1.3017], dev)?;
let t = t.reshape((1, 2, 3, 3))?;
let w = w.reshape((1, 2, 1, 1))?;
let res = t.conv2d(&w, 0, 1)?;
let res = t.conv2d(&w, 0, 1, 1)?;
assert_eq!(res.dims(), [1, 1, 3, 3]);
assert_eq!(
test_utils::to_vec1_round(&res.flatten_all()?, 4)?,
@ -162,7 +162,7 @@ fn conv2d_smaller(dev: &Device) -> Result<()> {
let w = Tensor::new(&[1f32, 1., 1., 1., 1., 1., 1., 1., 1.], dev)?;
let t = t.reshape((1, 1, 3, 3))?;
let w = w.reshape((1, 1, 3, 3))?;
let res = t.conv2d(&w, 0, 1)?;
let res = t.conv2d(&w, 0, 1, 1)?;
assert_eq!(res.dims(), [1, 1, 1, 1]);
assert_eq!(
test_utils::to_vec1_round(&res.flatten_all()?, 4)?,