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Add to the cuda example a reproduction of the issue. (#579)

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* Add to the cuda example a reproduction of the issue.

* Tweak.

* Add a test using non-square matrixes.

* Fix the conv2d kernel.

* Display the error.

* And tweak the comment.
This commit is contained in:
Laurent Mazare
2023-08-24 12:07:31 +01:00
committed by GitHub
parent dd64465899
commit ca318a6ec7
3 changed files with 58 additions and 12 deletions
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36
candle-core/tests/conv_tests.rs
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@ -183,8 +183,44 @@ fn conv2d_smaller(dev: &Device) -> Result<()> {
Ok(())
}
/* This test is based on the following script.
import torch
torch.manual_seed(4242)
t = torch.randn((1, 2, 4, 2))
w = torch.randn((1, 2, 1, 1))
print(t.flatten())
print(w.flatten())
res = torch.nn.functional.conv2d(t, w)
print(res.flatten())
*/
fn conv2d_non_square(dev: &Device) -> Result<()> {
let t = Tensor::new(
&[
0.4056f32, -0.8689, -0.0773, -1.5630, -2.8012, -1.5059, 0.3972, 1.0852, 0.4997, 3.0616,
1.6541, 0.0964, -0.8338, -1.6523, -0.8323, -0.1699,
],
dev,
)?;
let w = Tensor::new(&[-1.1351f32, 1.3841], dev)?;
let t = t.reshape((1, 2, 4, 2))?;
let w = w.reshape((1, 2, 1, 1))?;
let res = t.conv2d(&w, 0, 1, 1)?;
assert_eq!(res.dims(), [1, 1, 4, 2]);
assert_eq!(
test_utils::to_vec1_round(&res.flatten_all()?, 4)?,
[0.2312, 5.2238, 2.3772, 1.9076, 2.0256, -0.5776, -1.6028, -1.467]
);
Ok(())
}
test_device!(conv1d, conv1d_cpu, conv1d_gpu);
test_device!(conv1d_small, conv1d_small_cpu, conv1d_small_gpu);
test_device!(conv2d, conv2d_cpu, conv2d_gpu);
test_device!(
conv2d_non_square,
conv2d_non_square_cpu,
conv2d_non_square_gpu
);
test_device!(conv2d_small, conv2d_small_cpu, conv2d_small_gpu);
test_device!(conv2d_smaller, conv2d_smaller_cpu, conv2d_smaller_gpu);