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Dilated convolutions (#657)

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* Add the dilation parameter.

* Restore the basic optimizer example.

* Dilation support in cudnn.

* Use the dilation parameter in the cpu backend.

* More dilation support.

* No support for dilation in transposed convolutions.

* Add dilation to a test.

* Remove a print.

* Helper function.
This commit is contained in:
Laurent Mazare
2023-08-29 16:12:11 +01:00
committed by GitHub
parent ee8bb1bde1
commit a044907ffc
20 changed files with 231 additions and 45 deletions
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6
candle-core/examples/cuda_basics.rs
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@ -11,11 +11,11 @@ fn main() -> Result<()> {
let device = Device::new_cuda(0)?;
let in_t = Tensor::rand(-1f32, 1f32, (1, 3, 12, 7), &device)?;
let k_t = Tensor::rand(-1f32, 1f32, (6, 3, 1, 1), &device)?;
let out_t = in_t.conv2d(&k_t, 0, 1, 1)?;
let out_t = in_t.conv2d(&k_t, 0, 1, 1, 1)?;
println!("{out_t}");
let in_t = in_t.to_device(&Device::Cpu)?;
let k_t = k_t.to_device(&Device::Cpu)?;
let out_t2 = in_t.conv2d(&k_t, 0, 1, 1)?;
let out_t2 = in_t.conv2d(&k_t, 0, 1, 1, 1)?;
let diff = (out_t.to_device(&Device::Cpu)? - out_t2)?
.sqr()?
.sum_all()?;
@ -23,7 +23,7 @@ fn main() -> Result<()> {
let t = Tensor::randn(0f32, 1f32, (2, 4, 96, 96), &device)?;
let w = Tensor::randn(0f32, 1f32, (320, 4, 3, 3), &device)?;
let res = t.conv2d(&w, 1, 1, 1)?;
let res = t.conv2d(&w, 1, 1, 1, 1)?;
println!("{res:?}");
Ok(())
}