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Add a test for conv2d with padding + bugfix the random number generation on cuda. (#578)

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* Add a test for conv2d with padding.

* Cosmetic changes.

* Bugfix the rand function on the cuda backend.
This commit is contained in:
Laurent Mazare
2023-08-24 10:16:37 +01:00
committed by GitHub
parent 79916c2edb
commit dd64465899
3 changed files with 24 additions and 8 deletions
Download Patch File Download Diff File Expand all files Collapse all files

3
candle-core/examples/cuda_basics.rs
View File

@ -9,6 +9,9 @@ use candle_core::{Device, Tensor};
fn main() -> Result<()> {
let device = Device::new_cuda(0)?;
let t = Tensor::rand(-1f32, 1f32, 96, &device)?;
println!("{t}");
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)?;

17
candle-core/src/cuda_backend.rs
View File

@ -295,10 +295,12 @@ impl BackendDevice for CudaDevice {
CudaStorageSlice::F64(data)
}
};
if lo != 0.0 || up != 1.0 {
let slice = if lo == 0. && up == 1.0 {
slice
} else {
let layout = Layout::contiguous(shape);
Affine(up - lo, lo).map(&slice, self, &layout)?;
}
Affine(up - lo, lo).map(&slice, self, &layout)?
};
Ok(CudaStorage {
slice,
device: self.clone(),
@ -955,7 +957,7 @@ impl<'a> Map2 for Conv1D<'a> {
} else if dims.len() == 2 {
[&[1], dims, &[1], inp_l.stride(), k_l.dims(), k_l.stride()].concat()
} else {
panic!("unexpected input shape for conv1d {dims:?}")
crate::bail!("unexpected input shape for conv1d {dims:?}")
};
let ds = dev.htod_copy(ds).w()?;
let params = (el, l_out, p.stride, p.padding, &ds, inp, k, &out);
@ -993,7 +995,7 @@ impl<'a> Map2 for Conv2D<'a> {
let ds = if dims.len() == 4 {
[dims, inp_l.stride(), k_l.dims(), k_l.stride()].concat()
} else {
panic!("unexpected input shape for conv1d {dims:?}")
crate::bail!("unexpected input shape for conv2d {dims:?}")
};
let ds = dev.htod_copy(ds).w()?;
let params = (el, out_w, out_h, p.stride, p.padding, &ds, inp, k, &out);
@ -1030,7 +1032,7 @@ impl Map1 for Pool2D {
let ds = if dims.len() == 4 {
[dims, inp_l.stride()].concat()
} else {
panic!("unexpected input shape for conv1d {dims:?}")
crate::bail!("unexpected input shape for pool {dims:?}")
};
let el = shape.elem_count();
let out_w = (dims[2] - self.w_k) / self.w_stride + 1;
@ -1076,7 +1078,7 @@ impl Map1 for UpsampleNearest2D {
let ds = if dims.len() == 4 {
[dims, inp_l.stride()].concat()
} else {
panic!("unexpected input shape for conv1d {dims:?}")
crate::bail!("unexpected input shape for upsample {dims:?}")
};
let (out_w, out_h) = (self.0, self.1);
let dst_el = out_w * out_h * dims[0] * dims[1];
@ -1622,7 +1624,6 @@ impl BackendStorage for CudaStorage {
.map_err(crate::Error::wrap)?;
S::F16(out)
}
(S::F32(inp), S::F32(k)) => {
let inp = &inp.slice(inp_l.start_offset()..);
let k = &k.slice(kernel_l.start_offset()..);

12
candle-core/tests/conv_tests.rs
View File

@ -149,6 +149,18 @@ fn conv2d_small(dev: &Device) -> Result<()> {
test_utils::to_vec1_round(&res.flatten_all()?, 4)?,
[0.164, -0.0111, -0.1742, 2.6437, -2.0268, 1.1823, 3.2855, -1.0324, 0.2539]
);
let res = t.conv2d(&w, 2, 1, 1)?;
assert_eq!(res.dims(), [1, 1, 7, 7]);
assert_eq!(
test_utils::to_vec1_round(&res.flatten_all()?, 4)?,
[
0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,
0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.1640, -0.0111, -0.1742, 0.0000, 0.0000,
0.0000, 0.0000, 2.6437, -2.0268, 1.1823, 0.0000, 0.0000, 0.0000, 0.0000, 3.2855,
-1.0324, 0.2539, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,
0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000
]
);
Ok(())
}