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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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70
candle-core/src/tensor.rs
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@ -124,7 +124,7 @@ macro_rules! broadcast_binary_op {
}
/// Creates a fresh tensor structure based on a storage and a shape, this uses contiguous strides.
fn from_storage<S: Into<Shape>>(
pub(crate) fn from_storage<S: Into<Shape>>(
storage: Storage,
shape: S,
op: BackpropOp,
@ -787,72 +787,6 @@ impl Tensor {
self.cmp(rhs, CmpOp::Le)
}
/// Applies a 1D convolution over the input tensor.
pub fn conv1d(&self, kernel: &Self, padding: usize, stride: usize) -> Result<Self> {
let (c_out, c_in_k, k_size) = kernel.dims3()?;
let (b_size, c_in, l_in) = self.dims3()?;
if c_in != c_in_k {
Err(Error::Conv1dInvalidArgs {
inp_shape: self.shape().clone(),
k_shape: kernel.shape().clone(),
padding,
stride,
msg: "the number of in-channels on the input doesn't match the kernel size",
}
.bt())?
}
let params = crate::conv::ParamsConv1D {
b_size,
l_in,
c_out,
c_in,
k_size,
padding,
stride,
};
let storage =
self.storage()
.conv1d(self.layout(), &kernel.storage(), kernel.layout(), &params)?;
let op = BackpropOp::new2(self, kernel, |arg, kernel| Op::Conv1D {
arg,
kernel,
padding,
stride,
});
let out_dims = params.out_dims();
Ok(from_storage(storage, out_dims, op, false))
}
pub fn conv2d(&self, kernel: &Self, padding: usize, stride: usize) -> Result<Self> {
let (b_size, c_in, i_h, i_w) = self.dims4()?;
let (c_out, c_in_k, k_h, k_w) = kernel.dims4()?;
if c_in != c_in_k {
crate::bail!("in_channel mismatch between input ({c_in}) and kernel ({c_in_k})")
}
let params = crate::conv::ParamsConv2D {
b_size,
i_h,
i_w,
k_h,
k_w,
c_out,
c_in,
padding,
stride,
};
let storage =
self.storage()
.conv2d(self.layout(), &kernel.storage(), kernel.layout(), &params)?;
let op = BackpropOp::new2(self, kernel, |arg, kernel| Op::Conv2D {
arg,
kernel,
padding,
stride,
});
let out_dims = params.out_dims();
Ok(from_storage(storage, out_dims, op, false))
}
pub fn upsample_nearest2d(&self, target_h: usize, target_w: usize) -> Result<Self> {
let (n, c, _h, _w) = self.dims4()?;
let op = BackpropOp::new1(self, Op::UpsampleNearest2D);
@ -1920,7 +1854,7 @@ impl Tensor {
}
}
fn storage(&self) -> std::sync::RwLockReadGuard<'_, Storage> {
pub(crate) fn storage(&self) -> std::sync::RwLockReadGuard<'_, Storage> {
self.storage.read().unwrap()
}