Struct dfdx::nn::Conv2D

pub struct Conv2D<const IN_CHAN: usize, const OUT_CHAN: usize, const KERNEL_SIZE: usize, const STRIDE: usize = 1, const PADDING: usize = 0> {
    pub weight: Tensor4D<OUT_CHAN, IN_CHAN, KERNEL_SIZE, KERNEL_SIZE>,
    pub bias: Tensor1D<OUT_CHAN>,
}

Requires Nightly Performs 2d convolutions on 3d and 4d images.

Pytorch Equivalent: torch.nn.Conv2d

Generics:

• IN_CHAN: The number of input channels in an image.
• OUT_CHAN: The number of channels in the output of the layer.
• KERNEL_SIZE: The size of the kernel applied to both width and height of the images.
• STRIDE: How far to move the kernel each step. Defaults to 1
• PADDING: How much zero padding to add around the images. Defaults to 0.

Examples:

#![cfg_attr(feature = "nightly", feature(generic_const_exprs))]
let m: Conv2D<16, 33, 3> = Default::default();
#[cfg(feature = "nightly")]
let _: Tensor3D<33, 30, 62> = m.forward(Tensor3D::<16, 32, 64>::zeros());
#[cfg(feature = "nightly")]
let _: Tensor4D<2, 33, 13, 12> = m.forward(Tensor4D::<2, 16, 15, 14>::zeros());

Fields

weight: Tensor4D<OUT_CHAN, IN_CHAN, KERNEL_SIZE, KERNEL_SIZE>

bias: Tensor1D<OUT_CHAN>

Trait Implementations

impl<const I: usize, const O: usize, const K: usize, const S: usize, const P: usize> CanUpdateWithGradients for Conv2D<I, O, K, S, P>

fn update<G: GradientProvider>(
    &mut self,
    grads: &mut G,
    unused: &mut UnusedTensors
)

Updates self given the GradientProvider. When any parameters that are NOT present in G, then this function should add the tensor’s UniqueId to UnusedTensors.

impl<const IN_CHAN: usize, const OUT_CHAN: usize, const KERNEL_SIZE: usize, const STRIDE: usize, const PADDING: usize> Clone for Conv2D<IN_CHAN, OUT_CHAN, KERNEL_SIZE, STRIDE, PADDING>

fn clone(&self) -> Conv2D<IN_CHAN, OUT_CHAN, KERNEL_SIZE, STRIDE, PADDING>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<const IN_CHAN: usize, const OUT_CHAN: usize, const KERNEL_SIZE: usize, const STRIDE: usize, const PADDING: usize> Debug for Conv2D<IN_CHAN, OUT_CHAN, KERNEL_SIZE, STRIDE, PADDING>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<const IN_CHAN: usize, const OUT_CHAN: usize, const KERNEL_SIZE: usize, const STRIDE: usize, const PADDING: usize> Default for Conv2D<IN_CHAN, OUT_CHAN, KERNEL_SIZE, STRIDE, PADDING>

fn default() -> Conv2D<IN_CHAN, OUT_CHAN, KERNEL_SIZE, STRIDE, PADDING>

Returns the “default value” for a type.

impl<const I: usize, const O: usize, const K: usize, const S: usize, const P: usize> LoadFromNpz for Conv2D<I, O, K, S, P>

fn read<R: Read + Seek>(
    &mut self,
    p: &str,
    r: &mut ZipArchive<R>
) -> Result<(), NpzError>

Reads this object from a ZipArchive. r with a base filename of filename_prefix.

fn load<P: AsRef<Path>>(&mut self, path: P) -> Result<(), NpzError>

Loads data from a .npz zip archive at the specified path.

impl<T: Tape, const I: usize, const O: usize, const K: usize, const S: usize, const P: usize, const H: usize, const W: usize> Module<Tensor3D<I, H, W, T>> for Conv2D<I, O, K, S, P>

type Output = Tensor3D<O, { (H + 2 * P - K) / S + 1 }, { (W + 2 * P - K) / S + 1 }, T>

The type that this unit produces given Input.

fn forward(&self, x: Tensor3D<I, H, W, T>) -> Self::Output

Forward Input through the module and produce Module::Output.

impl<T: Tape, const B: usize, const I: usize, const O: usize, const K: usize, const S: usize, const P: usize, const H: usize, const W: usize> Module<Tensor4D<B, I, H, W, T>> for Conv2D<I, O, K, S, P>

type Output = Tensor4D<B, O, { (H + 2 * P - K) / S + 1 }, { (W + 2 * P - K) / S + 1 }, T>

The type that this unit produces given Input.

fn forward(&self, x: Tensor4D<B, I, H, W, T>) -> Self::Output

Forward Input through the module and produce Module::Output.

impl<const I: usize, const O: usize, const K: usize, const S: usize, const P: usize, T> ModuleMut<T> for Conv2D<I, O, K, S, P>where
    Self: Module<T>,

type Output = <Conv2D<I, O, K, S, P> as Module<T>>::Output

The type that this unit produces given Input.

fn forward_mut(&mut self, input: T) -> Self::Output

Forward Input through the module and produce ModuleMut::Output.

impl<const I: usize, const O: usize, const K: usize, const S: usize, const P: usize> ResetParams for Conv2D<I, O, K, S, P>

fn reset_params<R: Rng>(&mut self, rng: &mut R)

Mutate the unit’s parameters using rand::Rng. Each implementor of this trait decides how the parameters are initialized. In fact, some impls may not even use the rng.

impl<const I: usize, const O: usize, const K: usize, const S: usize, const P: usize> SaveToNpz for Conv2D<I, O, K, S, P>

fn write<W: Write + Seek>(&self, p: &str, w: &mut ZipWriter<W>) -> ZipResult<()>

Write this object into ZipWriter w with a base filename of filename_prefix.

fn save<P: AsRef<Path>>(&self, path: P) -> ZipResult<()>

Save this object into the .npz file determined located at path.