Trait neuronika::ConvolveWithGroups

pub trait ConvolveWithGroups<Inp, Ker, Pad: PaddingMode> {
    type Output;
    fn convolve_with_groups(
        input: Inp, 
        kernel: Ker, 
        stride: &[usize], 
        dilation: &[usize], 
        padding: &[usize], 
        padding_mode: Pad, 
        groups: usize
    ) -> Self::Output;
}

Grouped convolution.

Associated Types

type Output

The type of the grouped convolution’s result. See the differentiability arithmetic for more details.

Required methods

fn convolve_with_groups(
    input: Inp,
    kernel: Ker,
    stride: &[usize],
    dilation: &[usize],
    padding: &[usize],
    padding_mode: Pad,
    groups: usize
) -> Self::Output

Applies a n-dimensional grouped convolution with the given parameters. n can be either 1, 2 or 3.

Implementors

impl<F1, B1, F2, B2, Pad> ConvolveWithGroups<VarDiff<F1, B1>, VarDiff<F2, B2>, Pad> for VarDiff<F1, B1> where
    F1: NData + Debug + Display + 'static,
    F1::Dim: RemoveAxis,
    <F1::Dim as Dimension>::Smaller: RemoveAxis,
    <<F1::Dim as Dimension>::Smaller as Dimension>::Smaller: ReflPad + ReplPad,
    B1: Gradient<Dim = F1::Dim> + Overwrite,
    F2: NData<Dim = F1::Dim> + Debug + Display + 'static,
    B2: Gradient<Dim = F2::Dim> + Overwrite,
    Pad: PaddingMode + 'static, 

type Output = VarDiff<GroupedConvolution<F1, F2, Pad>, GroupedConvolutionBackward<F1, B1, F2, B2, Pad>>

impl<F1, F2, B2, Pad> ConvolveWithGroups<Var<F1>, VarDiff<F2, B2>, Pad> for Var<F1> where
    F1: NData + 'static,
    F1::Dim: RemoveAxis,
    <F1::Dim as Dimension>::Smaller: RemoveAxis,
    <<F1::Dim as Dimension>::Smaller as Dimension>::Smaller: ReflPad + ReplPad,
    F2: NData<Dim = F1::Dim> + 'static,
    B2: Gradient<Dim = F2::Dim> + Overwrite,
    Pad: PaddingMode + 'static, 

type Output = VarDiff<GroupedConvolution<F1, F2, Pad>, GroupedConvolutionBackwardUnary<F1, B2, Pad>>

impl<F1, F2, Pad> ConvolveWithGroups<Var<F1>, Var<F2>, Pad> for Var<F1> where
    F1: NData + 'static,
    F1::Dim: RemoveAxis,
    <F1::Dim as Dimension>::Smaller: RemoveAxis,
    <<F1::Dim as Dimension>::Smaller as Dimension>::Smaller: ReflPad + ReplPad,
    F2: NData<Dim = F1::Dim> + 'static,
    Pad: PaddingMode + 'static, 

type Output = Var<GroupedConvolution<F1, F2, Pad>>