Enum collenchyma_nn::ConvBackwardDataAlgo

pub enum ConvBackwardDataAlgo {
    Auto,
    ImplicitGEMM,
    ImplicitGEMMSum,
    FFT,
}

Different algorithms to compute the gradient with respect to the filter.

Variants

Auto	Attempt to automatically find the best algorithm of all the other available ones.
ImplicitGEMM	Compute the convolution as matrix product without forming the matrix that holds the input data. Does not need any memory workspace. The results are deterministic.
ImplicitGEMMSum	Compute the convolution as sum of matrix product without forming the matrix that holds the input data. Does not need any memory workspace. The results are non-deterministic.
FFT	Compute the convolution as Fast-Fourier Transform. Needs a significant memory workspace. The results are deterministic.

Methods

impl ConvBackwardDataAlgo

fn is_auto(&self) -> bool

Check if algorithim should be chosen automatically.

Trait Implementations

Derived Implementations

impl Clone for ConvBackwardDataAlgo

fn clone(&self) -> ConvBackwardDataAlgo

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

impl Copy for ConvBackwardDataAlgo

impl Debug for ConvBackwardDataAlgo

fn fmt(&self, __arg_0: &mut Formatter) -> Result