Struct auto_diff::op::convolution::Conv2d

pub struct Conv2d { /* fields omitted */ }

Implementations

impl Conv2d

pub fn new(
    in_channels: usize,
    out_channels: usize,
    kernel_size: (usize, usize),
    stride: (usize, usize),
    padding: (usize, usize),
    dilation: (usize, usize),
    bias: bool,
    padding_mode: PaddingMode
) -> Conv2d

Trait Implementations

impl OpTrait for Conv2d

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

fn apply(&mut self, input: &[&Tensor], output: &[&Tensor])

Forward pass

fn grad(
    &self,
    input: &[&Tensor],
    output_grad: &[&Tensor],
    input_grad: &[&Tensor]
)

Given the forward input value and backward output_grad, Update weight gradient. return backward input gradeint.

fn get_values(&self) -> Vec<&Tensor>

access weight values

fn set_values(&self, v: &[Tensor])

fn get_grads(&self) -> Vec<&Tensor>

access gradient values

fn call(&mut self, input: &[&Tensor]) -> Vec<Tensor>