Struct auto_diff::op::convolution::Conv2d

pub struct Conv2d { /* private fields */ }

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

pub fn weight(&self) -> &Tensor

pub fn set_weight(&self, var: Var)

pub fn bias(&self) -> &Tensor

pub fn set_bias(&self, var: Var)

Trait Implementations

impl OpCall for Conv2d

fn call(&mut self, inputs: &[&Var]) -> Result<Vec<Var>, AutoDiffError>

impl OpTrait for Conv2d

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

access gradient values

fn get_name(&self) -> String

A conventional name for the op

fn get_input_size(&self) -> usize

The number of input needs by this op.

fn get_output_size(&self) -> usize

The number of output produced by this op.

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