Struct auto_diff::op::nonlinear::Sigmoid

pub struct Sigmoid {}

Implementations

impl Sigmoid

pub fn new() -> Sigmoid

Trait Implementations

impl OpTrait for Sigmoid

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

The first is the prediction, the second input is the label

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

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

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