[][src]Struct auto_diff::op::nonlinear::Sigmoid

pub struct Sigmoid {}

Implementations

impl Sigmoid[src]

pub fn new() -> Sigmoid[src]

Trait Implementations

impl OpTrait for Sigmoid[src]

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

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

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

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

fn get_values(&self) -> Vec<&Tensor>[src]

access weight values

fn get_grads(&self) -> Vec<&Tensor>[src]

access gradient values

Auto Trait Implementations

impl RefUnwindSafe for Sigmoid

impl Send for Sigmoid

impl Sync for Sigmoid

impl Unpin for Sigmoid

impl UnwindSafe for Sigmoid

Blanket Implementations

impl<T> Any for T where
    T: 'static + ?Sized
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impl<T> Borrow<T> for T where
    T: ?Sized
[src]

impl<T> BorrowMut<T> for T where
    T: ?Sized
[src]

impl<T> From<T> for T[src]

impl<T, U> Into<U> for T where
    U: From<T>, 
[src]

impl<T, U> TryFrom<U> for T where
    U: Into<T>, 
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type Error = Infallible

The type returned in the event of a conversion error.

impl<T, U> TryInto<U> for T where
    U: TryFrom<T>, 
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type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.

impl<V, T> VZip<V> for T where
    V: MultiLane<T>,