pub struct RegressionLayer { /* private fields */ }Expand description
layer for converting loss to regression output
Trait Implementations§
Source§impl<B: Backend> AI<LossOutput<B>, RegressionOutput<B>> for RegressionLayer
impl<B: Backend> AI<LossOutput<B>, RegressionOutput<B>> for RegressionLayer
Source§fn forward(&self, lossoutput: LossOutput<B>) -> RegressionOutput<B>
fn forward(&self, lossoutput: LossOutput<B>) -> RegressionOutput<B>
applies to the input
Source§fn forward_mut(&mut self, input: X) -> Y
fn forward_mut(&mut self, input: X) -> Y
applies to the input, possibly updating internal caches
Source§impl Clone for RegressionLayer
impl Clone for RegressionLayer
Source§fn clone(&self) -> RegressionLayer
fn clone(&self) -> RegressionLayer
Returns a duplicate of the value. Read more
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
Performs copy-assignment from
source. Read moreSource§impl Debug for RegressionLayer
impl Debug for RegressionLayer
Source§impl Decompose for RegressionLayer
impl Decompose for RegressionLayer
Source§type Decomposition = ()
type Decomposition = ()
the decomposed type
Source§fn compose(_decomposition: Self::Decomposition) -> Self
fn compose(_decomposition: Self::Decomposition) -> Self
recreates from the decomposition
Source§fn decompose_cloned(&self)
fn decompose_cloned(&self)
decomposition that copies data
Source§impl Default for RegressionLayer
impl Default for RegressionLayer
Source§fn default() -> RegressionLayer
fn default() -> RegressionLayer
Returns the “default value” for a type. Read more
Source§impl<'de> Deserialize<'de> for RegressionLayer
impl<'de> Deserialize<'de> for RegressionLayer
Source§fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where
__D: Deserializer<'de>,
fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where
__D: Deserializer<'de>,
Deserialize this value from the given Serde deserializer. Read more
Source§impl Op for RegressionLayer
impl Op for RegressionLayer
Source§type Output = RegressionOutput<NdArray>
type Output = RegressionOutput<NdArray>
suggested output type to help with composition coherence. Ideally, Self should implement AI<X,Self::Output> for some X
Source§fn chain<B>(self, b: B) -> Sequential<(Self, B)>
fn chain<B>(self, b: B) -> Sequential<(Self, B)>
sequences with another ai operation
Source§fn forward_fixed<Z>(&self, input: Z) -> Z
fn forward_fixed<Z>(&self, input: Z) -> Z
applies to the input
Source§fn forward_fixed_mut<Z>(&mut self, input: Z) -> Z
fn forward_fixed_mut<Z>(&mut self, input: Z) -> Z
applies to the input
Source§fn forward_typed<W, Z>(&self, input: W) -> Z
fn forward_typed<W, Z>(&self, input: W) -> Z
applies to the input
Source§fn forward_typed_mut<W, Z>(&mut self, input: W) -> Z
fn forward_typed_mut<W, Z>(&mut self, input: W) -> Z
applies to the input, possibly updating internal caches
Source§fn infer_autoregressive<X, Y>(self, input: X) -> Autoregression<Self, Y> ⓘ
fn infer_autoregressive<X, Y>(self, input: X) -> Autoregression<Self, Y> ⓘ
creates an autoregressive inference
Source§fn map<B>(self, b: B) -> Map<Sequential<(Self, B)>>
fn map<B>(self, b: B) -> Map<Sequential<(Self, B)>>
applies the operation to every output
Source§fn wrap_inner(self) -> Inner<Self>where
Self: Sized,
fn wrap_inner(self) -> Inner<Self>where
Self: Sized,
wraps the inner value so it can be unwrapped with unwrap inner
Source§impl Serialize for RegressionLayer
impl Serialize for RegressionLayer
impl Copy for RegressionLayer
Auto Trait Implementations§
impl Freeze for RegressionLayer
impl RefUnwindSafe for RegressionLayer
impl Send for RegressionLayer
impl Sync for RegressionLayer
impl Unpin for RegressionLayer
impl UnwindSafe for RegressionLayer
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
Source§impl<T> CloneToUninit for Twhere
T: Clone,
impl<T> CloneToUninit for Twhere
T: Clone,
Source§impl<T> IntoEither for T
impl<T> IntoEither for T
Source§fn into_either(self, into_left: bool) -> Either<Self, Self>
fn into_either(self, into_left: bool) -> Either<Self, Self>
Converts
self into a Left variant of Either<Self, Self>
if into_left is true.
Converts self into a Right variant of Either<Self, Self>
otherwise. Read moreSource§fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
Converts
self into a Left variant of Either<Self, Self>
if into_left(&self) returns true.
Converts self into a Right variant of Either<Self, Self>
otherwise. Read moreSource§impl<T> Pointable for T
impl<T> Pointable for T
Source§impl<T> Shortcuts for T
impl<T> Shortcuts for T
Source§fn classification(self) -> Classification<Self>
fn classification(self) -> Classification<Self>
wraps in a classification wrapper
Source§fn regression(self) -> Regression<Self>
fn regression(self) -> Regression<Self>
wraps in a regression wrapper