Struct nncombinator::layer::InputLayer

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pub struct InputLayer<U, O, LI>where
    U: UnitValue<U>,{ /* private fields */ }

Implementations

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impl<U, O, LI> InputLayer<U, O, LI>where
U: UnitValue,

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pub fn new() -> InputLayer<U, O, LI>

Trait Implementations

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impl<U, O, LI> BackwardAll for InputLayer<U, O, LI>where
 U: UnitValue,
 O: Debug + Send + Sync + 'static,
 LI: Debug,

type LossInput = LI

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fn backward_all<OP: Optimizer, L: LossFunction>(
 &mut self,
 _: Self::LossInput,
 _: Self::OutStack,
 _: &mut OP,
 _: &L
) -> Result<(), TrainingError>

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fn is_canonical_link<L: LossFunction>(&self, _: &L) -> bool

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impl<U, O, LI> BatchBackward for InputLayer<U, O, LI>where
 U: UnitValue,
 O: Debug + Send + Sync + 'static,
 LI: Debug,

type BatchLossInput = VecArr<U, LI>

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fn batch_backward<OP: Optimizer, L: LossFunction>(
 &mut self,
 _: Self::BatchLossInput,
 _: Self::BatchOutStack,
 _: &mut OP,
 _: &L
) -> Result<(), TrainingError>

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impl<U, O, LI> BatchForward for InputLayer<U, O, LI>where
 U: UnitValue,
 O: Debug + Send + Sync + 'static,
 LI: Debug,

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fn batch_forward(
&self,
input: Self::BatchInput
) -> Result<Self::BatchOutput, TrainingError>

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impl<U, O, LI> BatchForwardBase for InputLayer<U, O, LI>where
 U: UnitValue,
 O: Debug + Send + Sync + 'static,
 LI: Debug,

type BatchInput = VecArr<U, O>

type BatchOutput = VecArr<U, O>

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impl<U, O, LI> BatchLoss for InputLayer<U, O, LI>where
 U: UnitValue,
 O: Debug + Send + Sync + 'static,
 LI: Debug,

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fn batch_loss<L: LossFunction>(
 &self,
 loss: Self::BatchLossInput,
 _: &L,
 stack: Self::BatchOutStack
) -> Result<(Self::BatchOutStack, Self::BatchLossInput), TrainingError>

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impl<U, O, LI> BatchPreTrain for InputLayer<U, O, LI>where
 U: UnitValue,
 O: Debug + Send + Sync + 'static,
 LI: Debug,

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fn batch_pre_train(
&self,
input: Self::BatchInput
) -> Result<Self::BatchOutStack, TrainingError>

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impl<U, O, LI> BatchPreTrainBase for InputLayer<U, O, LI>where
 U: UnitValue,
 O: Debug + Send + Sync + 'static,
 LI: Debug,

type BatchOutStack = Cons<Nil, VecArr<U, O>>

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impl<U, O, LI> ForwardAll for InputLayer<U, O, LI>where
 U: UnitValue,
 O: Debug + Send + Sync + 'static,
 LI: Debug,

type Input = O

type Output = O

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fn forward_all(&self, input: Self::Input) -> Result<Self::Output, EvaluateError>

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impl<U, O, LI> Loss for InputLayer<U, O, LI>where
 U: UnitValue,
 O: Debug + Send + Sync + 'static,
 LI: Debug,

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fn loss<L: LossFunction>(
 &mut self,
 loss: Self::LossInput,
 _: &L,
 stack: Self::OutStack
) -> Result<(Self::OutStack, Self::LossInput), TrainingError>

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impl<T, U, O, LI> Persistence<U, T, Linear> for InputLayer<U, O, LI>where
T: LinearPersistence,
U: UnitValue,

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fn load(&mut self, _: &mut T) -> Result<(), ConfigReadError>

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fn save(&mut self, _: &mut T) -> Result<(), PersistenceError>

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impl<U, O, LI> Persistence<U, TextFilePersistence, Specialized> for InputLayer<U, O, LI>where
U: UnitValue + FromStr + Sized,

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fn load(&mut self, _: &mut TextFilePersistence) -> Result<(), ConfigReadError>

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fn save(
&mut self,
_: &mut TextFilePersistence
) -> Result<(), PersistenceError>

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impl<U, O, LI> PreTrain for InputLayer<U, O, LI>where
 U: UnitValue,
 O: Debug + Send + Sync + 'static,
 LI: Debug,

type OutStack = Cons<Nil, <InputLayer<U, O, LI> as ForwardAll>::Output>

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fn pre_train(&self, input: Self::Input) -> Result<Self::OutStack, EvaluateError>

Auto Trait Implementations

impl<U, O, LI> RefUnwindSafe for InputLayer<U, O, LI>where
 LI: RefUnwindSafe,
 O: RefUnwindSafe,
 U: RefUnwindSafe,

impl<U, O, LI> Send for InputLayer<U, O, LI>where
LI: Send,
O: Send,

impl<U, O, LI> Sync for InputLayer<U, O, LI>where
LI: Sync,
O: Sync,

impl<U, O, LI> Unpin for InputLayer<U, O, LI>where
 LI: Unpin,
 O: Unpin,
 U: Unpin,

impl<U, O, LI> UnwindSafe for InputLayer<U, O, LI>where
 LI: UnwindSafe,
 O: UnwindSafe,
 U: UnwindSafe,

Blanket Implementations

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fn type_id(&self) -> TypeId

Gets the TypeId of self. Read more

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impl<T> Borrow<T> for Twhere
T: ?Sized,

const: unstable · source

fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more

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impl<T> BorrowMut<T> for Twhere
T: ?Sized,

const: unstable · source

fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more

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impl<T, U> ForwardDiff for Twhere
T: PreTrain,
U: UnitValue,

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fn forward_diff(
&self,
input: <T as ForwardAll>::Input
) -> Result<<T as PreTrain>::OutStack, EvaluateError>

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impl<T> From<T> for T

const: unstable · source

fn from(t: T) -> T

Returns the argument unchanged.

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impl<T, U> Into for Twhere
U: From<T>,

const: unstable · source

fn into(self) -> U

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

impl<T> Pointable for T

const ALIGN: usize = mem::align_of::<T>()

The alignment of pointer.

type Init = T

The type for initializers.

unsafe fn init(init: <T as Pointable>::Init) -> usize

Initializes a with the given initializer. Read more

unsafe fn deref<'a>(ptr: usize) -> &'a T

Dereferences the given pointer. Read more

unsafe fn deref_mut<'a>(ptr: usize) -> &'a mut T

Mutably dereferences the given pointer. Read more

unsafe fn drop(ptr: usize)

Drops the object pointed to by the given pointer. Read more

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impl<T> TryAddLayer for Twhere
T: ForwardAll,

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fn try_add_layer<C, F>(self, f: F) -> Result<C, DeviceError>where
C: ForwardAll,
F: FnOnce(T) -> Result<C, DeviceError>,

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impl<T, U> TryAddLayerTrain for Twhere
T: PreTrain,
U: UnitValue,

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fn try_add_layer_train<C, F>(self, f: F) -> Result<C, DeviceError>where
C: Train,
F: FnOnce(T) -> Result<C, DeviceError>,

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impl<T, U> TryFrom for Twhere
U: Into<T>,

type Error = Infallible

The type returned in the event of a conversion error.

const: unstable · source

fn try_from(value: U) -> Result<T, <T as TryFrom>::Error>

Performs the conversion.

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impl<T, U> TryInto for Twhere
U: TryFrom<T>,

type Error = >::Error

The type returned in the event of a conversion error.

const: unstable · source

fn try_into(self) -> Result<U, >::Error>

Performs the conversion.

Struct nncombinator::layer::InputLayer

Implementations

impl<U, O, LI> InputLayer<U, O, LI>where U: UnitValue<U>,

pub fn new() -> InputLayer<U, O, LI>

Trait Implementations

impl<U, O, LI> BackwardAll<U> for InputLayer<U, O, LI>where U: UnitValue<U>, O: Debug + Send + Sync + 'static, LI: Debug,

type LossInput = LI

fn backward_all<OP: Optimizer<U>, L: LossFunction<U>>( &mut self, _: Self::LossInput, _: Self::OutStack, _: &mut OP, _: &L) -> Result<(), TrainingError>

fn is_canonical_link<L: LossFunction<U>>(&self, _: &L) -> bool

impl<U, O, LI> BatchBackward<U> for InputLayer<U, O, LI>where U: UnitValue<U>, O: Debug + Send + Sync + 'static, LI: Debug,

type BatchLossInput = VecArr<U, LI>

fn batch_backward<OP: Optimizer<U>, L: LossFunction<U>>( &mut self, _: Self::BatchLossInput, _: Self::BatchOutStack, _: &mut OP, _: &L) -> Result<(), TrainingError>

impl<U, O, LI> BatchForward for InputLayer<U, O, LI>where U: UnitValue<U>, O: Debug + Send + Sync + 'static, LI: Debug,

fn batch_forward( &self, input: Self::BatchInput) -> Result<Self::BatchOutput, TrainingError>

impl<U, O, LI> BatchForwardBase for InputLayer<U, O, LI>where U: UnitValue<U>, O: Debug + Send + Sync + 'static, LI: Debug,

type BatchInput = VecArr<U, O>

type BatchOutput = VecArr<U, O>

impl<U, O, LI> BatchLoss<U> for InputLayer<U, O, LI>where U: UnitValue<U>, O: Debug + Send + Sync + 'static, LI: Debug,

fn batch_loss<L: LossFunction<U>>( &self, loss: Self::BatchLossInput, _: &L, stack: Self::BatchOutStack) -> Result<(Self::BatchOutStack, Self::BatchLossInput), TrainingError>

impl<U, O, LI> BatchPreTrain<U> for InputLayer<U, O, LI>where U: UnitValue<U>, O: Debug + Send + Sync + 'static, LI: Debug,

fn batch_pre_train( &self, input: Self::BatchInput) -> Result<Self::BatchOutStack, TrainingError>

impl<U, O, LI> BatchPreTrainBase<U> for InputLayer<U, O, LI>where U: UnitValue<U>, O: Debug + Send + Sync + 'static, LI: Debug,

type BatchOutStack = Cons<Nil, VecArr<U, O>>

impl<U, O, LI> ForwardAll for InputLayer<U, O, LI>where U: UnitValue<U>, O: Debug + Send + Sync + 'static, LI: Debug,

type Input = O

type Output = O

fn forward_all(&self, input: Self::Input) -> Result<Self::Output, EvaluateError>

impl<U, O, LI> Loss<U> for InputLayer<U, O, LI>where U: UnitValue<U>, O: Debug + Send + Sync + 'static, LI: Debug,

fn loss<L: LossFunction<U>>( &mut self, loss: Self::LossInput, _: &L, stack: Self::OutStack) -> Result<(Self::OutStack, Self::LossInput), TrainingError>

impl<T, U, O, LI> Persistence<U, T, Linear> for InputLayer<U, O, LI>where T: LinearPersistence<U>, U: UnitValue<U>,

fn load(&mut self, _: &mut T) -> Result<(), ConfigReadError>

fn save(&mut self, _: &mut T) -> Result<(), PersistenceError>

impl<U, O, LI> Persistence<U, TextFilePersistence<U>, Specialized> for InputLayer<U, O, LI>where U: UnitValue<U> + FromStr + Sized,

fn load(&mut self, _: &mut TextFilePersistence<U>) -> Result<(), ConfigReadError>

fn save( &mut self, _: &mut TextFilePersistence<U>) -> Result<(), PersistenceError>

impl<U, O, LI> PreTrain<U> for InputLayer<U, O, LI>where U: UnitValue<U>, O: Debug + Send + Sync + 'static, LI: Debug,

type OutStack = Cons<Nil, <InputLayer<U, O, LI> as ForwardAll>::Output>

fn pre_train(&self, input: Self::Input) -> Result<Self::OutStack, EvaluateError>

Auto Trait Implementations

impl<U, O, LI> RefUnwindSafe for InputLayer<U, O, LI>where LI: RefUnwindSafe, O: RefUnwindSafe, U: RefUnwindSafe,

impl<U, O, LI> Send for InputLayer<U, O, LI>where LI: Send, O: Send,

impl<U, O, LI> Sync for InputLayer<U, O, LI>where LI: Sync, O: Sync,

impl<U, O, LI> Unpin for InputLayer<U, O, LI>where LI: Unpin, O: Unpin, U: Unpin,

impl<U, O, LI> UnwindSafe for InputLayer<U, O, LI>where LI: UnwindSafe, O: UnwindSafe, U: UnwindSafe,

Blanket Implementations

impl<T> AddLayer for Twhere T: ForwardAll,

fn add_layer<C, F>(self, f: F) -> Cwhere C: ForwardAll, F: FnOnce(T) -> C,

impl<T, U> AddLayerTrain<U> for Twhere T: PreTrain<U>, U: UnitValue<U>,

fn add_layer_train<C, F>(self, f: F) -> Cwhere C: Train<U>, F: FnOnce(T) -> C,

impl<T> Any for Twhere T: 'static + ?Sized,

fn type_id(&self) -> TypeId

impl<T> Borrow<T> for Twhere T: ?Sized,

fn borrow(&self) -> &T

impl<T> BorrowMut<T> for Twhere T: ?Sized,

fn borrow_mut(&mut self) -> &mut T

impl<T, U> ForwardDiff<U> for Twhere T: PreTrain<U>, U: UnitValue<U>,

fn forward_diff( &self, input: <T as ForwardAll>::Input) -> Result<<T as PreTrain<U>>::OutStack, EvaluateError>

impl<T> From<T> for T

fn from(t: T) -> T

impl<T, U> Into<U> for Twhere U: From<T>,

fn into(self) -> U

impl<T> Pointable for T

const ALIGN: usize = mem::align_of::<T>()

type Init = T

unsafe fn init(init: <T as Pointable>::Init) -> usize

unsafe fn deref<'a>(ptr: usize) -> &'a T

unsafe fn deref_mut<'a>(ptr: usize) -> &'a mut T

unsafe fn drop(ptr: usize)

impl<T> TryAddLayer for Twhere T: ForwardAll,

fn try_add_layer<C, F>(self, f: F) -> Result<C, DeviceError>where C: ForwardAll, F: FnOnce(T) -> Result<C, DeviceError>,

impl<T, U> TryAddLayerTrain<U> for Twhere T: PreTrain<U>, U: UnitValue<U>,

fn try_add_layer_train<C, F>(self, f: F) -> Result<C, DeviceError>where C: Train<U>, F: FnOnce(T) -> Result<C, DeviceError>,

impl<T, U> TryFrom<U> for Twhere U: Into<T>,

type Error = Infallible

fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

impl<T, U> TryInto<U> for Twhere U: TryFrom<T>,

type Error = <U as TryFrom<T>>::Error

fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>

impl<U, O, LI> InputLayer<U, O, LI>where
U: UnitValue<U>,

impl<U, O, LI> BackwardAll<U> for InputLayer<U, O, LI>where
U: UnitValue<U>,
O: Debug + Send + Sync + 'static,
LI: Debug,

fn backward_all<OP: Optimizer<U>, L: LossFunction<U>>(
&mut self,
_: Self::LossInput,
_: Self::OutStack,
_: &mut OP,
_: &L
) -> Result<(), TrainingError>

impl<U, O, LI> BatchBackward<U> for InputLayer<U, O, LI>where
U: UnitValue<U>,
O: Debug + Send + Sync + 'static,
LI: Debug,

fn batch_backward<OP: Optimizer<U>, L: LossFunction<U>>(
&mut self,
_: Self::BatchLossInput,
_: Self::BatchOutStack,
_: &mut OP,
_: &L
) -> Result<(), TrainingError>

impl<U, O, LI> BatchForward for InputLayer<U, O, LI>where
U: UnitValue<U>,
O: Debug + Send + Sync + 'static,
LI: Debug,

fn batch_forward(
&self,
input: Self::BatchInput
) -> Result<Self::BatchOutput, TrainingError>

impl<U, O, LI> BatchForwardBase for InputLayer<U, O, LI>where
U: UnitValue<U>,
O: Debug + Send + Sync + 'static,
LI: Debug,

impl<U, O, LI> BatchLoss<U> for InputLayer<U, O, LI>where
U: UnitValue<U>,
O: Debug + Send + Sync + 'static,
LI: Debug,

fn batch_loss<L: LossFunction<U>>(
&self,
loss: Self::BatchLossInput,
_: &L,
stack: Self::BatchOutStack
) -> Result<(Self::BatchOutStack, Self::BatchLossInput), TrainingError>

impl<U, O, LI> BatchPreTrain<U> for InputLayer<U, O, LI>where
U: UnitValue<U>,
O: Debug + Send + Sync + 'static,
LI: Debug,

fn batch_pre_train(
&self,
input: Self::BatchInput
) -> Result<Self::BatchOutStack, TrainingError>

impl<U, O, LI> BatchPreTrainBase<U> for InputLayer<U, O, LI>where
U: UnitValue<U>,
O: Debug + Send + Sync + 'static,
LI: Debug,

impl<U, O, LI> ForwardAll for InputLayer<U, O, LI>where
U: UnitValue<U>,
O: Debug + Send + Sync + 'static,
LI: Debug,

impl<U, O, LI> Loss<U> for InputLayer<U, O, LI>where
U: UnitValue<U>,
O: Debug + Send + Sync + 'static,
LI: Debug,

fn loss<L: LossFunction<U>>(
&mut self,
loss: Self::LossInput,
_: &L,
stack: Self::OutStack
) -> Result<(Self::OutStack, Self::LossInput), TrainingError>

impl<T, U, O, LI> Persistence<U, T, Linear> for InputLayer<U, O, LI>where
T: LinearPersistence<U>,
U: UnitValue<U>,

impl<U, O, LI> Persistence<U, TextFilePersistence<U>, Specialized> for InputLayer<U, O, LI>where
U: UnitValue<U> + FromStr + Sized,

fn save(
&mut self,
_: &mut TextFilePersistence<U>
) -> Result<(), PersistenceError>

impl<U, O, LI> PreTrain<U> for InputLayer<U, O, LI>where
U: UnitValue<U>,
O: Debug + Send + Sync + 'static,
LI: Debug,

impl<U, O, LI> RefUnwindSafe for InputLayer<U, O, LI>where
LI: RefUnwindSafe,
O: RefUnwindSafe,
U: RefUnwindSafe,

impl<U, O, LI> Send for InputLayer<U, O, LI>where
LI: Send,
O: Send,

impl<U, O, LI> Sync for InputLayer<U, O, LI>where
LI: Sync,
O: Sync,

impl<U, O, LI> Unpin for InputLayer<U, O, LI>where
LI: Unpin,
O: Unpin,
U: Unpin,

impl<U, O, LI> UnwindSafe for InputLayer<U, O, LI>where
LI: UnwindSafe,
O: UnwindSafe,
U: UnwindSafe,

impl<T> AddLayer for Twhere
T: ForwardAll,

fn add_layer<C, F>(self, f: F) -> Cwhere
C: ForwardAll,
F: FnOnce(T) -> C,

impl<T, U> AddLayerTrain<U> for Twhere
T: PreTrain<U>,
U: UnitValue<U>,

fn add_layer_train<C, F>(self, f: F) -> Cwhere
C: Train<U>,
F: FnOnce(T) -> C,

impl<T> Any for Twhere
T: 'static + ?Sized,

impl<T> Borrow<T> for Twhere
T: ?Sized,

impl<T> BorrowMut<T> for Twhere
T: ?Sized,

impl<T, U> ForwardDiff<U> for Twhere
T: PreTrain<U>,
U: UnitValue<U>,

fn forward_diff(
&self,
input: <T as ForwardAll>::Input
) -> Result<<T as PreTrain<U>>::OutStack, EvaluateError>

impl<T, U> Into<U> for Twhere
U: From<T>,

impl<T> TryAddLayer for Twhere
T: ForwardAll,

fn try_add_layer<C, F>(self, f: F) -> Result<C, DeviceError>where
C: ForwardAll,
F: FnOnce(T) -> Result<C, DeviceError>,

impl<T, U> TryAddLayerTrain<U> for Twhere
T: PreTrain<U>,
U: UnitValue<U>,

fn try_add_layer_train<C, F>(self, f: F) -> Result<C, DeviceError>where
C: Train<U>,
F: FnOnce(T) -> Result<C, DeviceError>,

impl<T, U> TryFrom<U> for Twhere
U: Into<T>,

impl<T, U> TryInto<U> for Twhere
U: TryFrom<T>,