gad::net

Struct InputData

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pub struct InputData<Data, Algebra>
where
    Data: HasDims,
{ /* private fields */ }
Expand description

A network that takes a single user data as input and returns it (after a dimension check).

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impl<Data, Algebra> InputData<Data, Algebra>
where Data: HasDims,

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pub fn new(dims: Data::Dims) -> Self

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impl<Data, Algebra: Clone> Clone for InputData<Data, Algebra>
where Data: HasDims + Clone, Data::Dims: Clone,

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fn clone(&self) -> InputData<Data, Algebra>

Returns a duplicate of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl<Data, Algebra: Debug> Debug for InputData<Data, Algebra>
where Data: HasDims + Debug, Data::Dims: Debug,

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more
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impl<Data, Value, Dims, Algebra> Net<Algebra> for InputData<Data, Algebra>
where Algebra: HasGradientReader + CoreAlgebra<Data, Value = Value>, Data: HasDims<Dims = Dims>, Dims: Clone + PartialEq + Debug,

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type Input = Data

Input of the network.
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type Output = Value

Output of the network.
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type Weights = ()

External representation for the weights of the network.
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type GradientInfo = ()

How to read the gradients of the weights after a backward pass.
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fn eval_with_gradient_info( &self, graph: &mut Algebra, input: Self::Input, ) -> Result<(Self::Output, Self::GradientInfo)>

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fn get_weights(&self) -> Self::Weights

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fn set_weights(&mut self, _weights: Self::Weights) -> Result<()>

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fn update_weights(&mut self, _delta: Self::Weights) -> Result<()>

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fn read_weight_gradients( &self, _info: Self::GradientInfo, _reader: &Algebra::GradientReader, ) -> Result<Self::Weights>

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fn eval(&self, graph: &mut Algebra, input: Self::Input) -> Result<Self::Output>

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fn map<F, O>(self, f: F) -> Map<Self, F>
where Self: Sized, F: Fn(&mut Algebra, Self::Output) -> Result<O>,

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fn using<N>(self, net: N) -> Using<Self, N>
where Self: Sized, N: Net<Algebra, Input = ()>,

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fn then<N>(self, net: N) -> Then<Self, N>
where Self: Sized, N: Net<Algebra, Input = Self::Output>,

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fn and<N>(self, net: N) -> (Self, N)
where Self: Sized, N: Net<Algebra>,

Auto Trait Implementations§

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impl<Data, Algebra> Freeze for InputData<Data, Algebra>
where <Data as HasDims>::Dims: Freeze,

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impl<Data, Algebra> RefUnwindSafe for InputData<Data, Algebra>
where <Data as HasDims>::Dims: RefUnwindSafe, Data: RefUnwindSafe, Algebra: RefUnwindSafe,

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impl<Data, Algebra> Send for InputData<Data, Algebra>
where <Data as HasDims>::Dims: Send, Data: Send, Algebra: Send,

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impl<Data, Algebra> Sync for InputData<Data, Algebra>
where <Data as HasDims>::Dims: Sync, Data: Sync, Algebra: Sync,

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impl<Data, Algebra> Unpin for InputData<Data, Algebra>
where <Data as HasDims>::Dims: Unpin, Data: Unpin, Algebra: Unpin,

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impl<Data, Algebra> UnwindSafe for InputData<Data, Algebra>
where <Data as HasDims>::Dims: UnwindSafe, Data: UnwindSafe, Algebra: UnwindSafe,

Blanket Implementations§

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

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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 T
where T: ?Sized,

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fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more
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impl<T> BorrowMut<T> for T
where T: ?Sized,

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

Mutably borrows from an owned value. Read more
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impl<N> CheckNet for N
where N: Net<Check>,

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

Run a forward pass that only checks dimensions.
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impl<T> CloneToUninit for T
where T: Clone,

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unsafe fn clone_to_uninit(&self, dest: *mut u8)

🔬This is a nightly-only experimental API. (clone_to_uninit)
Performs copy-assignment from self to dest. Read more
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impl<N> EvalNet for N
where N: Net<Eval>,

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

Run a forward pass to evaluate the network on the given input.
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impl<T> From<T> for T

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fn from(t: T) -> T

Returns the argument unchanged.

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

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fn into(self) -> U

Calls U::from(self).

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

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impl<Data, Algebra, N> SingleOutputNet<Data, Algebra> for N
where N: Net<Algebra>, Algebra: HasGradientReader + CoreAlgebra<Data, Value = <N as Net<Algebra>>::Output>,

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fn add_square_loss(self) -> SquareLoss<Self, Data>
where Self: Sized,

A network that takes an additional input and returns the L2-distance with the output of the initial network.
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impl<T> ToOwned for T
where T: Clone,

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type Owned = T

The resulting type after obtaining ownership.
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fn to_owned(&self) -> T

Creates owned data from borrowed data, usually by cloning. Read more
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fn clone_into(&self, target: &mut T)

Uses borrowed data to replace owned data, usually by cloning. Read more
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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.
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fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

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

Performs the conversion.