Struct dfdx::nn::TransformerDecoder

pub struct TransformerDecoder<const M: usize, const N: usize, const I: usize, const L: usize, const H: usize> where
    Assert<{ _ }>: ConstTrue, {
    pub blocks: [TransformerDecoderBlock<M, N, I, M, H>; L],
}

Requires Nightly A transformer decoder.

Generics

• M The embedding size of token vectors.
• N The size of encoder vectors.
• I The inner size of the feedforward layers.
• L The number of layers.
• H The number of heads for self attention. TODO: Doctests

Fields

blocks: [TransformerDecoderBlock<M, N, I, M, H>; L]

Trait Implementations

impl<const M: usize, const N: usize, const I: usize, const L: usize, const H: usize> CanUpdateWithGradients for TransformerDecoder<M, N, I, L, H> where
    Assert<{ _ }>: ConstTrue, 

fn update<G: GradientProvider>(
    &mut self,
    grads: &mut G,
    unused: &mut UnusedTensors
)

Updates self given the GradientProvider. When any parameters that are NOT present in G, then this function should add the tensor’s UniqueId to UnusedTensors.

impl<const M: usize, const N: usize, const I: usize, const L: usize, const H: usize> Debug for TransformerDecoder<M, N, I, L, H> where
    Assert<{ _ }>: ConstTrue, 

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

Formats the value using the given formatter.

impl<const M: usize, const N: usize, const I: usize, const L: usize, const H: usize> Default for TransformerDecoder<M, N, I, L, H> where
    Assert<{ _ }>: ConstTrue,
    [TransformerDecoderBlock<M, N, I, M, H>; L]: Default, 

fn default() -> Self

Returns the “default value” for a type.

impl<const M: usize, const N: usize, const I: usize, const L: usize, const H: usize, const S1: usize, const S2: usize, T: 'static + Tape> Module<(Tensor2D<S1, M, T>, Tensor2D<S2, N, T>)> for TransformerDecoder<M, N, I, L, H> where
    Assert<{ _ }>: ConstTrue,
    Assert<{ _ }>: ConstTrue,
    Assert<{ _ }>: ConstTrue,
    Assert<{ _ }>: ConstTrue, 

type Output = Tensor2D<S1, M, T>

The type that this unit produces given Input.

fn forward(
    &self,
    input: (Tensor2D<S1, M, T>, Tensor2D<S2, N, T>)
) -> Self::Output

Pass an Input through the unit and produce Self::Output. Can be implemented for multiple Input types.

fn forward_mut(&mut self, input: Input) -> Self::Output

Pass an Input through the unit and produce Self::Output. Can be implemented for multiple Input types.

impl<const M: usize, const N: usize, const I: usize, const L: usize, const H: usize, const S1: usize, const S2: usize, const B: usize, T: 'static + Tape> Module<(Tensor3D<B, S1, M, T>, Tensor3D<B, S2, N, NoneTape>)> for TransformerDecoder<M, N, I, L, H> where
    Assert<{ _ }>: ConstTrue,
    Assert<{ _ }>: ConstTrue,
    Assert<{ _ }>: ConstTrue,
    Assert<{ _ }>: ConstTrue, 

type Output = Tensor3D<B, S1, M, T>

The type that this unit produces given Input.

fn forward(
    &self,
    input: (Tensor3D<B, S1, M, T>, Tensor3D<B, S2, N>)
) -> Self::Output

Pass an Input through the unit and produce Self::Output. Can be implemented for multiple Input types.

fn forward_mut(&mut self, input: Input) -> Self::Output

Pass an Input through the unit and produce Self::Output. Can be implemented for multiple Input types.

impl<const M: usize, const N: usize, const I: usize, const L: usize, const H: usize> ResetParams for TransformerDecoder<M, N, I, L, H> where
    Assert<{ _ }>: ConstTrue, 

fn reset_params<R: Rng>(&mut self, rng: &mut R)

Mutate the unit’s parameters using rand::Rng. Each implementor of this trait decides how the parameters are initialized. In fact, some impls may not even use the rng.