Trait coaster_nn::Dropout

pub trait Dropout<F>: NN<F> {
    // Required methods
    fn new_dropout_config(
        &self,
        dropout: f32,
        seed: u64
    ) -> Result<Self::CDROP, Error>;
    fn dropout(
        &self,
        x: &SharedTensor<F>,
        result: &mut SharedTensor<F>,
        config: &Self::CDROP
    ) -> Result<(), Error>;
    fn dropout_grad(
        &self,
        x: &SharedTensor<F>,
        x_diff: &SharedTensor<F>,
        result: &SharedTensor<F>,
        result_diff: &mut SharedTensor<F>,
        config: &Self::CDROP
    ) -> Result<(), Error>;
}

Provides the functionality for a Backend to support Dropout operations.

Required Methods

fn new_dropout_config( &self, dropout: f32, seed: u64 ) -> Result<Self::CDROP, Error>

Creates a new DropoutConfig, which needs to be passed to further dropout Operations.

fn dropout( &self, x: &SharedTensor<F>, result: &mut SharedTensor<F>, config: &Self::CDROP ) -> Result<(), Error>

Computes non-linear down-sampling ([max Pooling][pooling]) over the input Tensor x. [pooling]: https://en.wikipedia.org/wiki/Convolutional_neural_network#Pooling_layer

Saves the result to result.

fn dropout_grad( &self, x: &SharedTensor<F>, x_diff: &SharedTensor<F>, result: &SharedTensor<F>, result_diff: &mut SharedTensor<F>, config: &Self::CDROP ) -> Result<(), Error>

Computes non-linear down-sampling ([max Pooling][pooling]) over the input Tensor x. [pooling]: https://en.wikipedia.org/wiki/Dropout_(neural_networks)

Saves the result to result.

Object Safety

This trait is not object safe.

Implementations on Foreign Types

impl<T> Dropout<T> for Backend<Cuda>

where T: Float + Default + DataTypeInfo,

fn new_dropout_config( &self, probability: f32, seed: u64 ) -> Result<Self::CDROP, Error>

fn dropout( &self, x: &SharedTensor<T>, result: &mut SharedTensor<T>, config: &Self::CDROP ) -> Result<(), Error>

fn dropout_grad( &self, x: &SharedTensor<T>, x_diff: &SharedTensor<T>, result: &SharedTensor<T>, result_diff: &mut SharedTensor<T>, config: &Self::CDROP ) -> Result<(), Error>

impl<T> Dropout<T> for Backend<Native>

where T: Float + Add<T, Output = T> + Mul<T, Output = T> + Default + Copy + PartialOrd + Bounded,

fn new_dropout_config( &self, probability: f32, seed: u64 ) -> Result<Self::CDROP, Error>

fn dropout( &self, x: &SharedTensor<T>, result: &mut SharedTensor<T>, config: &Self::CDROP ) -> Result<(), Error>

fn dropout_grad( &self, x: &SharedTensor<T>, x_diff: &SharedTensor<T>, result: &SharedTensor<T>, result_diff: &mut SharedTensor<T>, config: &Self::CDROP ) -> Result<(), Error>

Implementors