Trait collenchyma_nn::LRN

pub trait LRN<F>: NN<F> {
    fn new_lrn_config(
        &self, 
        n: u32, 
        alpha: f64, 
        beta: f64, 
        k: f64
    ) -> Result<Self::CLRN, Error>;
    fn lrn(
        &self, 
        x: &mut SharedTensor<F>, 
        result: &mut SharedTensor<F>, 
        config: &Self::CLRN
    ) -> Result<(), Error>;
    fn lrn_plain(
        &self, 
        x: &SharedTensor<F>, 
        result: &mut SharedTensor<F>, 
        config: &Self::CLRN
    ) -> Result<(), Error>;
    fn lrn_grad(
        &self, 
        x: &mut SharedTensor<F>, 
        x_diff: &mut SharedTensor<F>, 
        result: &mut SharedTensor<F>, 
        result_diff: &mut SharedTensor<F>, 
        config: &Self::CLRN
    ) -> Result<(), Error>;
    fn lrn_grad_plain(
        &self, 
        x: &SharedTensor<F>, 
        x_diff: &SharedTensor<F>, 
        result: &SharedTensor<F>, 
        result_diff: &mut SharedTensor<F>, 
        config: &Self::CLRN
    ) -> Result<(), Error>;
}

Provides the functionality for a Backend to support Local Response Normalization operations.

Required Methods

fn new_lrn_config(
    &self,
    n: u32,
    alpha: f64,
    beta: f64,
    k: f64
) -> Result<Self::CLRN, Error>

Creates a new (Local Response Normalization) LRNConfig, which needs to be passed to further LRN Operations.

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

Computes a LRN over the input Tensor x with complete memory management.

Saves the result to result.

For a no-memory managed version see lrn_plain.

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

Computes the LRN over the input Tensor x without any memory management.

Saves the result to result.

Attention:
For a correct computation result, you need to manage the memory allocation and synchronization yourself.
For a memory managed version see lrn.

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

Computes the gradient of a LRN over the input Tensor x with complete memory management.

Saves the result to result_diff.

For a no-memory managed version see lrn_grad_plain.

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

Computes the gradient of a LRN over the input Tensor x without any memory management.

Saves the result to result_diff.

Attention:
For a correct computation result, you need to manage the memory allocation and synchronization yourself.
For a memory managed version see lrn_grad.

Implementors

• impl LRN<f32> for Backend<Cuda>
• impl LRN<f64> for Backend<Cuda>