Trait collenchyma_nn::LRN [−] [src]

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