Trait collenchyma_nn::Sigmoid
[−]
[src]
pub trait Sigmoid<F>: NN<F> { fn sigmoid(
&self,
x: &mut SharedTensor<F>,
result: &mut SharedTensor<F>
) -> Result<(), Error>; fn sigmoid_plain(
&self,
x: &SharedTensor<F>,
result: &mut SharedTensor<F>
) -> Result<(), Error>; fn sigmoid_grad(
&self,
x: &mut SharedTensor<F>,
x_diff: &mut SharedTensor<F>,
result: &mut SharedTensor<F>,
result_diff: &mut SharedTensor<F>
) -> Result<(), Error>; fn sigmoid_grad_plain(
&self,
x: &SharedTensor<F>,
x_diff: &SharedTensor<F>,
result: &SharedTensor<F>,
result_diff: &mut SharedTensor<F>
) -> Result<(), Error>; }
Provides the functionality for a Backend to support Sigmoid operations.
Required Methods
fn sigmoid(
&self,
x: &mut SharedTensor<F>,
result: &mut SharedTensor<F>
) -> Result<(), Error>
&self,
x: &mut SharedTensor<F>,
result: &mut SharedTensor<F>
) -> Result<(), Error>
Computes the Sigmoid function over the input Tensor x
with complete memory management.
Saves the result to result
.
For a no-memory managed version see sigmoid_plain
.
fn sigmoid_plain(
&self,
x: &SharedTensor<F>,
result: &mut SharedTensor<F>
) -> Result<(), Error>
&self,
x: &SharedTensor<F>,
result: &mut SharedTensor<F>
) -> Result<(), Error>
Computes the Sigmoid function 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 sigmoid
.
fn sigmoid_grad(
&self,
x: &mut SharedTensor<F>,
x_diff: &mut SharedTensor<F>,
result: &mut SharedTensor<F>,
result_diff: &mut SharedTensor<F>
) -> Result<(), Error>
&self,
x: &mut SharedTensor<F>,
x_diff: &mut SharedTensor<F>,
result: &mut SharedTensor<F>,
result_diff: &mut SharedTensor<F>
) -> Result<(), Error>
Computes the gradient of a Sigmoid function over the input Tensor x
with complete memory management.
Saves the result to result_diff
.
For a no-memory managed version see sigmoid_grad_plain
.
fn sigmoid_grad_plain(
&self,
x: &SharedTensor<F>,
x_diff: &SharedTensor<F>,
result: &SharedTensor<F>,
result_diff: &mut SharedTensor<F>
) -> Result<(), Error>
&self,
x: &SharedTensor<F>,
x_diff: &SharedTensor<F>,
result: &SharedTensor<F>,
result_diff: &mut SharedTensor<F>
) -> Result<(), Error>
Computes the gradient of a Sigmoid function 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 sigmoid_grad
.