Enum coaster_nn::RnnInputMode

pub enum RnnInputMode {
    LinearInput,
    SkipInput,
}

Input Modes for RNN [cudnnRNNInputMode_t][1] [1]: https://docs.nvidia.com/deeplearning/sdk/cudnn-api/index.html#cudnnRNNInputMode_t

Variants

LinearInput

CUDNN_LINEAR_INPUT - A biased matrix multiplication is performed at the input of the first recurrent layer

SkipInput

CUDNN_SKIP_INPUT - No operation is performed at the input of the first recurrent layer - if this is used then the leading dimension of the input tensor must be equal to the hidden state size of the network.

Implementations

impl RnnInputMode

pub fn from_string(input: &str) -> Result<Self, &str>

Convert to RnnInputMode from String Representation

Trait Implementations

impl Clone for RnnInputMode

fn clone(&self) -> RnnInputMode

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for RnnInputMode

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

Formats the value using the given formatter.

impl Display for RnnInputMode

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

Formats the value using the given formatter.

impl PartialEq for RnnInputMode

fn eq(&self, other: &RnnInputMode) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Copy for RnnInputMode

impl Eq for RnnInputMode

impl StructuralPartialEq for RnnInputMode