Struct ThreadSafeRNN

pub struct ThreadSafeRNN<F: Float + Debug + Send + Sync> {
    pub input_size: usize,
    pub hidden_size: usize,
    pub activation: RecurrentActivation,
    /* private fields */
}

Thread-safe version of RNN for sequence processing

This implementation replaces RefCell with Arc<RwLock<>> for thread safety.

Fields

input_size: usize

Input size (number of input features)

hidden_size: usize

Hidden size (number of hidden units)

activation: RecurrentActivation

Activation function

Implementations

impl<F: Float + Debug + Send + Sync + ScalarOperand + 'static> ThreadSafeRNN<F>

pub fn new<R: Rng>( input_size: usize, hidden_size: usize, activation: RecurrentActivation, rng: &mut R, ) -> Result<Self>

Create a new thread-safe RNN layer

Trait Implementations

impl<F: Float + Debug + ScalarOperand + Send + Sync + 'static> Layer<F> for ThreadSafeRNN<F>

fn forward(&self, input: &Array<F, IxDyn>) -> Result<Array<F, IxDyn>>

Forward pass of the layer

fn backward( &self, input: &Array<F, IxDyn>, _grad_output: &Array<F, IxDyn>, ) -> Result<Array<F, IxDyn>>

Backward pass of the layer to compute gradients

fn update(&mut self, learning_rate: F) -> Result<()>

Update the layer parameters with the given gradients

fn as_any(&self) -> &dyn Any

Get the layer as a dyn Any for downcasting

fn as_any_mut(&mut self) -> &mut dyn Any

Get the layer as a mutable dyn Any for downcasting

fn params(&self) -> Vec<Array<F, IxDyn>>

Get the parameters of the layer

fn gradients(&self) -> Vec<Array<F, IxDyn>>

Get the gradients of the layer parameters

fn set_gradients(&mut self, _gradients: &[Array<F, IxDyn>]) -> Result<()>

Set the gradients of the layer parameters

fn set_params(&mut self, _params: &[Array<F, IxDyn>]) -> Result<()>

Set the parameters of the layer

fn set_training(&mut self, _training: bool)

Set the layer to training mode (true) or evaluation mode (false)

fn is_training(&self) -> bool

Get the current training mode

fn layer_type(&self) -> &str

Get the type of the layer (e.g., “Dense”, “Conv2D”)

fn parameter_count(&self) -> usize

Get the number of trainable parameters in this layer

fn layer_description(&self) -> String

Get a detailed description of this layer