Struct NeuralIntegration 

pub struct NeuralIntegration<A: Float, D: Dimension> { /* private fields */ }

Neural network integration manager

Implementations

impl<A: Float + ScalarOperand + Debug + 'static + FromPrimitive + Sum + Send + Sync, D: Dimension + 'static> NeuralIntegration<A, D>

pub fn new(config: OptimizationConfig<A>) -> Self

Create a new neural integration manager

pub fn register_forward_hook<H>(&mut self, layerid: LayerId, hook: H)

where H: ForwardHook<A, D> + 'static,

Register a forward hook for a layer

pub fn register_backward_hook<H>(&mut self, layerid: LayerId, hook: H)

where H: BackwardHook<A, D> + 'static,

Register a backward hook for a layer

pub fn enable_gradient_accumulation(&mut self)

Enable gradient accumulation

pub fn disable_gradient_accumulation(&mut self) -> HashMap<ParamId, Array<A, D>>

Disable gradient accumulation and return accumulated gradients

pub fn forward_pass( &mut self, layerid: &LayerId, inputs: &[Array<A, D>], ) -> Result<Vec<Array<A, D>>>

Execute forward pass with hooks

pub fn backward_pass( &mut self, layerid: &LayerId, grad_outputs: &[Array<A, D>], ) -> Result<Vec<Array<A, D>>>

Execute backward pass with hooks

pub fn accumulate_gradients( &mut self, gradients: HashMap<ParamId, Array<A, D>>, ) -> Result<()>

Accumulate gradients for parameters

pub fn parameter_manager(&self) -> &ParameterManager<A, D>

Get parameter manager

pub fn parameter_manager_mut(&mut self) -> &mut ParameterManager<A, D>

Get mutable parameter manager

pub fn accumulation_count(&self) -> usize

Get accumulation count