Struct AdaptiveAvgPool3D

pub struct AdaptiveAvgPool3D<F: Float + Debug + Send + Sync> { /* private fields */ }

3D Adaptive Average Pooling layer

Applies average pooling with adaptive output size for 3D data. The output size is specified, and the pooling kernel size and stride are computed automatically.

Implementations

impl<F: Float + Debug + ScalarOperand + Send + Sync + 'static> AdaptiveAvgPool3D<F>

pub fn new( output_size: (usize, usize, usize), name: Option<&str>, ) -> Result<Self>

Create a new adaptive average pooling layer for 3D data

Trait Implementations

impl<F: Float + Debug + ScalarOperand + Send + Sync + 'static> Layer<F> for AdaptiveAvgPool3D<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 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

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