Struct neuro::layers::MaxPool2D

pub struct MaxPool2D { /* fields omitted */ }

Defines a 2D max pooling layer.

Methods

impl MaxPool2D

pub fn new(pool_size: (u64, u64)) -> Box<MaxPool2D>

Creates a 2D max pooling layer.

By default, the horizontal and vertical strides are set to the height and width of the pooling window.

Arguments

• pool_size - The height and width of the pooling window.

pub fn with_param(pool_size: (u64, u64), stride: (u64, u64)) -> Box<MaxPool2D>

Creates a 2D max pooling layer with the specified parameters.

Arguments

• pool_size - The height and width of the moving window.
• stride - The vertical and horizontal stride.

Trait Implementations

impl Display for MaxPool2D

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

Formats the value using the given formatter.

impl Layer for MaxPool2D

fn name(&self) -> &str

Returns the name of the layer.

fn initialize_parameters(&mut self, input_shape: Dim4)

Initializes the parameters of the layer.

fn compute_activation(&self, input: &Tensor) -> Tensor

Computes the activation of the layer during the forward pass.

fn compute_activation_mut(&mut self, input: &Tensor) -> Tensor

Computes the forward pass and stores intermediate values for efficient backpropagation.

fn compute_dactivation_mut(&mut self, input: &Tensor) -> Tensor

Computes the backward pass through the layer.

fn output_shape(&self) -> Dim

Returns the shape of the output.

fn save(&self, group: &Group, layer_number: usize) -> Result<(), Error>

Writes the parameters of the layer in the HDF5 group.

fn parameters(&self) -> Option<Vec<&Tensor>>

Returns the trainable parameters of the layer.

fn parameters_mut(&mut self) -> Option<(Vec<&mut Tensor>, Vec<&Tensor>)>

Returns the trainable parameters of the layer and their derivatives.

fn set_regularizer(&mut self, _regularizer: Option<Regularizer>)

Sets the regularizer for the layer.

fn print(&self)

Displays the properties of the layer.