maxPool: Create a Maximum Pooling Layer for a CNN Architecture

In citoverse/cito: Building and Training Neural Networks

Create a Maximum Pooling Layer for a CNN Architecture

Description

This function creates a maxPool layer object of class citolayer for use in constructing a Convolutional Neural Network (CNN) architecture. The resulting layer object can be passed to the create_architecture function to define the structure of the network.

Usage

maxPool(kernel_size = NULL, stride = NULL, padding = NULL, dilation = NULL)

Arguments

kernel_size	(integer or tuple) The size of the kernel in this layer. Use a tuple if the kernel size varies across dimensions.
stride	(integer or tuple) The stride of the kernel in this layer. If NULL, the stride is set to the kernel size. Use a tuple if the stride differs across dimensions.
padding	(integer or tuple) The amount of zero-padding added to the input on both sides. Use a tuple if the padding differs across dimensions.
dilation	(integer or tuple) The dilation of the kernel in this layer. Use a tuple if the dilation varies across dimensions.

Details

This function creates a maxPool layer object, which represents a maximum pooling layer in a CNN architecture. Parameters not specified (and thus set to NULL) will be filled with default values provided to the create_architecture function.

Value

An S3 object of class "maxPool" "citolayer", representing a maximum pooling layer in the CNN architecture.

Author(s)

Armin Schenk

See Also

create_architecture

Examples

if(torch::torch_is_installed()){
library(cito)

# A maximum pooling layer where all available parameters are assigned
# No value will be overwritten by 'create_architecture()'
layer1 <- maxPool(3, 1, 0, 1)

# A maximum pooling layer where only the kernel size is assigned
# stride, padding and dilation are filled with the defaults
# passed to the 'create_architecture()' function
layer2 <- maxPool(kernel_size=4)
}

citoverse/cito documentation built on Jan. 16, 2025, 11:49 p.m.