avgPool: This function creates an 'avgPool' layer object of class...

In citoverse/cito: Building and Training Neural Networks

This function creates an avgPool 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.

Description

This function creates an avgPool 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

avgPool(kernel_size = NULL, stride = NULL, padding = NULL)

Arguments

kernel_size	(integer or tuple) The size of the kernel in this layer. Use a tuple if the kernel size differs 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.

Details

This function creates an avgPool layer object, which represents an average 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 "avgPool" "citolayer", representing an average pooling layer in the CNN architecture.

Author(s)

Armin Schenk

See Also

create_architecture

Examples

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

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

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

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