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.
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.
Value
An S3 object of class "maxPool" "citolayer", representing a maximum pooling layer in the CNN architecture.
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.
Examples
# \donttest{
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)
}
# }