This method provides a visual representation of the network architecture defined by an object of class citoarchitecture
, including information about each layer's configuration. It helps in understanding the structure of the architecture defined by create_architecture
.
Usage
# S3 method for class 'citoarchitecture'
plot(x, input_shape, output_shape = NULL, ...)
Arguments
- x
An object of class
citoarchitecture
, created bycreate_architecture
.- input_shape
A numeric vector specifying the dimensions of a single sample (e.g.,
c(3, 28, 28)
for an RGB image with height and width of 28 pixels). This argument is required for a detailed output.- output_shape
An integer specifying the number of nodes in the output layer. If
NULL
, no output layer is printed.- ...
Additional arguments (currently not used).
Examples
# \donttest{
if(torch::torch_is_installed()){
library(cito)
c1 <- conv(n_kernels = 8, kernel_size = 5)
c2 <- conv(n_kernels = 16, kernel_size = 3)
l <- linear(n_neurons = 100)
mP <- maxPool(kernel_size = 2)
architecture <- create_architecture(c1, c1, mP, c2, c2, mP, l,
default_dropout = list(linear=0.6, conv=0.4),
default_normalization = list(linear=TRUE),
default_activation = "selu")
# See how the finished CNN would look like for specific input and output shapes
plot(architecture, c(3,128,128), 10)
}
# }