LBBNN (version 0.1.2)

print.LBBNN_Net: Print summary of an LBBNN_Net object

Description

Provides a summary of a trained LBBNN_Net object. Includes the model type (input-skip or not), whether normalizing flows are used, module and sub-module structure, number of trainable parameters, and prior variance and inclusion probabilities for the weights.

Usage

# S3 method for LBBNN_Net
print(x, ...)

Value

Invisibly returns the input x.

Arguments

x

An object of class LBBNN_Net.

...

Further arguments passed to or from other methods.

Examples

# \donttest{ 
x<-torch::torch_randn(3,2) 
b <- torch::torch_rand(2)
y <- torch::torch_matmul(x,b)
train_data <- torch::tensor_dataset(x,y)
train_loader <- torch::dataloader(train_data,batch_size = 3,shuffle=FALSE)
problem<-'regression'
sizes <- c(2,1,1) 
inclusion_priors <-c(0.9,0.2) 
inclusion_inits <- matrix(rep(c(-10,10),2),nrow = 2,ncol = 2)
stds <- c(1.0,1.0)
model <- LBBNN_Net(problem,sizes,inclusion_priors,stds,inclusion_inits,flow = FALSE,
input_skip = TRUE)
print(model)
# }