README.md

In madgrad: 'MADGRAD' Method for Stochastic Optimization

madgrad

The Madgrad package is an R port of the original madgrad by Aaron Defazio and Samy Jelassi. See the Arxiv paper for details on the method.

Installation

Madgrad is not yet on CRAN. The development version from GitHub can be installed with:

# install.packages("devtools")
devtools::install_github("mlverse/madgrad")

Example

This is a small example showing how to use madgrad with torch to minimize a function, of course, madgrad is not the best algorithm for this task and should work better for neural network training.

library(madgrad)
library(torch)

torch_manual_seed(1)

f <- function(x, y) {
  log((1.5 - x + x*y)^2 + (2.25 - x - x*(y^2))^2 + (2.625 - x + x*(y^3))^2)
}

x <- torch_tensor(-5, requires_grad = TRUE)
y <- torch_tensor(-2, requires_grad = TRUE)

opt <- optim_madgrad(params = list(x, y), lr = 0.1)

for (i in 1:100) {
  opt$zero_grad()
  z <- f(x, y)
  z$backward()
  opt$step()
}
x
#> torch_tensor
#>  2.2882
#> [ CPUFloatType{1} ]
y
#> torch_tensor
#>  0.2412
#> [ CPUFloatType{1} ]

madgrad documentation built on May 10, 2021, 9:08 a.m.