get_pycox_optim: Get Pytorch Optimizer
In survivalmodels: Models for Survival Analysis

get_pycox_optim

R Documentation

Get Pytorch Optimizer

Description

Helper function to return a constructed pytorch optimizer from torch.optim.

Usage

get_pycox_optim(
  optimizer = "adam",
  net,
  rho = 0.9,
  eps = 1e-08,
  lr = 1,
  weight_decay = 0,
  learning_rate = 0.01,
  lr_decay = 0,
  betas = c(0.9, 0.999),
  amsgrad = FALSE,
  lambd = 1e-04,
  alpha = 0.75,
  t0 = 1e+06,
  momentum = 0,
  centered = TRUE,
  etas = c(0.5, 1.2),
  step_sizes = c(1e-06, 50),
  dampening = 0,
  nesterov = FALSE
)

Arguments

`optimizer`	`(character(1))` Optimizer, see details for list of implemented methods.
`net`	`(torch.nn.modules.module.Module)` Network architecture, can be built from build_pytorch_net.
`rho, lr, lr_decay`	`(numeric(1))` Passed to `adadelta`.
`eps`	`(numeric(1))` Passed to all methods except `asgd`, `rprop`, and `sgd`.
`weight_decay`	`(numeric(1))` Passed to all methods except `rprop` and `sparse_adam`.
`learning_rate`	`(numeric(1))` Passed to all methods except `adadelta`.
`betas`	`(numeric(2))` Passed to `adam`, `adamax`, `adamw`, and `sparse_adam`.
`amsgrad`	`(logical(1))` Passed to `adam` and `adamw`.
`lambd, t0`	`(numeric(1))` Passed to `asgd`.
`alpha`	`(numeric(1))` Passed to `asgd` and `rmsprop`.
`momentum`	`(numeric(1))` Passed to `rmsprop` and `sgd`.
`centered`	`(logical(1))` Passed to `rmsprop`.
`etas, step_sizes`	`(numeric(2))` Passed to `rprop`.
`dampening`	`(numeric(1))` Passed to `sgd`.
`nesterov`	`(logical(1))` Passed to `sgd`.