luz_callback_tfevents: tfevents callback

In luz: Higher Level 'API' for 'torch'

tfevents callback

Description

Logs metrics and other model information in the tfevents file format. Assuming tensorboard is installed, result can be visualized with

Usage

luz_callback_tfevents(logdir = "logs", histograms = FALSE, ...)

Arguments

logdir	A directory to where log will be written to.
histograms	A boolean specifying if histograms of model weights should be logged. It can also be a character vector specifying the name of the parameters that should be logged (names are the same as names(model$parameters)).
...	Currently not used. For future expansion.

Details

tensorboard --logdir=logs

Examples

if (torch::torch_is_installed()) {
library(torch)
x <- torch_randn(1000, 10)
y <- torch_randn(1000, 1)

model <- nn_linear %>%
  setup(loss = nnf_mse_loss, optimizer = optim_adam) %>%
  set_hparams(in_features = 10, out_features = 1) %>%
  set_opt_hparams(lr = 1e-4)

tmp <- tempfile()

model %>% fit(list(x, y), valid_data = 0.2, callbacks = list(
  luz_callback_tfevents(tmp, histograms = TRUE)
))
}

luz documentation built on April 17, 2023, 5:08 p.m.