tensorboard: TensorBoard Visualization Tool
In tensorflow: R Interface to 'TensorFlow'

tensorboard

R Documentation

TensorBoard Visualization Tool

Description

TensorBoard is a tool inspecting and understanding your TensorFlow runs and graphs.

Usage

tensorboard(
  log_dir,
  action = c("start", "stop"),
  host = "127.0.0.1",
  port = "auto",
  launch_browser = getOption("tensorflow.tensorboard.browser", interactive()),
  reload_interval = 5,
  purge_orphaned_data = TRUE
)

Arguments

`log_dir`	Directories to scan for training logs. If this is a named character vector then the specified names will be used as aliases within TensorBoard.
`action`	Specify whether to start or stop TensorBoard (TensorBoard will be stopped automatically when the R session from which it is launched is terminated).
`host`	Host for serving TensorBoard
`port`	Port for serving TensorBoard. If "auto" is specified (the default) then an unused port will be chosen automatically.
`launch_browser`	Open a web browser for TensorBoard after launching. Defaults to `TRUE` in interactive sessions. When running under RStudio uses an RStudio window by default (pass a function e.g. `utils::browseURL()` to open in an external browser). Use the `tensorflow.tensorboard.browser` option to establish a global default behavior.
`reload_interval`	How often the backend should load more data.
`purge_orphaned_data`	Whether to purge data that may have been orphaned due to TensorBoard restarts. Disabling purge_orphaned_data can be used to debug data disappearance.

Details

When TensorBoard is passed a logdir at startup, it recursively walks the directory tree rooted at logdir looking for subdirectories that contain tfevents data. Every time it encounters such a subdirectory, it loads it as a new run, and the frontend will organize the data accordingly.

The TensorBoard process will be automatically destroyed when the R session in which it is launched exits. You can pass action = "stop" to manually terminate TensorBoard.