TensorBoard Visualization Tool

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

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.

Value

URL for browsing TensorBoard (invisibly).

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.