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 = interactive(),
reload_interval = 5, purge_orphaned_data = TRUE)unique_log_dir(log_dir = "logs")
Root directory for training logs.
Specify whether to start or stop TensorBoard for the
given log_dir (TensorBoard will be stopped automatically when
the R session from which it is launched is terminated).
Host for serving TensorBoard
Port for serving TensorBoard. If "auto" is specified (the default) then an unused port will be chosen automatically.
TRUE to open a web browser for TensorBoard
after launching.
How often the backend should load more 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.
URL for browsing TensorBoard (invisibly).
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 a TensorBoard process for a givenlog_dir`.