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
)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 |
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. |
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.
URL for browsing TensorBoard (invisibly).
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.