tensorboard
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
| Arguments | Description |
|---|---|
| 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.
Value
URL for browsing TensorBoard (invisibly).