TensorBoard Usage
Learn how to use TensorBoard to visualize model training processes, model structure, and data distribution.
Introduction
TensorBoard is a visualization tool for TensorFlow. It can visualize the model's training process, model structure, data distribution, and other details, helping users better understand and debug their models.
Precautions
TensorBoard is used to visualize the model's training process, model structure, data distribution, and other details, helping users better understand and debug their models.
To use TensorBoard, users must ensure that logs are written to the path specified by the TENSORBOARD_LOG_PATH environment variable. TensorBoard will automatically read data from the corresponding directory.
Procedure
- On the container list page, locate the desired container instance.
- Click More Actions on the right side of the row for that instance, and select TensorBoard.
- The TensorBoard window will pop up, allowing you to view the logs.
Notice
If the TensorBoard page does not open, check if your browser's pop-up blocker is disabled.