The tensorboard_pr_curve.py example demonstrates the integration of ClearML into code that uses TensorFlow and TensorBoard.
The example script does the following:
- Creates three classes, R, G, and B, and generates colors within the RGB space from normal distributions. The true label of each random color is associated with the normal distribution that generated it.
- Computes the probability that each color belongs to the class, using three other normal distributions.
- Generate PR curves using those probabilities.
- Creates a summary per class using tensorboard.plugins.pr_curve.summary,
- Automatically logs the TensorBoard output, TensorFlow Definitions, and output to the console, using ClearML.
- When the script runs, Creates an experiment named
tensorboard pr_curve, which is associated with the
In the ClearML Web UI, the PR Curve summaries appear in the experiment's page under RESULTS > PLOTS.
- Blue PR curves
- Green PR curves
- Red PR curves
ClearML automatically logs TensorFlow Definitions. They appear in CONFIGURATIONS > HYPER PARAMETERS > TF_DEFINE.
All other console output appears in RESULTS > CONSOLE.