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You can use either the Vertex AI SDK for Python or the Google Cloud console to create or delete an experiment. The SDK is a library of Python code that you can use to programmatically create and manage experiments. The console is a web-based user interface that you can use to create and manage experiments visually.
When creating an experiment using the Google Cloud console for the first time, be sure that there's adefault
Metadata Store. To check, go to your project's Metadata page in the Google Cloud console. See Configure your project's metadata store Create experiment with a TensorBoard instance Vertex AI SDK for Python
Create an experiment and, optionally, associate a Vertex AI TensorBoard instance using the Vertex AI SDK for Python. Add a description for the experiment to document its purpose. See init
in the Vertex AI SDK reference documentation.
experiment_name
: Provide a name for your experiment.experiment_description
: Provide a description for your experiment.experiment_tensorboard
: Optional. The Vertex TensorBoard instance to use as a backing TensorBoard for the provided experiment. If no experiment_tensorboard
is provided, a default TB instance is created and used by this experiment. Note: If CMEK (encryption keys) need to be associated with the TensorBoard instance, then experiment_tensorboard
is no longer optional.project
: . You can find these IDs in the Google Cloud console welcome page.location
: See List of available locations Be sure to use a region that supports TensorBoard if creating a TensorBoard instance.Use these instructions to create an experiment.
Create an experiment. Add a description for the experiment to document its purpose. See init
in the Vertex AI SDK reference documentation.
experiment_name
: Provide a name for your experiment.experiment_description
: Provide a description for your experiment.project
: . You can find these IDs in the Google Cloud console welcome page.location
: See List of available locations Be sure to use a region that supports TensorBoard if creating a TensorBoard instance.Deleting an experiment deletes that experiment and all experiment runs associated with the experiment. The Vertex AI TensorBoard experiment associated with the experiment is not deleted. To delete a TensorBoard experiment, see Delete outdated Vertex AI TensorBoard experiment.
Also, any pipeline runs, artifacts, and executions associated with the deleted experiment are not removed. These can be found in the Google Cloud console. For artifacts and executions, a $10/GB monthly charge is handled by the Vertex ML Metadata service.
Vertex AI SDK for PythonThe following sample uses the delete
method from the ExperimentClass
.
experiment_name
: Provide a name for your experiment.project
: . You can find these IDs in the Google Cloud console welcome page.location
: See List of available locationsdelete_backing_tensorboard_runs
: If True will also delete the Vertex AI TensorBoard runs associated with the experiment runs under this experiment that we used to store time series metrics.Use the following instructions to delete an experiment.
In the Google Cloud console, in the Vertex AI section, go to the Experiments page.
Check to be sure you are in the correct project.
A list of experiments for your project appears in the Experiment tracking view.
If you associated a Vertex AI TensorBoard instance with your experiment it shows up in the list as "your-experiment Backing TensorBoard Experiment".
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2025-08-07 UTC.
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