[[["์ดํดํ๊ธฐ ์ฌ์","easyToUnderstand","thumb-up"],["๋ฌธ์ ๊ฐ ํด๊ฒฐ๋จ","solvedMyProblem","thumb-up"],["๊ธฐํ","otherUp","thumb-up"]],[["์ดํดํ๊ธฐ ์ด๋ ค์","hardToUnderstand","thumb-down"],["์๋ชป๋ ์ ๋ณด ๋๋ ์ํ ์ฝ๋","incorrectInformationOrSampleCode","thumb-down"],["ํ์ํ ์ ๋ณด/์ํ์ด ์์","missingTheInformationSamplesINeed","thumb-down"],["๋ฒ์ญ ๋ฌธ์ ","translationIssue","thumb-down"],["๊ธฐํ","otherDown","thumb-down"]],["์ต์ข ์ ๋ฐ์ดํธ: 2024-11-22(UTC)"],[],[],null,["# Create or delete an experiment\n\nYou can use either the Vertex AI SDK for Python or the Google Cloud console to\ncreate or delete an experiment. The SDK is a library of Python code that you\ncan use to programmatically create and manage experiments. The console is a\nweb-based user interface that you can use to create and manage experiments\nvisually.\n| When creating an experiment using the Google Cloud console for the first time, be sure that there's a `default` Metadata Store. To check, go to your project's **Metadata** page in the Google Cloud console. See [Configure your project's metadata store](/vertex-ai/docs/ml-metadata/configure)\n\nCreate experiment with a TensorBoard instance\n---------------------------------------------\n\n### Vertex AI SDK for Python\n\n\nCreate an experiment and, optionally, associate a Vertex AI TensorBoard instance using\nthe Vertex AI SDK for Python. Add a description for the\nexperiment to document its purpose. See [`init`](/python/docs/reference/aiplatform/latest/google.cloud.aiplatform#google_cloud_aiplatform_init)\nin the Vertex AI SDK reference documentation. \n\n### Python\n\n from typing import Optional, Union\n\n from google.cloud import aiplatform\n\n\n def create_experiment_sample(\n experiment_name: str,\n experiment_description: str,\n experiment_tensorboard: Optional[Union[str, aiplatform.Tensorboard]],\n project: str,\n location: str,\n ):\n aiplatform.init(\n experiment=experiment_name,\n experiment_description=experiment_description,\n experiment_tensorboard=experiment_tensorboard,\n project=project,\n location=location,\n )\n\n- `experiment_name`: Provide a name for your experiment.\n- `experiment_description`: Provide a description for your experiment.\n- `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.\n- `project`: . You can find these IDs in the Google Cloud console [welcome](https://console.cloud.google.com/welcome) page. \n- `location`: See [List of available locations](/vertex-ai/docs/general/locations) Be sure to use a region that supports TensorBoard if creating a TensorBoard instance.\n\n### Google Cloud console\n\n\nUse these instructions to create an experiment.\n\n1. In the Google Cloud console, go to the **Experiments** page. \n [Go to Experiments](https://console.cloud.google.com/vertex-ai/experiments)\n2. Be sure you're in the project you want to create the experiment in. \n3. Click **add_box\n Create** to open the **Experiment** pane. The **Create experiment** pane appears.\n4. In the **Experiment name** field, provide a name to uniquely identify your experiment.\n5. Optional. In the **TensorBoard instance** field, select an instance from the drop-down or provide a name for your new TensorBoard instance.\n6. Click **Create** to create your experiment.\n\nCreate an experiment without a default TensorBoard instance\n-----------------------------------------------------------\n\n### Vertex AI SDK for Python\n\n\nCreate an experiment. Add a description for the\nexperiment to document its purpose. See [`init`](/python/docs/reference/aiplatform/latest/google.cloud.aiplatform#google_cloud_aiplatform_init)\nin the Vertex AI SDK reference documentation. \n\n### Python\n\n from google.cloud import aiplatform\n\n\n def create_experiment_without_default_tensorboard_sample(\n experiment_name: str,\n experiment_description: str,\n project: str,\n location: str,\n ):\n aiplatform.init(\n experiment=experiment_name,\n experiment_description=experiment_description,\n experiment_tensorboard=False,\n project=project,\n location=location,\n )\n\n- `experiment_name`: Provide a name for your experiment.\n- `experiment_description`: Provide a description for your experiment.\n- `project`: . You can find these IDs in the Google Cloud console [welcome](https://console.cloud.google.com/welcome) page. \n- `location`: See [List of available locations](/vertex-ai/docs/general/locations) Be sure to use a region that supports TensorBoard if creating a TensorBoard instance.\n\nDelete experiment\n-----------------\n\nDeleting an experiment deletes that experiment and all experiment runs\nassociated with the experiment. The Vertex AI TensorBoard experiment\nassociated with the experiment is not deleted. To delete a TensorBoard\nexperiment, see\n[Delete outdated Vertex AI TensorBoard experiment](/vertex-ai/docs/experiments/user-journey/uj-delete-outdated-tb-experiments).\n\nAlso, any pipeline runs, artifacts, and executions associated with the deleted\nexperiment are not removed. These can be found in the Google Cloud console.\nFor artifacts and executions, a $10/GB monthly charge is handled by the\nVertex ML Metadata service. \n\n### Vertex AI SDK for Python\n\nThe following sample uses the\n[`delete`](/python/docs/reference/aiplatform/latest/google.cloud.aiplatform.ExperimentRun#google_cloud_aiplatform_ExperimentRun_delete)\nmethod from the\n[`ExperimentClass`](/python/docs/reference/aiplatform/latest/google.cloud.aiplatform.ExperimentRun).\n\n### Python\n\n from google.cloud import aiplatform\n\n\n def delete_experiment_sample(\n experiment_name: str,\n project: str,\n location: str,\n delete_backing_tensorboard_runs: bool = False,\n ):\n experiment = aiplatform.Experiment(\n experiment_name=experiment_name, project=project, location=location\n )\n\n experiment.delete(delete_backing_tensorboard_runs=delete_backing_tensorboard_runs)\n\n- `experiment_name`: Provide a name for your experiment.\n- `project`: . You can find these IDs in the Google Cloud console [welcome](https://console.cloud.google.com/welcome) page.\n- `location`: See [List of available locations](/vertex-ai/docs/general/locations)\n- `delete_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.\n\n### Console\n\n\nUse the following instructions to delete an experiment.\n\n1. In the Google Cloud console, go to the **Experiments** page. \n [Go to Experiments](https://console.cloud.google.com/vertex-ai/experiments)\n2. Select the checkbox associated with the experiment you want to delete. The **Delete** option appears.\n3. Click **Delete** .\n - Alternatively, you can go to the more_vert options menu that is in the same row as the experiment and select **delete**.\n\nView list of experiments in Google Cloud console\n------------------------------------------------\n\n1. In the Google Cloud console, in the Vertex AI section, go to the\n **Experiments** page.\n\n [Go to the Experiments page](https://console.cloud.google.com/vertex-ai/experiments)\n2. Check to be sure you are in the correct project.\n\n3. A list of experiments for your project appears in\n the **Experiment tracking** view. \n\n If you associated a Vertex AI TensorBoard instance with your\n experiment it shows up in the list as \"*your-experiment* Backing\n TensorBoard Experiment\".\n\nWhat's next\n-----------\n\n- [Create and manage experiment runs](/vertex-ai/docs/experiments/create-manage-exp-run)\n- [Delete outdated Vertex AI TensorBoard experiment](/vertex-ai/docs/experiments/user-journey/uj-delete-outdated-tb-experiments)\n\n### Relevant notebook sample\n\n- [Model training with prebuilt data pre-processing code](/vertex-ai/docs/experiments/user-journey/uj-model-training)"]]