Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Anda dapat menggunakan Vertex AI SDK untuk Python atau konsol Google Cloud guna
membuat atau menghapus eksperimen. SDK adalah library kode Python yang dapat Anda gunakan untuk membuat dan mengelola eksperimen secara terprogram. Konsol adalah antarmuka pengguna berbasis web yang dapat Anda gunakan untuk membuat dan mengelola eksperimen secara visual.
Membuat eksperimen dengan instance TensorBoard
Vertex AI SDK untuk Python
Buat eksperimen dan kaitkan instance Vertex AI TensorBoard menggunakan
Vertex AI SDK untuk Python. Tambahkan deskripsi untuk eksperimen guna mendokumentasikan tujuannya. Lihat init
dalam dokumentasi referensi Vertex AI SDK.
experiment_name: Berikan nama untuk eksperimen Anda.
experiment_description: Berikan deskripsi untuk eksperimen Anda.
experiment_tensorboard:
Opsional. Instance Vertex TensorBoard yang akan digunakan
sebagai TensorBoard pendukung untuk eksperimen yang disediakan.
Jika experiment_tensorboard tidak disediakan, instance TB default
akan dibuat dan digunakan oleh eksperimen ini. Catatan: Jika CMEK (kunci enkripsi) perlu dikaitkan dengan instance TensorBoard, experiment_tensorboard tidak lagi opsional.
project: . Anda dapat menemukan ID ini di halaman sambutan Google Cloud console.
location: Lihat Daftar lokasi yang tersedia
Pastikan Anda menggunakan wilayah yang mendukung TensorBoard jika membuat instance TensorBoard.
Google Cloud console
Gunakan petunjuk ini untuk membuat eksperimen.
Di konsol Google Cloud , buka halaman Experiments. Buka Eksperimen
Pastikan Anda berada dalam project tempat eksperimen akan dibuat.
Klik add_box
Create untuk membuka panel Experiment. Panel Create experiment akan muncul.
Di kolom Nama eksperimen, berikan nama untuk mengidentifikasi eksperimen Anda secara unik.
Opsional. Di kolom TensorBoard instance, pilih instance dari drop-down atau berikan nama untuk instance TensorBoard yang baru.
Klik Create untuk membuat eksperimen.
Membuat eksperimen tanpa instance TensorBoard default
Vertex AI SDK untuk Python
Membuat eksperimen. Tambahkan deskripsi untuk eksperimen guna mendokumentasikan tujuannya. Lihat init
dalam dokumentasi referensi Vertex AI SDK.
experiment_name: Berikan nama untuk eksperimen Anda.
experiment_description: Berikan deskripsi untuk eksperimen Anda.
project: . Anda dapat menemukan ID ini di halaman sambutan Google Cloud console.
location: Lihat Daftar lokasi yang tersedia
Pastikan Anda menggunakan wilayah yang mendukung TensorBoard jika membuat instance TensorBoard.
Hapus eksperimen
Menghapus satu eksperimen akan menghapus eksperimen tersebut dan semua eksperimen yang berjalan terkait dengan eksperimen tersebut. Eksperimen Vertex AI TensorBoard
yang terkait dengan eksperimen tidak dihapus. Untuk menghapus eksperimen TensorBoard, lihat
Menghapus eksperimen Vertex AI TensorBoard yang usang.
Selain itu, semua operasi, artefak, dan eksekusi pipeline yang terkait dengan eksperimen yang dihapus tidak dihapus. Informasi ini dapat ditemukan di konsol Google Cloud .
Untuk artefak dan eksekusi, biaya bulanan sebesar $10/GB ditangani oleh layanan
Vertex ML Metadata.
delete_backing_tensorboard_runs: Jika True juga akan menghapus
operasi Vertex AI TensorBoard yang terkait dengan eksperimen
yang berjalan dalam eksperimen ini, yang kami gunakan untuk menyimpan metrik deret waktu.
Konsol
Gunakan petunjuk berikut untuk menghapus eksperimen.
Di konsol Google Cloud , buka halaman Experiments. Buka Eksperimen
Centang kotak yang terkait dengan eksperimen yang ingin Anda hapus. Opsi Delete akan muncul.
Klik Delete.
Atau, Anda dapat membuka menu opsi more_vert yang berada di baris yang sama dengan eksperimen dan memilih delete.
Melihat daftar eksperimen di konsol Google Cloud
Di konsol Google Cloud , di bagian Vertex AI, buka halaman
Experiments.
Periksa untuk memastikan Anda berada dalam project yang benar.
Daftar eksperimen untuk project Anda akan muncul di tampilan Pelacakan eksperimen.
Jika Anda mengaitkan instance Vertex AI TensorBoard dengan eksperimen, instance tersebut akan muncul dalam daftar sebagai "your-experiment Backing
TensorBoard Experiment".
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-09-04 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)"]]
