Menyiapkan Vertex AI Experiments

Eksperimen Vertex AI didukung oleh Agent Platform SDK untuk Python dan Google Cloud konsol. Eksperimen Vertex AI memerlukan dan bergantung pada Vertex ML Metadata.

Siapkan

Login keakun Anda. Google Cloud Jika Anda baru menggunakan Google Cloud, buat akun untuk mengevaluasi performa produk kami dalam skenario dunia nyata. Pelanggan baru juga mendapatkan kredit gratis senilai $300 untuk menjalankan, menguji, dan men-deploy workload.

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

Roles required to select or create a project

• Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
• Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

Go to project selector

Verify that billing is enabled for your Google Cloud project.

Enable the required API.

Roles required to enable APIs

To enable APIs, you need the Service Usage Admin IAM role (roles/serviceusage.serviceUsageAdmin), which contains the serviceusage.services.enable permission. Learn how to grant roles.

Enable the API

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

Roles required to select or create a project

• Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
• Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

Go to project selector

Verify that billing is enabled for your Google Cloud project.

Enable the required API.

Roles required to enable APIs

To enable APIs, you need the Service Usage Admin IAM role (roles/serviceusage.serviceUsageAdmin), which contains the serviceusage.services.enable permission. Learn how to grant roles.

Enable the API

1. Membuat akun layanan. Lihat Membuat akun layanan dengan izin yang diperlukan.
2. Instal Agent Platform SDK untuk Python.
3. Periksa keberadaan Penyimpanan Metadata default di project Anda. (wajib)
   • Untuk melihat apakah project Anda memiliki default Penyimpanan Metadata, buka halaman Metadata di Google Cloud konsol.
   • Jika Penyimpanan Metadata default tidak ada, Penyimpanan Metadata tersebut akan dibuat saat
     • Anda menjalankan PipelineJob pertama,
     • atau, buat eksperimen pertama Anda di Agent Platform SDK untuk Python.
       Opsional: Untuk mengonfigurasi dengan CMEK, lihat Mengonfigurasi penyimpanan metadata project.

Lokasi yang Didukung

Tabel Ketersediaan fitur mencantumkan lokasi yang tersedia untuk Eksperimen Vertex AI. Saat menggunakan Agent Platform Pipelines atau Vertex AI TensorBoard, keduanya harus berada di lokasi yang sama dengan eksperimen Agent Platform Anda.

Langkah berikutnya

• Membuat eksperimen

Tutorial notebook yang relevan

1. Membandingkan model yang dilatih dan dievaluasi
2. Pelatihan model dengan kode prapemrosesan data bawaan
3. Membandingkan operasi pipeline
4. Autologging