Pelatihan kustom Vertex AI TensorBoard dengan container kustom: Notebook
Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Dalam tutorial ini, Anda akan mempelajari cara membuat tugas pelatihan kustom menggunakan container kustom, lalu memantau proses pelatihan Anda di Vertex AI TensorBoard secara mendekati real-time.
Notebook: Membuat tugas pelatihan kustom menggunakan container kustom
Tutorial ini menggunakan layanan dan resource ML Google Cloud berikut:
Vertex AI Training
Vertex AI TensorBoard
Langkah-langkah yang dilakukan meliputi:
Buat repositori dan konfigurasi Docker.
Buat image container kustom dengan kode pelatihan yang disesuaikan.
Siapkan akun layanan dan bucket Cloud Storage.
Buat dan luncurkan tugas pelatihan kustom Anda dengan container kustom.
[[["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,["# Vertex AI TensorBoard custom training with custom container: Notebook\n\nIn this tutorial, you learn how to create a custom training job using custom\ncontainers, and monitor your training process on Vertex AI TensorBoard\nin near real time.\n\nNotebook: Create custom training jobs using custom containers\n-------------------------------------------------------------\n\n| To see an example of tensorboard custom training with custom container,\n| run the \"Vertex AI TensorBoard custom training with custom container\" notebook in one of the following\n| environments:\n|\n| [Open in Colab](https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/tensorboard/tensorboard_custom_training_with_custom_container.ipynb)\n|\n|\n| \\|\n|\n| [Open in Colab Enterprise](https://console.cloud.google.com/vertex-ai/colab/import/https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Ftensorboard%2Ftensorboard_custom_training_with_custom_container.ipynb)\n|\n|\n| \\|\n|\n| [Open\n| in Vertex AI Workbench](https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Ftensorboard%2Ftensorboard_custom_training_with_custom_container.ipynb)\n|\n|\n| \\|\n|\n| [View on GitHub](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/tensorboard/tensorboard_custom_training_with_custom_container.ipynb)\n\nThis tutorial uses the following Google Cloud ML services and resources:\n\n- Vertex AI training\n- Vertex AI TensorBoard\n\nThe steps performed include:\n\n- Create a Docker repository and config.\n- Create a custom container image with your customized training code.\n- Set up a service account and Cloud Storage buckets.\n- Create and launch your custom training job with your custom container.\n\nRelevant content\n----------------\n\n- [Vertex AI TensorBoard](/vertex-ai/docs/experiments/tensorboard-introduction)\n- [Custom training](/vertex-ai/docs/training/overview)"]]
