Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Halaman ini akan memandu Anda membersihkan Google Cloud resource yang Anda buat untuk melatih model klasifikasi gambar dan menyajikan prediksi dari model tersebut.
Setiap halaman mengasumsikan bahwa Anda telah menjalankan petunjuk dari
halaman tutorial sebelumnya.
Bagian selanjutnya dari dokumen ini mengasumsikan bahwa Anda menggunakan lingkungan
Cloud Shell yang sama dengan yang Anda buat saat mengikuti halaman pertama tutorial
ini. Jika sesi Cloud Shell asli Anda tidak lagi
terbuka, Anda dapat kembali ke lingkungan dengan melakukan tindakan berikut:
In the Google Cloud console, activate Cloud Shell.
Dalam sesi Cloud Shell, jalankan perintah berikut:
cdhello-custom-sample
Menghapus resource Vertex AI
Bagian ini menjelaskan cara menghapus semua resource Vertex AI
yang Anda buat untuk tutorial ini.
Membatalkan deployment model dari endpoint
Bagian ini menjelaskan cara membatalkan deployment model dari endpoint. Anda dapat
menganggap tindakan ini sebagai cara untuk memutuskan koneksi model dari endpoint.
Klik hello_custom untuk membuka halaman detail endpoint.
Di baris untuk model Anda, hello_custom, klik Batalkan deployment model
delete.
Pada dialog Batalkan deployment model dari endpoint, klik Batalkan deployment.
Menghapus endpoint
Sebelum menghapus endpoint, Anda harus membatalkan deployment model dari
endpoint. Setelah menghapus endpoint, Anda tidak akan
dapat menggunakan kembali nama endpoint tersebut hingga 7 hari.
Setelah Anda membatalkan deployment model dari endpoint, lakukan tindakan berikut
untuk menghapus endpoint:
Di konsol Google Cloud , di bagian Vertex AI, buka halaman Endpoints.
Temukan baris model, hello_custom. Pada baris tersebut, klik Tampilkan
lebih banyak more_vert. Lalu
klik Hapus model.
Pada dialog Hapus model, klik Hapus.
Menghapus tugas dan pipeline pelatihan kustom
Pipeline pelatihan dan tugas kustom Anda hanyalah catatan dari pelatihan
yang telah dijalankan sebelumnya. Jika Anda ingin menghapus tugas kustom, lakukan langkah berikut:
Di konsol Google Cloud , di bagian Vertex AI, buka halaman Training pipelines.
[[["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 2025-08-19 UTC."],[],[],null,["# Hello custom training: Clean up your project\n\nThis page guides you through cleaning up the Google Cloud resources that you\ncreated to train your image classification model and serve predictions from it.\nThis tutorial has several pages:\n\n\u003cbr /\u003e\n\n1. [Setting up your project and environment.](/vertex-ai/docs/tutorials/image-classification-custom)\n\n2. [Training a custom image classification\n model.](/vertex-ai/docs/tutorials/image-classification-custom/training)\n\n3. [Serving predictions from a custom image classification\n model.](/vertex-ai/docs/tutorials/image-classification-custom/serving)\n\n4. Cleaning up your project.\n\nEach page assumes that you have already performed the instructions from the\nprevious pages of the tutorial.\nThe rest of this document assumes that you are using the same Cloud Shell environment that you created when following the [first page of this\ntutorial](/vertex-ai/docs/tutorials/image-classification-custom). If your original Cloud Shell session is no longer open, you can return to the environment by doing the following:\n\n\u003cbr /\u003e\n\n1. In the Google Cloud console, activate Cloud Shell.\n\n [Activate Cloud Shell](https://console.cloud.google.com/?cloudshell=true)\n2. In the Cloud Shell session, run the following command:\n\n ```bash\n cd hello-custom-sample\n ```\n\nDelete Vertex AI resources\n--------------------------\n\nThis section describes how to delete all of the Vertex AI resources\nthat you created for this tutorial.\n\n### Undeploy your model from your endpoint\n\nThis section describes how to undeploy your model from your endpoint. You can\nthink about this action as a way of disconnecting your model from your endpoint.\n\nYou must follow this section before you can [delete your\nendpoint](#delete-endpoint) or [delete your model](#delete-model).\n\n1. In the Google Cloud console, in the Vertex AI section, go to\n the **Endpoints** page.\n\n [Go to Endpoints](https://console.cloud.google.com/vertex-ai/endpoints)\n2. Click `hello_custom` to go to the endpoint details page.\n\n3. On the row for your model, `hello_custom`, click **Undeploy model\n delete**.\n\n4. In the **Undeploy model from endpoint** dialog, click **Undeploy**.\n\n### Delete your endpoint\n\nBefore you delete an endpoint, you must [undeploy your model from your\nendpoint](#undeploy-model). After you've deleted your endpoint, you won't\nbe able to re-use that endpoint name for up to 7 days.\n\nAfter you've undeployed your model from the endpoint, do the following\nto delete your endpoint:\n\n1. In the Google Cloud console, in the Vertex AI section, go to\n the **Endpoints** page.\n\n [Go to Endpoints](https://console.cloud.google.com/vertex-ai/endpoints)\n2. Find your the row of your endpoint, `hello_custom`, again. On that row, click\n **View more more_vert** . Then click **Remove endpoint**.\n\n3. In the **Remove endpoint** dialog, click **Confirm**.\n\n### Delete your model\n\nBefore you follow this section, you must [undeploy your model from your\nendpoint](#undeploy-model). Afterward, do the following to delete your model:\n\n1. In the Google Cloud console, in the Vertex AI section, go to\n the **Models** page.\n\n [Go to Models](https://console.cloud.google.com/vertex-ai/models)\n2. Find your the row of your model, `hello_custom`. On that row, click **View\n more more_vert** . Then\n click **Delete model**.\n\n3. In the **Delete model** dialog, click **Delete**.\n\n### Delete your custom training pipeline and job\n\nYour training pipeline and custom job are just records of the training that\nhappened earlier. If you want to delete your custom job, do the following:\n\n1. In the Google Cloud console, in the Vertex AI section, go to\n the **Training pipelines** page.\n\n [Go to Training pipelines](https://console.cloud.google.com/vertex-ai/training/training-pipelines)\n2. Find your the row of your training pipeline, `hello_custom`. On that row,\n click **View more more_vert** . Then click **Delete training\n pipeline**.\n\n3. In the **Delete training job** dialog, click **Delete**.\n\n4. To go to the **Custom jobs** page, click **Custom job** in the\n Google Cloud console, or click the following link:\n\n [Go to Custom jobs](https://console.cloud.google.com/vertex-ai/training/custom-jobs)\n5. Find your the row of your custom job, `hello_custom-custom-job`. On that row,\n click **View more more_vert** . Then click **Delete custom job**.\n\n6. In the **Delete training job** dialog, click **Delete**.\n\nClean up your Cloud Shell session\n---------------------------------\n\nCloud Shell incurs no charges, and it [automatically deletes your home\ndisk after a period of inactivity](/shell/docs/limitations). However, if you\nplan to use Cloud Shell for other purposes in the near future, you\nmight want to manually remove the files that you created for this tutorial.\n\nIn your Cloud Shell session, run the following commands: \n\n cd ..\n rm -rf hello-custom-sample\n\nDelete your Cloud Storage bucket\n--------------------------------\n\nIn your Cloud Shell session, run the following command: \n\n gcloud storage rm gs://\u003cvar translate=\"no\"\u003eBUCKET_NAME\u003c/var\u003e --recursive --continue-on-error\n\nReplace \u003cvar translate=\"no\"\u003eBUCKET_NAME\u003c/var\u003e with the name of the Cloud Storage\nbucket that you created when reading the [first page of this\ntutorial](/vertex-ai/docs/tutorials/image-classification-custom).\n\nDelete your Cloud Run function\n------------------------------\n\nIn your Cloud Shell session, run the following command: \n\n gcloud functions delete classify_flower --region=us-central1 --quiet\n\nWhat's next\n-----------\n\n- To learn about additional ways to train ML models on Vertex AI,\n try one of the other [Vertex AI tutorials](/vertex-ai/docs/tutorials).\n\n- Read an [overview of how Vertex AI\n works](/vertex-ai/docs/start/introduction-unified-platform)."]]
