Kebijakan dukungan framework Deep Learning Containers
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Deep Learning Containers memublikasikan container dan image virtual machine untuk menyederhanakan
konfigurasi workload machine learning (ML) Anda. Gambar ini berisi sistem operasi, framework ML, driver, dan library lainnya. Kami memublikasikan
image versi baru secara rutin untuk menyertakan patch, update keamanan, dan
fitur baru. Setiap image yang disediakan oleh Deep Learning Containers menyediakan dukungan untuk
versi minor tertentu dari framework ML.
Dengan demikian, Anda memiliki waktu untuk memperbarui dan menguji kode saat berpindah dari satu versi framework ke versi framework lainnya. Anda harus selalu menguji
tugas dan model Anda secara menyeluruh saat beralih ke versi framework baru, terlepas dari
apakah itu update besar atau kecil.
Untuk semua layanan, berlanggananlah ke halaman catatan rilis Deep Learning Containers
untuk mengetahui pengumuman tentang rilis versi baru untuk container, image, dan
framework Anda.
Mengamankan workload Anda di Deep Learning Containers merupakan tanggung jawab bersama. Meskipun
Deep Learning Containers secara rutin memublikasikan versi gambar baru untuk mengatasi
kerentanan keamanan, Anda bertanggung jawab atas tugas-tugas berikut:
Upgrade secara manual ke versi terbaru.
Memastikan bahwa Anda telah mengonfigurasi layanan dengan benar untuk menggunakan versi terbaru.
Selama periode yang didukung untuk versi framework ML, kami akan memublikasikan versi image baru secara rutin. Update dapat mencakup hal berikut:
Mem-patch update untuk framework yang didukung. Misalnya, jika kami mendukung TensorFlow 2.7, dan TensorFlow merilis 2.7.1 untuk mengatasi bug, kami akan merilis versi image baru.
Update keamanan untuk framework yang didukung.
Update yang tidak menyebabkan gangguan pada paket dan software lain yang diinstal pada image.
Update untuk dependensi yang telah mencapai akhir dukungan. Misalnya, jika suatu gambar memiliki Python 3.7 yang terinstal dan mencapai tanggal akhir dukungan, kami akan merilis versi image baru. Jika perubahan pada dependensi mungkin merupakan
perubahan yang dapat menyebabkan gangguan, kami akan memperbarui Pilih image container
untuk menunjukkan perubahan pada dependensi.
Setelah dipublikasikan, versi image tidak dapat diubah dan tidak berubah. Anda harus
selalu menggunakan versi image terbaru, karena versi yang lebih lama mungkin memiliki kerentanan
keamanan atau bug penting lainnya.
Jadwal kebijakan dukungan
Periode dukungan untuk setiap versi framework mengikuti jadwal ini:
Akhir patch dan tanggal dukungan: Setelah tanggal ini, Deep Learning Containers tidak
lagi memublikasikan versi image baru untuk versi framework tersebut. Resource yang ada
yang telah di-deploy ke Deep Learning Containers akan terus berfungsi.
Setelah tanggal ini, sebaiknya Anda beralih ke versi framework
yang lebih baru.
Untuk menerima dukungan pemecahan masalah dari Deep Learning Containers, Anda mungkin diminta
untuk mengupgrade ke versi framework yang berada dalam jangka waktu yang didukung.
Tanggal akhir ketersediaan: Setelah tanggal ini, Anda tidak dapat lagi menggunakan gambar
untuk versi framework ini. Layanan mungkin memblokir pembuatan resource baru
menggunakan image ini, dan image tersebut tidak akan lagi tersedia untuk didownload.
[[["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 2025-08-18 UTC."],[[["\u003cp\u003eDeep Learning Containers offers pre-configured container and virtual machine images to streamline machine learning workload setup, including the OS, ML frameworks, drivers, and libraries.\u003c/p\u003e\n"],["\u003cp\u003eNew image versions are regularly released by Deep Learning Containers to provide patches, security updates, and new features, always supporting a specific minor version of an ML framework.\u003c/p\u003e\n"],["\u003cp\u003eUsers are responsible for manually upgrading to the latest image versions and ensuring their services are configured to use them, as securing workloads is a shared responsibility.\u003c/p\u003e\n"],["\u003cp\u003eDuring the supported period of an ML framework, Deep Learning Containers regularly updates images with patches, security updates, non-breaking package updates, and dependency upgrades.\u003c/p\u003e\n"],["\u003cp\u003eEach framework version has an end-of-patch and support date after which new image versions are no longer published, as well as an end-of-availability date when those images are no longer usable.\u003c/p\u003e\n"]]],[],null,["# Deep Learning Containers framework support policy\n\nDeep Learning Containers publishes containers and virtual machine images to simplify the\nconfiguration of your machine learning (ML) workloads. These images contain the\noperating system, the ML frameworks, drivers, and other libraries. We publish\nnew versions of images regularly to include new patches, security updates, and\nfeatures. Each image provided by Deep Learning Containers provides support for a\nspecific minor version of an ML framework.\n\nThis allows you time to update and test your code\nwhen moving from one framework version to another. You should always test your\njobs and models thoroughly when switching to a new framework version, regardless\nof whether it's a major or minor update.\n\nFor all services, subscribe to the [Deep Learning Containers release notes](/deep-learning-containers/docs/release-notes) page\nfor announcements about new version releases for your containers, images, and\nframeworks.\n\nFor the list of supported framework versions, see [Choose a container image](/deep-learning-containers/docs/choosing-container#deciding).\n\nShared responsibility\n---------------------\n\nSecuring your workloads on Deep Learning Containers is a shared responsibility. While\nDeep Learning Containers regularly publishes new versions of images to address\nsecurity vulnerabilities, you are responsible for tasks such as the following:\n\n- Manually upgrading to the latest version.\n\n- Ensuring that you properly configured your services to use the latest version.\n\nFor more information, see [Shared responsibility](/deep-learning-containers/docs/shared-responsibility).\n\nSupport policy for framework versions\n-------------------------------------\n\nDuring the supported period for an ML framework version, we will publish new\nimage versions regularly. The updates may include the following:\n\n- Patch updates for supported frameworks. For example, if we support\n TensorFlow 2.7, and TensorFlow releases 2.7.1 to address bugs, we will\n release a new image version.\n\n- Security updates for supported frameworks.\n\n- Non-breaking updates to other packages and software installed on the image.\n\n- Updates to dependencies that have reached end-of-support. For example, if an\n image has Python 3.7 installed and it reaches the end-of-support date, we\n will release a new image version. If the change in dependency may be a\n breaking change, we will update [Choose a container image](/deep-learning-containers/docs/choosing-container#deciding)\n to indicate the change in the dependency.\n\nOnce published, an image version is immutable and does not change. You should\nalways use the latest image version, as older versions may have security\nvulnerabilities or other critical bugs.\n\n### Support policy schedule\n\nSupport periods for each framework version follows this schedule:\n\n- **End-of-patch and support date:** After this date, Deep Learning Containers will no\n longer publish new image versions for that framework version. Existing\n resources that have been deployed to Deep Learning Containers continue to function.\n After this date, we recommend you plan to switch to a more recent framework\n version.\n\n To receive troubleshooting support from Deep Learning Containers, you may be asked\n to upgrade to a framework version that is within the supported time period.\n- **End-of-availability date:** After this date, you can no longer use images\n for this framework version. Services may block the creation of new resources\n using these images, and the images will no longer be available for download.\n\nWhat's next\n-----------\n\n- Review the [list of supported framework versions](/deep-learning-containers/docs/choosing-container#deciding)."]]
