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O Deep Learning VM Images é um conjunto de
imagens de máquina virtual otimizadas para tarefas de ciência de dados e
machine learning. Todas essas imagens vêm com os principais frameworks e ferramentas de ML
pré-instalados. É possível usá-los imediatamente em instâncias com
GPUs para acelerar as tarefas de processamento de dados.
As imagens de VM de aprendizado profundo podem aceitar muitas combinações
de framework e processador. Atualmente, há imagens compatíveis com o TensorFlow Enterprise,
o TensorFlow, o PyTorch e a computação de alto desempenho genérica, com versões para fluxos de trabalho somente de CPU e ativados para GPU.
As imagens são baseadas nos sistemas operacionais Debian 11 e Ubuntu 22.04
e podem ser
configuradas para incluir o seguinte:
Frameworks específicos (por exemplo, TensorFlow) e
pacotes de suporte.
Python 3.10 com os seguintes pacotes:
numpy
scipy
matplotlib
pandas
nltk
pillow
scikit-image
opencv-python
scikit-learn
muitos outros
Ambientes de notebook do JupyterLab para prototipagem rápida
Pacotes da Nvidia com o driver mais recente dela para instâncias com GPU:
CUDA 11.x e 12.x (a versão depende do framework)
CuDNN 7.x e NCCL 2.x (a versão depende da versão do CUDA)
Atualizações
Deep Learning VM Images são atualizadas regularmente com correções de bugs
e atualizações de pacotes. Consulte as notas de lançamento
para mais informações.
Suporte da comunidade
Faça uma pergunta sobre a VM de aprendizado profundo no Stack
Overflow
ou participe do grupo do Google
google-dl-platform
para conversar sobre esse recurso.
[[["Fácil de entender","easyToUnderstand","thumb-up"],["Meu problema foi resolvido","solvedMyProblem","thumb-up"],["Outro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Informações incorretas ou exemplo de código","incorrectInformationOrSampleCode","thumb-down"],["Não contém as informações/amostras de que eu preciso","missingTheInformationSamplesINeed","thumb-down"],["Problema na tradução","translationIssue","thumb-down"],["Outro","otherDown","thumb-down"]],["Última atualização 2025-08-17 UTC."],[[["\u003cp\u003eDeep Learning VM Images are pre-configured virtual machines optimized for data science and machine learning, with key ML frameworks and tools already installed.\u003c/p\u003e\n"],["\u003cp\u003eThese images support various framework and processor combinations, including TensorFlow, TensorFlow Enterprise, PyTorch, and high-performance computing, with options for CPU-only and GPU-enabled workflows.\u003c/p\u003e\n"],["\u003cp\u003eThe images include pre-installed packages like Python 3.10, popular data science libraries, and JupyterLab environments, and Nvidia drivers for GPU acceleration.\u003c/p\u003e\n"],["\u003cp\u003eDeep Learning VM Images are based on Debian 11 or Ubuntu 22.04 and are regularly updated with bug fixes and package updates.\u003c/p\u003e\n"],["\u003cp\u003eCommunity support for Deep Learning VM is available through Stack Overflow and the google-dl-platform Google group.\u003c/p\u003e\n"]]],[],null,["# Introduction to Deep Learning VM\n\nDeep Learning VM Images is a set of\nvirtual machine images optimized for data science and machine\nlearning tasks. All images come with key ML frameworks and tools\npre-installed. You can use them out of the box on instances with\nGPUs to accelerate your data processing tasks.\n\nDeep Learning VM images are available to support many combinations\nof framework and processor. There are currently images supporting\n[TensorFlow Enterprise](/tensorflow-enterprise/docs),\nTensorFlow, PyTorch, and generic high-performance computing,\nwith versions for both CPU-only and GPU-enabled workflows.\n\nTo see a list of frameworks available, see [Choosing an\nimage](/deep-learning-vm/docs/images).\n\nPre-installed packages\n----------------------\n\nImages are based on the Debian 11 and Ubuntu 22.04\noperating systems, and these images can be\nconfigured to include the following:\n\n- Specific frameworks (for example, TensorFlow) and\n supporting packages.\n\n- Python 3.10 with the following packages:\n\n - numpy\n - scipy\n - matplotlib\n - pandas\n - nltk\n - pillow\n - scikit-image\n - opencv-python\n - scikit-learn\n - many more\n- JupyterLab notebook environments for quick prototyping\n\n- Nvidia packages with the latest Nvidia driver for GPU-enabled instances:\n\n - CUDA 11.*x* and 12.*x* (the version depends on the framework)\n - CuDNN 7.*x* and NCCL 2.*x* (the version depends on the CUDA version)\n\nUpdates\n-------\n\nDeep Learning VM images are updated regularly with bug fixes\nand package updates. Check the [release notes](/deep-learning-vm/docs/release-notes)\nfor information about updates.\n\nCommunity support\n-----------------\n\nAsk a question about Deep Learning VM on [Stack\nOverflow](https://stackoverflow.com/questions/tagged/google-dl-platform)\nor join the\n[google-dl-platform](https://groups.google.com/forum/#!forum/google-dl-platform)\nGoogle group to discuss Deep Learning VM.\n\n[Learn more about getting support from the\ncommunity](/deep-learning-vm/docs/getting-support#get_support_from_the_community).\n\nWhat's next\n-----------\n\nTo get started using Deep Learning VM, create a new instance\n[using the Cloud Marketplace](/deep-learning-vm/docs/cloud-marketplace)\nor [using the command line](/deep-learning-vm/docs/cli)."]]
