选择容器映像

本页面可帮助您选择要使用的容器映像。

选择容器映像类型

每个容器映像都提供 Python 3 环境,并包含选定的数据科学框架(例如 PyTorch 或 TensorFlow)、Conda、GPU 映像的 NVIDIA 堆栈(CUDA、cuDNN、NCCL2)以及许多其他支持软件包和工具。如需查找所需的容器映像,请参阅下表。

以下 Deep Learning Containers 映像类型列表按框架类型进行组织。

框架 处理器 容器映像名称
基本 GPU gcr.io/deeplearning-platform-release/base-cu100
gcr.io/deeplearning-platform-release/base-cu101
gcr.io/deeplearning-platform-release/base-cu110
CPU gcr.io/deeplearning-platform-release/base-cpu
TensorFlow 企业版 2.x GPU gcr.io/deeplearning-platform-release/tf2-gpu.2-1
gcr.io/deeplearning-platform-release/tf2-gpu.2-3
gcr.io/deeplearning-platform-release/tf2-gpu.2-5
CPU gcr.io/deeplearning-platform-release/tf2-cpu.2-1
gcr.io/deeplearning-platform-release/tf2-cpu.2-3
gcr.io/deeplearning-platform-release/tf2-cpu.2-5
TensorFlow 企业版 1.x GPU gcr.io/deeplearning-platform-release/tf-gpu
gcr.io/deeplearning-platform-release/tf-gpu.1-15
CPU gcr.io/deeplearning-platform-release/tf-cpu
gcr.io/deeplearning-platform-release/tf-cpu.1-15
TensorFlow 2.x GPU gcr.io/deeplearning-platform-release/tf2-gpu
gcr.io/deeplearning-platform-release/tf2-gpu.2-0
gcr.io/deeplearning-platform-release/tf2-gpu.2-2
gcr.io/deeplearning-platform-release/tf2-gpu.2-4
CPU gcr.io/deeplearning-platform-release/tf2-cpu
gcr.io/deeplearning-platform-release/tf2-cpu.2-0
gcr.io/deeplearning-platform-release/tf2-cpu.2-2
gcr.io/deeplearning-platform-release/tf2-cpu.2-4
TensorFlow 1.x GPU gcr.io/deeplearning-platform-release/tf-gpu.1-13
gcr.io/deeplearning-platform-release/tf-gpu.1-14
CPU gcr.io/deeplearning-platform-release/tf-cpu.1-13
gcr.io/deeplearning-platform-release/tf-cpu.1-14
PyTorch GPU gcr.io/deeplearning-platform-release/pytorch-gpu
gcr.io/deeplearning-platform-release/pytorch-gpu.1-0
gcr.io/deeplearning-platform-release/pytorch-gpu.1-1
gcr.io/deeplearning-platform-release/pytorch-gpu.1-2
gcr.io/deeplearning-platform-release/pytorch-gpu.1-3
gcr.io/deeplearning-platform-release/pytorch-gpu.1-4
gcr.io/deeplearning-platform-release/pytorch-gpu.1-6
gcr.io/deeplearning-platform-release/pytorch-gpu.1-7
gcr.io/deeplearning-platform-release/pytorch-gpu.1-8
CPU gcr.io/deeplearning-platform-release/pytorch-cpu
gcr.io/deeplearning-platform-release/pytorch-cpu.1-0
gcr.io/deeplearning-platform-release/pytorch-cpu.1-1
gcr.io/deeplearning-platform-release/pytorch-cpu.1-2
gcr.io/deeplearning-platform-release/pytorch-cpu.1-3
gcr.io/deeplearning-platform-release/pytorch-cpu.1-4
PyTorch XLA TPU/GPU/CPU(实验性) gcr.io/deeplearning-platform-release/pytorch-xla.1-6
gcr.io/deeplearning-platform-release/pytorch-xla.1-7
gcr.io/deeplearning-platform-release/pytorch-xla.1-8
R CPU(实验性) gcr.io/deeplearning-platform-release/r-cpu
gcr.io/deeplearning-platform-release/r-cpu.4-0
Scikit-learn CPU(实验性) gcr.io/deeplearning-platform-release/sklearn-cpu
gcr.io/deeplearning-platform-release/sklearn-cpu.0-23
XGBoost CPU(实验性) gcr.io/deeplearning-platform-release/xgboost-cpu
gcr.io/deeplearning-platform-release/xgboost-cpu.1-1

TensorFlow 企业版容器映像

TensorFlow 企业版容器映像为您提供了经过 Google Cloud 优化的 TensorFlow 发行版,TensorFlow 企业版发行版的特定版本还提供长期版本支持。如需详细了解 TensorFlow 企业版,请参阅 TensorFlow 企业版概览

实验映像

某些 Deep Learning Containers 映像系列处于实验阶段,如映像系列表所示。实验性映像受到了最大程度的支持,并且在框架每次发布新版本时可能不会刷新。

列出所有可用的版本

如果您需要特定框架或 CUDA 版本,您可以搜索可用容器映像的完整列表。如需列出所有可用的 Deep Learning Containers 映像,请在首选终端的 gcloud 命令行工具中或在 Cloud Shell 中使用以下命令。

gcloud container images list --repository="gcr.io/deeplearning-platform-release"

在本地使用

您可以在本地拉取和使用 Deep Learning Containers。为此,请参阅本地 Deep Learning Containers 使用入门

后续步骤

  • 阅读 Deep Learning Containers 概览,详细了解容器映像中预安装的内容。
  • 逐步浏览方法指南,了解如何构建和推送深度学习容器映像,以开始使用 Deep Learning Containers。