Updated on 2024-10-29 GMT+08:00

Preset Dedicated Images in Notebook Instances

ModelArts DevEnviron provides Docker container images, which can run as preset containers. Certain preset images are built on common AI engine frameworks such as PyTorch, TensorFlow, and MindSpore. These images are named using the AI engines. Additionally, many common packages are preset in these images, relieving you from the package installation.

The images preset in ModelArts DevEnviron include:

  • Typical preset packages: AI engines based on standard Conda, data analysis software packages such as Pandas and Numpy, and tool software such as CUDA and cuDNN are included to meet your needs.
  • Preset Conda environments: A Conda environment and basic Conda Python (excluding any AI engine) are created for each preset image. The following figure shows the Conda environment for a preset MindSpore image.

    Select a Conda environment based on whether MindSpore is used for debugging.

  • Notebook: a web application that enables you to code on the GUI and combine the code, mathematical equations, and visualized content into a document.
  • JupyterLab plug-ins: enable flavor changing, case sharing to AI Gallery for communication, and instance stopping to improve user experience.
  • Remote SSH: allows you to remotely start and debug a notebook instance from a local PC.
  • Images preset in ModelArts DevEnviron: After these preset images support function development, the custom images created based on these preset images can be directly used for ModelArts training jobs.
Table 1 Preset x86 images

Engine

Image

PyTorch

pytorch1.8-cuda10.2-cudnn7-ubuntu18.04

pytorch1.10-cuda10.2-cudnn7-ubuntu18.04

pytorch1.4-cuda10.1-cudnn7-ubuntu18.04

Tensorflow

tensorflow2.1-cuda10.1-cudnn7-ubuntu18.04

tensorflow1.13-cuda10.0-cudnn7-ubuntu18.04

MindSpore

mindspore1.7.0-cuda10.1-py3.7-ubuntu18.04

mindspore1.7.0-py3.7-ubuntu18.04

mindspore1.2.0-cuda10.1-cudnn7-ubuntu18.04

mindspore1.2.0-openmpi2.1.1-ubuntu18.04

No AI engine (base images dedicated for image customization)

conda3-cuda10.2-cudnn7-ubuntu18.04

conda3-ubuntu18.04

x86-powered TensorFlow Base Images

TensorFlow contains two types of images:

x86-powered Custom Dedicated Base Images

ModelArts provides the following notebook base images powered by custom images (x86): conda3-cuda10.2-cudnn7-ubuntu18.04 and conda3-ubuntu18.04. These images do not have AI engines or related software packages. The image size is only 2 GB to 5 GB. You can use these images as base images and install your desired engine and dependency packages, improving scalability. In addition, these images are preset with some configurations required for starting the development environment. You can use these images after installing required software packages, without the need for any adaptations.

Such images are the most basic ones and have no component installed. They are small enough to facilitate image customization. If you need to use the OBS SDK, use ModelArts SDK instead to copy files. For details, see Transferring Files.