Introduction to AI Platform Deep Learning VM Image

Deep Learning VM images are virtual machine images optimized for data science and machine learning tasks. All images come with key ML frameworks and tools pre-installed, and you can use them out of the box on instances with GPUs to accelerate your data processing tasks.

Frameworks and processors

Deep Learning VM images are available to support many combinations of framework and processor. There are currently images supporting TensorFlow Enterprise, TensorFlow, PyTorch, and generic high-performance computing, with versions for both CPU-only and GPU-enabled workflows.

To see a list of frameworks available, see Choosing an image.

Pre-installed packages

Images are based on the Debian 10, Debian 9, and Ubuntu 18.04 operating systems, and can be configured to include:

  • Specific frameworks (for example, TensorFlow) and supporting packages.

  • Python 3.7 with the following packages:

    • numpy
    • scipy
    • matplotlib
    • pandas
    • nltk
    • pillow
    • scikit-image
    • opencv-python
    • scikit-learn
    • fairness-indicators for TensorFlow 2.3 and 2.4 Deep Learning VM instances
    • many more
  • JupyterLab notebook environments for quick prototyping

  • Nvidia packages with the latest Nvidia driver for GPU-enabled instances:

    • CUDA 9.*, 10.*, and 11.* (the version depends on the framework)
    • CuDNN 7.* and NCCL 2.* (the version depends on the CUDA version)

What's next

To get started using a Deep Learning VM, create a new instance using the Cloud Marketplace or using the command line.