As usual, 2 weeks since M4 revision is out we are ready to show the world revision M5. This revision include quite noticeable changes.

Nvidia-Docker. Probably the most noticeable one is that now we have Docker installed on all our images and Nvidia-Docker on all GPU images.

Nvidia stack is also upgraded:

TensorRT 4 now included in all our images!

we now have the latest CuDNN 7.2.1, and the latest Nvidia Driver 396.44.

TensorFlow 1.10.0 has been re-compiled with the latest CuDNN 7.2.1.

TensorFlow 1.10.0 now compiled with TensorRT support!

Jupyter Lab improvements:

Jupyter Lab now opens in dedicated folder (not the home folder).

Dedicated folder for the Jupyter Lab workspace has pre-baked tutorials (either TensorFlow or PyTorch).

Binary swapping. Now, if you are using image from GPU family on the instance that does not have GPU it will automatically detect it and will swap the GPU binaries with the CPU-optimized binaries.

Last but not the least. If you are using our images and have a functional test that you want us to run in the pre-release cycle, so you will know that new release images will NOT break you, please let us know by sending a letter to our public group: https://groups.google.com/forum/#!forum/google-dl-platform

Also, please keep in mind that best advice is never to use latest image till after you will run all your tests and confirmed that it is safe to use it in production!

Some additional notes, there is no changes in our main image family names, they are still the same:

As usually you can create VM with GPU with our images with the following command:

Or if you need just CPU instance: