After launching the image "Deep Learning" through the Marketplace and selecting the Framework "a XGBoost(CUDA 9.2)[EXPERIMENTAL]" the users are getting a "deprecated image" warning.
What you expected to happen:
Users expect the solution Deep Learning VM (Google Click to Deploy) use the latest image.
Steps to reproduce:
1.- Go to the "Deep Learning VM GCP Marketplace" page in the Google Cloud Platform Console.
2.- Click Launch on Compute Engine.
3.- Enter a Deployment name which will be the root of your VM name. Compute Engine appends -vm to this name when naming your instance.
4.- Choose your Framework and Zone. For ML Framework choose "XGBoost(CUDA 9.2)[EXPERIMENTAL]"
5.- In the GPU section, set the number of GPUs to Zero and enter n/a in the Quota confirmation field.
6.- In the CPU section, select your Machine type.
7.- Select your boot disk type and size.
8.- Click Deploy.
You will get the following warning:
tensorflow has resource level warnings
tensorflow-1-vm: The resource 'projects/click-to-deploy-images/global/images/xgboost-0-90-cu92-experimental-20200603' is deprecated. A suggested replacement is 'projects/click-to-deploy-images/global/images/xgboost-0-90-cu92-experimental-20200617'.
Other information (workarounds you have tried, documentation consulted, etc): N/A
Description
Problem you have encountered:
After launching the image "Deep Learning" through the Marketplace and selecting the Framework "a XGBoost(CUDA 9.2)[EXPERIMENTAL]" the users are getting a "deprecated image" warning.
What you expected to happen: Users expect the solution Deep Learning VM (Google Click to Deploy) use the latest image.
Steps to reproduce:
You will get the following warning:
Other information (workarounds you have tried, documentation consulted, etc): N/A