How do I set up TensorFlow in the Google cloud?

Question

How do I set up a TensorFlow in the Google cloud? I understand how to create a Google Compute Engine instance, and how to run TensorFlow locally; and a recent Google blog post suggests that there ought to be a way to create a Google Compute Engine instance and run TensorFlow applications in the cloud:

Machine Learning projects can come in many sizes, and as we’ve seen with our open source offering TensorFlow, projects often need to scale up. Some small tasks are best handled with a local solution running on one’s desktop, while large scale applications require both the scale and dependability of a hosted solution. Google Cloud Machine Learning aims to support the full range and provide a seamless transition from local to cloud environment.

Even if I'm reading a bit much into this, it has to be the case, given what competing platforms such as Microsoft's Azure offer, that there's a way to set up TensorFlow applications (developed locally and "seamlessly" scaled up into the cloud, presumably using GPUs) in the Google cloud.

For example, I'd like to work locally in my IDE tuning the features and code for my project, running limited training and validation there, and push the code periodically to the cloud to run train there with (arbitrarily) greater resources, and then save and download the trained model. Or perhaps even better, just run the graphs (or parts of graphs) in the cloud using tunable resources.

Is there a way to do this; is one planned? How do I set up TensorFlow in the Google cloud?

Answer 1

This is still in limited preview. The best you can do is sign up and hope that they select you to be part of the preview.

https://cloud.google.com/ml/

Edit: CloudML is now in public beta so anyone can use it without signing up and requesting access. We hope you give it a try! We have a tag for questions: google-cloud-ml.