Quick Start - Keras

In this tutorial, we will create a Keras machine learning project based on our Keras example on GitHub and run a deep mind transform on it.

1. Sign in

  1. Register to the Valohai platform.
  2. Sign in on the same page.

2. Create a project

  1. Go to the Valohai platform front page after signing in
  2. Press the Create Project button
  3. Set a Name for your project, e.g. test-keras
  4. You can leave Description blank, that is more in detail definition of your project
  5. Press the Create button

4. Create an execution

  1. Go to the Executions tab inside your project
  2. Press the Create execution button
  3. The Step field lists all available types of executions. Make sure tensorflow-deep-dream is selected.
  4. You don’t need to worry about the rest of the configuration for now. The default inputs and parameters of the form are loaded from the valohai.yaml configuration file and should be good for this example execution.
  5. Press Submit to start the execution.

5. View the results

After you start the execution, you are forwarded to the execution page.

This page has several tabs with execution details:

The Information tab shows the basic information about the execution, most of which could’ve been modified in the previous execution creation step.

The Log tab shows real-time log output from the execution. Anything that your code prints to the standard output (stdout) or standard error (stderr) streams is shown here.

The Metadata tab shows all the metadata output from the execution. You can also plot the metadata on a line chart. Metadata is any data your execution writes to the standard output stream in JSON which we can parse. If no plottable metadata has been output, this tab is not visible.

The Output tab contains download links for all the output artifacts created by the execution. The execution defines these outputs by writing them into /valohai/outputs directory. The artifacts are stored in AWS S3. If the execution has not finished, or did not output any files, this tab will not be visible.

6. Next steps

Congratulations on running actual machine learning code on the cloud!

For next steps we would encourage reading about the core concepts of Valohai platform to gain a better understanding of all the bells and whistles.