Valohai is completely technology agnostic. You can develop in notebooks or scripts in a language and framework of your choice.
Valohai expects that you have a valohai.yaml config file in your repository. The file defines what kind of jobs can be executed inside your project, and the different properties of each job type (these are called steps in Valohai).
You can either write the
valohai.yaml by hand or if you’re using Python, you can use the valohai-utils Toolkit to define the configuration file in your code.
Let’s start by bringing just a single job type to Valohai
Create a valohai.yaml
Create a new file called
valohai.yaml and define a Step inside it.
In our example below we’re defining two commands to be run every time the step called
train is run. You can remove the pip install command if you don’t need it.
- step: name: train image: tensorflow/tensorflow:2.6.1-gpu command: - pip install -r requirements.txt - python myfilename.py
You can now upload your local code to Valohai and run the
train step inside the Docker container you just defined.
vh execution run --adhoc train
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