Azure/azureml-examples overall contributing guide.
Pull requests (PRs) to this repo require review and approval by the Azure Machine Learning team to merge. Please follow the pre-defined template and read all relevant sections below.
Important: PRs from forks of this repository are likely to fail automated workflows due to access to secrets. PRs from forks will be considered but may experience additional delay for testing.
Example asset YAML files should be placed under the assets directory in the appropriate subdirectory. The test for assets currently runs az ml {asset} create.
The jobs directory is structured by scenario then tool then project. The project directory should contain at least one job YAML file and a source code directory named src. A docker context or file can also be placed at the root of the project directory for use in the job file, although using prebuilt docker images is preferred.
Jobs should:
- use public cloud data
- use inline environment definitions
- use inline data definitions
- have a good description
- use a pre-existing compute target (defined in
setup.sh) - follow the YAML section order
code > command > inputs > environment > compute > experiment_name > description
Endpoints are currently only tested through documentation scripts.
Documentation scripts are bash scripts with the .sh extension at the root of the directory. They directly correspond to a markdown file in the MicrosoftDocs/azure-docs repository.