Image creation: A Docker image is created that matches the Python environment specified by the Azure ML environment. The image is uploaded to the workspace. Image creation and uploading takes about five minutes. This stage happens once for each Python environment because the container is cached for subsequent runs. During image creation, logs are streamed to the run history.

The script takes the conda environment name as an optional parameter. The default conda environment name is azure_automl. The exact command depends on the operating system. This is useful if you are creating a new environment or upgrading to a new version. For example you can use'automl_setup.cmd