Azure ML scripts#
Olive provides a couple of scripts to help you manage your Azure ML assets.
Scripts list#
manage_compute_instance
#
This Python script provides a command-line interface for managing compute resources in an Azure Machine Learning workspace.
--create
or-c
: A flag indicating that a new compute resource should be created. This is mutually exclusive with--delete
- only one of them can be specified at a time.--delete
or-d
: A flag indicating that an existing compute resource should be deleted. This is mutually exclusive with--create
- only one of them can be specified at a time.--subscription_id
: The ID of your Azure subscription.--resource_group
: The name of your Azure resource group.--workspace_name
: The name of your Azure Machine Learning workspace.--aml_config_path
: The path to your AzureML config file. If this is provided, subscription_id, resource_group and workspace_name are ignored.--compute_name
: The name of the new compute resource. This is a required argument.--vm_size
: The VM size of the new compute resource. This is required if you are creating a compute instance.--location
: The location where the new compute resource should be created. This is required if you are creating a compute instance.--min_nodes
: The minimum number of nodes for the new compute resource. If this is not provided, the default value is 0.--max_nodes
: The maximum number of nodes for the new compute resource. If this is not provided, the default value is 2.--idle_time_before_scale_down
: The number of idle seconds before the compute resource scales down. If this is not provided, the default value is 120 seconds.
aml_config_path
is a json file for your azureml config:
{
"subscription_id": "<subscription_id>",
"resource_group": "<resource_group>",
"workspace_name": "<workspace_name>",
}
Usage#
You can use olive manage-aml-compute
command line tool to create an AzureML compute instance from the command line like this:
olive manage-aml-compute --create --subscription_id <subscription_id> --resource_group <resource_group> --workspace_name <workspace_name> --compute_name <compute_name> --vm_size <vm_size> --location <location> --min_nodes <min_nodes> --max_nodes <max_nodes> --idle_time_before_scale_down <idle_time_before_scale_down>
or
olive manage-aml-compute --create --aml_config_path </path/to/aml_config.json> --compute_name <compute_name> --vm_size <vm_size> --location <location> --min_nodes <min_nodes> --max_nodes <max_nodes> --idle_time_before_scale_down <idle_time_before_scale_down>
You can delete an AzureML compute instance by:
olive manage-aml-compute --delete --compute_name <compute_name>
More details can be found at Command Line Tools.