There is a command group 'az_ml_compute'. This group of commands could 'manage azure ml compute resources'. The group of commands has global parameter '--debug' which means 'Increase logging verbosity to show all debug logs.'. The group of commands has global parameter '--help -h' which means 'Show this help message and exit.'. The group of commands has global parameter '--only-show-errors' which means 'Only show errors, suppressing warnings.'. The group of commands has global parameter '--output -o' which means 'Output format.'. The group of commands has global parameter '--query' which means 'JMESPath query string. See <a href="http://jmespath.org/">http://jmespath.org/</a> for more information and examples.'. The group of commands has global parameter '--subscription' which means 'Name or ID of subscription. You can configure the default subscription using `az account set -s NAME_OR_ID`.'. The group of commands has global parameter '--verbose' which means 'Increase logging verbosity. Use --debug for full debug logs.'. This group contains a child command 'az_ml_compute_attach'.The syntax is: az ml compute attach --resource-group
                     --workspace-name
                     [--admin-password]
                     [--admin-username]
                     [--file]
                     [--identity-type]
                     [--name]
                     [--namespace]
                     [--no-wait]
                     [--resource-id]
                     [--ssh-port]
                     [--ssh-private-key-file]
                     [--type]
                     [--user-assigned-identities]. The parameter '--resource-group -g' is required. It is used to name of resource group. you can configure the default group using `az configure --defaults group=<name>`.. The parameter '--workspace-name -w' is required. It is used to name of the azure ml workspace. you can configure the default workspace using `az configure --defaults workspace=<name>`.. The parameter '--admin-password' is optional. the administrator user password that can be used to ssh into the node(s).. The parameter '--admin-username' is optional. name of the administrator user account that can be used to ssh into the node(s).. The parameter '--file -f' is optional. local path to the yaml file containing the azure ml compute specification.. The parameter '--identity-type' is optional. the type of manged identity. allowed values: systemassigned, userassigned.. The parameter '--name -n' is optional. name of the compute target (required if not specified in the yaml file).. The parameter '--namespace' is optional. namespace of a kubernetescompute.. The parameter '--no-wait' is optional. do not wait for the long-running operation to finish.. The parameter '--resource-id' is optional. the fully qualified id of the resource, including the resource name and resource type (required if not specified in the yaml file).. The parameter '--ssh-port' is optional. the port number that can be used to ssh into the node(s). if not specified, the default (port 22) will be used.. The parameter '--ssh-private-key-file' is optional. the file containing the ssh private key of the administrator user account.. The parameter '--type -t' is optional. the type of compute target. allowed values: virtualmachine, kubernetes.. The parameter '--user-assigned-identities -i' is optional. the user assigned identity's resource id, required for --identity_type=userassigned.. 