ComputeOperations Class

ComputeOperations.

This class should not be instantiated directly. Instead, use the compute attribute of an MLClient object.

Inheritance
azure.ai.ml._scope_dependent_operations._ScopeDependentOperations
ComputeOperations

Constructor

ComputeOperations(operation_scope: OperationScope, operation_config: OperationConfig, service_client: AzureMachineLearningWorkspaces, service_client_2024: AzureMachineLearningWorkspaces, **kwargs: Dict)

Parameters

Name Description
operation_scope
Required
<xref:azure.ai.ml._scope_dependent_operations.OperationScope>

Scope variables for the operations classes of an MLClient object.

operation_config
Required
<xref:azure.ai.ml._scope_dependent_operations.OperationConfig>

Common configuration for operations classes of an MLClient object.

service_client
Required
<xref:azure.ai.ml._restclient.v2023_02_01_preview.AzureMachineLearningWorkspaces>

Service client to allow end users to operate on Azure Machine Learning Workspace resources.

service_client_2024
Required

Methods

begin_attach

Attach a compute resource to the workspace.

begin_create_or_update

Create and register a compute resource.

begin_delete

Delete or detach a compute resource.

begin_restart

Restart a compute instance.

begin_start

Start a compute instance.

begin_stop

Stop a compute instance.

begin_update

Update a compute resource. Currently only valid for AmlCompute resource types.

enable_sso

Note

This is an experimental method, and may change at any time. Please see https://aka.ms/azuremlexperimental for more information.

enable sso for a compute instance.

get

Get a compute resource.

list

List computes of the workspace.

list_nodes

Retrieve a list of a compute resource's nodes.

list_sizes

List the supported VM sizes in a location.

list_usage

List the current usage information as well as AzureML resource limits for the given subscription and location.

begin_attach

Attach a compute resource to the workspace.

begin_attach(compute: Compute, **kwargs: Any) -> LROPoller[Compute]

Parameters

Name Description
compute
Required

The compute resource definition.

Returns

Type Description

An instance of LROPoller that returns a Compute object once the long-running operation is complete.

Examples

Attaching a compute resource to the workspace.


   from azure.ai.ml.entities import AmlCompute

   compute_obj = AmlCompute(
       name=compute_name_2,
       tags={"key1": "value1", "key2": "value2"},
       min_instances=0,
       max_instances=10,
       idle_time_before_scale_down=100,
   )
   attached_compute = ml_client.compute.begin_attach(compute_obj)

begin_create_or_update

Create and register a compute resource.

begin_create_or_update(compute: Compute) -> LROPoller[Compute]

Parameters

Name Description
compute
Required

The compute resource definition.

Returns

Type Description

An instance of LROPoller that returns a Compute object once the long-running operation is complete.

Examples

Creating and registering a compute resource.


   from azure.ai.ml.entities import AmlCompute

   compute_obj = AmlCompute(
       name=compute_name_1,
       tags={"key1": "value1", "key2": "value2"},
       min_instances=0,
       max_instances=10,
       idle_time_before_scale_down=100,
   )
   registered_compute = ml_client.compute.begin_create_or_update(compute_obj)

begin_delete

Delete or detach a compute resource.

begin_delete(name: str, *, action: str = 'Delete') -> LROPoller[None]

Parameters

Name Description
name
Required
str

The name of the compute resource.

Keyword-Only Parameters

Name Description
action

Action to perform. Possible values: ["Delete", "Detach"]. Defaults to "Delete".

Returns

Type Description

A poller to track the operation status.

Examples

Delete compute example.


   ml_client.compute.begin_delete(compute_name_1, action="Detach")

   ml_client.compute.begin_delete(compute_name_2)

begin_restart

Restart a compute instance.

begin_restart(name: str) -> LROPoller[None]

Parameters

Name Description
name
Required
str

The name of the compute instance.

Returns

Type Description

A poller to track the operation status.

Examples

Restarting a stopped compute instance.


   ml_client.compute.begin_restart(ci_name)

begin_start

Start a compute instance.

begin_start(name: str) -> LROPoller[None]

Parameters

Name Description
name
Required
str

The name of the compute instance.

Returns

Type Description

A poller to track the operation status.

Examples

Starting a compute instance.


   ml_client.compute.begin_start(ci_name)

begin_stop

Stop a compute instance.

begin_stop(name: str) -> LROPoller[None]

Parameters

Name Description
name
Required
str

The name of the compute instance.

Returns

Type Description

A poller to track the operation status.

Examples

Stopping a compute instance.


   ml_client.compute.begin_stop(ci_name)

begin_update

Update a compute resource. Currently only valid for AmlCompute resource types.

begin_update(compute: Compute) -> LROPoller[Compute]

Parameters

Name Description
compute
Required

The compute resource definition.

Returns

Type Description

An instance of LROPoller that returns a Compute object once the long-running operation is complete.

Examples

Updating an AmlCompute resource.


   compute_obj = ml_client.compute.get("cpu-cluster")
   compute_obj.idle_time_before_scale_down = 200
   updated_compute = ml_client.compute.begin_update(compute_obj)

enable_sso

Note

This is an experimental method, and may change at any time. Please see https://aka.ms/azuremlexperimental for more information.

enable sso for a compute instance.

enable_sso(*, name: str, enable_sso: bool = True) -> None

Keyword-Only Parameters

Name Description
name
str

Name of the compute instance.

enable_sso

enable sso bool flag Default to True

get

Get a compute resource.

get(name: str) -> Compute

Parameters

Name Description
name
Required
str

Name of the compute resource.

Returns

Type Description

A Compute object.

Examples

Retrieving a compute resource from a workspace.


   cpu_cluster = ml_client.compute.get("cpu-cluster")

list

List computes of the workspace.

list(*, compute_type: str | None = None) -> Iterable[Compute]

Keyword-Only Parameters

Name Description
compute_type

The type of the compute to be listed, case-insensitive. Defaults to AMLCompute.

Returns

Type Description

An iterator like instance of Compute objects.

Examples

Retrieving a list of the AzureML Kubernetes compute resources in a workspace.


   compute_list = ml_client.compute.list(compute_type="AMLK8s")  # cspell:disable-line

list_nodes

Retrieve a list of a compute resource's nodes.

list_nodes(name: str) -> Iterable[AmlComputeNodeInfo]

Parameters

Name Description
name
Required
str

Name of the compute resource.

Returns

Type Description

An iterator-like instance of AmlComputeNodeInfo objects.

Examples

Retrieving a list of nodes from a compute resource.


   node_list = ml_client.compute.list_nodes(name="cpu-cluster")

list_sizes

List the supported VM sizes in a location.

list_sizes(*, location: str | None = None, compute_type: str | None = None) -> Iterable[VmSize]

Keyword-Only Parameters

Name Description
location
str

The location upon which virtual-machine-sizes is queried. Defaults to workspace location.

compute_type

The type of the compute to be listed, case-insensitive. Defaults to AMLCompute.

Returns

Type Description

An iterator over virtual machine size objects.

Examples

Listing the supported VM sizes in the workspace location.


   size_list = ml_client.compute.list_sizes()

list_usage

List the current usage information as well as AzureML resource limits for the given subscription and location.

list_usage(*, location: str | None = None) -> Iterable[Usage]

Keyword-Only Parameters

Name Description
location

The location for which resource usage is queried. Defaults to workspace location.

Returns

Type Description

An iterator over current usage info objects.

Examples

Listing resource usage for the workspace location.


   usage_list = ml_client.compute.list_usage()