azure.mgmt.machinelearningservices.operations module¶

class azure.mgmt.machinelearningservices.operations.Operations(client, config, serializer, deserializer)[source]¶

Bases: object

Operations operations.

You should not instantiate directly this class, but create a Client instance that will create it for you and attach it as attribute.

Parameters

client – Client for service requests.
config – Configuration of service client.
serializer – An object model serializer.
deserializer – An object model deserializer.

Variables

api_version – Version of Azure Machine Learning resource provider API. Constant value: “2019-05-01”.

list(custom_headers=None, raw=False, **operation_config)[source]¶

Lists all of the available Azure Machine Learning Workspaces REST API operations.

Parameters

custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

An iterator like instance of Operation

Return type

OperationPaged[Operation]

Raises

MachineLearningServiceErrorException

models = <module 'azure.mgmt.machinelearningservices.models' from '/home/vsts/work/1/s/sdk/machinelearning/azure-mgmt-machinelearningservices/.tox/sphinx/lib/python3.6/site-packages/azure/mgmt/machinelearningservices/models/__init__.py'>¶

class azure.mgmt.machinelearningservices.operations.WorkspacesOperations(client, config, serializer, deserializer)[source]¶

Bases: object

WorkspacesOperations operations.

You should not instantiate directly this class, but create a Client instance that will create it for you and attach it as attribute.

Parameters

client – Client for service requests.
config – Configuration of service client.
serializer – An object model serializer.
deserializer – An object model deserializer.

Variables

api_version – Version of Azure Machine Learning resource provider API. Constant value: “2019-05-01”.

create_or_update(resource_group_name, workspace_name, parameters, custom_headers=None, raw=False, **operation_config)[source]¶

Creates or updates a workspace with the specified parameters.

Parameters

resource_group_name (str) – Name of the resource group in which workspace is located.
workspace_name (str) – Name of Azure Machine Learning workspace.
parameters (Workspace) – The parameters for creating or updating a machine learning workspace.
custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

Workspace or ClientRawResponse if raw=true

Return type

Workspace or ClientRawResponse

Raises

MachineLearningServiceErrorException

delete(resource_group_name, workspace_name, custom_headers=None, raw=False, **operation_config)[source]¶

Deletes a machine learning workspace.

Parameters

resource_group_name (str) – Name of the resource group in which workspace is located.
workspace_name (str) – Name of Azure Machine Learning workspace.
custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

None or ClientRawResponse if raw=true

Return type

None or ClientRawResponse

Raises

MachineLearningServiceErrorException

get(resource_group_name, workspace_name, custom_headers=None, raw=False, **operation_config)[source]¶

Gets the properties of the specified machine learning workspace.

Parameters

resource_group_name (str) – Name of the resource group in which workspace is located.
workspace_name (str) – Name of Azure Machine Learning workspace.
custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

Workspace or ClientRawResponse if raw=true

Return type

Workspace or ClientRawResponse

Raises

MachineLearningServiceErrorException

list_by_resource_group(resource_group_name, skiptoken=None, custom_headers=None, raw=False, **operation_config)[source]¶

Lists all the available machine learning workspaces under the specified resource group.

Parameters

resource_group_name (str) – Name of the resource group in which workspace is located.
skiptoken (str) – Continuation token for pagination.
custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

An iterator like instance of Workspace

Return type

WorkspacePaged[Workspace]

Raises

MachineLearningServiceErrorException

list_by_subscription(skiptoken=None, custom_headers=None, raw=False, **operation_config)[source]¶

Lists all the available machine learning workspaces under the specified subscription.

Parameters

skiptoken (str) – Continuation token for pagination.
custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

An iterator like instance of Workspace

Return type

WorkspacePaged[Workspace]

Raises

MachineLearningServiceErrorException

list_keys(resource_group_name, workspace_name, custom_headers=None, raw=False, **operation_config)[source]¶

Lists all the keys associated with this workspace. This includes keys for the storage account, app insights and password for container registry.

Parameters

resource_group_name (str) – Name of the resource group in which workspace is located.
workspace_name (str) – Name of Azure Machine Learning workspace.
custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

ListWorkspaceKeysResult or ClientRawResponse if raw=true

Return type

ListWorkspaceKeysResult or ClientRawResponse

Raises

MachineLearningServiceErrorException

resync_keys(resource_group_name, workspace_name, custom_headers=None, raw=False, **operation_config)[source]¶

Resync all the keys associated with this workspace. This includes keys for the storage account, app insights and password for container registry.

Parameters

resource_group_name (str) – Name of the resource group in which workspace is located.
workspace_name (str) – Name of Azure Machine Learning workspace.
custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

None or ClientRawResponse if raw=true

Return type

None or ClientRawResponse

Raises

MachineLearningServiceErrorException

update(resource_group_name, workspace_name, parameters, custom_headers=None, raw=False, **operation_config)[source]¶

Updates a machine learning workspace with the specified parameters.

Parameters

resource_group_name (str) – Name of the resource group in which workspace is located.
workspace_name (str) – Name of Azure Machine Learning workspace.
parameters (WorkspaceUpdateParameters) – The parameters for updating a machine learning workspace.
custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

Workspace or ClientRawResponse if raw=true

Return type

Workspace or ClientRawResponse

Raises

MachineLearningServiceErrorException

models = <module 'azure.mgmt.machinelearningservices.models' from '/home/vsts/work/1/s/sdk/machinelearning/azure-mgmt-machinelearningservices/.tox/sphinx/lib/python3.6/site-packages/azure/mgmt/machinelearningservices/models/__init__.py'>¶

class azure.mgmt.machinelearningservices.operations.UsagesOperations(client, config, serializer, deserializer)[source]¶

Bases: object

UsagesOperations operations.

You should not instantiate directly this class, but create a Client instance that will create it for you and attach it as attribute.

Parameters

client – Client for service requests.
config – Configuration of service client.
serializer – An object model serializer.
deserializer – An object model deserializer.

Variables

api_version – Version of Azure Machine Learning resource provider API. Constant value: “2019-05-01”.

list(location, custom_headers=None, raw=False, **operation_config)[source]¶

Gets the current usage information as well as limits for AML resources for given subscription and location.

Parameters

location (str) – The location for which resource usage is queried.
custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

An iterator like instance of Usage

Return type

UsagePaged[Usage]

Raises

CloudError

models = <module 'azure.mgmt.machinelearningservices.models' from '/home/vsts/work/1/s/sdk/machinelearning/azure-mgmt-machinelearningservices/.tox/sphinx/lib/python3.6/site-packages/azure/mgmt/machinelearningservices/models/__init__.py'>¶

class azure.mgmt.machinelearningservices.operations.VirtualMachineSizesOperations(client, config, serializer, deserializer)[source]¶

Bases: object

VirtualMachineSizesOperations operations.

You should not instantiate directly this class, but create a Client instance that will create it for you and attach it as attribute.

Parameters

client – Client for service requests.
config – Configuration of service client.
serializer – An object model serializer.
deserializer – An object model deserializer.

Variables

api_version – Version of Azure Machine Learning resource provider API. Constant value: “2019-05-01”.

list(location, custom_headers=None, raw=False, **operation_config)[source]¶

Returns supported VM Sizes in a location.

Parameters

location (str) – The location upon which virtual-machine-sizes is queried.
custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

VirtualMachineSizeListResult or ClientRawResponse if raw=true

Return type

VirtualMachineSizeListResult or ClientRawResponse

Raises

CloudError

models = <module 'azure.mgmt.machinelearningservices.models' from '/home/vsts/work/1/s/sdk/machinelearning/azure-mgmt-machinelearningservices/.tox/sphinx/lib/python3.6/site-packages/azure/mgmt/machinelearningservices/models/__init__.py'>¶

class azure.mgmt.machinelearningservices.operations.MachineLearningComputeOperations(client, config, serializer, deserializer)[source]¶

Bases: object

MachineLearningComputeOperations operations.

You should not instantiate directly this class, but create a Client instance that will create it for you and attach it as attribute.

Parameters

client – Client for service requests.
config – Configuration of service client.
serializer – An object model serializer.
deserializer – An object model deserializer.

Variables

api_version – Version of Azure Machine Learning resource provider API. Constant value: “2019-05-01”.

create_or_update(resource_group_name, workspace_name, compute_name, parameters, custom_headers=None, raw=False, polling=True, **operation_config)[source]¶

Creates or updates compute. This call will overwrite a compute if it exists. This is a nonrecoverable operation. If your intent is to create a new compute, do a GET first to verify that it does not exist yet.

Parameters

resource_group_name (str) – Name of the resource group in which workspace is located.
workspace_name (str) – Name of Azure Machine Learning workspace.
compute_name (str) – Name of the Azure Machine Learning compute.
parameters (ComputeResource) – Payload with Machine Learning compute definition.
custom_headers (dict) – headers that will be added to the request
raw (bool) – The poller return type is ClientRawResponse, the direct response alongside the deserialized response
polling – True for ARMPolling, False for no polling, or a polling object for personal polling strategy

Returns

An instance of LROPoller that returns ComputeResource or ClientRawResponse<ComputeResource> if raw==True

Return type

AzureOperationPoller[ComputeResource] or AzureOperationPoller[ClientRawResponse[ComputeResource]]

Raises

MachineLearningServiceErrorException

delete(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers=None, raw=False, polling=True, **operation_config)[source]¶

Deletes specified Machine Learning compute.

Parameters

resource_group_name (str) – Name of the resource group in which workspace is located.
workspace_name (str) – Name of Azure Machine Learning workspace.
compute_name (str) – Name of the Azure Machine Learning compute.
underlying_resource_action (str or UnderlyingResourceAction) – Delete the underlying compute if ‘Delete’, or detach the underlying compute from workspace if ‘Detach’. Possible values include: ‘Delete’, ‘Detach’
custom_headers (dict) – headers that will be added to the request
raw (bool) – The poller return type is ClientRawResponse, the direct response alongside the deserialized response
polling – True for ARMPolling, False for no polling, or a polling object for personal polling strategy

Returns

An instance of LROPoller that returns None or ClientRawResponse<None> if raw==True

Return type

AzureOperationPoller[None] or AzureOperationPoller[ClientRawResponse[None]]

Raises

MachineLearningServiceErrorException

get(resource_group_name, workspace_name, compute_name, custom_headers=None, raw=False, **operation_config)[source]¶

Gets compute definition by its name. Any secrets (storage keys, service credentials, etc) are not returned - use ‘keys’ nested resource to get them.

Parameters

resource_group_name (str) – Name of the resource group in which workspace is located.
workspace_name (str) – Name of Azure Machine Learning workspace.
compute_name (str) – Name of the Azure Machine Learning compute.
custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

ComputeResource or ClientRawResponse if raw=true

Return type

ComputeResource or ClientRawResponse

Raises

MachineLearningServiceErrorException

list_by_workspace(resource_group_name, workspace_name, skiptoken=None, custom_headers=None, raw=False, **operation_config)[source]¶

Gets computes in specified workspace.

Parameters

resource_group_name (str) – Name of the resource group in which workspace is located.
workspace_name (str) – Name of Azure Machine Learning workspace.
skiptoken (str) – Continuation token for pagination.
custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

An iterator like instance of ComputeResource

Return type

ComputeResourcePaged[ComputeResource]

Raises

MachineLearningServiceErrorException

list_keys(resource_group_name, workspace_name, compute_name, custom_headers=None, raw=False, **operation_config)[source]¶

Gets secrets related to Machine Learning compute (storage keys, service credentials, etc).

Parameters

resource_group_name (str) – Name of the resource group in which workspace is located.
workspace_name (str) – Name of Azure Machine Learning workspace.
compute_name (str) – Name of the Azure Machine Learning compute.
custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

ComputeSecrets or ClientRawResponse if raw=true

Return type

ComputeSecrets or ClientRawResponse

Raises

MachineLearningServiceErrorException

list_nodes(resource_group_name, workspace_name, compute_name, custom_headers=None, raw=False, **operation_config)[source]¶

Get the details (e.g IP address, port etc) of all the compute nodes in the compute.

Parameters

resource_group_name (str) – Name of the resource group in which workspace is located.
workspace_name (str) – Name of Azure Machine Learning workspace.
compute_name (str) – Name of the Azure Machine Learning compute.
custom_headers (dict) – headers that will be added to the request
raw (bool) – returns the direct response alongside the deserialized response
operation_config – Operation configuration overrides.

Returns

AmlComputeNodesInformation or ClientRawResponse if raw=true

Return type

AmlComputeNodesInformation or ClientRawResponse

Raises

MachineLearningServiceErrorException

update(resource_group_name, workspace_name, compute_name, scale_settings=None, custom_headers=None, raw=False, polling=True, **operation_config)[source]¶

Updates properties of a compute. This call will overwrite a compute if it exists. This is a nonrecoverable operation.

Parameters

resource_group_name (str) – Name of the resource group in which workspace is located.
workspace_name (str) – Name of Azure Machine Learning workspace.
compute_name (str) – Name of the Azure Machine Learning compute.
scale_settings (ScaleSettings) – Scale settings. Desired scale settings for the amlCompute.
custom_headers (dict) – headers that will be added to the request
raw (bool) – The poller return type is ClientRawResponse, the direct response alongside the deserialized response
polling – True for ARMPolling, False for no polling, or a polling object for personal polling strategy

Returns

An instance of LROPoller that returns ComputeResource or ClientRawResponse<ComputeResource> if raw==True

Return type

AzureOperationPoller[ComputeResource] or AzureOperationPoller[ClientRawResponse[ComputeResource]]

Raises

MachineLearningServiceErrorException

models = <module 'azure.mgmt.machinelearningservices.models' from '/home/vsts/work/1/s/sdk/machinelearning/azure-mgmt-machinelearningservices/.tox/sphinx/lib/python3.6/site-packages/azure/mgmt/machinelearningservices/models/__init__.py'>¶