BatchDeploymentOperations Class

  • Reference

BatchDeploymentOperations.

You should not instantiate this class directly. Instead, you should create an MLClient instance that instantiates it for you and attaches it as an attribute.

Inheritance
azure.ai.ml._scope_dependent_operations._ScopeDependentOperations
BatchDeploymentOperations

Constructor

BatchDeploymentOperations(operation_scope: OperationScope, operation_config: OperationConfig, service_client_01_2024_preview: AzureMachineLearningWorkspaces, all_operations: OperationsContainer, credentials: TokenCredential | None = None, **kwargs: Any)

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_05_2022
Required
<xref:<xref:azure.ai.ml._restclient.v2022_05_01._azure_machine_learning_workspaces. AzureMachineLearningWorkspaces>>

Service client to allow end users to operate on Azure Machine Learning Workspace resources.
all_operations
Required
<xref:azure.ai.ml._scope_dependent_operations.OperationsContainer>

All operations classes of an MLClient object.
credentials
TokenCredential

Credential to use for authentication.

Default value: None
service_client_01_2024_preview
Required

Methods

begin_create_or_update

Create or update a batch deployment.
begin_delete

Delete a batch deployment.
get

Get a deployment resource.
list

List a deployment resource.
list_jobs

List jobs under the provided batch endpoint deployment. This is only valid for batch endpoint.

begin_create_or_update

Create or update a batch deployment.

begin_create_or_update(deployment: DeploymentType, *, skip_script_validation: bool = False, **kwargs: Any) -> LROPoller[DeploymentType]

Parameters

Name Description
deployment
Required
BatchDeployment

The deployment entity.

Keyword-Only Parameters

Name Description
skip_script_validation
bool

If set to True, the script validation will be skipped. Defaults to False.

Returns

Type Description
LROPoller[BatchDeployment]

A poller to track the operation status.

Exceptions

Type Description
ValidationException

Raised if BatchDeployment cannot be successfully validated. Details will be provided in the error message.
AssetException

Raised if BatchDeployment assets (e.g. Data, Code, Model, Environment) cannot be successfully validated. Details will be provided in the error message.
ModelException

Raised if BatchDeployment model cannot be successfully validated. Details will be provided in the error message.

Examples

Create example.


   from azure.ai.ml import load_batch_deployment
   from azure.ai.ml.entities import BatchDeployment

   deployment_example = load_batch_deployment(
       source="./sdk/ml/azure-ai-ml/tests/test_configs/deployments/batch/batch_deployment_anon_env_with_image.yaml",
       params_override=[{"name": f"deployment-{randint(0, 1000)}", "endpoint_name": endpoint_example.name}],
   )

   ml_client.batch_deployments.begin_create_or_update(deployment=deployment_example, skip_script_validation=True)

begin_delete

Delete a batch deployment.

begin_delete(name: str, endpoint_name: str) -> LROPoller[None]

Parameters

Name Description
name
Required
str

Name of the batch deployment.
endpoint_name
Required
str

Name of the batch endpoint

Keyword-Only Parameters

Name Description
skip_script_validation
bool

If set to True, the script validation will be skipped. Defaults to False.

Returns

Type Description
LROPoller[None]

A poller to track the operation status.

Exceptions

Type Description
ValidationException

Raised if BatchDeployment cannot be successfully validated. Details will be provided in the error message.
AssetException

Raised if BatchDeployment assets (e.g. Data, Code, Model, Environment) cannot be successfully validated. Details will be provided in the error message.
ModelException

Raised if BatchDeployment model cannot be successfully validated. Details will be provided in the error message.

Examples

Delete example.


   ml_client.batch_deployments.begin_delete(deployment_name, endpoint_name)

get

Get a deployment resource.

get(name: str, endpoint_name: str) -> BatchDeployment

Parameters

Name Description
name
Required
str

The name of the deployment
endpoint_name
Required
str

The name of the endpoint

Keyword-Only Parameters

Name Description
skip_script_validation
bool

If set to True, the script validation will be skipped. Defaults to False.

Returns

Type Description
BatchDeployment

A deployment entity

Exceptions

Type Description
ValidationException

Raised if BatchDeployment cannot be successfully validated. Details will be provided in the error message.
AssetException

Raised if BatchDeployment assets (e.g. Data, Code, Model, Environment) cannot be successfully validated. Details will be provided in the error message.
ModelException

Raised if BatchDeployment model cannot be successfully validated. Details will be provided in the error message.

Examples

Get example.


   ml_client.batch_deployments.get(deployment_name, endpoint_name)

list

List a deployment resource.

list(endpoint_name: str) -> ItemPaged[BatchDeployment]

Parameters

Name Description
endpoint_name
Required
str

The name of the endpoint

Keyword-Only Parameters

Name Description
skip_script_validation
bool

If set to True, the script validation will be skipped. Defaults to False.

Returns

Type Description
ItemPaged[BatchDeployment]

An iterator of deployment entities

Exceptions

Type Description
ValidationException

Raised if BatchDeployment cannot be successfully validated. Details will be provided in the error message.
AssetException

Raised if BatchDeployment assets (e.g. Data, Code, Model, Environment) cannot be successfully validated. Details will be provided in the error message.
ModelException

Raised if BatchDeployment model cannot be successfully validated. Details will be provided in the error message.

Examples

List deployment resource example.


   ml_client.batch_deployments.list(endpoint_name)

list_jobs

List jobs under the provided batch endpoint deployment. This is only valid for batch endpoint.

list_jobs(endpoint_name: str, *, name: str | None = None) -> ItemPaged[BatchJob]

Parameters

Name Description
endpoint_name
Required
str

Name of endpoint.

Keyword-Only Parameters

Name Description
name
str

(Optional) Name of deployment.

Returns

Type Description
ItemPaged[BatchJob]

List of jobs

Exceptions

Type Description
ValidationException

Raised if BatchDeployment cannot be successfully validated. Details will be provided in the error message.
AssetException

Raised if BatchDeployment assets (e.g. Data, Code, Model, Environment) cannot be successfully validated. Details will be provided in the error message.
ModelException

Raised if BatchDeployment model cannot be successfully validated. Details will be provided in the error message.

Examples

List jobs example.


   ml_client.batch_deployments.list_jobs(deployment_name, endpoint_name)