BatchCompute Class

Manages a Batch compute target in Azure Machine Learning.

Azure Batch is used to run large-scale parallel and high-performance computing (HPC) applications efficiently in the cloud. BatchCompute is used in Azure Machine Learning Pipelines to submit jobs to an Azure Batch pool of machines using an AzureBatchStep. For more information, see What are compute targets in Azure Machine Learning?

Class ComputeTarget constructor.

Retrieve a cloud representation of a Compute object associated with the provided workspace. Returns an instance of a child class corresponding to the specific type of the retrieved Compute object.

Inheritance

ComputeTarget

BatchCompute

Constructor

BatchCompute(workspace, name)

Parameters

workspace

Workspace

Required

The workspace object containing the BatchCompute object to retrieve.

name

str

Required

The name of the BatchCompute object to retrieve.

workspace

Workspace

Required

The workspace object containing the Compute object to retrieve.

name

str

Required

The name of the of the Compute object to retrieve.

Remarks

Create an Azure Batch account before using it. To create one, see Create a Batch account with the Azure portal.

The following example shows how to attach a Azure Batch compute account to a workspace using attach_configuration.

   batch_compute_name = 'mybatchcompute' # Name to associate with new compute in workspace

   # Batch account details needed to attach as compute to workspace
   batch_account_name = "<batch_account_name>" # Name of the Batch account
   batch_resource_group = "<batch_resource_group>" # Name of the resource group which contains this account

   try:
       # check if already attached
       batch_compute = BatchCompute(ws, batch_compute_name)
   except ComputeTargetException:
       print('Attaching Batch compute...')
       provisioning_config = BatchCompute.attach_configuration(resource_group=batch_resource_group,
                                                               account_name=batch_account_name)
       batch_compute = ComputeTarget.attach(ws, batch_compute_name, provisioning_config)
       batch_compute.wait_for_completion()
       print("Provisioning state:{}".format(batch_compute.provisioning_state))
       print("Provisioning errors:{}".format(batch_compute.provisioning_errors))

   print("Using Batch compute:{}".format(batch_compute.cluster_resource_id))

Full sample is available from https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-how-to-use-azurebatch-to-run-a-windows-executable.ipynb

Methods

attach_configuration	Create a configuration object for attaching a Batch compute target.
delete	Delete is not supported for a BatchCompute object. Use detach instead.
deserialize	Convert a JSON object into a BatchCompute object.
detach	Detaches the Batch object from its associated workspace. Underlying cloud objects are not deleted, only the association is removed.
refresh_state	Perform an in-place update of the properties of the object. This method updates the properties based on the current state of the corresponding cloud object. This is primarily used for manual polling of compute state.
serialize	Convert this BatchCompute object into a JSON serialized dictionary.

attach_configuration

Create a configuration object for attaching a Batch compute target.

static attach_configuration(resource_group=None, account_name=None, resource_id=None)

Parameters

resource_group

str

default value: None

The name of the resource group in which the Batch account is located.

account_name

str

default value: None

The Batch account name.

resource_id

str

default value: None

The Azure resource ID for the compute resource being attached.

Returns

A configuration object to be used when attaching a Compute object.

Return type

BatchAttachConfiguration

delete

Delete is not supported for a BatchCompute object. Use detach instead.

delete()

Exceptions

ComputeTargetException

deserialize

Convert a JSON object into a BatchCompute object.

static deserialize(workspace, object_dict)

Parameters

workspace

Workspace

Required

The workspace object the BatchCompute object is associated with.

object_dict

dict

Required

A JSON object to convert to a BatchCompute object.

Returns

The BatchCompute representation of the provided JSON object.

Return type

BatchCompute

Exceptions

ComputeTargetException

Remarks

Raises a ComputeTargetException if the provided workspace is not the workspace the Compute is associated with.

detach

Detaches the Batch object from its associated workspace.

Underlying cloud objects are not deleted, only the association is removed.

detach()

Exceptions

ComputeTargetException

refresh_state

Perform an in-place update of the properties of the object.

This method updates the properties based on the current state of the corresponding cloud object. This is primarily used for manual polling of compute state.

refresh_state()

serialize

Convert this BatchCompute object into a JSON serialized dictionary.

serialize()

Returns

The JSON representation of this BatchCompute object.

Return type

dict