Class CustomJobSpec (1.7.1)

CustomJobSpec(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Represents the spec of a CustomJob.

Attributes

NameDescription
worker_pool_specs Sequence[google.cloud.aiplatform_v1.types.WorkerPoolSpec]
Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
scheduling google.cloud.aiplatform_v1.types.Scheduling
Scheduling options for a CustomJob.
service_account str
Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the `Vertex AI Custom Code Service Agent
network str
The full name of the Compute Engine `network `__ to which the Job should be peered. For example, ``projects/12345/global/networks/myVPC``. `Format `__ is of the form ``projects/{project}/global/networks/{network}``. Where {project} is a project number, as in ``12345``, and {network} is a network name. Private services access must already be configured for the network. If left unspecified, the job is not peered with any network.
base_output_directory google.cloud.aiplatform_v1.types.GcsDestination
The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: - AIP_MODEL_DIR = ``
enable_web_access bool
Optional. Whether you want Vertex AI to enable `interactive shell access

Inheritance

builtins.object > proto.message.Message > CustomJobSpec