Class CustomJobSpec (1.90.0) 

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

Represents the spec of a CustomJob.

Attributes
Name Description
persistent_resource_id str
Optional. The ID of the PersistentResource in the same Project and Location which to run If this is specified, the job will be run on existing machines held by the PersistentResource instead of on-demand short-live machines. The network and CMEK configs on the job should be consistent with those on the PersistentResource, otherwise, the job will be rejected.
worker_pool_specs MutableSequence[google.cloud.aiplatform_v1beta1.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_v1beta1.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
Optional. 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. To specify this field, you must have already `configured VPC Network Peering for Vertex AI
reserved_ip_ranges MutableSequence[str]
Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
psc_interface_config google.cloud.aiplatform_v1beta1.types.PscInterfaceConfig
Optional. Configuration for PSC-I for CustomJob.
base_output_directory google.cloud.aiplatform_v1beta1.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 = - AIP_CHECKPOINT_DIR = - AIP_TENSORBOARD_LOG_DIR = For CustomJob backing a Trial of HyperparameterTuningJob: - AIP_MODEL_DIR = - AIP_CHECKPOINT_DIR = - AIP_TENSORBOARD_LOG_DIR =
protected_artifact_location_id str
The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
tensorboard str
Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}
enable_web_access bool
Optional. Whether you want Vertex AI to enable `interactive shell access
enable_dashboard_access bool
Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to true, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
experiment str
Optional. The Experiment associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}
experiment_run str
Optional. The Experiment Run associated with this job. Format: projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}
models MutableSequence[str]
Optional. The name of the Model resources for which to generate a mapping to artifact URIs. Applicable only to some of the Google-provided custom jobs. Format: projects/{project}/locations/{location}/models/{model} In order to retrieve a specific version of the model, also provide the version ID or version alias. Example: projects/{project}/locations/{location}/models/{model}@2 or projects/{project}/locations/{location}/models/{model}@golden If no version ID or alias is specified, the "default" version will be returned. The "default" version alias is created for the first version of the model, and can be moved to other versions later on. There will be exactly one default version.

Methods

CustomJobSpec

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

Represents the spec of a CustomJob.