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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
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
AIreserved_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'].
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 =
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}
