Package vertexai (1.52.0)

API documentation for vertexai package.

Packages

generative_models

API documentation for generative_models package.

language_models

API documentation for language_models package.

preview

API documentation for preview package.

vision_models

API documentation for vision_models package.

resources

API documentation for resources package.

Packages Functions

init

init(
    *,
    project: typing.Optional[str] = None,
    ___location: typing.Optional[str] = None,
    experiment: typing.Optional[str] = None,
    experiment_description: typing.Optional[str] = None,
    experiment_tensorboard: typing.Optional[
        typing.Union[
            str,
            google.cloud.aiplatform.tensorboard.tensorboard_resource.Tensorboard,
            bool,
        ]
    ] = None,
    staging_bucket: typing.Optional[str] = None,
    credentials: typing.Optional[google.auth.credentials.Credentials] = None,
    encryption_spec_key_name: typing.Optional[str] = None,
    network: typing.Optional[str] = None,
    service_account: typing.Optional[str] = None,
    api_endpoint: typing.Optional[str] = None,
    api_transport: typing.Optional[str] = None
)

Updates common initialization parameters with provided options.

Parameters
Name Description
project

The default project to use when making API calls.
___location

The default ___location to use when making API calls. If not set defaults to us-central-1.
experiment

Optional. The experiment name.
experiment_description

Optional. The description of the experiment.
experiment_tensorboard

Optional. The Vertex AI TensorBoard instance, Tensorboard resource name, or Tensorboard resource ID to use as a backing Tensorboard for the provided experiment. Example tensorboard resource name format: "projects/123/locations/us-central1/tensorboards/456" If experiment_tensorboard is provided and experiment is not, the provided experiment_tensorboard will be set as the global Tensorboard. Any subsequent calls to aiplatform.init() with experiment and without experiment_tensorboard will automatically assign the global Tensorboard to the experiment. If experiment_tensorboard is ommitted or set to True or None the global Tensorboard will be assigned to the experiment. If a global Tensorboard is not set, the default Tensorboard instance will be used, and created if it does not exist. To disable creating and using Tensorboard with experiment, set experiment_tensorboard to False. Any subsequent calls to aiplatform.init() should include this setting as well.
staging_bucket

The default staging bucket to use to stage artifacts when making API calls. In the form gs://...
credentials

The default custom credentials to use when making API calls. If not provided credentials will be ascertained from the environment.
encryption_spec_key_name

Optional. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created. If set, this resource and all sub-resources will be secured by this key.
network

Optional. The full name of the Compute Engine network to which jobs and resources should be peered. E.g. "projects/12345/global/networks/myVPC". Private services access must already be configured for the network. If specified, all eligible jobs and resources created will be peered with this VPC.
service_account

Optional. The service account used to launch jobs and deploy models. Jobs that use service_account: BatchPredictionJob, CustomJob, PipelineJob, HyperparameterTuningJob, CustomTrainingJob, CustomPythonPackageTrainingJob, CustomContainerTrainingJob, ModelEvaluationJob.
api_endpoint

Optional. The desired API endpoint, e.g., us-central1-aiplatform.googleapis.com
api_transport

Optional. The transport method which is either 'grpc' or 'rest'. NOTE: "rest" transport functionality is currently in a beta state (preview).