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API documentation for aiplatform
package.
Classes
AutoMLImageTrainingJob
Constructs a AutoML Image Training Job.
AutoMLTabularTrainingJob
Constructs a AutoML Tabular Training Job.
AutoMLTextTrainingJob
Constructs a AutoML Text Training Job.
AutoMLVideoTrainingJob
Constructs a AutoML Video Training Job.
BatchPredictionJob
Retrieves a BatchPredictionJob resource and instantiates its representation.
CustomContainerTrainingJob
Class to launch a Custom Training Job in AI Platform using a Container.
CustomPythonPackageTrainingJob
Class to launch a Custom Training Job in AI Platform using a Python Package.
Takes a training implementation as a python package and executes that package in Cloud AI Platform Training.
CustomTrainingJob
Class to launch a Custom Training Job in AI Platform using a script.
Takes a training implementation as a python script and executes that script in Cloud AI Platform Training.
Endpoint
Retrieves an endpoint resource.
ImageDataset
Managed image dataset resource for AI Platform.
Model
Retrieves the model resource and instantiates its representation.
TabularDataset
Managed tabular dataset resource for AI Platform.
TextDataset
Managed text dataset resource for AI Platform.
VideoDataset
Managed video dataset resource for AI Platform.
Packages Functions
init
init(
*,
project: Optional[str] = None,
location: Optional[str] = None,
experiment: Optional[str] = None,
staging_bucket: Optional[str] = None,
credentials: Optional[google.auth.credentials.Credentials] = None,
encryption_spec_key_name: Optional[str] = None
)
Updates common initalization parameters with provided options.
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 |
The experiment to assign |
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 crendentials 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: |