Class TensorboardExperiment (1.24.1)

Version 1.24.1

• 1.75.0 (latest)
• 1.74.0
• 1.73.0
• 1.72.0
• 1.71.1
• 1.70.0
• 1.69.0
• 1.68.0
• 1.67.1
• 1.66.0
• 1.65.0
• 1.63.0
• 1.62.0
• 1.60.0
• 1.59.0
• 1.58.0
• 1.57.0
• 1.56.0
• 1.55.0
• 1.54.1
• 1.53.0
• 1.52.0
• 1.51.0
• 1.50.0
• 1.49.0
• 1.48.0
• 1.47.0
• 1.46.0
• 1.45.0
• 1.44.0
• 1.43.0
• 1.39.0
• 1.38.1
• 1.37.0
• 1.36.4
• 1.35.0
• 1.34.0
• 1.33.1
• 1.32.0
• 1.31.1
• 1.30.1
• 1.29.0
• 1.28.1
• 1.27.1
• 1.26.1
• 1.25.0
• 1.24.1
• 1.23.0
• 1.22.1
• 1.21.0
• 1.20.0
• 1.19.1
• 1.18.3
• 1.17.1
• 1.16.1
• 1.15.1
• 1.14.0
• 1.13.1
• 1.12.1
• 1.11.0
• 1.10.0
• 1.9.0
• 1.8.1
• 1.7.1
• 1.6.2
• 1.5.0
• 1.4.3
• 1.3.0
• 1.2.0
• 1.1.1
• 1.0.1
• 0.9.0
• 0.8.0
• 0.7.1
• 0.6.0
• 0.5.1
• 0.4.0
• 0.3.1

TensorboardExperiment(
    tensorboard_experiment_name: str,
    tensorboard_id: Optional[str] = None,
    project: Optional[str] = None,
    location: Optional[str] = None,
    credentials: Optional[google.auth.credentials.Credentials] = None,
)

Managed tensorboard resource for Vertex AI.

Inheritance

builtins.object > google.cloud.aiplatform.base.VertexAiResourceNoun > builtins.object > google.cloud.aiplatform.base.FutureManager > google.cloud.aiplatform.base.VertexAiResourceNounWithFutureManager > google.cloud.aiplatform.tensorboard.tensorboard_resource._TensorboardServiceResource > TensorboardExperiment

Properties

create_time

Time this resource was created.

display_name

Display name of this resource.

encryption_spec

Customer-managed encryption key options for this Vertex AI resource.

If this is set, then all resources created by this Vertex AI resource will be encrypted with the provided encryption key.

gca_resource

The underlying resource proto representation.

labels

User-defined labels containing metadata about this resource.

Read more about labels at https://goo.gl/xmQnxf

name

Name of this resource.

resource_name

Full qualified resource name.

update_time

Time this resource was last updated.

Methods

TensorboardExperiment

TensorboardExperiment(
    tensorboard_experiment_name: str,
    tensorboard_id: Optional[str] = None,
    project: Optional[str] = None,
    location: Optional[str] = None,
    credentials: Optional[google.auth.credentials.Credentials] = None,
)

Retrieves an existing tensorboard experiment given a tensorboard experiment name or ID.

Example Usage:

tb_exp = aiplatform.TensorboardExperiment(
    tensorboard_experiment_name= "projects/123/locations/us-central1/tensorboards/456/experiments/678"
)

tb_exp = aiplatform.TensorboardExperiment(
    tensorboard_experiment_name= "678"
    tensorboard_id = "456"
)

Parameters
Name	Description
tensorboard_experiment_name	str Required. A fully-qualified tensorboard experiment resource name or resource ID. Example: "projects/123/locations/us-central1/tensorboards/456/experiments/678" or "678" when tensorboard_id is passed and project and location are initialized or passed.
tensorboard_id	str Optional. A tensorboard resource ID.
project	str Optional. Project to retrieve tensorboard from. If not set, project set in aiplatform.init will be used.
location	str Optional. Location to retrieve tensorboard from. If not set, location set in aiplatform.init will be used.
credentials	auth_credentials.Credentials Optional. Custom credentials to use to retrieve this Tensorboard. Overrides credentials set in aiplatform.init.

create

create(
    tensorboard_experiment_id: str,
    tensorboard_name: str,
    display_name: Optional[str] = None,
    description: Optional[str] = None,
    labels: Optional[Dict[str, str]] = None,
    project: Optional[str] = None,
    location: Optional[str] = None,
    credentials: Optional[google.auth.credentials.Credentials] = None,
    request_metadata: Sequence[Tuple[str, str]] = (),
    create_request_timeout: Optional[float] = None,
)

Creates a new TensorboardExperiment.

Example Usage:

tb_exp = aiplatform.TensorboardExperiment.create(
    tensorboard_experiment_id='my-experiment'
    tensorboard_id='456'
    display_name='my display name',
    description='my description',
    labels={
        'key1': 'value1',
        'key2': 'value2'
    }
)

Parameters
Name	Description
tensorboard_experiment_id	str Required. The ID to use for the Tensorboard experiment, which will become the final component of the Tensorboard experiment's resource name. This value should be 1-128 characters, and valid characters are /a-z][0-9]-/. This corresponds to the tensorboard_experiment_id field on the request instance; if request is provided, this should not be set.
tensorboard_name	str Required. The resource name or ID of the Tensorboard to create the TensorboardExperiment in. Format of resource name: projects/{project}/locations/{location}/tensorboards/{tensorboard}
display_name	str Optional. The user-defined name of the Tensorboard Experiment. The name can be up to 128 characters long and can be consist of any UTF-8 characters.
description	str Optional. Description of this Tensorboard Experiment.
labels	Dict[str, str] Optional. Labels with user-defined metadata to organize your Tensorboards. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Tensorboard (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
project	str Optional. Project to upload this model to. Overrides project set in aiplatform.init.
location	str Optional. Location to upload this model to. Overrides location set in aiplatform.init.
credentials	auth_credentials.Credentials Optional. Custom credentials to use to upload this model. Overrides credentials set in aiplatform.init.
request_metadata	Sequence[Tuple[str, str]] Optional. Strings which should be sent along with the request as metadata.
create_request_timeout	float Optional. The timeout for the create request in seconds.

Returns
Type	Description
TensorboardExperiment	The TensorboardExperiment resource.

delete

delete(sync: bool = True)

Deletes this Vertex AI resource. WARNING: This deletion is permanent.

Parameter
Name	Description
sync	bool Whether to execute this deletion synchronously. If False, this method will be executed in concurrent Future and any downstream object will be immediately returned and synced when the Future has completed.

list

list(
    tensorboard_name: str,
    filter: Optional[str] = None,
    order_by: Optional[str] = None,
    project: Optional[str] = None,
    location: Optional[str] = None,
    credentials: Optional[google.auth.credentials.Credentials] = None,
)

List TensorboardExperiemnts in a Tensorboard resource.

Example Usage:

aiplatform.TensorboardExperiment.list(
    tensorboard_name='projects/my-project/locations/us-central1/tensorboards/123'
)

Parameters
Name	Description
tensorboard_name	str Required. The resource name or resource ID of the Tensorboard to list TensorboardExperiments. Format, if resource name: 'projects/{project}/locations/{location}/tensorboards/{tensorboard}'
filter	str Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported.
order_by	str Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: display_name, create_time, update_time
project	str Optional. Project to retrieve list from. If not set, project set in aiplatform.init will be used.
location	str Optional. Location to retrieve list from. If not set, location set in aiplatform.init will be used.
credentials	auth_credentials.Credentials Optional. Custom credentials to use to retrieve list. Overrides credentials set in aiplatform.init.

to_dict

to_dict()

Returns the resource proto as a dictionary.

wait

wait()

Helper method that blocks until all futures are complete.