Class Tensorboard (1.22.1)

Tensorboard(
    tensorboard_name: str,
    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 > Tensorboard

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

Tensorboard

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

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

Parameters

Name	Description
`tensorboard_name`	`str` Required. A fully-qualified tensorboard resource name or tensorboard ID. Example: "projects/123/locations/us-central1/tensorboards/456" or "456" when project and location are initialized or passed.
`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(
    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: Optional[Sequence[Tuple[str, str]]] = (),
    encryption_spec_key_name: Optional[str] = None,
    create_request_timeout: Optional[float] = None,
)

Creates a new tensorboard.

Example Usage:

tb = aiplatform.Tensorboard.create(
    display_name='my display name',
    description='my description',
    labels={
        'key1': 'value1',
        'key2': 'value2'
    }
)

Parameters

Name	Description
`display_name`	`str` Optional. The user-defined name of the Tensorboard. 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.
`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.
`encryption_spec_key_name`	`str` Optional. Cloud KMS resource identifier of the customer managed encryption key used to protect the tensorboard. 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 Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Overrides encryption_spec_key_name set in aiplatform.init.
`create_request_timeout`	`float` Optional. The timeout for the create request in seconds.

Returns

Type	Description
`tensorboard (Tensorboard)`	Instantiated representation of the managed tensorboard 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(
    filter: Optional[str] = None,
    order_by: Optional[str] = None,
    project: Optional[str] = None,
    location: Optional[str] = None,
    credentials: Optional[google.auth.credentials.Credentials] = None,
    parent: Optional[str] = None,
)

List all instances of this Vertex AI Resource.

Example Usage:

aiplatform.BatchPredictionJobs.list( filter='state="JOB_STATE_SUCCEEDED" AND display_name="my_job"', )

aiplatform.Model.list(order_by="create_time desc, display_name")

Parameters

Name	Description
`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.
`parent`	`str` Optional. The parent resource name if any to retrieve list from.

to_dict

to_dict()

Returns the resource proto as a dictionary.

update

update(
    display_name: Optional[str] = None,
    description: Optional[str] = None,
    labels: Optional[Dict[str, str]] = None,
    request_metadata: Optional[Sequence[Tuple[str, str]]] = (),
    encryption_spec_key_name: Optional[str] = None,
)

Updates an existing tensorboard.

Example Usage:

tb = aiplatform.Tensorboard(tensorboard_name='123456')
tb.update(
    display_name='update my display name',
    description='update my description',
)

Parameters

Name	Description
`display_name`	`str` Optional. User-defined name of the Tensorboard. 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.
`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.
`request_metadata`	`Sequence[Tuple[str, str]]` Optional. Strings which should be sent along with the request as metadata.
`encryption_spec_key_name`	`str` Optional. Cloud KMS resource identifier of the customer managed encryption key used to protect the tensorboard. 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 Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Overrides encryption_spec_key_name set in aiplatform.init.

Returns

Type	Description
`Tensorboard`	The managed tensorboard resource.

wait

wait()

Helper method that blocks until all futures are complete.