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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 > TensorboardProperties
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.
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'
}
)
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: |
create_request_timeout |
float
Optional. The timeout for the create request in seconds. |
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.
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")
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: |
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',
)
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: |
Type | Description |
Tensorboard | The managed tensorboard resource. |
wait
wait()
Helper method that blocks until all futures are complete.