Class TensorboardTimeSeries (1.25.0)

Version 1.25.0

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TensorboardTimeSeries(
    tensorboard_time_series_name: str,
    tensorboard_id: Optional[str] = None,
    tensorboard_experiment_id: Optional[str] = None,
    tensorboard_run_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 > TensorboardTimeSeries

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

TensorboardTimeSeries

TensorboardTimeSeries(
    tensorboard_time_series_name: str,
    tensorboard_id: Optional[str] = None,
    tensorboard_experiment_id: Optional[str] = None,
    tensorboard_run_id: Optional[str] = None,
    project: Optional[str] = None,
    location: Optional[str] = None,
    credentials: Optional[google.auth.credentials.Credentials] = None,
)

Retrieves an existing tensorboard time series given a tensorboard time series name or ID.

Example Usage:

tb_ts = aiplatform.TensorboardTimeSeries(
    tensorboard_time_series_name="projects/123/locations/us-central1/tensorboards/456/experiments/789/run/1011/timeSeries/mse"
)

tb_ts = aiplatform.TensorboardTimeSeries(
    tensorboard_time_series_name= "mse",
    tensorboard_id = "456",
    tensorboard_experiment_id = "789"
    tensorboard_run_id = "1011"
)

Parameters
Name	Description
tensorboard_time_series_name	str Required. A fully-qualified tensorboard time series resource name or resource ID. Example: "projects/123/locations/us-central1/tensorboards/456/experiments/789/run/1011/timeSeries/mse" or "mse" when tensorboard_id, tensorboard_experiment_id, tensorboard_run_id are passed and project and location are initialized or passed.
tensorboard_id	str Optional. A tensorboard resource ID.
tensorboard_experiment_id	str Optional. A tensorboard experiment resource ID.
tensorboard_run_id	str Optional. A tensorboard run 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.

Exceptions
Type	Description
ValueError	if only one of tensorboard_id or tensorboard_experiment_id is provided.

create

create(
    display_name: str,
    tensorboard_run_name: str,
    tensorboard_id: Optional[str] = None,
    tensorboard_experiment_id: Optional[str] = None,
    value_type: Union[
        google.cloud.aiplatform_v1.types.tensorboard_time_series.TensorboardTimeSeries.ValueType,
        str,
    ] = "SCALAR",
    plugin_name: str = "scalars",
    plugin_data: Optional[bytes] = None,
    description: Optional[str] = None,
    project: Optional[str] = None,
    location: Optional[str] = None,
    credentials: Optional[google.auth.credentials.Credentials] = None,
)

Creates a new tensorboard time series.

Example Usage:

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

Parameters
Name	Description
display_name	str Optional. User provided name of this TensorboardTimeSeries. This value should be unique among all TensorboardTimeSeries resources belonging to the same TensorboardRun resource (parent resource).
tensorboard_run_name	str Required. The resource name or ID of the TensorboardRun to create the TensorboardTimeseries in. Resource name format: projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run} If resource ID is provided then tensorboard_id and tensorboard_experiment_id must be provided.
tensorboard_id	str Optional. The resource ID of the Tensorboard to create the TensorboardTimeSeries in.
tensorboard_experiment_id	str Optional. The ID of the TensorboardExperiment to create the TensorboardTimeSeries in.
value_type	Union[gca_tensorboard_time_series.TensorboardTimeSeries.ValueType, str] Optional. Type of TensorboardTimeSeries value. One of 'SCALAR', 'TENSOR', 'BLOB_SEQUENCE'.
plugin_name	str Optional. Name of the plugin this time series pertain to.
plugin_data	bytes Optional. Data of the current plugin, with the size limited to 65KB.
description	str Optional. Description of this TensorboardTimeseries.
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.

Returns
Type	Description
TensorboardTimeSeries	The TensorboardTimeSeries 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_run_name: str,
    tensorboard_id: Optional[str] = None,
    tensorboard_experiment_id: Optional[str] = None,
    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 all instances of TensorboardTimeSeries in TensorboardRun.

Example Usage:

aiplatform.TensorboardTimeSeries.list(
    tensorboard_run_name='projects/my-project/locations/us-central1/tensorboards/123/experiments/my-experiment/runs/my-run'
)

Parameters
Name	Description
tensorboard_run_name	str Required. The resource name or ID of the TensorboardRun to list the TensorboardTimeseries from. Resource name format: projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run} If resource ID is provided then tensorboard_id and tensorboard_experiment_id must be provided.
tensorboard_id	str Optional. The resource ID of the Tensorboard to list the TensorboardTimeSeries from.
tensorboard_experiment_id	str Optional. The ID of the TensorboardExperiment to list the TensorboardTimeSeries from.
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.