Class TensorboardRun (1.24.1)

Version 1.24.1

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TensorboardRun(
    tensorboard_run_name: str,
    tensorboard_id: Optional[str] = None,
    tensorboard_experiment_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 > TensorboardRun

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

TensorboardRun

TensorboardRun(
    tensorboard_run_name: str,
    tensorboard_id: Optional[str] = None,
    tensorboard_experiment_id: Optional[str] = None,
    project: Optional[str] = None,
    location: Optional[str] = None,
    credentials: Optional[google.auth.credentials.Credentials] = None,
)

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

Example Usage:

tb_run = aiplatform.TensorboardRun(
    tensorboard_run_name= "projects/123/locations/us-central1/tensorboards/456/experiments/678/run/8910"
)

tb_run = aiplatform.TensorboardRun(
    tensorboard_run_name= "8910",
    tensorboard_id = "456",
    tensorboard_experiment_id = "678"
)

Parameters
Name	Description
tensorboard_run_name	str Required. A fully-qualified tensorboard run resource name or resource ID. Example: "projects/123/locations/us-central1/tensorboards/456/experiments/678/runs/8910" or "8910" when tensorboard_id and tensorboard_experiment_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.
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(
    tensorboard_run_id: str,
    tensorboard_experiment_name: str,
    tensorboard_id: Optional[str] = None,
    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 tensorboard run.

Example Usage:

tb_run = aiplatform.TensorboardRun.create(
    tensorboard_run_id='my-run'
    tensorboard_experiment_name='my-experiment'
    tensorboard_id='456'
    display_name='my display name',
    description='my description',
    labels={
        'key1': 'value1',
        'key2': 'value2'
    }
)

Parameters
Name	Description
tensorboard_run_id	str Required. The ID to use for the Tensorboard run, which will become the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid: characters are /a-z][0-9]-/.
tensorboard_experiment_name	str Required. The resource name or ID of the TensorboardExperiment to create the TensorboardRun in. Resource name format: projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment} If resource ID is provided then tensorboard_id must be provided.
tensorboard_id	str Optional. The resource ID of the Tensorboard to create the TensorboardRun in.
display_name	str Optional. The user-defined name of the Tensorboard Run. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment. If not provided tensorboard_run_id will be used.
description	str Optional. Description of this Tensorboard Run.
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
TensorboardRun	The TensorboardRun resource.

create_tensorboard_time_series

create_tensorboard_time_series(
    display_name: str,
    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,
)

Creates a new tensorboard time series.

Example Usage:

tb_ts = tensorboard_run.create_tensorboard_time_series(
    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).
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. Such as Scalar, Tensor, Blob.
plugin_data	bytes Optional. Data of the current plugin, with the size limited to 65KB.
description	str Optional. Description of this TensorboardTimeseries.

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_experiment_name: str,
    tensorboard_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 TensorboardRun in TensorboardExperiment.

Example Usage:

aiplatform.TensorboardRun.list(
    tensorboard_experiment_name='projects/my-project/locations/us-central1/tensorboards/123/experiments/456'
)

Parameters
Name	Description
tensorboard_experiment_name	str Required. The resource name or resource ID of the TensorboardExperiment to list TensorboardRun. Format, if resource name: 'projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}' If resource ID is provided then tensorboard_id must be provided.
tensorboard_id	str Optional. The resource ID of the Tensorboard that contains the TensorboardExperiment to list TensorboardRun.
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.

read_time_series_data

read_time_series_data()

Read the time series data of this run.

time_series_data = tensorboard_run.read_time_series_data()

print(time_series_data['loss'].values[-1].scalar.value)

to_dict

to_dict()

Returns the resource proto as a dictionary.

wait

wait()

Helper method that blocks until all futures are complete.

write_tensorboard_scalar_data

write_tensorboard_scalar_data(
    time_series_data: Dict[str, float],
    step: int,
    wall_time: Optional[google.protobuf.timestamp_pb2.Timestamp] = None,
)

Writes tensorboard scalar data to this run.

Parameters
Name	Description
time_series_data	Dict[str, float] Required. Dictionary of where keys are TensorboardTimeSeries display name and values are the scalar value..
step	int Required. Step index of this data point within the run.
wall_time	timestamp_pb2.Timestamp Optional. Wall clock timestamp when this data point is generated by the end user. If not provided, this will be generated based on the value from time.time()