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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 > TensorboardRunProperties
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"
)
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. |
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'
}
)
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 / |
tensorboard_experiment_name |
str
Required. The resource name or ID of the TensorboardExperiment to create the TensorboardRun in. Resource name format: |
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. |
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'
}
)
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. |
Type | Description |
TensorboardTimeSeries |
The TensorboardTimeSeries 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(
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'
)
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: |
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.
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() |