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Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::TensorboardRun.
TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#create_time
def create_time() -> ::Google::Protobuf::Timestamp
- (::Google::Protobuf::Timestamp) — Output only. Timestamp when this TensorboardRun was created.
#description
def description() -> ::String
- (::String) — Description of this TensorboardRun.
#description=
def description=(value) -> ::String
- value (::String) — Description of this TensorboardRun.
- (::String) — Description of this TensorboardRun.
#display_name
def display_name() -> ::String
- (::String) — Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
#display_name=
def display_name=(value) -> ::String
- value (::String) — Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
- (::String) — Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
#etag
def etag() -> ::String
- (::String) — Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
#etag=
def etag=(value) -> ::String
- value (::String) — Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
- (::String) — Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
#labels
def labels() -> ::Google::Protobuf::Map{::String => ::String}
-
(::Google::Protobuf::Map{::String => ::String}) — The labels with user-defined metadata to organize your TensorboardRuns.
This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI.
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 TensorboardRun (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.
#labels=
def labels=(value) -> ::Google::Protobuf::Map{::String => ::String}
-
value (::Google::Protobuf::Map{::String => ::String}) — The labels with user-defined metadata to organize your TensorboardRuns.
This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI.
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 TensorboardRun (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.
-
(::Google::Protobuf::Map{::String => ::String}) — The labels with user-defined metadata to organize your TensorboardRuns.
This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI.
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 TensorboardRun (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.
#name
def name() -> ::String
-
(::String) — Output only. Name of the TensorboardRun.
Format:
projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}
#update_time
def update_time() -> ::Google::Protobuf::Timestamp
- (::Google::Protobuf::Timestamp) — Output only. Timestamp when this TensorboardRun was last updated.