Struct googapis::google::cloud::aiplatform::v1beta1::TensorboardRun [−][src]
pub struct TensorboardRun {
pub name: String,
pub display_name: String,
pub description: String,
pub create_time: Option<Timestamp>,
pub update_time: Option<Timestamp>,
pub labels: HashMap<String, String>,
pub etag: String,
}
Expand description
TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc
Fields
name: String
Output only. Name of the TensorboardRun.
Format:
projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}
display_name: String
Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
description: String
Description of this TensorboardRun.
create_time: Option<Timestamp>
Output only. Timestamp when this TensorboardRun was created.
update_time: Option<Timestamp>
Output only. Timestamp when this TensorboardRun was last updated.
labels: HashMap<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.
etag: String
Used to perform a consistent read-modify-write updates. If not set, a blind “overwrite” update happens.
Trait Implementations
fn merge_field<B>(
&mut self,
tag: u32,
wire_type: WireType,
buf: &mut B,
ctx: DecodeContext
) -> Result<(), DecodeError> where
B: Buf,
Returns the encoded length of the message without a length delimiter.
Encodes the message to a buffer. Read more
Encodes the message to a newly allocated buffer.
Encodes the message with a length-delimiter to a buffer. Read more
Encodes the message with a length-delimiter to a newly allocated buffer.
Decodes an instance of the message from a buffer. Read more
fn decode_length_delimited<B>(buf: B) -> Result<Self, DecodeError> where
Self: Default,
B: Buf,
fn decode_length_delimited<B>(buf: B) -> Result<Self, DecodeError> where
Self: Default,
B: Buf,
Decodes a length-delimited instance of the message from the buffer.
Decodes an instance of the message from a buffer, and merges it into self
. Read more
Decodes a length-delimited instance of the message from buffer, and
merges it into self
. Read more
This method tests for self
and other
values to be equal, and is used
by ==
. Read more
This method tests for !=
.
Auto Trait Implementations
impl RefUnwindSafe for TensorboardRun
impl Send for TensorboardRun
impl Sync for TensorboardRun
impl Unpin for TensorboardRun
impl UnwindSafe for TensorboardRun
Blanket Implementations
Mutably borrows from an owned value. Read more
Wrap the input message T
in a tonic::Request
pub fn vzip(self) -> V
Attaches the provided Subscriber
to this type, returning a
WithDispatch
wrapper. Read more
Attaches the current default Subscriber
to this type, returning a
WithDispatch
wrapper. Read more