Struct google_api_proto::google::cloud::aiplatform::v1::TensorboardExperiment

pub struct TensorboardExperiment {
    pub name: String,
    pub display_name: String,
    pub description: String,
    pub create_time: Option<Timestamp>,
    pub update_time: Option<Timestamp>,
    pub labels: BTreeMap<String, String>,
    pub etag: String,
    pub source: String,
}

A TensorboardExperiment is a group of TensorboardRuns, that are typically the results of a training job run, in a Tensorboard.

Fields

name: String

Output only. Name of the TensorboardExperiment. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}

display_name: String

User provided name of this TensorboardExperiment.

description: String

Description of this TensorboardExperiment.

create_time: Option<Timestamp>

Output only. Timestamp when this TensorboardExperiment was created.

update_time: Option<Timestamp>

Output only. Timestamp when this TensorboardExperiment was last updated.

labels: BTreeMap<String, String>

The labels with user-defined metadata to organize your TensorboardExperiment.

Label keys and values cannot be 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 Dataset (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. The following system labels exist for each Dataset:

• aiplatform.googleapis.com/dataset_metadata_schema: output only. Its value is the [metadata_schema’s][google.cloud.aiplatform.v1.Dataset.metadata_schema_uri] title.

etag: String

Used to perform consistent read-modify-write updates. If not set, a blind “overwrite” update happens.

source: String

Immutable. Source of the TensorboardExperiment. Example: a custom training job.

Trait Implementations

impl Clone for TensorboardExperiment

fn clone(&self) -> TensorboardExperiment

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for TensorboardExperiment

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for TensorboardExperiment

fn default() -> Self

Returns the “default value” for a type.

impl Message for TensorboardExperiment

fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)

Clears the message, resetting all fields to their default.

fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message to a buffer.

fn encode_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message to a newly allocated buffer.

fn encode_length_delimited( &self, buf: &mut impl BufMut, ) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message with a length-delimiter to a buffer.

fn encode_length_delimited_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message with a length-delimiter to a newly allocated buffer.

fn decode(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes an instance of the message from a buffer.

fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes a length-delimited instance of the message from the buffer.

fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes an instance of the message from a buffer, and merges it into self.

fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq for TensorboardExperiment

fn eq(&self, other: &TensorboardExperiment) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for TensorboardExperiment