Struct googapis::google::cloud::aiplatform::v1::DeployedModel [−][src]
pub struct DeployedModel {
pub id: String,
pub model: String,
pub display_name: String,
pub create_time: Option<Timestamp>,
pub explanation_spec: Option<ExplanationSpec>,
pub service_account: String,
pub disable_container_logging: bool,
pub enable_access_logging: bool,
pub private_endpoints: Option<PrivateEndpoints>,
pub prediction_resources: Option<PredictionResources>,
}
Expand description
A deployment of a Model. Endpoints contain one or more DeployedModels.
Fields
id: String
Output only. The ID of the DeployedModel.
model: String
Required. The name of the Model that this is the deployment of. Note that the Model may be in a different location than the DeployedModel’s Endpoint.
display_name: String
The display name of the DeployedModel. If not provided upon creation, the Model’s display_name is used.
create_time: Option<Timestamp>
Output only. Timestamp when the DeployedModel was created.
explanation_spec: Option<ExplanationSpec>
Explanation configuration for this DeployedModel.
When deploying a Model using [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel], this value overrides the value of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]. All fields of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] are optional in the request. If a field of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] is not populated, the value of the same field of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is inherited. If the corresponding [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is not populated, all fields of the [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] will be used for the explanation configuration.
service_account: String
The service account that the DeployedModel’s container runs as. Specify the email address of the service account. If this service account is not specified, the container runs as a service account that doesn’t have access to the resource project.
Users deploying the Model must have the iam.serviceAccounts.actAs
permission on this service account.
disable_container_logging: bool
For custom-trained Models and AutoML Tabular Models, the container of the
DeployedModel instances will send stderr
and stdout
streams to
Stackdriver Logging by default. Please note that the logs incur cost,
which are subject to Cloud Logging
pricing.
User can disable container logging by setting this flag to true.
enable_access_logging: bool
These logs are like standard server access logs, containing information like timestamp and latency for each prediction request.
Note that Stackdriver logs may incur a cost, especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option.
private_endpoints: Option<PrivateEndpoints>
Output only. Provide paths for users to send predict/explain/health requests directly to the deployed model services running on Cloud via private services access. This field is populated if [network][google.cloud.aiplatform.v1.Endpoint.network] is configured.
prediction_resources: Option<PredictionResources>
The prediction (for example, the machine) resources that the DeployedModel uses. The user is billed for the resources (at least their minimal amount) even if the DeployedModel receives no traffic. Not all Models support all resources types. See [Model.supported_deployment_resources_types][google.cloud.aiplatform.v1.Model.supported_deployment_resources_types].
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 DeployedModel
impl Send for DeployedModel
impl Sync for DeployedModel
impl Unpin for DeployedModel
impl UnwindSafe for DeployedModel
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