Struct gapi_grpc::google::cloud::aiplatform::v1beta1::DeployedModel [−][src]
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.v1beta1.EndpointService.DeployModel], this value overrides the value of [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec]. All fields of [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] are optional in the request. If a field of [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] is not populated, the value of the same field of [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec] is inherited. If the corresponding [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec] is not populated, all fields of the [explanation_spec][google.cloud.aiplatform.v1beta1.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.
enable_container_logging: bool
If true, the container of the DeployedModel instances will send stderr
and stdout
streams to Stackdriver Logging.
Only supported for custom-trained Models and AutoML Tabular Models.
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.
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.v1beta1.Model.supported_deployment_resources_types].
Trait Implementations
impl Clone for DeployedModel
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fn clone(&self) -> DeployedModel
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pub fn clone_from(&mut self, source: &Self)
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impl Debug for DeployedModel
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impl Default for DeployedModel
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fn default() -> DeployedModel
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impl Message for DeployedModel
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fn encode_raw<B>(&self, buf: &mut B) where
B: BufMut,
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B: BufMut,
fn merge_field<B>(
&mut self,
tag: u32,
wire_type: WireType,
buf: &mut B,
ctx: DecodeContext
) -> Result<(), DecodeError> where
B: Buf,
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&mut self,
tag: u32,
wire_type: WireType,
buf: &mut B,
ctx: DecodeContext
) -> Result<(), DecodeError> where
B: Buf,
fn encoded_len(&self) -> usize
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fn clear(&mut self)
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pub fn encode<B>(&self, buf: &mut B) -> Result<(), EncodeError> where
B: BufMut,
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B: BufMut,
pub fn encode_length_delimited<B>(&self, buf: &mut B) -> Result<(), EncodeError> where
B: BufMut,
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B: BufMut,
pub fn decode<B>(buf: B) -> Result<Self, DecodeError> where
Self: Default,
B: Buf,
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Self: Default,
B: Buf,
pub fn decode_length_delimited<B>(buf: B) -> Result<Self, DecodeError> where
Self: Default,
B: Buf,
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Self: Default,
B: Buf,
pub fn merge<B>(&mut self, buf: B) -> Result<(), DecodeError> where
B: Buf,
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B: Buf,
pub fn merge_length_delimited<B>(&mut self, buf: B) -> Result<(), DecodeError> where
B: Buf,
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B: Buf,
impl PartialEq<DeployedModel> for DeployedModel
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fn eq(&self, other: &DeployedModel) -> bool
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fn ne(&self, other: &DeployedModel) -> bool
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impl StructuralPartialEq for DeployedModel
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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
impl<T> Any for T where
T: 'static + ?Sized,
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T: 'static + ?Sized,
impl<T> Borrow<T> for T where
T: ?Sized,
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T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
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T: ?Sized,
pub fn borrow_mut(&mut self) -> &mut T
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impl<T> From<T> for T
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impl<T> Instrument for T
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pub fn instrument(self, span: Span) -> Instrumented<Self>
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pub fn in_current_span(self) -> Instrumented<Self>
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impl<T> Instrument for T
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pub fn instrument(self, span: Span) -> Instrumented<Self>
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pub fn in_current_span(self) -> Instrumented<Self>
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impl<T, U> Into<U> for T where
U: From<T>,
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U: From<T>,
impl<T> IntoRequest<T> for T
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pub fn into_request(self) -> Request<T>
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impl<T> ToOwned for T where
T: Clone,
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T: Clone,
type Owned = T
The resulting type after obtaining ownership.
pub fn to_owned(&self) -> T
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pub fn clone_into(&self, target: &mut T)
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impl<T, U> TryFrom<U> for T where
U: Into<T>,
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U: Into<T>,
type Error = Infallible
The type returned in the event of a conversion error.
pub fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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impl<T, U> TryInto<U> for T where
U: TryFrom<T>,
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U: TryFrom<T>,
type Error = <U as TryFrom<T>>::Error
The type returned in the event of a conversion error.
pub fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>
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impl<V, T> VZip<V> for T where
V: MultiLane<T>,
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V: MultiLane<T>,
impl<T> WithSubscriber for T
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pub fn with_subscriber<S>(self, subscriber: S) -> WithDispatch<Self> where
S: Into<Dispatch>,
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S: Into<Dispatch>,