public final class DeployedModel extends GeneratedMessageV3 implements DeployedModelOrBuilder
A deployment of a Model. Endpoints contain one or more DeployedModels.
Protobuf type google.cloud.aiplatform.v1.DeployedModel
Static Fields
public static final int AUTOMATIC_RESOURCES_FIELD_NUMBER
Field Value
public static final int CREATE_TIME_FIELD_NUMBER
Field Value
public static final int DEDICATED_RESOURCES_FIELD_NUMBER
Field Value
public static final int DISABLE_CONTAINER_LOGGING_FIELD_NUMBER
Field Value
public static final int DISPLAY_NAME_FIELD_NUMBER
Field Value
public static final int ENABLE_ACCESS_LOGGING_FIELD_NUMBER
Field Value
public static final int EXPLANATION_SPEC_FIELD_NUMBER
Field Value
public static final int ID_FIELD_NUMBER
Field Value
public static final int MODEL_FIELD_NUMBER
Field Value
public static final int PRIVATE_ENDPOINTS_FIELD_NUMBER
Field Value
public static final int SERVICE_ACCOUNT_FIELD_NUMBER
Field Value
Static Methods
public static DeployedModel getDefaultInstance()
Returns
public static final Descriptors.Descriptor getDescriptor()
Returns
public static DeployedModel.Builder newBuilder()
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public static DeployedModel.Builder newBuilder(DeployedModel prototype)
Parameter
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public static DeployedModel parseDelimitedFrom(InputStream input)
Parameter
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Exceptions
public static DeployedModel parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
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Exceptions
public static DeployedModel parseFrom(byte[] data)
Parameter
| Name | Description |
| data | byte[]
|
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Exceptions
public static DeployedModel parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
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Exceptions
public static DeployedModel parseFrom(ByteString data)
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public static DeployedModel parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
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Exceptions
public static DeployedModel parseFrom(CodedInputStream input)
Parameter
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Exceptions
public static DeployedModel parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
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Exceptions
public static DeployedModel parseFrom(InputStream input)
Parameter
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Exceptions
public static DeployedModel parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
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public static DeployedModel parseFrom(ByteBuffer data)
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public static DeployedModel parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
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Exceptions
public static Parser<DeployedModel> parser()
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Methods
public boolean equals(Object obj)
Parameter
Returns
Overrides
public AutomaticResources getAutomaticResources()
A description of resources that to large degree are decided by Vertex
AI, and require only a modest additional configuration.
.google.cloud.aiplatform.v1.AutomaticResources automatic_resources = 8;
public AutomaticResourcesOrBuilder getAutomaticResourcesOrBuilder()
A description of resources that to large degree are decided by Vertex
AI, and require only a modest additional configuration.
.google.cloud.aiplatform.v1.AutomaticResources automatic_resources = 8;
public Timestamp getCreateTime()
Output only. Timestamp when the DeployedModel was created.
.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
public TimestampOrBuilder getCreateTimeOrBuilder()
Output only. Timestamp when the DeployedModel was created.
.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
public DedicatedResources getDedicatedResources()
A description of resources that are dedicated to the DeployedModel, and
that need a higher degree of manual configuration.
.google.cloud.aiplatform.v1.DedicatedResources dedicated_resources = 7;
public DedicatedResourcesOrBuilder getDedicatedResourcesOrBuilder()
A description of resources that are dedicated to the DeployedModel, and
that need a higher degree of manual configuration.
.google.cloud.aiplatform.v1.DedicatedResources dedicated_resources = 7;
public DeployedModel getDefaultInstanceForType()
Returns
public boolean getDisableContainerLogging()
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.
bool disable_container_logging = 15;
| Type | Description |
| boolean | The disableContainerLogging.
|
public String getDisplayName()
The display name of the DeployedModel. If not provided upon creation,
the Model's display_name is used.
string display_name = 3;
| Type | Description |
| String | The displayName.
|
public ByteString getDisplayNameBytes()
The display name of the DeployedModel. If not provided upon creation,
the Model's display_name is used.
string display_name = 3;
| Type | Description |
| ByteString | The bytes for displayName.
|
public boolean getEnableAccessLogging()
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.
bool enable_access_logging = 13;
| Type | Description |
| boolean | The enableAccessLogging.
|
public ExplanationSpec getExplanationSpec()
Explanation configuration for this DeployedModel.
When deploying a Model using EndpointService.DeployModel, this value
overrides the value of Model.explanation_spec. All fields of
explanation_spec are optional in the request. If a field of
explanation_spec is not populated, the value of the same field of
Model.explanation_spec is inherited. If the corresponding
Model.explanation_spec is not populated, all fields of the
explanation_spec will be used for the explanation configuration.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 9;
public ExplanationSpecOrBuilder getExplanationSpecOrBuilder()
Explanation configuration for this DeployedModel.
When deploying a Model using EndpointService.DeployModel, this value
overrides the value of Model.explanation_spec. All fields of
explanation_spec are optional in the request. If a field of
explanation_spec is not populated, the value of the same field of
Model.explanation_spec is inherited. If the corresponding
Model.explanation_spec is not populated, all fields of the
explanation_spec will be used for the explanation configuration.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 9;
Immutable. The ID of the DeployedModel. If not provided upon deployment, Vertex AI
will generate a value for this ID.
This value should be 1-10 characters, and valid characters are /[0-9]/.
string id = 1 [(.google.api.field_behavior) = IMMUTABLE];
public ByteString getIdBytes()
Immutable. The ID of the DeployedModel. If not provided upon deployment, Vertex AI
will generate a value for this ID.
This value should be 1-10 characters, and valid characters are /[0-9]/.
string id = 1 [(.google.api.field_behavior) = IMMUTABLE];
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.
string model = 2 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
| Type | Description |
| String | The model.
|
public ByteString getModelBytes()
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.
string model = 2 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
public Parser<DeployedModel> getParserForType()
Returns
Overrides
public DeployedModel.PredictionResourcesCase getPredictionResourcesCase()
Returns
public PrivateEndpoints getPrivateEndpoints()
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 is configured.
.google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
public PrivateEndpointsOrBuilder getPrivateEndpointsOrBuilder()
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 is configured.
.google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
public int getSerializedSize()
Returns
Overrides
public String getServiceAccount()
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.
string service_account = 11;
| Type | Description |
| String | The serviceAccount.
|
public ByteString getServiceAccountBytes()
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.
string service_account = 11;
| Type | Description |
| ByteString | The bytes for serviceAccount.
|
public final UnknownFieldSet getUnknownFields()
Returns
Overrides
public boolean hasAutomaticResources()
A description of resources that to large degree are decided by Vertex
AI, and require only a modest additional configuration.
.google.cloud.aiplatform.v1.AutomaticResources automatic_resources = 8;
| Type | Description |
| boolean | Whether the automaticResources field is set.
|
public boolean hasCreateTime()
Output only. Timestamp when the DeployedModel was created.
.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| boolean | Whether the createTime field is set.
|
public boolean hasDedicatedResources()
A description of resources that are dedicated to the DeployedModel, and
that need a higher degree of manual configuration.
.google.cloud.aiplatform.v1.DedicatedResources dedicated_resources = 7;
| Type | Description |
| boolean | Whether the dedicatedResources field is set.
|
public boolean hasExplanationSpec()
Explanation configuration for this DeployedModel.
When deploying a Model using EndpointService.DeployModel, this value
overrides the value of Model.explanation_spec. All fields of
explanation_spec are optional in the request. If a field of
explanation_spec is not populated, the value of the same field of
Model.explanation_spec is inherited. If the corresponding
Model.explanation_spec is not populated, all fields of the
explanation_spec will be used for the explanation configuration.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 9;
| Type | Description |
| boolean | Whether the explanationSpec field is set.
|
public boolean hasPrivateEndpoints()
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 is configured.
.google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| boolean | Whether the privateEndpoints field is set.
|
Returns
Overrides
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
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Overrides
public final boolean isInitialized()
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Overrides
public DeployedModel.Builder newBuilderForType()
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protected DeployedModel.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Parameter
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Overrides
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Parameter
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Overrides
public DeployedModel.Builder toBuilder()
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public void writeTo(CodedOutputStream output)
Parameter
Overrides
Exceptions
