Class DeployedModel (2.9.8)

public final class DeployedModel extends GeneratedMessageV3 implements DeployedModelOrBuilder

A deployment of a Model. Endpoints contain one or more DeployedModels.

Protobuf type google.cloud.aiplatform.v1beta1.DeployedModel

Static Fields

AUTOMATIC_RESOURCES_FIELD_NUMBER

public static final int AUTOMATIC_RESOURCES_FIELD_NUMBER
Field Value
TypeDescription
int

CREATE_TIME_FIELD_NUMBER

public static final int CREATE_TIME_FIELD_NUMBER
Field Value
TypeDescription
int

DEDICATED_RESOURCES_FIELD_NUMBER

public static final int DEDICATED_RESOURCES_FIELD_NUMBER
Field Value
TypeDescription
int

DISPLAY_NAME_FIELD_NUMBER

public static final int DISPLAY_NAME_FIELD_NUMBER
Field Value
TypeDescription
int

ENABLE_ACCESS_LOGGING_FIELD_NUMBER

public static final int ENABLE_ACCESS_LOGGING_FIELD_NUMBER
Field Value
TypeDescription
int

ENABLE_CONTAINER_LOGGING_FIELD_NUMBER

public static final int ENABLE_CONTAINER_LOGGING_FIELD_NUMBER
Field Value
TypeDescription
int

EXPLANATION_SPEC_FIELD_NUMBER

public static final int EXPLANATION_SPEC_FIELD_NUMBER
Field Value
TypeDescription
int

ID_FIELD_NUMBER

public static final int ID_FIELD_NUMBER
Field Value
TypeDescription
int

MODEL_FIELD_NUMBER

public static final int MODEL_FIELD_NUMBER
Field Value
TypeDescription
int

MODEL_VERSION_ID_FIELD_NUMBER

public static final int MODEL_VERSION_ID_FIELD_NUMBER
Field Value
TypeDescription
int

PRIVATE_ENDPOINTS_FIELD_NUMBER

public static final int PRIVATE_ENDPOINTS_FIELD_NUMBER
Field Value
TypeDescription
int

SERVICE_ACCOUNT_FIELD_NUMBER

public static final int SERVICE_ACCOUNT_FIELD_NUMBER
Field Value
TypeDescription
int

Static Methods

getDefaultInstance()

public static DeployedModel getDefaultInstance()
Returns
TypeDescription
DeployedModel

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
TypeDescription
Descriptor

newBuilder()

public static DeployedModel.Builder newBuilder()
Returns
TypeDescription
DeployedModel.Builder

newBuilder(DeployedModel prototype)

public static DeployedModel.Builder newBuilder(DeployedModel prototype)
Parameter
NameDescription
prototypeDeployedModel
Returns
TypeDescription
DeployedModel.Builder

parseDelimitedFrom(InputStream input)

public static DeployedModel parseDelimitedFrom(InputStream input)
Parameter
NameDescription
inputInputStream
Returns
TypeDescription
DeployedModel
Exceptions
TypeDescription
IOException

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static DeployedModel parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
DeployedModel
Exceptions
TypeDescription
IOException

parseFrom(byte[] data)

public static DeployedModel parseFrom(byte[] data)
Parameter
NameDescription
databyte[]
Returns
TypeDescription
DeployedModel
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

public static DeployedModel parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
databyte[]
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
DeployedModel
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(ByteString data)

public static DeployedModel parseFrom(ByteString data)
Parameter
NameDescription
dataByteString
Returns
TypeDescription
DeployedModel
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

public static DeployedModel parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
dataByteString
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
DeployedModel
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(CodedInputStream input)

public static DeployedModel parseFrom(CodedInputStream input)
Parameter
NameDescription
inputCodedInputStream
Returns
TypeDescription
DeployedModel
Exceptions
TypeDescription
IOException

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public static DeployedModel parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
DeployedModel
Exceptions
TypeDescription
IOException

parseFrom(InputStream input)

public static DeployedModel parseFrom(InputStream input)
Parameter
NameDescription
inputInputStream
Returns
TypeDescription
DeployedModel
Exceptions
TypeDescription
IOException

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static DeployedModel parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
DeployedModel
Exceptions
TypeDescription
IOException

parseFrom(ByteBuffer data)

public static DeployedModel parseFrom(ByteBuffer data)
Parameter
NameDescription
dataByteBuffer
Returns
TypeDescription
DeployedModel
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

public static DeployedModel parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
dataByteBuffer
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
DeployedModel
Exceptions
TypeDescription
InvalidProtocolBufferException

parser()

public static Parser<DeployedModel> parser()
Returns
TypeDescription
Parser<DeployedModel>

Methods

equals(Object obj)

public boolean equals(Object obj)
Parameter
NameDescription
objObject
Returns
TypeDescription
boolean
Overrides

getAutomaticResources()

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.v1beta1.AutomaticResources automatic_resources = 8;

Returns
TypeDescription
AutomaticResources

The automaticResources.

getAutomaticResourcesOrBuilder()

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.v1beta1.AutomaticResources automatic_resources = 8;

Returns
TypeDescription
AutomaticResourcesOrBuilder

getCreateTime()

public Timestamp getCreateTime()

Output only. Timestamp when the DeployedModel was created.

.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
TypeDescription
Timestamp

The createTime.

getCreateTimeOrBuilder()

public TimestampOrBuilder getCreateTimeOrBuilder()

Output only. Timestamp when the DeployedModel was created.

.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
TypeDescription
TimestampOrBuilder

getDedicatedResources()

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.v1beta1.DedicatedResources dedicated_resources = 7;

Returns
TypeDescription
DedicatedResources

The dedicatedResources.

getDedicatedResourcesOrBuilder()

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.v1beta1.DedicatedResources dedicated_resources = 7;

Returns
TypeDescription
DedicatedResourcesOrBuilder

getDefaultInstanceForType()

public DeployedModel getDefaultInstanceForType()
Returns
TypeDescription
DeployedModel

getDisplayName()

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;

Returns
TypeDescription
String

The displayName.

getDisplayNameBytes()

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;

Returns
TypeDescription
ByteString

The bytes for displayName.

getEnableAccessLogging()

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;

Returns
TypeDescription
boolean

The enableAccessLogging.

getEnableContainerLogging()

public boolean getEnableContainerLogging()

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.

bool enable_container_logging = 12;

Returns
TypeDescription
boolean

The enableContainerLogging.

getExplanationSpec()

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.v1beta1.ExplanationSpec explanation_spec = 9;

Returns
TypeDescription
ExplanationSpec

The explanationSpec.

getExplanationSpecOrBuilder()

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.v1beta1.ExplanationSpec explanation_spec = 9;

Returns
TypeDescription
ExplanationSpecOrBuilder

getId()

public String getId()

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];

Returns
TypeDescription
String

The id.

getIdBytes()

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];

Returns
TypeDescription
ByteString

The bytes for id.

getModel()

public String getModel()

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) = { ... }

Returns
TypeDescription
String

The model.

getModelBytes()

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) = { ... }

Returns
TypeDescription
ByteString

The bytes for model.

getModelVersionId()

public String getModelVersionId()

Output only. The version ID of the model that is deployed.

string model_version_id = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
TypeDescription
String

The modelVersionId.

getModelVersionIdBytes()

public ByteString getModelVersionIdBytes()

Output only. The version ID of the model that is deployed.

string model_version_id = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
TypeDescription
ByteString

The bytes for modelVersionId.

getParserForType()

public Parser<DeployedModel> getParserForType()
Returns
TypeDescription
Parser<DeployedModel>
Overrides

getPredictionResourcesCase()

public DeployedModel.PredictionResourcesCase getPredictionResourcesCase()
Returns
TypeDescription
DeployedModel.PredictionResourcesCase

getPrivateEndpoints()

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.v1beta1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
TypeDescription
PrivateEndpoints

The privateEndpoints.

getPrivateEndpointsOrBuilder()

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.v1beta1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
TypeDescription
PrivateEndpointsOrBuilder

getSerializedSize()

public int getSerializedSize()
Returns
TypeDescription
int
Overrides

getServiceAccount()

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;

Returns
TypeDescription
String

The serviceAccount.

getServiceAccountBytes()

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;

Returns
TypeDescription
ByteString

The bytes for serviceAccount.

getUnknownFields()

public final UnknownFieldSet getUnknownFields()
Returns
TypeDescription
UnknownFieldSet
Overrides

hasAutomaticResources()

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.v1beta1.AutomaticResources automatic_resources = 8;

Returns
TypeDescription
boolean

Whether the automaticResources field is set.

hasCreateTime()

public boolean hasCreateTime()

Output only. Timestamp when the DeployedModel was created.

.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
TypeDescription
boolean

Whether the createTime field is set.

hasDedicatedResources()

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.v1beta1.DedicatedResources dedicated_resources = 7;

Returns
TypeDescription
boolean

Whether the dedicatedResources field is set.

hasExplanationSpec()

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.v1beta1.ExplanationSpec explanation_spec = 9;

Returns
TypeDescription
boolean

Whether the explanationSpec field is set.

hasPrivateEndpoints()

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.v1beta1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
TypeDescription
boolean

Whether the privateEndpoints field is set.

hashCode()

public int hashCode()
Returns
TypeDescription
int
Overrides

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

newBuilderForType()

public DeployedModel.Builder newBuilderForType()
Returns
TypeDescription
DeployedModel.Builder

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

protected DeployedModel.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Parameter
NameDescription
parentBuilderParent
Returns
TypeDescription
DeployedModel.Builder
Overrides

newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Parameter
NameDescription
unusedUnusedPrivateParameter
Returns
TypeDescription
Object
Overrides

toBuilder()

public DeployedModel.Builder toBuilder()
Returns
TypeDescription
DeployedModel.Builder

writeTo(CodedOutputStream output)

public void writeTo(CodedOutputStream output)
Parameter
NameDescription
outputCodedOutputStream
Overrides Exceptions
TypeDescription
IOException