Package com.google.cloud.aiplatform.v1beta1

Interface PublisherModel.CallToAction.DeployOrBuilder

    • Method Detail

      • hasDedicatedResources

        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 = 5;
        Returns:
        Whether the dedicatedResources field is set.

      • getDedicatedResources

        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 = 5;
        Returns:
        The dedicatedResources.

      • getDedicatedResourcesOrBuilder

        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 = 5;

      • hasAutomaticResources

        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 = 6;
        Returns:
        Whether the automaticResources field is set.

      • getAutomaticResources

        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 = 6;
        Returns:
        The automaticResources.

      • getAutomaticResourcesOrBuilder

        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 = 6;

      • hasSharedResources

        boolean hasSharedResources()
         The resource name of the shared DeploymentResourcePool to deploy on.
 Format:
 `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`
        string shared_resources = 7;
        Returns:
        Whether the sharedResources field is set.

      • getSharedResources

        String getSharedResources()
         The resource name of the shared DeploymentResourcePool to deploy on.
 Format:
 `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`
        string shared_resources = 7;
        Returns:
        The sharedResources.

      • getSharedResourcesBytes

        com.google.protobuf.ByteString getSharedResourcesBytes()
         The resource name of the shared DeploymentResourcePool to deploy on.
 Format:
 `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`
        string shared_resources = 7;
        Returns:
        The bytes for sharedResources.

      • getModelDisplayName

        String getModelDisplayName()
         Optional. Default model display name.
        string model_display_name = 1 [(.google.api.field_behavior) = OPTIONAL];
        Returns:
        The modelDisplayName.

      • getModelDisplayNameBytes

        com.google.protobuf.ByteString getModelDisplayNameBytes()
         Optional. Default model display name.
        string model_display_name = 1 [(.google.api.field_behavior) = OPTIONAL];
        Returns:
        The bytes for modelDisplayName.

      • hasLargeModelReference

        boolean hasLargeModelReference()
         Optional. Large model reference. When this is set, model_artifact_spec
 is not needed.
        .google.cloud.aiplatform.v1beta1.LargeModelReference large_model_reference = 2 [(.google.api.field_behavior) = OPTIONAL];
        Returns:
        Whether the largeModelReference field is set.

      • getLargeModelReference

        LargeModelReference getLargeModelReference()
         Optional. Large model reference. When this is set, model_artifact_spec
 is not needed.
        .google.cloud.aiplatform.v1beta1.LargeModelReference large_model_reference = 2 [(.google.api.field_behavior) = OPTIONAL];
        Returns:
        The largeModelReference.

      • getLargeModelReferenceOrBuilder

        LargeModelReferenceOrBuilder getLargeModelReferenceOrBuilder()
         Optional. Large model reference. When this is set, model_artifact_spec
 is not needed.
        .google.cloud.aiplatform.v1beta1.LargeModelReference large_model_reference = 2 [(.google.api.field_behavior) = OPTIONAL];

      • hasContainerSpec

        boolean hasContainerSpec()
         Optional. The specification of the container that is to be used when
 deploying this Model in Vertex AI. Not present for Large Models.
        .google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 3 [(.google.api.field_behavior) = OPTIONAL];
        Returns:
        Whether the containerSpec field is set.

      • getContainerSpec

        ModelContainerSpec getContainerSpec()
         Optional. The specification of the container that is to be used when
 deploying this Model in Vertex AI. Not present for Large Models.
        .google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 3 [(.google.api.field_behavior) = OPTIONAL];
        Returns:
        The containerSpec.

      • getContainerSpecOrBuilder

        ModelContainerSpecOrBuilder getContainerSpecOrBuilder()
         Optional. The specification of the container that is to be used when
 deploying this Model in Vertex AI. Not present for Large Models.
        .google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 3 [(.google.api.field_behavior) = OPTIONAL];

      • getArtifactUri

        String getArtifactUri()
         Optional. The path to the directory containing the Model artifact and
 any of its supporting files.
        string artifact_uri = 4 [(.google.api.field_behavior) = OPTIONAL];
        Returns:
        The artifactUri.

      • getArtifactUriBytes

        com.google.protobuf.ByteString getArtifactUriBytes()
         Optional. The path to the directory containing the Model artifact and
 any of its supporting files.
        string artifact_uri = 4 [(.google.api.field_behavior) = OPTIONAL];
        Returns:
        The bytes for artifactUri.

      • getTitle

        String getTitle()
         Required. The title of the regional resource reference.
        string title = 8 [(.google.api.field_behavior) = REQUIRED];
        Returns:
        The title.

      • getTitleBytes

        com.google.protobuf.ByteString getTitleBytes()
         Required. The title of the regional resource reference.
        string title = 8 [(.google.api.field_behavior) = REQUIRED];
        Returns:
        The bytes for title.