Package com.google.cloud.aiplatform.v1

Class DedicatedResources.Builder

  • All Implemented Interfaces:
    DedicatedResourcesOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
    Enclosing class:
    DedicatedResources
    public static final class DedicatedResources.Builder
extends com.google.protobuf.GeneratedMessageV3.Builder<DedicatedResources.Builder>
implements DedicatedResourcesOrBuilder
     A description of resources that are dedicated to a DeployedModel, and
 that need a higher degree of manual configuration.
    Protobuf type google.cloud.aiplatform.v1.DedicatedResources

    • Method Detail

      • getDescriptor

        public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<DedicatedResources.Builder>

      • clear

        public DedicatedResources.Builder clear()
        Specified by:
        clear in interface com.google.protobuf.Message.Builder
        Specified by:
        clear in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        clear in class com.google.protobuf.GeneratedMessageV3.Builder<DedicatedResources.Builder>

      • getDescriptorForType

        public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
        Specified by:
        getDescriptorForType in interface com.google.protobuf.Message.Builder
        Specified by:
        getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
        Overrides:
        getDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<DedicatedResources.Builder>

      • getDefaultInstanceForType

        public DedicatedResources getDefaultInstanceForType()
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

      • build

        public DedicatedResources build()
        Specified by:
        build in interface com.google.protobuf.Message.Builder
        Specified by:
        build in interface com.google.protobuf.MessageLite.Builder

      • buildPartial

        public DedicatedResources buildPartial()
        Specified by:
        buildPartial in interface com.google.protobuf.Message.Builder
        Specified by:
        buildPartial in interface com.google.protobuf.MessageLite.Builder

      • clone

        public DedicatedResources.Builder clone()
        Specified by:
        clone in interface com.google.protobuf.Message.Builder
        Specified by:
        clone in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        clone in class com.google.protobuf.GeneratedMessageV3.Builder<DedicatedResources.Builder>

      • setField

        public DedicatedResources.Builder setField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                           Object value)
        Specified by:
        setField in interface com.google.protobuf.Message.Builder
        Overrides:
        setField in class com.google.protobuf.GeneratedMessageV3.Builder<DedicatedResources.Builder>

      • clearField

        public DedicatedResources.Builder clearField​(com.google.protobuf.Descriptors.FieldDescriptor field)
        Specified by:
        clearField in interface com.google.protobuf.Message.Builder
        Overrides:
        clearField in class com.google.protobuf.GeneratedMessageV3.Builder<DedicatedResources.Builder>

      • clearOneof

        public DedicatedResources.Builder clearOneof​(com.google.protobuf.Descriptors.OneofDescriptor oneof)
        Specified by:
        clearOneof in interface com.google.protobuf.Message.Builder
        Overrides:
        clearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<DedicatedResources.Builder>

      • setRepeatedField

        public DedicatedResources.Builder setRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                   int index,
                                                   Object value)
        Specified by:
        setRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        setRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<DedicatedResources.Builder>

      • addRepeatedField

        public DedicatedResources.Builder addRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                   Object value)
        Specified by:
        addRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        addRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<DedicatedResources.Builder>

      • mergeFrom

        public DedicatedResources.Builder mergeFrom​(com.google.protobuf.Message other)
        Specified by:
        mergeFrom in interface com.google.protobuf.Message.Builder
        Overrides:
        mergeFrom in class com.google.protobuf.AbstractMessage.Builder<DedicatedResources.Builder>

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<DedicatedResources.Builder>

      • mergeFrom

        public DedicatedResources.Builder mergeFrom​(com.google.protobuf.CodedInputStream input,
                                            com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                     throws IOException
        Specified by:
        mergeFrom in interface com.google.protobuf.Message.Builder
        Specified by:
        mergeFrom in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        mergeFrom in class com.google.protobuf.AbstractMessage.Builder<DedicatedResources.Builder>
        Throws:
        IOException

      • hasMachineSpec

        public boolean hasMachineSpec()
         Required. Immutable. The specification of a single machine used by the
 prediction.
        .google.cloud.aiplatform.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        hasMachineSpec in interface DedicatedResourcesOrBuilder
        Returns:
        Whether the machineSpec field is set.

      • getMachineSpec

        public MachineSpec getMachineSpec()
         Required. Immutable. The specification of a single machine used by the
 prediction.
        .google.cloud.aiplatform.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getMachineSpec in interface DedicatedResourcesOrBuilder
        Returns:
        The machineSpec.

      • setMachineSpec

        public DedicatedResources.Builder setMachineSpec​(MachineSpec value)
         Required. Immutable. The specification of a single machine used by the
 prediction.
        .google.cloud.aiplatform.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];

      • setMachineSpec

        public DedicatedResources.Builder setMachineSpec​(MachineSpec.Builder builderForValue)
         Required. Immutable. The specification of a single machine used by the
 prediction.
        .google.cloud.aiplatform.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];

      • mergeMachineSpec

        public DedicatedResources.Builder mergeMachineSpec​(MachineSpec value)
         Required. Immutable. The specification of a single machine used by the
 prediction.
        .google.cloud.aiplatform.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];

      • clearMachineSpec

        public DedicatedResources.Builder clearMachineSpec()
         Required. Immutable. The specification of a single machine used by the
 prediction.
        .google.cloud.aiplatform.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];

      • getMachineSpecBuilder

        public MachineSpec.Builder getMachineSpecBuilder()
         Required. Immutable. The specification of a single machine used by the
 prediction.
        .google.cloud.aiplatform.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];

      • getMachineSpecOrBuilder

        public MachineSpecOrBuilder getMachineSpecOrBuilder()
         Required. Immutable. The specification of a single machine used by the
 prediction.
        .google.cloud.aiplatform.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getMachineSpecOrBuilder in interface DedicatedResourcesOrBuilder

      • getMinReplicaCount

        public int getMinReplicaCount()
         Required. Immutable. The minimum number of machine replicas this
 DeployedModel will be always deployed on. This value must be greater than
 or equal to 1.

 If traffic against the DeployedModel increases, it may dynamically be
 deployed onto more replicas, and as traffic decreases, some of these extra
 replicas may be freed.
        int32 min_replica_count = 2 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getMinReplicaCount in interface DedicatedResourcesOrBuilder
        Returns:
        The minReplicaCount.

      • setMinReplicaCount

        public DedicatedResources.Builder setMinReplicaCount​(int value)
         Required. Immutable. The minimum number of machine replicas this
 DeployedModel will be always deployed on. This value must be greater than
 or equal to 1.

 If traffic against the DeployedModel increases, it may dynamically be
 deployed onto more replicas, and as traffic decreases, some of these extra
 replicas may be freed.
        int32 min_replica_count = 2 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
        Parameters:
        value - The minReplicaCount to set.
        Returns:
        This builder for chaining.

      • clearMinReplicaCount

        public DedicatedResources.Builder clearMinReplicaCount()
         Required. Immutable. The minimum number of machine replicas this
 DeployedModel will be always deployed on. This value must be greater than
 or equal to 1.

 If traffic against the DeployedModel increases, it may dynamically be
 deployed onto more replicas, and as traffic decreases, some of these extra
 replicas may be freed.
        int32 min_replica_count = 2 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
        Returns:
        This builder for chaining.

      • getMaxReplicaCount

        public int getMaxReplicaCount()
         Immutable. The maximum number of replicas this DeployedModel may be
 deployed on when the traffic against it increases. If the requested value
 is too large, the deployment will error, but if deployment succeeds then
 the ability to scale the model to that many replicas is guaranteed (barring
 service outages). If traffic against the DeployedModel increases beyond
 what its replicas at maximum may handle, a portion of the traffic will be
 dropped. If this value is not provided, will use
 [min_replica_count][google.cloud.aiplatform.v1.DedicatedResources.min_replica_count]
 as the default value.

 The value of this field impacts the charge against Vertex CPU and GPU
 quotas. Specifically, you will be charged for (max_replica_count *
 number of cores in the selected machine type) and (max_replica_count *
 number of GPUs per replica in the selected machine type).
        int32 max_replica_count = 3 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getMaxReplicaCount in interface DedicatedResourcesOrBuilder
        Returns:
        The maxReplicaCount.

      • setMaxReplicaCount

        public DedicatedResources.Builder setMaxReplicaCount​(int value)
         Immutable. The maximum number of replicas this DeployedModel may be
 deployed on when the traffic against it increases. If the requested value
 is too large, the deployment will error, but if deployment succeeds then
 the ability to scale the model to that many replicas is guaranteed (barring
 service outages). If traffic against the DeployedModel increases beyond
 what its replicas at maximum may handle, a portion of the traffic will be
 dropped. If this value is not provided, will use
 [min_replica_count][google.cloud.aiplatform.v1.DedicatedResources.min_replica_count]
 as the default value.

 The value of this field impacts the charge against Vertex CPU and GPU
 quotas. Specifically, you will be charged for (max_replica_count *
 number of cores in the selected machine type) and (max_replica_count *
 number of GPUs per replica in the selected machine type).
        int32 max_replica_count = 3 [(.google.api.field_behavior) = IMMUTABLE];
        Parameters:
        value - The maxReplicaCount to set.
        Returns:
        This builder for chaining.

      • clearMaxReplicaCount

        public DedicatedResources.Builder clearMaxReplicaCount()
         Immutable. The maximum number of replicas this DeployedModel may be
 deployed on when the traffic against it increases. If the requested value
 is too large, the deployment will error, but if deployment succeeds then
 the ability to scale the model to that many replicas is guaranteed (barring
 service outages). If traffic against the DeployedModel increases beyond
 what its replicas at maximum may handle, a portion of the traffic will be
 dropped. If this value is not provided, will use
 [min_replica_count][google.cloud.aiplatform.v1.DedicatedResources.min_replica_count]
 as the default value.

 The value of this field impacts the charge against Vertex CPU and GPU
 quotas. Specifically, you will be charged for (max_replica_count *
 number of cores in the selected machine type) and (max_replica_count *
 number of GPUs per replica in the selected machine type).
        int32 max_replica_count = 3 [(.google.api.field_behavior) = IMMUTABLE];
        Returns:
        This builder for chaining.

      • getAutoscalingMetricSpecsList

        public List<AutoscalingMetricSpec> getAutoscalingMetricSpecsList()
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getAutoscalingMetricSpecsList in interface DedicatedResourcesOrBuilder

      • getAutoscalingMetricSpecsCount

        public int getAutoscalingMetricSpecsCount()
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getAutoscalingMetricSpecsCount in interface DedicatedResourcesOrBuilder

      • getAutoscalingMetricSpecs

        public AutoscalingMetricSpec getAutoscalingMetricSpecs​(int index)
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getAutoscalingMetricSpecs in interface DedicatedResourcesOrBuilder

      • setAutoscalingMetricSpecs

        public DedicatedResources.Builder setAutoscalingMetricSpecs​(int index,
                                                            AutoscalingMetricSpec value)
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • setAutoscalingMetricSpecs

        public DedicatedResources.Builder setAutoscalingMetricSpecs​(int index,
                                                            AutoscalingMetricSpec.Builder builderForValue)
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • addAutoscalingMetricSpecs

        public DedicatedResources.Builder addAutoscalingMetricSpecs​(AutoscalingMetricSpec value)
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • addAutoscalingMetricSpecs

        public DedicatedResources.Builder addAutoscalingMetricSpecs​(int index,
                                                            AutoscalingMetricSpec value)
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • addAutoscalingMetricSpecs

        public DedicatedResources.Builder addAutoscalingMetricSpecs​(AutoscalingMetricSpec.Builder builderForValue)
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • addAutoscalingMetricSpecs

        public DedicatedResources.Builder addAutoscalingMetricSpecs​(int index,
                                                            AutoscalingMetricSpec.Builder builderForValue)
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • addAllAutoscalingMetricSpecs

        public DedicatedResources.Builder addAllAutoscalingMetricSpecs​(Iterable<? extends AutoscalingMetricSpec> values)
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • clearAutoscalingMetricSpecs

        public DedicatedResources.Builder clearAutoscalingMetricSpecs()
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • removeAutoscalingMetricSpecs

        public DedicatedResources.Builder removeAutoscalingMetricSpecs​(int index)
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • getAutoscalingMetricSpecsBuilder

        public AutoscalingMetricSpec.Builder getAutoscalingMetricSpecsBuilder​(int index)
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • getAutoscalingMetricSpecsOrBuilder

        public AutoscalingMetricSpecOrBuilder getAutoscalingMetricSpecsOrBuilder​(int index)
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getAutoscalingMetricSpecsOrBuilder in interface DedicatedResourcesOrBuilder

      • getAutoscalingMetricSpecsOrBuilderList

        public List<? extends AutoscalingMetricSpecOrBuilder> getAutoscalingMetricSpecsOrBuilderList()
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getAutoscalingMetricSpecsOrBuilderList in interface DedicatedResourcesOrBuilder

      • addAutoscalingMetricSpecsBuilder

        public AutoscalingMetricSpec.Builder addAutoscalingMetricSpecsBuilder()
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • addAutoscalingMetricSpecsBuilder

        public AutoscalingMetricSpec.Builder addAutoscalingMetricSpecsBuilder​(int index)
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • getAutoscalingMetricSpecsBuilderList

        public List<AutoscalingMetricSpec.Builder> getAutoscalingMetricSpecsBuilderList()
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • setUnknownFields

        public final DedicatedResources.Builder setUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        setUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        setUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<DedicatedResources.Builder>

      • mergeUnknownFields

        public final DedicatedResources.Builder mergeUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        mergeUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        mergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<DedicatedResources.Builder>