com.google.cloud.visionai.v1.DedicatedResources Maven / Gradle / Ivy
/*
* Copyright 2024 Google LLC
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: google/cloud/visionai/v1/platform.proto
// Protobuf Java Version: 3.25.3
package com.google.cloud.visionai.v1;
/**
*
*
*
* A description of resources that are dedicated to a DeployedModel, and
* that need a higher degree of manual configuration.
*
*
* Protobuf type {@code google.cloud.visionai.v1.DedicatedResources}
*/
public final class DedicatedResources extends com.google.protobuf.GeneratedMessageV3
implements
// @@protoc_insertion_point(message_implements:google.cloud.visionai.v1.DedicatedResources)
DedicatedResourcesOrBuilder {
private static final long serialVersionUID = 0L;
// Use DedicatedResources.newBuilder() to construct.
private DedicatedResources(com.google.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
}
private DedicatedResources() {
autoscalingMetricSpecs_ = java.util.Collections.emptyList();
}
@java.lang.Override
@SuppressWarnings({"unused"})
protected java.lang.Object newInstance(UnusedPrivateParameter unused) {
return new DedicatedResources();
}
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
return com.google.cloud.visionai.v1.PlatformProto
.internal_static_google_cloud_visionai_v1_DedicatedResources_descriptor;
}
@java.lang.Override
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return com.google.cloud.visionai.v1.PlatformProto
.internal_static_google_cloud_visionai_v1_DedicatedResources_fieldAccessorTable
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com.google.cloud.visionai.v1.DedicatedResources.class,
com.google.cloud.visionai.v1.DedicatedResources.Builder.class);
}
private int bitField0_;
public static final int MACHINE_SPEC_FIELD_NUMBER = 1;
private com.google.cloud.visionai.v1.MachineSpec machineSpec_;
/**
*
*
*
* Required. Immutable. The specification of a single machine used by the
* prediction.
*
*
*
* .google.cloud.visionai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
*
*
* @return Whether the machineSpec field is set.
*/
@java.lang.Override
public boolean hasMachineSpec() {
return ((bitField0_ & 0x00000001) != 0);
}
/**
*
*
*
* Required. Immutable. The specification of a single machine used by the
* prediction.
*
*
*
* .google.cloud.visionai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
*
*
* @return The machineSpec.
*/
@java.lang.Override
public com.google.cloud.visionai.v1.MachineSpec getMachineSpec() {
return machineSpec_ == null
? com.google.cloud.visionai.v1.MachineSpec.getDefaultInstance()
: machineSpec_;
}
/**
*
*
*
* Required. Immutable. The specification of a single machine used by the
* prediction.
*
*
*
* .google.cloud.visionai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
*
*/
@java.lang.Override
public com.google.cloud.visionai.v1.MachineSpecOrBuilder getMachineSpecOrBuilder() {
return machineSpec_ == null
? com.google.cloud.visionai.v1.MachineSpec.getDefaultInstance()
: machineSpec_;
}
public static final int MIN_REPLICA_COUNT_FIELD_NUMBER = 2;
private int minReplicaCount_ = 0;
/**
*
*
*
* 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];
*
*
* @return The minReplicaCount.
*/
@java.lang.Override
public int getMinReplicaCount() {
return minReplicaCount_;
}
public static final int MAX_REPLICA_COUNT_FIELD_NUMBER = 3;
private int maxReplicaCount_ = 0;
/**
*
*
*
* 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.visionai.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];
*
* @return The maxReplicaCount.
*/
@java.lang.Override
public int getMaxReplicaCount() {
return maxReplicaCount_;
}
public static final int AUTOSCALING_METRIC_SPECS_FIELD_NUMBER = 4;
@SuppressWarnings("serial")
private java.util.List
autoscalingMetricSpecs_;
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
@java.lang.Override
public java.util.List
getAutoscalingMetricSpecsList() {
return autoscalingMetricSpecs_;
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
@java.lang.Override
public java.util.List
getAutoscalingMetricSpecsOrBuilderList() {
return autoscalingMetricSpecs_;
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
@java.lang.Override
public int getAutoscalingMetricSpecsCount() {
return autoscalingMetricSpecs_.size();
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
@java.lang.Override
public com.google.cloud.visionai.v1.AutoscalingMetricSpec getAutoscalingMetricSpecs(int index) {
return autoscalingMetricSpecs_.get(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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
@java.lang.Override
public com.google.cloud.visionai.v1.AutoscalingMetricSpecOrBuilder
getAutoscalingMetricSpecsOrBuilder(int index) {
return autoscalingMetricSpecs_.get(index);
}
private byte memoizedIsInitialized = -1;
@java.lang.Override
public final boolean isInitialized() {
byte isInitialized = memoizedIsInitialized;
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if (isInitialized == 0) return false;
memoizedIsInitialized = 1;
return true;
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}
if (minReplicaCount_ != 0) {
output.writeInt32(2, minReplicaCount_);
}
if (maxReplicaCount_ != 0) {
output.writeInt32(3, maxReplicaCount_);
}
for (int i = 0; i < autoscalingMetricSpecs_.size(); i++) {
output.writeMessage(4, autoscalingMetricSpecs_.get(i));
}
getUnknownFields().writeTo(output);
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@java.lang.Override
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size = 0;
if (((bitField0_ & 0x00000001) != 0)) {
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size += getUnknownFields().getSerializedSize();
memoizedSize = size;
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@java.lang.Override
public boolean equals(final java.lang.Object obj) {
if (obj == this) {
return true;
}
if (!(obj instanceof com.google.cloud.visionai.v1.DedicatedResources)) {
return super.equals(obj);
}
com.google.cloud.visionai.v1.DedicatedResources other =
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if (hasMachineSpec() != other.hasMachineSpec()) return false;
if (hasMachineSpec()) {
if (!getMachineSpec().equals(other.getMachineSpec())) return false;
}
if (getMinReplicaCount() != other.getMinReplicaCount()) return false;
if (getMaxReplicaCount() != other.getMaxReplicaCount()) return false;
if (!getAutoscalingMetricSpecsList().equals(other.getAutoscalingMetricSpecsList()))
return false;
if (!getUnknownFields().equals(other.getUnknownFields())) return false;
return true;
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public int hashCode() {
if (memoizedHashCode != 0) {
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int hash = 41;
hash = (19 * hash) + getDescriptor().hashCode();
if (hasMachineSpec()) {
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hash = (53 * hash) + getMachineSpec().hashCode();
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hash = (37 * hash) + MIN_REPLICA_COUNT_FIELD_NUMBER;
hash = (53 * hash) + getMinReplicaCount();
hash = (37 * hash) + MAX_REPLICA_COUNT_FIELD_NUMBER;
hash = (53 * hash) + getMaxReplicaCount();
if (getAutoscalingMetricSpecsCount() > 0) {
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hash = (53 * hash) + getAutoscalingMetricSpecsList().hashCode();
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hash = (29 * hash) + getUnknownFields().hashCode();
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return hash;
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public static com.google.cloud.visionai.v1.DedicatedResources parseFrom(java.nio.ByteBuffer data)
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public static com.google.cloud.visionai.v1.DedicatedResources parseFrom(
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/**
*
*
*
* A description of resources that are dedicated to a DeployedModel, and
* that need a higher degree of manual configuration.
*
*
* Protobuf type {@code google.cloud.visionai.v1.DedicatedResources}
*/
public static final class Builder extends com.google.protobuf.GeneratedMessageV3.Builder
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// @@protoc_insertion_point(builder_implements:google.cloud.visionai.v1.DedicatedResources)
com.google.cloud.visionai.v1.DedicatedResourcesOrBuilder {
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
return com.google.cloud.visionai.v1.PlatformProto
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com.google.protobuf.Descriptors.FieldDescriptor field, int index, java.lang.Object value) {
return super.setRepeatedField(field, index, value);
}
@java.lang.Override
public Builder addRepeatedField(
com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value) {
return super.addRepeatedField(field, value);
}
@java.lang.Override
public Builder mergeFrom(com.google.protobuf.Message other) {
if (other instanceof com.google.cloud.visionai.v1.DedicatedResources) {
return mergeFrom((com.google.cloud.visionai.v1.DedicatedResources) other);
} else {
super.mergeFrom(other);
return this;
}
}
public Builder mergeFrom(com.google.cloud.visionai.v1.DedicatedResources other) {
if (other == com.google.cloud.visionai.v1.DedicatedResources.getDefaultInstance())
return this;
if (other.hasMachineSpec()) {
mergeMachineSpec(other.getMachineSpec());
}
if (other.getMinReplicaCount() != 0) {
setMinReplicaCount(other.getMinReplicaCount());
}
if (other.getMaxReplicaCount() != 0) {
setMaxReplicaCount(other.getMaxReplicaCount());
}
if (autoscalingMetricSpecsBuilder_ == null) {
if (!other.autoscalingMetricSpecs_.isEmpty()) {
if (autoscalingMetricSpecs_.isEmpty()) {
autoscalingMetricSpecs_ = other.autoscalingMetricSpecs_;
bitField0_ = (bitField0_ & ~0x00000008);
} else {
ensureAutoscalingMetricSpecsIsMutable();
autoscalingMetricSpecs_.addAll(other.autoscalingMetricSpecs_);
}
onChanged();
}
} else {
if (!other.autoscalingMetricSpecs_.isEmpty()) {
if (autoscalingMetricSpecsBuilder_.isEmpty()) {
autoscalingMetricSpecsBuilder_.dispose();
autoscalingMetricSpecsBuilder_ = null;
autoscalingMetricSpecs_ = other.autoscalingMetricSpecs_;
bitField0_ = (bitField0_ & ~0x00000008);
autoscalingMetricSpecsBuilder_ =
com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders
? getAutoscalingMetricSpecsFieldBuilder()
: null;
} else {
autoscalingMetricSpecsBuilder_.addAllMessages(other.autoscalingMetricSpecs_);
}
}
}
this.mergeUnknownFields(other.getUnknownFields());
onChanged();
return this;
}
@java.lang.Override
public final boolean isInitialized() {
return true;
}
@java.lang.Override
public Builder mergeFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
if (extensionRegistry == null) {
throw new java.lang.NullPointerException();
}
try {
boolean done = false;
while (!done) {
int tag = input.readTag();
switch (tag) {
case 0:
done = true;
break;
case 10:
{
input.readMessage(getMachineSpecFieldBuilder().getBuilder(), extensionRegistry);
bitField0_ |= 0x00000001;
break;
} // case 10
case 16:
{
minReplicaCount_ = input.readInt32();
bitField0_ |= 0x00000002;
break;
} // case 16
case 24:
{
maxReplicaCount_ = input.readInt32();
bitField0_ |= 0x00000004;
break;
} // case 24
case 34:
{
com.google.cloud.visionai.v1.AutoscalingMetricSpec m =
input.readMessage(
com.google.cloud.visionai.v1.AutoscalingMetricSpec.parser(),
extensionRegistry);
if (autoscalingMetricSpecsBuilder_ == null) {
ensureAutoscalingMetricSpecsIsMutable();
autoscalingMetricSpecs_.add(m);
} else {
autoscalingMetricSpecsBuilder_.addMessage(m);
}
break;
} // case 34
default:
{
if (!super.parseUnknownField(input, extensionRegistry, tag)) {
done = true; // was an endgroup tag
}
break;
} // default:
} // switch (tag)
} // while (!done)
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
throw e.unwrapIOException();
} finally {
onChanged();
} // finally
return this;
}
private int bitField0_;
private com.google.cloud.visionai.v1.MachineSpec machineSpec_;
private com.google.protobuf.SingleFieldBuilderV3<
com.google.cloud.visionai.v1.MachineSpec,
com.google.cloud.visionai.v1.MachineSpec.Builder,
com.google.cloud.visionai.v1.MachineSpecOrBuilder>
machineSpecBuilder_;
/**
*
*
*
* Required. Immutable. The specification of a single machine used by the
* prediction.
*
*
*
* .google.cloud.visionai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
*
*
* @return Whether the machineSpec field is set.
*/
public boolean hasMachineSpec() {
return ((bitField0_ & 0x00000001) != 0);
}
/**
*
*
*
* Required. Immutable. The specification of a single machine used by the
* prediction.
*
*
*
* .google.cloud.visionai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
*
*
* @return The machineSpec.
*/
public com.google.cloud.visionai.v1.MachineSpec getMachineSpec() {
if (machineSpecBuilder_ == null) {
return machineSpec_ == null
? com.google.cloud.visionai.v1.MachineSpec.getDefaultInstance()
: machineSpec_;
} else {
return machineSpecBuilder_.getMessage();
}
}
/**
*
*
*
* Required. Immutable. The specification of a single machine used by the
* prediction.
*
*
*
* .google.cloud.visionai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
*
*/
public Builder setMachineSpec(com.google.cloud.visionai.v1.MachineSpec value) {
if (machineSpecBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
machineSpec_ = value;
} else {
machineSpecBuilder_.setMessage(value);
}
bitField0_ |= 0x00000001;
onChanged();
return this;
}
/**
*
*
*
* Required. Immutable. The specification of a single machine used by the
* prediction.
*
*
*
* .google.cloud.visionai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
*
*/
public Builder setMachineSpec(
com.google.cloud.visionai.v1.MachineSpec.Builder builderForValue) {
if (machineSpecBuilder_ == null) {
machineSpec_ = builderForValue.build();
} else {
machineSpecBuilder_.setMessage(builderForValue.build());
}
bitField0_ |= 0x00000001;
onChanged();
return this;
}
/**
*
*
*
* Required. Immutable. The specification of a single machine used by the
* prediction.
*
*
*
* .google.cloud.visionai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
*
*/
public Builder mergeMachineSpec(com.google.cloud.visionai.v1.MachineSpec value) {
if (machineSpecBuilder_ == null) {
if (((bitField0_ & 0x00000001) != 0)
&& machineSpec_ != null
&& machineSpec_ != com.google.cloud.visionai.v1.MachineSpec.getDefaultInstance()) {
getMachineSpecBuilder().mergeFrom(value);
} else {
machineSpec_ = value;
}
} else {
machineSpecBuilder_.mergeFrom(value);
}
if (machineSpec_ != null) {
bitField0_ |= 0x00000001;
onChanged();
}
return this;
}
/**
*
*
*
* Required. Immutable. The specification of a single machine used by the
* prediction.
*
*
*
* .google.cloud.visionai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
*
*/
public Builder clearMachineSpec() {
bitField0_ = (bitField0_ & ~0x00000001);
machineSpec_ = null;
if (machineSpecBuilder_ != null) {
machineSpecBuilder_.dispose();
machineSpecBuilder_ = null;
}
onChanged();
return this;
}
/**
*
*
*
* Required. Immutable. The specification of a single machine used by the
* prediction.
*
*
*
* .google.cloud.visionai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
*
*/
public com.google.cloud.visionai.v1.MachineSpec.Builder getMachineSpecBuilder() {
bitField0_ |= 0x00000001;
onChanged();
return getMachineSpecFieldBuilder().getBuilder();
}
/**
*
*
*
* Required. Immutable. The specification of a single machine used by the
* prediction.
*
*
*
* .google.cloud.visionai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
*
*/
public com.google.cloud.visionai.v1.MachineSpecOrBuilder getMachineSpecOrBuilder() {
if (machineSpecBuilder_ != null) {
return machineSpecBuilder_.getMessageOrBuilder();
} else {
return machineSpec_ == null
? com.google.cloud.visionai.v1.MachineSpec.getDefaultInstance()
: machineSpec_;
}
}
/**
*
*
*
* Required. Immutable. The specification of a single machine used by the
* prediction.
*
*
*
* .google.cloud.visionai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
*
*/
private com.google.protobuf.SingleFieldBuilderV3<
com.google.cloud.visionai.v1.MachineSpec,
com.google.cloud.visionai.v1.MachineSpec.Builder,
com.google.cloud.visionai.v1.MachineSpecOrBuilder>
getMachineSpecFieldBuilder() {
if (machineSpecBuilder_ == null) {
machineSpecBuilder_ =
new com.google.protobuf.SingleFieldBuilderV3<
com.google.cloud.visionai.v1.MachineSpec,
com.google.cloud.visionai.v1.MachineSpec.Builder,
com.google.cloud.visionai.v1.MachineSpecOrBuilder>(
getMachineSpec(), getParentForChildren(), isClean());
machineSpec_ = null;
}
return machineSpecBuilder_;
}
private int minReplicaCount_;
/**
*
*
*
* 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];
*
*
* @return The minReplicaCount.
*/
@java.lang.Override
public int getMinReplicaCount() {
return minReplicaCount_;
}
/**
*
*
*
* 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];
*
*
* @param value The minReplicaCount to set.
* @return This builder for chaining.
*/
public Builder setMinReplicaCount(int value) {
minReplicaCount_ = value;
bitField0_ |= 0x00000002;
onChanged();
return this;
}
/**
*
*
*
* 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];
*
*
* @return This builder for chaining.
*/
public Builder clearMinReplicaCount() {
bitField0_ = (bitField0_ & ~0x00000002);
minReplicaCount_ = 0;
onChanged();
return this;
}
private int maxReplicaCount_;
/**
*
*
*
* 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.visionai.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];
*
* @return The maxReplicaCount.
*/
@java.lang.Override
public int getMaxReplicaCount() {
return maxReplicaCount_;
}
/**
*
*
*
* 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.visionai.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];
*
* @param value The maxReplicaCount to set.
* @return This builder for chaining.
*/
public Builder setMaxReplicaCount(int value) {
maxReplicaCount_ = value;
bitField0_ |= 0x00000004;
onChanged();
return this;
}
/**
*
*
*
* 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.visionai.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];
*
* @return This builder for chaining.
*/
public Builder clearMaxReplicaCount() {
bitField0_ = (bitField0_ & ~0x00000004);
maxReplicaCount_ = 0;
onChanged();
return this;
}
private java.util.List
autoscalingMetricSpecs_ = java.util.Collections.emptyList();
private void ensureAutoscalingMetricSpecsIsMutable() {
if (!((bitField0_ & 0x00000008) != 0)) {
autoscalingMetricSpecs_ =
new java.util.ArrayList(
autoscalingMetricSpecs_);
bitField0_ |= 0x00000008;
}
}
private com.google.protobuf.RepeatedFieldBuilderV3<
com.google.cloud.visionai.v1.AutoscalingMetricSpec,
com.google.cloud.visionai.v1.AutoscalingMetricSpec.Builder,
com.google.cloud.visionai.v1.AutoscalingMetricSpecOrBuilder>
autoscalingMetricSpecsBuilder_;
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public java.util.List
getAutoscalingMetricSpecsList() {
if (autoscalingMetricSpecsBuilder_ == null) {
return java.util.Collections.unmodifiableList(autoscalingMetricSpecs_);
} else {
return autoscalingMetricSpecsBuilder_.getMessageList();
}
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public int getAutoscalingMetricSpecsCount() {
if (autoscalingMetricSpecsBuilder_ == null) {
return autoscalingMetricSpecs_.size();
} else {
return autoscalingMetricSpecsBuilder_.getCount();
}
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public com.google.cloud.visionai.v1.AutoscalingMetricSpec getAutoscalingMetricSpecs(int index) {
if (autoscalingMetricSpecsBuilder_ == null) {
return autoscalingMetricSpecs_.get(index);
} else {
return autoscalingMetricSpecsBuilder_.getMessage(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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public Builder setAutoscalingMetricSpecs(
int index, com.google.cloud.visionai.v1.AutoscalingMetricSpec value) {
if (autoscalingMetricSpecsBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureAutoscalingMetricSpecsIsMutable();
autoscalingMetricSpecs_.set(index, value);
onChanged();
} else {
autoscalingMetricSpecsBuilder_.setMessage(index, value);
}
return this;
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public Builder setAutoscalingMetricSpecs(
int index, com.google.cloud.visionai.v1.AutoscalingMetricSpec.Builder builderForValue) {
if (autoscalingMetricSpecsBuilder_ == null) {
ensureAutoscalingMetricSpecsIsMutable();
autoscalingMetricSpecs_.set(index, builderForValue.build());
onChanged();
} else {
autoscalingMetricSpecsBuilder_.setMessage(index, builderForValue.build());
}
return this;
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public Builder addAutoscalingMetricSpecs(
com.google.cloud.visionai.v1.AutoscalingMetricSpec value) {
if (autoscalingMetricSpecsBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureAutoscalingMetricSpecsIsMutable();
autoscalingMetricSpecs_.add(value);
onChanged();
} else {
autoscalingMetricSpecsBuilder_.addMessage(value);
}
return this;
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public Builder addAutoscalingMetricSpecs(
int index, com.google.cloud.visionai.v1.AutoscalingMetricSpec value) {
if (autoscalingMetricSpecsBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureAutoscalingMetricSpecsIsMutable();
autoscalingMetricSpecs_.add(index, value);
onChanged();
} else {
autoscalingMetricSpecsBuilder_.addMessage(index, value);
}
return this;
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public Builder addAutoscalingMetricSpecs(
com.google.cloud.visionai.v1.AutoscalingMetricSpec.Builder builderForValue) {
if (autoscalingMetricSpecsBuilder_ == null) {
ensureAutoscalingMetricSpecsIsMutable();
autoscalingMetricSpecs_.add(builderForValue.build());
onChanged();
} else {
autoscalingMetricSpecsBuilder_.addMessage(builderForValue.build());
}
return this;
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public Builder addAutoscalingMetricSpecs(
int index, com.google.cloud.visionai.v1.AutoscalingMetricSpec.Builder builderForValue) {
if (autoscalingMetricSpecsBuilder_ == null) {
ensureAutoscalingMetricSpecsIsMutable();
autoscalingMetricSpecs_.add(index, builderForValue.build());
onChanged();
} else {
autoscalingMetricSpecsBuilder_.addMessage(index, builderForValue.build());
}
return this;
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public Builder addAllAutoscalingMetricSpecs(
java.lang.Iterable values) {
if (autoscalingMetricSpecsBuilder_ == null) {
ensureAutoscalingMetricSpecsIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(values, autoscalingMetricSpecs_);
onChanged();
} else {
autoscalingMetricSpecsBuilder_.addAllMessages(values);
}
return this;
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public Builder clearAutoscalingMetricSpecs() {
if (autoscalingMetricSpecsBuilder_ == null) {
autoscalingMetricSpecs_ = java.util.Collections.emptyList();
bitField0_ = (bitField0_ & ~0x00000008);
onChanged();
} else {
autoscalingMetricSpecsBuilder_.clear();
}
return this;
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public Builder removeAutoscalingMetricSpecs(int index) {
if (autoscalingMetricSpecsBuilder_ == null) {
ensureAutoscalingMetricSpecsIsMutable();
autoscalingMetricSpecs_.remove(index);
onChanged();
} else {
autoscalingMetricSpecsBuilder_.remove(index);
}
return this;
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public com.google.cloud.visionai.v1.AutoscalingMetricSpec.Builder
getAutoscalingMetricSpecsBuilder(int index) {
return getAutoscalingMetricSpecsFieldBuilder().getBuilder(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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public com.google.cloud.visionai.v1.AutoscalingMetricSpecOrBuilder
getAutoscalingMetricSpecsOrBuilder(int index) {
if (autoscalingMetricSpecsBuilder_ == null) {
return autoscalingMetricSpecs_.get(index);
} else {
return autoscalingMetricSpecsBuilder_.getMessageOrBuilder(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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public java.util.List
getAutoscalingMetricSpecsOrBuilderList() {
if (autoscalingMetricSpecsBuilder_ != null) {
return autoscalingMetricSpecsBuilder_.getMessageOrBuilderList();
} else {
return java.util.Collections.unmodifiableList(autoscalingMetricSpecs_);
}
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public com.google.cloud.visionai.v1.AutoscalingMetricSpec.Builder
addAutoscalingMetricSpecsBuilder() {
return getAutoscalingMetricSpecsFieldBuilder()
.addBuilder(com.google.cloud.visionai.v1.AutoscalingMetricSpec.getDefaultInstance());
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public com.google.cloud.visionai.v1.AutoscalingMetricSpec.Builder
addAutoscalingMetricSpecsBuilder(int index) {
return getAutoscalingMetricSpecsFieldBuilder()
.addBuilder(
index, com.google.cloud.visionai.v1.AutoscalingMetricSpec.getDefaultInstance());
}
/**
*
*
*
* 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.visionai.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.visionai.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.visionai.v1.AutoscalingMetricSpec.metric_name]
* to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
* [autoscaling_metric_specs.target][google.cloud.visionai.v1.AutoscalingMetricSpec.target]
* to `80`.
*
*
*
* repeated .google.cloud.visionai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];
*
*/
public java.util.List
getAutoscalingMetricSpecsBuilderList() {
return getAutoscalingMetricSpecsFieldBuilder().getBuilderList();
}
private com.google.protobuf.RepeatedFieldBuilderV3<
com.google.cloud.visionai.v1.AutoscalingMetricSpec,
com.google.cloud.visionai.v1.AutoscalingMetricSpec.Builder,
com.google.cloud.visionai.v1.AutoscalingMetricSpecOrBuilder>
getAutoscalingMetricSpecsFieldBuilder() {
if (autoscalingMetricSpecsBuilder_ == null) {
autoscalingMetricSpecsBuilder_ =
new com.google.protobuf.RepeatedFieldBuilderV3<
com.google.cloud.visionai.v1.AutoscalingMetricSpec,
com.google.cloud.visionai.v1.AutoscalingMetricSpec.Builder,
com.google.cloud.visionai.v1.AutoscalingMetricSpecOrBuilder>(
autoscalingMetricSpecs_,
((bitField0_ & 0x00000008) != 0),
getParentForChildren(),
isClean());
autoscalingMetricSpecs_ = null;
}
return autoscalingMetricSpecsBuilder_;
}
@java.lang.Override
public final Builder setUnknownFields(final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFields(unknownFields);
}
@java.lang.Override
public final Builder mergeUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:google.cloud.visionai.v1.DedicatedResources)
}
// @@protoc_insertion_point(class_scope:google.cloud.visionai.v1.DedicatedResources)
private static final com.google.cloud.visionai.v1.DedicatedResources DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new com.google.cloud.visionai.v1.DedicatedResources();
}
public static com.google.cloud.visionai.v1.DedicatedResources getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final com.google.protobuf.Parser PARSER =
new com.google.protobuf.AbstractParser() {
@java.lang.Override
public DedicatedResources parsePartialFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
Builder builder = newBuilder();
try {
builder.mergeFrom(input, extensionRegistry);
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
throw e.setUnfinishedMessage(builder.buildPartial());
} catch (com.google.protobuf.UninitializedMessageException e) {
throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial());
} catch (java.io.IOException e) {
throw new com.google.protobuf.InvalidProtocolBufferException(e)
.setUnfinishedMessage(builder.buildPartial());
}
return builder.buildPartial();
}
};
public static com.google.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public com.google.protobuf.Parser getParserForType() {
return PARSER;
}
@java.lang.Override
public com.google.cloud.visionai.v1.DedicatedResources getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
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