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PROTO library for proto-google-cloud-automl-v1beta1
/*
* 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/automl/v1beta1/regression.proto
// Protobuf Java Version: 3.25.3
package com.google.cloud.automl.v1beta1;
public final class RegressionProto {
private RegressionProto() {}
public static void registerAllExtensions(com.google.protobuf.ExtensionRegistryLite registry) {}
public static void registerAllExtensions(com.google.protobuf.ExtensionRegistry registry) {
registerAllExtensions((com.google.protobuf.ExtensionRegistryLite) registry);
}
public interface RegressionEvaluationMetricsOrBuilder
extends
// @@protoc_insertion_point(interface_extends:google.cloud.automl.v1beta1.RegressionEvaluationMetrics)
com.google.protobuf.MessageOrBuilder {
/**
*
*
*
* Output only. Root Mean Squared Error (RMSE).
*
*
* float root_mean_squared_error = 1;
*
* @return The rootMeanSquaredError.
*/
float getRootMeanSquaredError();
/**
*
*
*
* Output only. Mean Absolute Error (MAE).
*
*
* float mean_absolute_error = 2;
*
* @return The meanAbsoluteError.
*/
float getMeanAbsoluteError();
/**
*
*
*
* Output only. Mean absolute percentage error. Only set if all ground truth
* values are are positive.
*
*
* float mean_absolute_percentage_error = 3;
*
* @return The meanAbsolutePercentageError.
*/
float getMeanAbsolutePercentageError();
/**
*
*
*
* Output only. R squared.
*
*
* float r_squared = 4;
*
* @return The rSquared.
*/
float getRSquared();
/**
*
*
*
* Output only. Root mean squared log error.
*
*
* float root_mean_squared_log_error = 5;
*
* @return The rootMeanSquaredLogError.
*/
float getRootMeanSquaredLogError();
}
/**
*
*
*
* Metrics for regression problems.
*
*
* Protobuf type {@code google.cloud.automl.v1beta1.RegressionEvaluationMetrics}
*/
public static final class RegressionEvaluationMetrics
extends com.google.protobuf.GeneratedMessageV3
implements
// @@protoc_insertion_point(message_implements:google.cloud.automl.v1beta1.RegressionEvaluationMetrics)
RegressionEvaluationMetricsOrBuilder {
private static final long serialVersionUID = 0L;
// Use RegressionEvaluationMetrics.newBuilder() to construct.
private RegressionEvaluationMetrics(com.google.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
}
private RegressionEvaluationMetrics() {}
@java.lang.Override
@SuppressWarnings({"unused"})
protected java.lang.Object newInstance(UnusedPrivateParameter unused) {
return new RegressionEvaluationMetrics();
}
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
return com.google.cloud.automl.v1beta1.RegressionProto
.internal_static_google_cloud_automl_v1beta1_RegressionEvaluationMetrics_descriptor;
}
@java.lang.Override
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return com.google.cloud.automl.v1beta1.RegressionProto
.internal_static_google_cloud_automl_v1beta1_RegressionEvaluationMetrics_fieldAccessorTable
.ensureFieldAccessorsInitialized(
com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics.class,
com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics.Builder
.class);
}
public static final int ROOT_MEAN_SQUARED_ERROR_FIELD_NUMBER = 1;
private float rootMeanSquaredError_ = 0F;
/**
*
*
*
* Output only. Root Mean Squared Error (RMSE).
*
*
* float root_mean_squared_error = 1;
*
* @return The rootMeanSquaredError.
*/
@java.lang.Override
public float getRootMeanSquaredError() {
return rootMeanSquaredError_;
}
public static final int MEAN_ABSOLUTE_ERROR_FIELD_NUMBER = 2;
private float meanAbsoluteError_ = 0F;
/**
*
*
*
* Output only. Mean Absolute Error (MAE).
*
*
* float mean_absolute_error = 2;
*
* @return The meanAbsoluteError.
*/
@java.lang.Override
public float getMeanAbsoluteError() {
return meanAbsoluteError_;
}
public static final int MEAN_ABSOLUTE_PERCENTAGE_ERROR_FIELD_NUMBER = 3;
private float meanAbsolutePercentageError_ = 0F;
/**
*
*
*
* Output only. Mean absolute percentage error. Only set if all ground truth
* values are are positive.
*
*
* float mean_absolute_percentage_error = 3;
*
* @return The meanAbsolutePercentageError.
*/
@java.lang.Override
public float getMeanAbsolutePercentageError() {
return meanAbsolutePercentageError_;
}
public static final int R_SQUARED_FIELD_NUMBER = 4;
private float rSquared_ = 0F;
/**
*
*
*
* Output only. R squared.
*
*
* float r_squared = 4;
*
* @return The rSquared.
*/
@java.lang.Override
public float getRSquared() {
return rSquared_;
}
public static final int ROOT_MEAN_SQUARED_LOG_ERROR_FIELD_NUMBER = 5;
private float rootMeanSquaredLogError_ = 0F;
/**
*
*
*
* Output only. Root mean squared log error.
*
*
* float root_mean_squared_log_error = 5;
*
* @return The rootMeanSquaredLogError.
*/
@java.lang.Override
public float getRootMeanSquaredLogError() {
return rootMeanSquaredLogError_;
}
private byte memoizedIsInitialized = -1;
@java.lang.Override
public final boolean isInitialized() {
byte isInitialized = memoizedIsInitialized;
if (isInitialized == 1) return true;
if (isInitialized == 0) return false;
memoizedIsInitialized = 1;
return true;
}
@java.lang.Override
public void writeTo(com.google.protobuf.CodedOutputStream output) throws java.io.IOException {
if (java.lang.Float.floatToRawIntBits(rootMeanSquaredError_) != 0) {
output.writeFloat(1, rootMeanSquaredError_);
}
if (java.lang.Float.floatToRawIntBits(meanAbsoluteError_) != 0) {
output.writeFloat(2, meanAbsoluteError_);
}
if (java.lang.Float.floatToRawIntBits(meanAbsolutePercentageError_) != 0) {
output.writeFloat(3, meanAbsolutePercentageError_);
}
if (java.lang.Float.floatToRawIntBits(rSquared_) != 0) {
output.writeFloat(4, rSquared_);
}
if (java.lang.Float.floatToRawIntBits(rootMeanSquaredLogError_) != 0) {
output.writeFloat(5, rootMeanSquaredLogError_);
}
getUnknownFields().writeTo(output);
}
@java.lang.Override
public int getSerializedSize() {
int size = memoizedSize;
if (size != -1) return size;
size = 0;
if (java.lang.Float.floatToRawIntBits(rootMeanSquaredError_) != 0) {
size += com.google.protobuf.CodedOutputStream.computeFloatSize(1, rootMeanSquaredError_);
}
if (java.lang.Float.floatToRawIntBits(meanAbsoluteError_) != 0) {
size += com.google.protobuf.CodedOutputStream.computeFloatSize(2, meanAbsoluteError_);
}
if (java.lang.Float.floatToRawIntBits(meanAbsolutePercentageError_) != 0) {
size +=
com.google.protobuf.CodedOutputStream.computeFloatSize(3, meanAbsolutePercentageError_);
}
if (java.lang.Float.floatToRawIntBits(rSquared_) != 0) {
size += com.google.protobuf.CodedOutputStream.computeFloatSize(4, rSquared_);
}
if (java.lang.Float.floatToRawIntBits(rootMeanSquaredLogError_) != 0) {
size += com.google.protobuf.CodedOutputStream.computeFloatSize(5, rootMeanSquaredLogError_);
}
size += getUnknownFields().getSerializedSize();
memoizedSize = size;
return size;
}
@java.lang.Override
public boolean equals(final java.lang.Object obj) {
if (obj == this) {
return true;
}
if (!(obj
instanceof com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics)) {
return super.equals(obj);
}
com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics other =
(com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics) obj;
if (java.lang.Float.floatToIntBits(getRootMeanSquaredError())
!= java.lang.Float.floatToIntBits(other.getRootMeanSquaredError())) return false;
if (java.lang.Float.floatToIntBits(getMeanAbsoluteError())
!= java.lang.Float.floatToIntBits(other.getMeanAbsoluteError())) return false;
if (java.lang.Float.floatToIntBits(getMeanAbsolutePercentageError())
!= java.lang.Float.floatToIntBits(other.getMeanAbsolutePercentageError())) return false;
if (java.lang.Float.floatToIntBits(getRSquared())
!= java.lang.Float.floatToIntBits(other.getRSquared())) return false;
if (java.lang.Float.floatToIntBits(getRootMeanSquaredLogError())
!= java.lang.Float.floatToIntBits(other.getRootMeanSquaredLogError())) return false;
if (!getUnknownFields().equals(other.getUnknownFields())) return false;
return true;
}
@java.lang.Override
public int hashCode() {
if (memoizedHashCode != 0) {
return memoizedHashCode;
}
int hash = 41;
hash = (19 * hash) + getDescriptor().hashCode();
hash = (37 * hash) + ROOT_MEAN_SQUARED_ERROR_FIELD_NUMBER;
hash = (53 * hash) + java.lang.Float.floatToIntBits(getRootMeanSquaredError());
hash = (37 * hash) + MEAN_ABSOLUTE_ERROR_FIELD_NUMBER;
hash = (53 * hash) + java.lang.Float.floatToIntBits(getMeanAbsoluteError());
hash = (37 * hash) + MEAN_ABSOLUTE_PERCENTAGE_ERROR_FIELD_NUMBER;
hash = (53 * hash) + java.lang.Float.floatToIntBits(getMeanAbsolutePercentageError());
hash = (37 * hash) + R_SQUARED_FIELD_NUMBER;
hash = (53 * hash) + java.lang.Float.floatToIntBits(getRSquared());
hash = (37 * hash) + ROOT_MEAN_SQUARED_LOG_ERROR_FIELD_NUMBER;
hash = (53 * hash) + java.lang.Float.floatToIntBits(getRootMeanSquaredLogError());
hash = (29 * hash) + getUnknownFields().hashCode();
memoizedHashCode = hash;
return hash;
}
public static com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
parseFrom(java.nio.ByteBuffer data)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
parseFrom(
java.nio.ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
}
public static com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
parseFrom(com.google.protobuf.ByteString data)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
parseFrom(
com.google.protobuf.ByteString data,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
}
public static com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
parseFrom(byte[] data) throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
parseFrom(byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
}
public static com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
parseFrom(java.io.InputStream input) throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3.parseWithIOException(PARSER, input);
}
public static com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
parseFrom(
java.io.InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3.parseWithIOException(
PARSER, input, extensionRegistry);
}
public static com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
parseDelimitedFrom(java.io.InputStream input) throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3.parseDelimitedWithIOException(PARSER, input);
}
public static com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
parseDelimitedFrom(
java.io.InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3.parseDelimitedWithIOException(
PARSER, input, extensionRegistry);
}
public static com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
parseFrom(com.google.protobuf.CodedInputStream input) throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3.parseWithIOException(PARSER, input);
}
public static com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
parseFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3.parseWithIOException(
PARSER, input, extensionRegistry);
}
@java.lang.Override
public Builder newBuilderForType() {
return newBuilder();
}
public static Builder newBuilder() {
return DEFAULT_INSTANCE.toBuilder();
}
public static Builder newBuilder(
com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics prototype) {
return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype);
}
@java.lang.Override
public Builder toBuilder() {
return this == DEFAULT_INSTANCE ? new Builder() : new Builder().mergeFrom(this);
}
@java.lang.Override
protected Builder newBuilderForType(
com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
Builder builder = new Builder(parent);
return builder;
}
/**
*
*
*
* Metrics for regression problems.
*
*
* Protobuf type {@code google.cloud.automl.v1beta1.RegressionEvaluationMetrics}
*/
public static final class Builder
extends com.google.protobuf.GeneratedMessageV3.Builder
implements
// @@protoc_insertion_point(builder_implements:google.cloud.automl.v1beta1.RegressionEvaluationMetrics)
com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetricsOrBuilder {
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
return com.google.cloud.automl.v1beta1.RegressionProto
.internal_static_google_cloud_automl_v1beta1_RegressionEvaluationMetrics_descriptor;
}
@java.lang.Override
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return com.google.cloud.automl.v1beta1.RegressionProto
.internal_static_google_cloud_automl_v1beta1_RegressionEvaluationMetrics_fieldAccessorTable
.ensureFieldAccessorsInitialized(
com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics.class,
com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics.Builder
.class);
}
// Construct using
// com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics.newBuilder()
private Builder() {}
private Builder(com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
super(parent);
}
@java.lang.Override
public Builder clear() {
super.clear();
bitField0_ = 0;
rootMeanSquaredError_ = 0F;
meanAbsoluteError_ = 0F;
meanAbsolutePercentageError_ = 0F;
rSquared_ = 0F;
rootMeanSquaredLogError_ = 0F;
return this;
}
@java.lang.Override
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType() {
return com.google.cloud.automl.v1beta1.RegressionProto
.internal_static_google_cloud_automl_v1beta1_RegressionEvaluationMetrics_descriptor;
}
@java.lang.Override
public com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
getDefaultInstanceForType() {
return com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
.getDefaultInstance();
}
@java.lang.Override
public com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics build() {
com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics result =
buildPartial();
if (!result.isInitialized()) {
throw newUninitializedMessageException(result);
}
return result;
}
@java.lang.Override
public com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
buildPartial() {
com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics result =
new com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics(this);
if (bitField0_ != 0) {
buildPartial0(result);
}
onBuilt();
return result;
}
private void buildPartial0(
com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics result) {
int from_bitField0_ = bitField0_;
if (((from_bitField0_ & 0x00000001) != 0)) {
result.rootMeanSquaredError_ = rootMeanSquaredError_;
}
if (((from_bitField0_ & 0x00000002) != 0)) {
result.meanAbsoluteError_ = meanAbsoluteError_;
}
if (((from_bitField0_ & 0x00000004) != 0)) {
result.meanAbsolutePercentageError_ = meanAbsolutePercentageError_;
}
if (((from_bitField0_ & 0x00000008) != 0)) {
result.rSquared_ = rSquared_;
}
if (((from_bitField0_ & 0x00000010) != 0)) {
result.rootMeanSquaredLogError_ = rootMeanSquaredLogError_;
}
}
@java.lang.Override
public Builder clone() {
return super.clone();
}
@java.lang.Override
public Builder setField(
com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value) {
return super.setField(field, value);
}
@java.lang.Override
public Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field) {
return super.clearField(field);
}
@java.lang.Override
public Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof) {
return super.clearOneof(oneof);
}
@java.lang.Override
public Builder setRepeatedField(
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.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics) {
return mergeFrom(
(com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics) other);
} else {
super.mergeFrom(other);
return this;
}
}
public Builder mergeFrom(
com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics other) {
if (other
== com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
.getDefaultInstance()) return this;
if (other.getRootMeanSquaredError() != 0F) {
setRootMeanSquaredError(other.getRootMeanSquaredError());
}
if (other.getMeanAbsoluteError() != 0F) {
setMeanAbsoluteError(other.getMeanAbsoluteError());
}
if (other.getMeanAbsolutePercentageError() != 0F) {
setMeanAbsolutePercentageError(other.getMeanAbsolutePercentageError());
}
if (other.getRSquared() != 0F) {
setRSquared(other.getRSquared());
}
if (other.getRootMeanSquaredLogError() != 0F) {
setRootMeanSquaredLogError(other.getRootMeanSquaredLogError());
}
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 13:
{
rootMeanSquaredError_ = input.readFloat();
bitField0_ |= 0x00000001;
break;
} // case 13
case 21:
{
meanAbsoluteError_ = input.readFloat();
bitField0_ |= 0x00000002;
break;
} // case 21
case 29:
{
meanAbsolutePercentageError_ = input.readFloat();
bitField0_ |= 0x00000004;
break;
} // case 29
case 37:
{
rSquared_ = input.readFloat();
bitField0_ |= 0x00000008;
break;
} // case 37
case 45:
{
rootMeanSquaredLogError_ = input.readFloat();
bitField0_ |= 0x00000010;
break;
} // case 45
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 float rootMeanSquaredError_;
/**
*
*
*
* Output only. Root Mean Squared Error (RMSE).
*
*
* float root_mean_squared_error = 1;
*
* @return The rootMeanSquaredError.
*/
@java.lang.Override
public float getRootMeanSquaredError() {
return rootMeanSquaredError_;
}
/**
*
*
*
* Output only. Root Mean Squared Error (RMSE).
*
*
* float root_mean_squared_error = 1;
*
* @param value The rootMeanSquaredError to set.
* @return This builder for chaining.
*/
public Builder setRootMeanSquaredError(float value) {
rootMeanSquaredError_ = value;
bitField0_ |= 0x00000001;
onChanged();
return this;
}
/**
*
*
*
* Output only. Root Mean Squared Error (RMSE).
*
*
* float root_mean_squared_error = 1;
*
* @return This builder for chaining.
*/
public Builder clearRootMeanSquaredError() {
bitField0_ = (bitField0_ & ~0x00000001);
rootMeanSquaredError_ = 0F;
onChanged();
return this;
}
private float meanAbsoluteError_;
/**
*
*
*
* Output only. Mean Absolute Error (MAE).
*
*
* float mean_absolute_error = 2;
*
* @return The meanAbsoluteError.
*/
@java.lang.Override
public float getMeanAbsoluteError() {
return meanAbsoluteError_;
}
/**
*
*
*
* Output only. Mean Absolute Error (MAE).
*
*
* float mean_absolute_error = 2;
*
* @param value The meanAbsoluteError to set.
* @return This builder for chaining.
*/
public Builder setMeanAbsoluteError(float value) {
meanAbsoluteError_ = value;
bitField0_ |= 0x00000002;
onChanged();
return this;
}
/**
*
*
*
* Output only. Mean Absolute Error (MAE).
*
*
* float mean_absolute_error = 2;
*
* @return This builder for chaining.
*/
public Builder clearMeanAbsoluteError() {
bitField0_ = (bitField0_ & ~0x00000002);
meanAbsoluteError_ = 0F;
onChanged();
return this;
}
private float meanAbsolutePercentageError_;
/**
*
*
*
* Output only. Mean absolute percentage error. Only set if all ground truth
* values are are positive.
*
*
* float mean_absolute_percentage_error = 3;
*
* @return The meanAbsolutePercentageError.
*/
@java.lang.Override
public float getMeanAbsolutePercentageError() {
return meanAbsolutePercentageError_;
}
/**
*
*
*
* Output only. Mean absolute percentage error. Only set if all ground truth
* values are are positive.
*
*
* float mean_absolute_percentage_error = 3;
*
* @param value The meanAbsolutePercentageError to set.
* @return This builder for chaining.
*/
public Builder setMeanAbsolutePercentageError(float value) {
meanAbsolutePercentageError_ = value;
bitField0_ |= 0x00000004;
onChanged();
return this;
}
/**
*
*
*
* Output only. Mean absolute percentage error. Only set if all ground truth
* values are are positive.
*
*
* float mean_absolute_percentage_error = 3;
*
* @return This builder for chaining.
*/
public Builder clearMeanAbsolutePercentageError() {
bitField0_ = (bitField0_ & ~0x00000004);
meanAbsolutePercentageError_ = 0F;
onChanged();
return this;
}
private float rSquared_;
/**
*
*
*
* Output only. R squared.
*
*
* float r_squared = 4;
*
* @return The rSquared.
*/
@java.lang.Override
public float getRSquared() {
return rSquared_;
}
/**
*
*
*
* Output only. R squared.
*
*
* float r_squared = 4;
*
* @param value The rSquared to set.
* @return This builder for chaining.
*/
public Builder setRSquared(float value) {
rSquared_ = value;
bitField0_ |= 0x00000008;
onChanged();
return this;
}
/**
*
*
*
* Output only. R squared.
*
*
* float r_squared = 4;
*
* @return This builder for chaining.
*/
public Builder clearRSquared() {
bitField0_ = (bitField0_ & ~0x00000008);
rSquared_ = 0F;
onChanged();
return this;
}
private float rootMeanSquaredLogError_;
/**
*
*
*
* Output only. Root mean squared log error.
*
*
* float root_mean_squared_log_error = 5;
*
* @return The rootMeanSquaredLogError.
*/
@java.lang.Override
public float getRootMeanSquaredLogError() {
return rootMeanSquaredLogError_;
}
/**
*
*
*
* Output only. Root mean squared log error.
*
*
* float root_mean_squared_log_error = 5;
*
* @param value The rootMeanSquaredLogError to set.
* @return This builder for chaining.
*/
public Builder setRootMeanSquaredLogError(float value) {
rootMeanSquaredLogError_ = value;
bitField0_ |= 0x00000010;
onChanged();
return this;
}
/**
*
*
*
* Output only. Root mean squared log error.
*
*
* float root_mean_squared_log_error = 5;
*
* @return This builder for chaining.
*/
public Builder clearRootMeanSquaredLogError() {
bitField0_ = (bitField0_ & ~0x00000010);
rootMeanSquaredLogError_ = 0F;
onChanged();
return this;
}
@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.automl.v1beta1.RegressionEvaluationMetrics)
}
// @@protoc_insertion_point(class_scope:google.cloud.automl.v1beta1.RegressionEvaluationMetrics)
private static final com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE =
new com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics();
}
public static com.google.cloud.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final com.google.protobuf.Parser PARSER =
new com.google.protobuf.AbstractParser() {
@java.lang.Override
public RegressionEvaluationMetrics 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.automl.v1beta1.RegressionProto.RegressionEvaluationMetrics
getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
private static final com.google.protobuf.Descriptors.Descriptor
internal_static_google_cloud_automl_v1beta1_RegressionEvaluationMetrics_descriptor;
private static final com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internal_static_google_cloud_automl_v1beta1_RegressionEvaluationMetrics_fieldAccessorTable;
public static com.google.protobuf.Descriptors.FileDescriptor getDescriptor() {
return descriptor;
}
private static com.google.protobuf.Descriptors.FileDescriptor descriptor;
static {
java.lang.String[] descriptorData = {
"\n,google/cloud/automl/v1beta1/regression"
+ ".proto\022\033google.cloud.automl.v1beta1\"\273\001\n\033"
+ "RegressionEvaluationMetrics\022\037\n\027root_mean"
+ "_squared_error\030\001 \001(\002\022\033\n\023mean_absolute_er"
+ "ror\030\002 \001(\002\022&\n\036mean_absolute_percentage_er"
+ "ror\030\003 \001(\002\022\021\n\tr_squared\030\004 \001(\002\022#\n\033root_mea"
+ "n_squared_log_error\030\005 \001(\002B\252\001\n\037com.google"
+ ".cloud.automl.v1beta1B\017RegressionProtoZ7"
+ "cloud.google.com/go/automl/apiv1beta1/au"
+ "tomlpb;automlpb\312\002\033Google\\Cloud\\AutoMl\\V1"
+ "beta1\352\002\036Google::Cloud::AutoML::V1beta1b\006"
+ "proto3"
};
descriptor =
com.google.protobuf.Descriptors.FileDescriptor.internalBuildGeneratedFileFrom(
descriptorData, new com.google.protobuf.Descriptors.FileDescriptor[] {});
internal_static_google_cloud_automl_v1beta1_RegressionEvaluationMetrics_descriptor =
getDescriptor().getMessageTypes().get(0);
internal_static_google_cloud_automl_v1beta1_RegressionEvaluationMetrics_fieldAccessorTable =
new com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
internal_static_google_cloud_automl_v1beta1_RegressionEvaluationMetrics_descriptor,
new java.lang.String[] {
"RootMeanSquaredError",
"MeanAbsoluteError",
"MeanAbsolutePercentageError",
"RSquared",
"RootMeanSquaredLogError",
});
}
// @@protoc_insertion_point(outer_class_scope)
}