implements
// @@protoc_insertion_point(builder_implements:google.cloud.automl.v1.TextSentimentEvaluationMetrics)
com.google.cloud.automl.v1.TextSentimentEvaluationMetricsOrBuilder {
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
return com.google.cloud.automl.v1.TextSentimentProto
.internal_static_google_cloud_automl_v1_TextSentimentEvaluationMetrics_descriptor;
}
@java.lang.Override
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return com.google.cloud.automl.v1.TextSentimentProto
.internal_static_google_cloud_automl_v1_TextSentimentEvaluationMetrics_fieldAccessorTable
.ensureFieldAccessorsInitialized(
com.google.cloud.automl.v1.TextSentimentEvaluationMetrics.class,
com.google.cloud.automl.v1.TextSentimentEvaluationMetrics.Builder.class);
}
// Construct using com.google.cloud.automl.v1.TextSentimentEvaluationMetrics.newBuilder()
private Builder() {}
private Builder(com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
super(parent);
}
@java.lang.Override
public Builder clear() {
super.clear();
bitField0_ = 0;
precision_ = 0F;
recall_ = 0F;
f1Score_ = 0F;
meanAbsoluteError_ = 0F;
meanSquaredError_ = 0F;
linearKappa_ = 0F;
quadraticKappa_ = 0F;
confusionMatrix_ = null;
if (confusionMatrixBuilder_ != null) {
confusionMatrixBuilder_.dispose();
confusionMatrixBuilder_ = null;
}
return this;
}
@java.lang.Override
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType() {
return com.google.cloud.automl.v1.TextSentimentProto
.internal_static_google_cloud_automl_v1_TextSentimentEvaluationMetrics_descriptor;
}
@java.lang.Override
public com.google.cloud.automl.v1.TextSentimentEvaluationMetrics getDefaultInstanceForType() {
return com.google.cloud.automl.v1.TextSentimentEvaluationMetrics.getDefaultInstance();
}
@java.lang.Override
public com.google.cloud.automl.v1.TextSentimentEvaluationMetrics build() {
com.google.cloud.automl.v1.TextSentimentEvaluationMetrics result = buildPartial();
if (!result.isInitialized()) {
throw newUninitializedMessageException(result);
}
return result;
}
@java.lang.Override
public com.google.cloud.automl.v1.TextSentimentEvaluationMetrics buildPartial() {
com.google.cloud.automl.v1.TextSentimentEvaluationMetrics result =
new com.google.cloud.automl.v1.TextSentimentEvaluationMetrics(this);
if (bitField0_ != 0) {
buildPartial0(result);
}
onBuilt();
return result;
}
private void buildPartial0(com.google.cloud.automl.v1.TextSentimentEvaluationMetrics result) {
int from_bitField0_ = bitField0_;
if (((from_bitField0_ & 0x00000001) != 0)) {
result.precision_ = precision_;
}
if (((from_bitField0_ & 0x00000002) != 0)) {
result.recall_ = recall_;
}
if (((from_bitField0_ & 0x00000004) != 0)) {
result.f1Score_ = f1Score_;
}
if (((from_bitField0_ & 0x00000008) != 0)) {
result.meanAbsoluteError_ = meanAbsoluteError_;
}
if (((from_bitField0_ & 0x00000010) != 0)) {
result.meanSquaredError_ = meanSquaredError_;
}
if (((from_bitField0_ & 0x00000020) != 0)) {
result.linearKappa_ = linearKappa_;
}
if (((from_bitField0_ & 0x00000040) != 0)) {
result.quadraticKappa_ = quadraticKappa_;
}
if (((from_bitField0_ & 0x00000080) != 0)) {
result.confusionMatrix_ =
confusionMatrixBuilder_ == null ? confusionMatrix_ : confusionMatrixBuilder_.build();
}
}
@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.v1.TextSentimentEvaluationMetrics) {
return mergeFrom((com.google.cloud.automl.v1.TextSentimentEvaluationMetrics) other);
} else {
super.mergeFrom(other);
return this;
}
}
public Builder mergeFrom(com.google.cloud.automl.v1.TextSentimentEvaluationMetrics other) {
if (other == com.google.cloud.automl.v1.TextSentimentEvaluationMetrics.getDefaultInstance())
return this;
if (other.getPrecision() != 0F) {
setPrecision(other.getPrecision());
}
if (other.getRecall() != 0F) {
setRecall(other.getRecall());
}
if (other.getF1Score() != 0F) {
setF1Score(other.getF1Score());
}
if (other.getMeanAbsoluteError() != 0F) {
setMeanAbsoluteError(other.getMeanAbsoluteError());
}
if (other.getMeanSquaredError() != 0F) {
setMeanSquaredError(other.getMeanSquaredError());
}
if (other.getLinearKappa() != 0F) {
setLinearKappa(other.getLinearKappa());
}
if (other.getQuadraticKappa() != 0F) {
setQuadraticKappa(other.getQuadraticKappa());
}
if (other.hasConfusionMatrix()) {
mergeConfusionMatrix(other.getConfusionMatrix());
}
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:
{
precision_ = input.readFloat();
bitField0_ |= 0x00000001;
break;
} // case 13
case 21:
{
recall_ = input.readFloat();
bitField0_ |= 0x00000002;
break;
} // case 21
case 29:
{
f1Score_ = input.readFloat();
bitField0_ |= 0x00000004;
break;
} // case 29
case 37:
{
meanAbsoluteError_ = input.readFloat();
bitField0_ |= 0x00000008;
break;
} // case 37
case 45:
{
meanSquaredError_ = input.readFloat();
bitField0_ |= 0x00000010;
break;
} // case 45
case 53:
{
linearKappa_ = input.readFloat();
bitField0_ |= 0x00000020;
break;
} // case 53
case 61:
{
quadraticKappa_ = input.readFloat();
bitField0_ |= 0x00000040;
break;
} // case 61
case 66:
{
input.readMessage(getConfusionMatrixFieldBuilder().getBuilder(), extensionRegistry);
bitField0_ |= 0x00000080;
break;
} // case 66
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 precision_;
/**
*
*
*
* Output only. Precision.
*
*
* float precision = 1;
*
* @return The precision.
*/
@java.lang.Override
public float getPrecision() {
return precision_;
}
/**
*
*
*
* Output only. Precision.
*
*
* float precision = 1;
*
* @param value The precision to set.
* @return This builder for chaining.
*/
public Builder setPrecision(float value) {
precision_ = value;
bitField0_ |= 0x00000001;
onChanged();
return this;
}
/**
*
*
*
* Output only. Precision.
*
*
* float precision = 1;
*
* @return This builder for chaining.
*/
public Builder clearPrecision() {
bitField0_ = (bitField0_ & ~0x00000001);
precision_ = 0F;
onChanged();
return this;
}
private float recall_;
/**
*
*
*
* Output only. Recall.
*
*
* float recall = 2;
*
* @return The recall.
*/
@java.lang.Override
public float getRecall() {
return recall_;
}
/**
*
*
*
* Output only. Recall.
*
*
* float recall = 2;
*
* @param value The recall to set.
* @return This builder for chaining.
*/
public Builder setRecall(float value) {
recall_ = value;
bitField0_ |= 0x00000002;
onChanged();
return this;
}
/**
*
*
*
* Output only. Recall.
*
*
* float recall = 2;
*
* @return This builder for chaining.
*/
public Builder clearRecall() {
bitField0_ = (bitField0_ & ~0x00000002);
recall_ = 0F;
onChanged();
return this;
}
private float f1Score_;
/**
*
*
*
* Output only. The harmonic mean of recall and precision.
*
*
* float f1_score = 3;
*
* @return The f1Score.
*/
@java.lang.Override
public float getF1Score() {
return f1Score_;
}
/**
*
*
*
* Output only. The harmonic mean of recall and precision.
*
*
* float f1_score = 3;
*
* @param value The f1Score to set.
* @return This builder for chaining.
*/
public Builder setF1Score(float value) {
f1Score_ = value;
bitField0_ |= 0x00000004;
onChanged();
return this;
}
/**
*
*
*
* Output only. The harmonic mean of recall and precision.
*
*
* float f1_score = 3;
*
* @return This builder for chaining.
*/
public Builder clearF1Score() {
bitField0_ = (bitField0_ & ~0x00000004);
f1Score_ = 0F;
onChanged();
return this;
}
private float meanAbsoluteError_;
/**
*
*
*
* Output only. Mean absolute error. Only set for the overall model
* evaluation, not for evaluation of a single annotation spec.
*
*
* float mean_absolute_error = 4;
*
* @return The meanAbsoluteError.
*/
@java.lang.Override
public float getMeanAbsoluteError() {
return meanAbsoluteError_;
}
/**
*
*
*
* Output only. Mean absolute error. Only set for the overall model
* evaluation, not for evaluation of a single annotation spec.
*
*
* float mean_absolute_error = 4;
*
* @param value The meanAbsoluteError to set.
* @return This builder for chaining.
*/
public Builder setMeanAbsoluteError(float value) {
meanAbsoluteError_ = value;
bitField0_ |= 0x00000008;
onChanged();
return this;
}
/**
*
*
*
* Output only. Mean absolute error. Only set for the overall model
* evaluation, not for evaluation of a single annotation spec.
*
*
* float mean_absolute_error = 4;
*
* @return This builder for chaining.
*/
public Builder clearMeanAbsoluteError() {
bitField0_ = (bitField0_ & ~0x00000008);
meanAbsoluteError_ = 0F;
onChanged();
return this;
}
private float meanSquaredError_;
/**
*
*
*
* Output only. Mean squared error. Only set for the overall model
* evaluation, not for evaluation of a single annotation spec.
*
*
* float mean_squared_error = 5;
*
* @return The meanSquaredError.
*/
@java.lang.Override
public float getMeanSquaredError() {
return meanSquaredError_;
}
/**
*
*
*
* Output only. Mean squared error. Only set for the overall model
* evaluation, not for evaluation of a single annotation spec.
*
*
* float mean_squared_error = 5;
*
* @param value The meanSquaredError to set.
* @return This builder for chaining.
*/
public Builder setMeanSquaredError(float value) {
meanSquaredError_ = value;
bitField0_ |= 0x00000010;
onChanged();
return this;
}
/**
*
*
*
* Output only. Mean squared error. Only set for the overall model
* evaluation, not for evaluation of a single annotation spec.
*
*
* float mean_squared_error = 5;
*
* @return This builder for chaining.
*/
public Builder clearMeanSquaredError() {
bitField0_ = (bitField0_ & ~0x00000010);
meanSquaredError_ = 0F;
onChanged();
return this;
}
private float linearKappa_;
/**
*
*
*
* Output only. Linear weighted kappa. Only set for the overall model
* evaluation, not for evaluation of a single annotation spec.
*
*
* float linear_kappa = 6;
*
* @return The linearKappa.
*/
@java.lang.Override
public float getLinearKappa() {
return linearKappa_;
}
/**
*
*
*
* Output only. Linear weighted kappa. Only set for the overall model
* evaluation, not for evaluation of a single annotation spec.
*
*
* float linear_kappa = 6;
*
* @param value The linearKappa to set.
* @return This builder for chaining.
*/
public Builder setLinearKappa(float value) {
linearKappa_ = value;
bitField0_ |= 0x00000020;
onChanged();
return this;
}
/**
*
*
*
* Output only. Linear weighted kappa. Only set for the overall model
* evaluation, not for evaluation of a single annotation spec.
*
*
* float linear_kappa = 6;
*
* @return This builder for chaining.
*/
public Builder clearLinearKappa() {
bitField0_ = (bitField0_ & ~0x00000020);
linearKappa_ = 0F;
onChanged();
return this;
}
private float quadraticKappa_;
/**
*
*
*
* Output only. Quadratic weighted kappa. Only set for the overall model
* evaluation, not for evaluation of a single annotation spec.
*
*
* float quadratic_kappa = 7;
*
* @return The quadraticKappa.
*/
@java.lang.Override
public float getQuadraticKappa() {
return quadraticKappa_;
}
/**
*
*
*
* Output only. Quadratic weighted kappa. Only set for the overall model
* evaluation, not for evaluation of a single annotation spec.
*
*
* float quadratic_kappa = 7;
*
* @param value The quadraticKappa to set.
* @return This builder for chaining.
*/
public Builder setQuadraticKappa(float value) {
quadraticKappa_ = value;
bitField0_ |= 0x00000040;
onChanged();
return this;
}
/**
*
*
*
* Output only. Quadratic weighted kappa. Only set for the overall model
* evaluation, not for evaluation of a single annotation spec.
*
*
* float quadratic_kappa = 7;
*
* @return This builder for chaining.
*/
public Builder clearQuadraticKappa() {
bitField0_ = (bitField0_ & ~0x00000040);
quadraticKappa_ = 0F;
onChanged();
return this;
}
private com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix
confusionMatrix_;
private com.google.protobuf.SingleFieldBuilderV3<
com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix,
com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix.Builder,
com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrixOrBuilder>
confusionMatrixBuilder_;
/**
*
*
*
* Output only. Confusion matrix of the evaluation.
* Only set for the overall model evaluation, not for evaluation of a single
* annotation spec.
*
*
*
* .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 8;
*
*
* @return Whether the confusionMatrix field is set.
*/
public boolean hasConfusionMatrix() {
return ((bitField0_ & 0x00000080) != 0);
}
/**
*
*
*
* Output only. Confusion matrix of the evaluation.
* Only set for the overall model evaluation, not for evaluation of a single
* annotation spec.
*
*
*
* .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 8;
*
*
* @return The confusionMatrix.
*/
public com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix
getConfusionMatrix() {
if (confusionMatrixBuilder_ == null) {
return confusionMatrix_ == null
? com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix
.getDefaultInstance()
: confusionMatrix_;
} else {
return confusionMatrixBuilder_.getMessage();
}
}
/**
*
*
*
* Output only. Confusion matrix of the evaluation.
* Only set for the overall model evaluation, not for evaluation of a single
* annotation spec.
*
*
*
* .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 8;
*
*/
public Builder setConfusionMatrix(
com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix value) {
if (confusionMatrixBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
confusionMatrix_ = value;
} else {
confusionMatrixBuilder_.setMessage(value);
}
bitField0_ |= 0x00000080;
onChanged();
return this;
}
/**
*
*
*
* Output only. Confusion matrix of the evaluation.
* Only set for the overall model evaluation, not for evaluation of a single
* annotation spec.
*
*
*
* .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 8;
*
*/
public Builder setConfusionMatrix(
com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix.Builder
builderForValue) {
if (confusionMatrixBuilder_ == null) {
confusionMatrix_ = builderForValue.build();
} else {
confusionMatrixBuilder_.setMessage(builderForValue.build());
}
bitField0_ |= 0x00000080;
onChanged();
return this;
}
/**
*
*
*
* Output only. Confusion matrix of the evaluation.
* Only set for the overall model evaluation, not for evaluation of a single
* annotation spec.
*
*
*
* .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 8;
*
*/
public Builder mergeConfusionMatrix(
com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix value) {
if (confusionMatrixBuilder_ == null) {
if (((bitField0_ & 0x00000080) != 0)
&& confusionMatrix_ != null
&& confusionMatrix_
!= com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix
.getDefaultInstance()) {
getConfusionMatrixBuilder().mergeFrom(value);
} else {
confusionMatrix_ = value;
}
} else {
confusionMatrixBuilder_.mergeFrom(value);
}
bitField0_ |= 0x00000080;
onChanged();
return this;
}
/**
*
*
*
* Output only. Confusion matrix of the evaluation.
* Only set for the overall model evaluation, not for evaluation of a single
* annotation spec.
*
*
*
* .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 8;
*
*/
public Builder clearConfusionMatrix() {
bitField0_ = (bitField0_ & ~0x00000080);
confusionMatrix_ = null;
if (confusionMatrixBuilder_ != null) {
confusionMatrixBuilder_.dispose();
confusionMatrixBuilder_ = null;
}
onChanged();
return this;
}
/**
*
*
*
* Output only. Confusion matrix of the evaluation.
* Only set for the overall model evaluation, not for evaluation of a single
* annotation spec.
*
*
*
* .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 8;
*
*/
public com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix.Builder
getConfusionMatrixBuilder() {
bitField0_ |= 0x00000080;
onChanged();
return getConfusionMatrixFieldBuilder().getBuilder();
}
/**
*
*
*
* Output only. Confusion matrix of the evaluation.
* Only set for the overall model evaluation, not for evaluation of a single
* annotation spec.
*
*
*
* .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 8;
*
*/
public com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrixOrBuilder
getConfusionMatrixOrBuilder() {
if (confusionMatrixBuilder_ != null) {
return confusionMatrixBuilder_.getMessageOrBuilder();
} else {
return confusionMatrix_ == null
? com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix
.getDefaultInstance()
: confusionMatrix_;
}
}
/**
*
*
*
* Output only. Confusion matrix of the evaluation.
* Only set for the overall model evaluation, not for evaluation of a single
* annotation spec.
*
*
*
* .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 8;
*
*/
private com.google.protobuf.SingleFieldBuilderV3<
com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix,
com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix.Builder,
com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrixOrBuilder>
getConfusionMatrixFieldBuilder() {
if (confusionMatrixBuilder_ == null) {
confusionMatrixBuilder_ =
new com.google.protobuf.SingleFieldBuilderV3<
com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix,
com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix.Builder,
com.google.cloud.automl.v1.ClassificationEvaluationMetrics
.ConfusionMatrixOrBuilder>(
getConfusionMatrix(), getParentForChildren(), isClean());
confusionMatrix_ = null;
}
return confusionMatrixBuilder_;
}
@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.v1.TextSentimentEvaluationMetrics)
}
// @@protoc_insertion_point(class_scope:google.cloud.automl.v1.TextSentimentEvaluationMetrics)
private static final com.google.cloud.automl.v1.TextSentimentEvaluationMetrics DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new com.google.cloud.automl.v1.TextSentimentEvaluationMetrics();
}
public static com.google.cloud.automl.v1.TextSentimentEvaluationMetrics getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final com.google.protobuf.Parser PARSER =
new com.google.protobuf.AbstractParser() {
@java.lang.Override
public TextSentimentEvaluationMetrics 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.v1.TextSentimentEvaluationMetrics getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}