Class EvaluationJobConfig.Builder (0.149.0)

public static final class EvaluationJobConfig.Builder extends GeneratedMessageV3.Builder<EvaluationJobConfig.Builder> implements EvaluationJobConfigOrBuilder

Configures specific details of how a continuous evaluation job works. Provide this configuration when you create an EvaluationJob.

Protobuf type google.cloud.datalabeling.v1beta1.EvaluationJobConfig

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > EvaluationJobConfig.Builder

Implements

EvaluationJobConfigOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns
Type	Description
`Descriptor`

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public EvaluationJobConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
`field`	`FieldDescriptor`
`value`	`Object`

Returns
Type	Description
`EvaluationJobConfig.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

build()

public EvaluationJobConfig build()

Returns
Type	Description
`EvaluationJobConfig`

buildPartial()

public EvaluationJobConfig buildPartial()

Returns
Type	Description
`EvaluationJobConfig`

clear()

public EvaluationJobConfig.Builder clear()

Returns
Type	Description
`EvaluationJobConfig.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearBigqueryImportKeys()

public EvaluationJobConfig.Builder clearBigqueryImportKeys()

Returns
Type	Description
`EvaluationJobConfig.Builder`

clearBoundingPolyConfig()

public EvaluationJobConfig.Builder clearBoundingPolyConfig()

Specify this field if your model version performs image object detection (bounding box detection).

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet.

.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;

Returns
Type	Description
`EvaluationJobConfig.Builder`

clearEvaluationConfig()

public EvaluationJobConfig.Builder clearEvaluationConfig()

Required. Details for calculating evaluation metrics and creating Evaulations. If your model version performs image object detection, you must specify the boundingBoxEvaluationOptions field within this configuration. Otherwise, provide an empty object for this configuration.

.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;

Returns
Type	Description
`EvaluationJobConfig.Builder`

clearEvaluationJobAlertConfig()

public EvaluationJobConfig.Builder clearEvaluationJobAlertConfig()

Optional. Configuration details for evaluation job alerts. Specify this field if you want to receive email alerts if the evaluation job finds that your predictions have low mean average precision during a run.

.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;

Returns
Type	Description
`EvaluationJobConfig.Builder`

clearExampleCount()

public EvaluationJobConfig.Builder clearExampleCount()

Required. The maximum number of predictions to sample and save to BigQuery during each evaluation interval. This limit overrides example_sample_percentage: even if the service has not sampled enough predictions to fulfill example_sample_perecentage during an interval, it stops sampling predictions when it meets this limit.

int32 example_count = 10;

Returns
Type	Description
`EvaluationJobConfig.Builder`	This builder for chaining.

clearExampleSamplePercentage()

public EvaluationJobConfig.Builder clearExampleSamplePercentage()

Required. Fraction of predictions to sample and save to BigQuery during each evaluation interval. For example, 0.1 means 10% of predictions served by your model version get saved to BigQuery.

double example_sample_percentage = 11;

Returns
Type	Description
`EvaluationJobConfig.Builder`	This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public EvaluationJobConfig.Builder clearField(Descriptors.FieldDescriptor field)

Parameter
Name	Description
`field`	`FieldDescriptor`

Returns
Type	Description
`EvaluationJobConfig.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

clearHumanAnnotationConfig()

public EvaluationJobConfig.Builder clearHumanAnnotationConfig()

Optional. Details for human annotation of your data. If you set labelMissingGroundTruth to true for this evaluation job, then you must specify this field. If you plan to provide your own ground truth labels, then omit this field.

Note that you must create an Instruction resource before you can specify this field. Provide the name of the instruction resource in the instruction field within this configuration.

.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;

Returns
Type	Description
`EvaluationJobConfig.Builder`

clearHumanAnnotationRequestConfig()

public EvaluationJobConfig.Builder clearHumanAnnotationRequestConfig()

Returns
Type	Description
`EvaluationJobConfig.Builder`

clearImageClassificationConfig()

public EvaluationJobConfig.Builder clearImageClassificationConfig()

Specify this field if your model version performs image classification or general classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;

Returns
Type	Description
`EvaluationJobConfig.Builder`

clearInputConfig()

public EvaluationJobConfig.Builder clearInputConfig()

Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:

dataType must be one of IMAGE, TEXT, or GENERAL_DATA.
annotationType must be one of IMAGE_CLASSIFICATION_ANNOTATION, TEXT_CLASSIFICATION_ANNOTATION, GENERAL_CLASSIFICATION_ANNOTATION, or IMAGE_BOUNDING_BOX_ANNOTATION (image object detection).
If your machine learning model performs classification, you must specify classificationMetadata.isMultiLabel.
You must specify bigquerySource (not gcsSource).

.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;

Returns
Type	Description
`EvaluationJobConfig.Builder`

clearOneof(Descriptors.OneofDescriptor oneof)

public EvaluationJobConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter
Name	Description
`oneof`	`OneofDescriptor`

Returns
Type	Description
`EvaluationJobConfig.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

clearTextClassificationConfig()

public EvaluationJobConfig.Builder clearTextClassificationConfig()

Specify this field if your model version performs text classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;

Returns
Type	Description
`EvaluationJobConfig.Builder`

clone()

public EvaluationJobConfig.Builder clone()

Returns
Type	Description
`EvaluationJobConfig.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

containsBigqueryImportKeys(String key)

public boolean containsBigqueryImportKeys(String key)

Required. Prediction keys that tell Data Labeling Service where to find the data for evaluation in your BigQuery table. When the service samples prediction input and output from your model version and saves it to BigQuery, the data gets stored as JSON strings in the BigQuery table. These keys tell Data Labeling Service how to parse the JSON.

You can provide the following entries in this field:

data_json_key: the data key for prediction input. You must provide either this key or reference_json_key.
reference_json_key: the data reference key for prediction input. You must provide either this key or data_json_key.
label_json_key: the label key for prediction output. Required.
label_score_json_key: the score key for prediction output. Required.
bounding_box_json_key: the bounding box key for prediction output. Required if your model version perform image object detection.

Learn how to configure prediction keys.

map<string, string> bigquery_import_keys = 9;

Parameter
Name	Description
`key`	`String`

Returns
Type	Description
`boolean`

getBigqueryImportKeys()

public Map<String,String> getBigqueryImportKeys()

Use #getBigqueryImportKeysMap() instead.

Returns
Type	Description
`Map<String,String>`

getBigqueryImportKeysCount()

public int getBigqueryImportKeysCount()

You can provide the following entries in this field:

data_json_key: the data key for prediction input. You must provide either this key or reference_json_key.
reference_json_key: the data reference key for prediction input. You must provide either this key or data_json_key.
label_json_key: the label key for prediction output. Required.
label_score_json_key: the score key for prediction output. Required.
bounding_box_json_key: the bounding box key for prediction output. Required if your model version perform image object detection.

Learn how to configure prediction keys.

map<string, string> bigquery_import_keys = 9;

Returns
Type	Description
`int`

getBigqueryImportKeysMap()

public Map<String,String> getBigqueryImportKeysMap()

You can provide the following entries in this field:

data_json_key: the data key for prediction input. You must provide either this key or reference_json_key.
reference_json_key: the data reference key for prediction input. You must provide either this key or data_json_key.
label_json_key: the label key for prediction output. Required.
label_score_json_key: the score key for prediction output. Required.
bounding_box_json_key: the bounding box key for prediction output. Required if your model version perform image object detection.

Learn how to configure prediction keys.

map<string, string> bigquery_import_keys = 9;

Returns
Type	Description
`Map<String,String>`

getBigqueryImportKeysOrDefault(String key, String defaultValue)

public String getBigqueryImportKeysOrDefault(String key, String defaultValue)

You can provide the following entries in this field:

data_json_key: the data key for prediction input. You must provide either this key or reference_json_key.
reference_json_key: the data reference key for prediction input. You must provide either this key or data_json_key.
label_json_key: the label key for prediction output. Required.
label_score_json_key: the score key for prediction output. Required.
bounding_box_json_key: the bounding box key for prediction output. Required if your model version perform image object detection.

Learn how to configure prediction keys.

map<string, string> bigquery_import_keys = 9;

Parameters
Name	Description
`key`	`String`
`defaultValue`	`String`

Returns
Type	Description
`String`

getBigqueryImportKeysOrThrow(String key)

public String getBigqueryImportKeysOrThrow(String key)

You can provide the following entries in this field:

data_json_key: the data key for prediction input. You must provide either this key or reference_json_key.
reference_json_key: the data reference key for prediction input. You must provide either this key or data_json_key.
label_json_key: the label key for prediction output. Required.
label_score_json_key: the score key for prediction output. Required.
bounding_box_json_key: the bounding box key for prediction output. Required if your model version perform image object detection.

Learn how to configure prediction keys.

map<string, string> bigquery_import_keys = 9;

Parameter
Name	Description
`key`	`String`

Returns
Type	Description
`String`

getBoundingPolyConfig()

public BoundingPolyConfig getBoundingPolyConfig()

Specify this field if your model version performs image object detection (bounding box detection).

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet.

.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;

Returns
Type	Description
`BoundingPolyConfig`	The boundingPolyConfig.

getBoundingPolyConfigBuilder()

public BoundingPolyConfig.Builder getBoundingPolyConfigBuilder()

Specify this field if your model version performs image object detection (bounding box detection).

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet.

.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;

Returns
Type	Description
`BoundingPolyConfig.Builder`

getBoundingPolyConfigOrBuilder()

public BoundingPolyConfigOrBuilder getBoundingPolyConfigOrBuilder()

Specify this field if your model version performs image object detection (bounding box detection).

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet.

.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;

Returns
Type	Description
`BoundingPolyConfigOrBuilder`

getDefaultInstanceForType()

public EvaluationJobConfig getDefaultInstanceForType()

Returns
Type	Description
`EvaluationJobConfig`

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns
Type	Description
`Descriptor`

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getEvaluationConfig()

public EvaluationConfig getEvaluationConfig()

.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;

Returns
Type	Description
`EvaluationConfig`	The evaluationConfig.

getEvaluationConfigBuilder()

public EvaluationConfig.Builder getEvaluationConfigBuilder()

.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;

Returns
Type	Description
`EvaluationConfig.Builder`

getEvaluationConfigOrBuilder()

public EvaluationConfigOrBuilder getEvaluationConfigOrBuilder()

.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;

Returns
Type	Description
`EvaluationConfigOrBuilder`

getEvaluationJobAlertConfig()

public EvaluationJobAlertConfig getEvaluationJobAlertConfig()

.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;

Returns
Type	Description
`EvaluationJobAlertConfig`	The evaluationJobAlertConfig.

getEvaluationJobAlertConfigBuilder()

public EvaluationJobAlertConfig.Builder getEvaluationJobAlertConfigBuilder()

.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;

Returns
Type	Description
`EvaluationJobAlertConfig.Builder`

getEvaluationJobAlertConfigOrBuilder()

public EvaluationJobAlertConfigOrBuilder getEvaluationJobAlertConfigOrBuilder()

.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;

Returns
Type	Description
`EvaluationJobAlertConfigOrBuilder`

getExampleCount()

public int getExampleCount()

int32 example_count = 10;

Returns
Type	Description
`int`	The exampleCount.

getExampleSamplePercentage()

public double getExampleSamplePercentage()

Required. Fraction of predictions to sample and save to BigQuery during each evaluation interval. For example, 0.1 means 10% of predictions served by your model version get saved to BigQuery.

double example_sample_percentage = 11;

Returns
Type	Description
`double`	The exampleSamplePercentage.

getHumanAnnotationConfig()

public HumanAnnotationConfig getHumanAnnotationConfig()

Note that you must create an Instruction resource before you can specify this field. Provide the name of the instruction resource in the instruction field within this configuration.

.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;

Returns
Type	Description
`HumanAnnotationConfig`	The humanAnnotationConfig.

getHumanAnnotationConfigBuilder()

public HumanAnnotationConfig.Builder getHumanAnnotationConfigBuilder()

Note that you must create an Instruction resource before you can specify this field. Provide the name of the instruction resource in the instruction field within this configuration.

.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;

Returns
Type	Description
`HumanAnnotationConfig.Builder`

getHumanAnnotationConfigOrBuilder()

public HumanAnnotationConfigOrBuilder getHumanAnnotationConfigOrBuilder()

Note that you must create an Instruction resource before you can specify this field. Provide the name of the instruction resource in the instruction field within this configuration.

.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;

Returns
Type	Description
`HumanAnnotationConfigOrBuilder`

getHumanAnnotationRequestConfigCase()

public EvaluationJobConfig.HumanAnnotationRequestConfigCase getHumanAnnotationRequestConfigCase()

Returns
Type	Description
`EvaluationJobConfig.HumanAnnotationRequestConfigCase`

getImageClassificationConfig()

public ImageClassificationConfig getImageClassificationConfig()

Specify this field if your model version performs image classification or general classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;

Returns
Type	Description
`ImageClassificationConfig`	The imageClassificationConfig.

getImageClassificationConfigBuilder()

public ImageClassificationConfig.Builder getImageClassificationConfigBuilder()

Specify this field if your model version performs image classification or general classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;

Returns
Type	Description
`ImageClassificationConfig.Builder`

getImageClassificationConfigOrBuilder()

public ImageClassificationConfigOrBuilder getImageClassificationConfigOrBuilder()

Specify this field if your model version performs image classification or general classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;

Returns
Type	Description
`ImageClassificationConfigOrBuilder`

getInputConfig()

public InputConfig getInputConfig()

Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:

dataType must be one of IMAGE, TEXT, or GENERAL_DATA.
annotationType must be one of IMAGE_CLASSIFICATION_ANNOTATION, TEXT_CLASSIFICATION_ANNOTATION, GENERAL_CLASSIFICATION_ANNOTATION, or IMAGE_BOUNDING_BOX_ANNOTATION (image object detection).
If your machine learning model performs classification, you must specify classificationMetadata.isMultiLabel.
You must specify bigquerySource (not gcsSource).

.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;

Returns
Type	Description
`InputConfig`	The inputConfig.

getInputConfigBuilder()

public InputConfig.Builder getInputConfigBuilder()

Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:

dataType must be one of IMAGE, TEXT, or GENERAL_DATA.
annotationType must be one of IMAGE_CLASSIFICATION_ANNOTATION, TEXT_CLASSIFICATION_ANNOTATION, GENERAL_CLASSIFICATION_ANNOTATION, or IMAGE_BOUNDING_BOX_ANNOTATION (image object detection).
If your machine learning model performs classification, you must specify classificationMetadata.isMultiLabel.
You must specify bigquerySource (not gcsSource).

.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;

Returns
Type	Description
`InputConfig.Builder`

getInputConfigOrBuilder()

public InputConfigOrBuilder getInputConfigOrBuilder()

Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:

dataType must be one of IMAGE, TEXT, or GENERAL_DATA.
annotationType must be one of IMAGE_CLASSIFICATION_ANNOTATION, TEXT_CLASSIFICATION_ANNOTATION, GENERAL_CLASSIFICATION_ANNOTATION, or IMAGE_BOUNDING_BOX_ANNOTATION (image object detection).
If your machine learning model performs classification, you must specify classificationMetadata.isMultiLabel.
You must specify bigquerySource (not gcsSource).

.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;

Returns
Type	Description
`InputConfigOrBuilder`

getMutableBigqueryImportKeys()

public Map<String,String> getMutableBigqueryImportKeys()

Use alternate mutation accessors instead.

Returns
Type	Description
`Map<String,String>`

getTextClassificationConfig()

public TextClassificationConfig getTextClassificationConfig()

Specify this field if your model version performs text classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;

Returns
Type	Description
`TextClassificationConfig`	The textClassificationConfig.

getTextClassificationConfigBuilder()

public TextClassificationConfig.Builder getTextClassificationConfigBuilder()

Specify this field if your model version performs text classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;

Returns
Type	Description
`TextClassificationConfig.Builder`

getTextClassificationConfigOrBuilder()

public TextClassificationConfigOrBuilder getTextClassificationConfigOrBuilder()

Specify this field if your model version performs text classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;

Returns
Type	Description
`TextClassificationConfigOrBuilder`

hasBoundingPolyConfig()

public boolean hasBoundingPolyConfig()

Specify this field if your model version performs image object detection (bounding box detection).

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet.

.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;

Returns
Type	Description
`boolean`	Whether the boundingPolyConfig field is set.

hasEvaluationConfig()

public boolean hasEvaluationConfig()

.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;

Returns
Type	Description
`boolean`	Whether the evaluationConfig field is set.

hasEvaluationJobAlertConfig()

public boolean hasEvaluationJobAlertConfig()

.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;

Returns
Type	Description
`boolean`	Whether the evaluationJobAlertConfig field is set.

hasHumanAnnotationConfig()

public boolean hasHumanAnnotationConfig()

Note that you must create an Instruction resource before you can specify this field. Provide the name of the instruction resource in the instruction field within this configuration.

.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;

Returns
Type	Description
`boolean`	Whether the humanAnnotationConfig field is set.

hasImageClassificationConfig()

public boolean hasImageClassificationConfig()

Specify this field if your model version performs image classification or general classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;

Returns
Type	Description
`boolean`	Whether the imageClassificationConfig field is set.

hasInputConfig()

public boolean hasInputConfig()

Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:

dataType must be one of IMAGE, TEXT, or GENERAL_DATA.
annotationType must be one of IMAGE_CLASSIFICATION_ANNOTATION, TEXT_CLASSIFICATION_ANNOTATION, GENERAL_CLASSIFICATION_ANNOTATION, or IMAGE_BOUNDING_BOX_ANNOTATION (image object detection).
If your machine learning model performs classification, you must specify classificationMetadata.isMultiLabel.
You must specify bigquerySource (not gcsSource).

.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;

Returns
Type	Description
`boolean`	Whether the inputConfig field is set.

hasTextClassificationConfig()

public boolean hasTextClassificationConfig()

Specify this field if your model version performs text classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;

Returns
Type	Description
`boolean`	Whether the textClassificationConfig field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns
Type	Description
`FieldAccessorTable`

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

internalGetMapField(int number)

protected MapField internalGetMapField(int number)

Parameter
Name	Description
`number`	`int`

Returns
Type	Description
`MapField`

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetMapField(int fieldNumber)

internalGetMutableMapField(int number)

protected MapField internalGetMutableMapField(int number)

Parameter
Name	Description
`number`	`int`

Returns
Type	Description
`MapField`

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetMutableMapField(int fieldNumber)

isInitialized()

public final boolean isInitialized()

Returns
Type	Description
`boolean`

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeBoundingPolyConfig(BoundingPolyConfig value)

public EvaluationJobConfig.Builder mergeBoundingPolyConfig(BoundingPolyConfig value)

Specify this field if your model version performs image object detection (bounding box detection).

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet.

.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;

Parameter
Name	Description
`value`	`BoundingPolyConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

mergeEvaluationConfig(EvaluationConfig value)

public EvaluationJobConfig.Builder mergeEvaluationConfig(EvaluationConfig value)

.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;

Parameter
Name	Description
`value`	`EvaluationConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

mergeEvaluationJobAlertConfig(EvaluationJobAlertConfig value)

public EvaluationJobConfig.Builder mergeEvaluationJobAlertConfig(EvaluationJobAlertConfig value)

.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;

Parameter
Name	Description
`value`	`EvaluationJobAlertConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

mergeFrom(EvaluationJobConfig other)

public EvaluationJobConfig.Builder mergeFrom(EvaluationJobConfig other)

Parameter
Name	Description
`other`	`EvaluationJobConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public EvaluationJobConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
`input`	`CodedInputStream`
`extensionRegistry`	`ExtensionRegistryLite`

Returns
Type	Description
`EvaluationJobConfig.Builder`

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions
Type	Description
`IOException`

mergeFrom(Message other)

public EvaluationJobConfig.Builder mergeFrom(Message other)

Parameter
Name	Description
`other`	`Message`

Returns
Type	Description
`EvaluationJobConfig.Builder`

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

mergeHumanAnnotationConfig(HumanAnnotationConfig value)

public EvaluationJobConfig.Builder mergeHumanAnnotationConfig(HumanAnnotationConfig value)

Note that you must create an Instruction resource before you can specify this field. Provide the name of the instruction resource in the instruction field within this configuration.

.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;

Parameter
Name	Description
`value`	`HumanAnnotationConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

mergeImageClassificationConfig(ImageClassificationConfig value)

public EvaluationJobConfig.Builder mergeImageClassificationConfig(ImageClassificationConfig value)

Specify this field if your model version performs image classification or general classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;

Parameter
Name	Description
`value`	`ImageClassificationConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

mergeInputConfig(InputConfig value)

public EvaluationJobConfig.Builder mergeInputConfig(InputConfig value)

Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:

dataType must be one of IMAGE, TEXT, or GENERAL_DATA.
annotationType must be one of IMAGE_CLASSIFICATION_ANNOTATION, TEXT_CLASSIFICATION_ANNOTATION, GENERAL_CLASSIFICATION_ANNOTATION, or IMAGE_BOUNDING_BOX_ANNOTATION (image object detection).
If your machine learning model performs classification, you must specify classificationMetadata.isMultiLabel.
You must specify bigquerySource (not gcsSource).

.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;

Parameter
Name	Description
`value`	`InputConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

mergeTextClassificationConfig(TextClassificationConfig value)

public EvaluationJobConfig.Builder mergeTextClassificationConfig(TextClassificationConfig value)

Specify this field if your model version performs text classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;

Parameter
Name	Description
`value`	`TextClassificationConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

mergeUnknownFields(UnknownFieldSet unknownFields)

public final EvaluationJobConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
`unknownFields`	`UnknownFieldSet`

Returns
Type	Description
`EvaluationJobConfig.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

putAllBigqueryImportKeys(Map<String,String> values)

public EvaluationJobConfig.Builder putAllBigqueryImportKeys(Map<String,String> values)

You can provide the following entries in this field:

data_json_key: the data key for prediction input. You must provide either this key or reference_json_key.
reference_json_key: the data reference key for prediction input. You must provide either this key or data_json_key.
label_json_key: the label key for prediction output. Required.
label_score_json_key: the score key for prediction output. Required.
bounding_box_json_key: the bounding box key for prediction output. Required if your model version perform image object detection.

Learn how to configure prediction keys.

map<string, string> bigquery_import_keys = 9;

Parameter
Name	Description
`values`	`Map<String,String>`

Returns
Type	Description
`EvaluationJobConfig.Builder`

putBigqueryImportKeys(String key, String value)

public EvaluationJobConfig.Builder putBigqueryImportKeys(String key, String value)

You can provide the following entries in this field:

data_json_key: the data key for prediction input. You must provide either this key or reference_json_key.
reference_json_key: the data reference key for prediction input. You must provide either this key or data_json_key.
label_json_key: the label key for prediction output. Required.
label_score_json_key: the score key for prediction output. Required.
bounding_box_json_key: the bounding box key for prediction output. Required if your model version perform image object detection.

Learn how to configure prediction keys.

map<string, string> bigquery_import_keys = 9;

Parameters
Name	Description
`key`	`String`
`value`	`String`

Returns
Type	Description
`EvaluationJobConfig.Builder`

removeBigqueryImportKeys(String key)

public EvaluationJobConfig.Builder removeBigqueryImportKeys(String key)

You can provide the following entries in this field:

data_json_key: the data key for prediction input. You must provide either this key or reference_json_key.
reference_json_key: the data reference key for prediction input. You must provide either this key or data_json_key.
label_json_key: the label key for prediction output. Required.
label_score_json_key: the score key for prediction output. Required.
bounding_box_json_key: the bounding box key for prediction output. Required if your model version perform image object detection.

Learn how to configure prediction keys.

map<string, string> bigquery_import_keys = 9;

Parameter
Name	Description
`key`	`String`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setBoundingPolyConfig(BoundingPolyConfig value)

public EvaluationJobConfig.Builder setBoundingPolyConfig(BoundingPolyConfig value)

Specify this field if your model version performs image object detection (bounding box detection).

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet.

.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;

Parameter
Name	Description
`value`	`BoundingPolyConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setBoundingPolyConfig(BoundingPolyConfig.Builder builderForValue)

public EvaluationJobConfig.Builder setBoundingPolyConfig(BoundingPolyConfig.Builder builderForValue)

Specify this field if your model version performs image object detection (bounding box detection).

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet.

.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;

Parameter
Name	Description
`builderForValue`	`BoundingPolyConfig.Builder`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setEvaluationConfig(EvaluationConfig value)

public EvaluationJobConfig.Builder setEvaluationConfig(EvaluationConfig value)

.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;

Parameter
Name	Description
`value`	`EvaluationConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setEvaluationConfig(EvaluationConfig.Builder builderForValue)

public EvaluationJobConfig.Builder setEvaluationConfig(EvaluationConfig.Builder builderForValue)

.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;

Parameter
Name	Description
`builderForValue`	`EvaluationConfig.Builder`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setEvaluationJobAlertConfig(EvaluationJobAlertConfig value)

public EvaluationJobConfig.Builder setEvaluationJobAlertConfig(EvaluationJobAlertConfig value)

.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;

Parameter
Name	Description
`value`	`EvaluationJobAlertConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setEvaluationJobAlertConfig(EvaluationJobAlertConfig.Builder builderForValue)

public EvaluationJobConfig.Builder setEvaluationJobAlertConfig(EvaluationJobAlertConfig.Builder builderForValue)

.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;

Parameter
Name	Description
`builderForValue`	`EvaluationJobAlertConfig.Builder`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setExampleCount(int value)

public EvaluationJobConfig.Builder setExampleCount(int value)

int32 example_count = 10;

Parameter
Name	Description
`value`	`int` The exampleCount to set.

Returns
Type	Description
`EvaluationJobConfig.Builder`	This builder for chaining.

setExampleSamplePercentage(double value)

public EvaluationJobConfig.Builder setExampleSamplePercentage(double value)

Required. Fraction of predictions to sample and save to BigQuery during each evaluation interval. For example, 0.1 means 10% of predictions served by your model version get saved to BigQuery.

double example_sample_percentage = 11;

Parameter
Name	Description
`value`	`double` The exampleSamplePercentage to set.

Returns
Type	Description
`EvaluationJobConfig.Builder`	This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public EvaluationJobConfig.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
`field`	`FieldDescriptor`
`value`	`Object`

Returns
Type	Description
`EvaluationJobConfig.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

setHumanAnnotationConfig(HumanAnnotationConfig value)

public EvaluationJobConfig.Builder setHumanAnnotationConfig(HumanAnnotationConfig value)

Note that you must create an Instruction resource before you can specify this field. Provide the name of the instruction resource in the instruction field within this configuration.

.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;

Parameter
Name	Description
`value`	`HumanAnnotationConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setHumanAnnotationConfig(HumanAnnotationConfig.Builder builderForValue)

public EvaluationJobConfig.Builder setHumanAnnotationConfig(HumanAnnotationConfig.Builder builderForValue)

Note that you must create an Instruction resource before you can specify this field. Provide the name of the instruction resource in the instruction field within this configuration.

.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;

Parameter
Name	Description
`builderForValue`	`HumanAnnotationConfig.Builder`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setImageClassificationConfig(ImageClassificationConfig value)

public EvaluationJobConfig.Builder setImageClassificationConfig(ImageClassificationConfig value)

Specify this field if your model version performs image classification or general classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;

Parameter
Name	Description
`value`	`ImageClassificationConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setImageClassificationConfig(ImageClassificationConfig.Builder builderForValue)

public EvaluationJobConfig.Builder setImageClassificationConfig(ImageClassificationConfig.Builder builderForValue)

Specify this field if your model version performs image classification or general classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;

Parameter
Name	Description
`builderForValue`	`ImageClassificationConfig.Builder`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setInputConfig(InputConfig value)

public EvaluationJobConfig.Builder setInputConfig(InputConfig value)

Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:

dataType must be one of IMAGE, TEXT, or GENERAL_DATA.
annotationType must be one of IMAGE_CLASSIFICATION_ANNOTATION, TEXT_CLASSIFICATION_ANNOTATION, GENERAL_CLASSIFICATION_ANNOTATION, or IMAGE_BOUNDING_BOX_ANNOTATION (image object detection).
If your machine learning model performs classification, you must specify classificationMetadata.isMultiLabel.
You must specify bigquerySource (not gcsSource).

.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;

Parameter
Name	Description
`value`	`InputConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setInputConfig(InputConfig.Builder builderForValue)

public EvaluationJobConfig.Builder setInputConfig(InputConfig.Builder builderForValue)

Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:

dataType must be one of IMAGE, TEXT, or GENERAL_DATA.
annotationType must be one of IMAGE_CLASSIFICATION_ANNOTATION, TEXT_CLASSIFICATION_ANNOTATION, GENERAL_CLASSIFICATION_ANNOTATION, or IMAGE_BOUNDING_BOX_ANNOTATION (image object detection).
If your machine learning model performs classification, you must specify classificationMetadata.isMultiLabel.
You must specify bigquerySource (not gcsSource).

.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;

Parameter
Name	Description
`builderForValue`	`InputConfig.Builder`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public EvaluationJobConfig.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

Parameters
Name	Description
`field`	`FieldDescriptor`
`index`	`int`
`value`	`Object`

Returns
Type	Description
`EvaluationJobConfig.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

setTextClassificationConfig(TextClassificationConfig value)

public EvaluationJobConfig.Builder setTextClassificationConfig(TextClassificationConfig value)

Specify this field if your model version performs text classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;

Parameter
Name	Description
`value`	`TextClassificationConfig`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setTextClassificationConfig(TextClassificationConfig.Builder builderForValue)

public EvaluationJobConfig.Builder setTextClassificationConfig(TextClassificationConfig.Builder builderForValue)

Specify this field if your model version performs text classification.

annotationSpecSet in this configuration must match EvaluationJob.annotationSpecSet. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in input_config.

.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;

Parameter
Name	Description
`builderForValue`	`TextClassificationConfig.Builder`

Returns
Type	Description
`EvaluationJobConfig.Builder`

setUnknownFields(UnknownFieldSet unknownFields)

public final EvaluationJobConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
`unknownFields`	`UnknownFieldSet`

Returns
Type	Description
`EvaluationJobConfig.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)