Class EvaluationJobConfig (0.166.0)

public final class EvaluationJobConfig extends GeneratedMessageV3 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

Static Fields

BIGQUERY_IMPORT_KEYS_FIELD_NUMBER

public static final int BIGQUERY_IMPORT_KEYS_FIELD_NUMBER
Field Value
Type Description
int

BOUNDING_POLY_CONFIG_FIELD_NUMBER

public static final int BOUNDING_POLY_CONFIG_FIELD_NUMBER
Field Value
Type Description
int

EVALUATION_CONFIG_FIELD_NUMBER

public static final int EVALUATION_CONFIG_FIELD_NUMBER
Field Value
Type Description
int

EVALUATION_JOB_ALERT_CONFIG_FIELD_NUMBER

public static final int EVALUATION_JOB_ALERT_CONFIG_FIELD_NUMBER
Field Value
Type Description
int

EXAMPLE_COUNT_FIELD_NUMBER

public static final int EXAMPLE_COUNT_FIELD_NUMBER
Field Value
Type Description
int

EXAMPLE_SAMPLE_PERCENTAGE_FIELD_NUMBER

public static final int EXAMPLE_SAMPLE_PERCENTAGE_FIELD_NUMBER
Field Value
Type Description
int

HUMAN_ANNOTATION_CONFIG_FIELD_NUMBER

public static final int HUMAN_ANNOTATION_CONFIG_FIELD_NUMBER
Field Value
Type Description
int

IMAGE_CLASSIFICATION_CONFIG_FIELD_NUMBER

public static final int IMAGE_CLASSIFICATION_CONFIG_FIELD_NUMBER
Field Value
Type Description
int

INPUT_CONFIG_FIELD_NUMBER

public static final int INPUT_CONFIG_FIELD_NUMBER
Field Value
Type Description
int

TEXT_CLASSIFICATION_CONFIG_FIELD_NUMBER

public static final int TEXT_CLASSIFICATION_CONFIG_FIELD_NUMBER
Field Value
Type Description
int

Static Methods

getDefaultInstance()

public static EvaluationJobConfig getDefaultInstance()
Returns
Type Description
EvaluationJobConfig

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
Type Description
Descriptor

newBuilder()

public static EvaluationJobConfig.Builder newBuilder()
Returns
Type Description
EvaluationJobConfig.Builder

newBuilder(EvaluationJobConfig prototype)

public static EvaluationJobConfig.Builder newBuilder(EvaluationJobConfig prototype)
Parameter
Name Description
prototype EvaluationJobConfig
Returns
Type Description
EvaluationJobConfig.Builder

parseDelimitedFrom(InputStream input)

public static EvaluationJobConfig parseDelimitedFrom(InputStream input)
Parameter
Name Description
input InputStream
Returns
Type Description
EvaluationJobConfig
Exceptions
Type Description
IOException

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static EvaluationJobConfig parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input InputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
EvaluationJobConfig
Exceptions
Type Description
IOException

parseFrom(byte[] data)

public static EvaluationJobConfig parseFrom(byte[] data)
Parameter
Name Description
data byte[]
Returns
Type Description
EvaluationJobConfig
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

public static EvaluationJobConfig parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data byte[]
extensionRegistry ExtensionRegistryLite
Returns
Type Description
EvaluationJobConfig
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteString data)

public static EvaluationJobConfig parseFrom(ByteString data)
Parameter
Name Description
data ByteString
Returns
Type Description
EvaluationJobConfig
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

public static EvaluationJobConfig parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data ByteString
extensionRegistry ExtensionRegistryLite
Returns
Type Description
EvaluationJobConfig
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(CodedInputStream input)

public static EvaluationJobConfig parseFrom(CodedInputStream input)
Parameter
Name Description
input CodedInputStream
Returns
Type Description
EvaluationJobConfig
Exceptions
Type Description
IOException

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public static EvaluationJobConfig parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input CodedInputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
EvaluationJobConfig
Exceptions
Type Description
IOException

parseFrom(InputStream input)

public static EvaluationJobConfig parseFrom(InputStream input)
Parameter
Name Description
input InputStream
Returns
Type Description
EvaluationJobConfig
Exceptions
Type Description
IOException

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static EvaluationJobConfig parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input InputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
EvaluationJobConfig
Exceptions
Type Description
IOException

parseFrom(ByteBuffer data)

public static EvaluationJobConfig parseFrom(ByteBuffer data)
Parameter
Name Description
data ByteBuffer
Returns
Type Description
EvaluationJobConfig
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

public static EvaluationJobConfig parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data ByteBuffer
extensionRegistry ExtensionRegistryLite
Returns
Type Description
EvaluationJobConfig
Exceptions
Type Description
InvalidProtocolBufferException

parser()

public static Parser<EvaluationJobConfig> parser()
Returns
Type Description
Parser<EvaluationJobConfig>

Methods

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

equals(Object obj)

public boolean equals(Object obj)
Parameter
Name Description
obj Object
Returns
Type Description
boolean
Overrides

getBigqueryImportKeys() (deprecated)

public Map<String,String> getBigqueryImportKeys()
Returns
Type Description
Map<String,String>

getBigqueryImportKeysCount()

public int getBigqueryImportKeysCount()

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;

Returns
Type Description
int

getBigqueryImportKeysMap()

public Map<String,String> getBigqueryImportKeysMap()

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;

Returns
Type Description
Map<String,String>

getBigqueryImportKeysOrDefault(String key, String defaultValue)

public String getBigqueryImportKeysOrDefault(String key, String defaultValue)

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;

Parameters
Name Description
key String
defaultValue String
Returns
Type Description
String

getBigqueryImportKeysOrThrow(String key)

public String getBigqueryImportKeysOrThrow(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
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.

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

getEvaluationConfig()

public EvaluationConfig getEvaluationConfig()

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
EvaluationConfig

The evaluationConfig.

getEvaluationConfigOrBuilder()

public EvaluationConfigOrBuilder getEvaluationConfigOrBuilder()

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
EvaluationConfigOrBuilder

getEvaluationJobAlertConfig()

public EvaluationJobAlertConfig getEvaluationJobAlertConfig()

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
EvaluationJobAlertConfig

The evaluationJobAlertConfig.

getEvaluationJobAlertConfigOrBuilder()

public EvaluationJobAlertConfigOrBuilder getEvaluationJobAlertConfigOrBuilder()

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
EvaluationJobAlertConfigOrBuilder

getExampleCount()

public int getExampleCount()

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
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()

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
HumanAnnotationConfig

The humanAnnotationConfig.

getHumanAnnotationConfigOrBuilder()

public HumanAnnotationConfigOrBuilder getHumanAnnotationConfigOrBuilder()

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
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.

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.

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

getParserForType()

public Parser<EvaluationJobConfig> getParserForType()
Returns
Type Description
Parser<EvaluationJobConfig>
Overrides

getSerializedSize()

public int getSerializedSize()
Returns
Type Description
int
Overrides

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.

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()

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
boolean

Whether the evaluationConfig field is set.

hasEvaluationJobAlertConfig()

public boolean hasEvaluationJobAlertConfig()

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
boolean

Whether the evaluationJobAlertConfig field is set.

hasHumanAnnotationConfig()

public boolean hasHumanAnnotationConfig()

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
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.

hashCode()

public int hashCode()
Returns
Type Description
int
Overrides

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Type Description
FieldAccessorTable
Overrides

internalGetMapFieldReflection(int number)

protected MapFieldReflectionAccessor internalGetMapFieldReflection(int number)
Parameter
Name Description
number int
Returns
Type Description
com.google.protobuf.MapFieldReflectionAccessor
Overrides
com.google.protobuf.GeneratedMessageV3.internalGetMapFieldReflection(int)

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

newBuilderForType()

public EvaluationJobConfig.Builder newBuilderForType()
Returns
Type Description
EvaluationJobConfig.Builder

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

protected EvaluationJobConfig.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Parameter
Name Description
parent BuilderParent
Returns
Type Description
EvaluationJobConfig.Builder
Overrides

newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Parameter
Name Description
unused UnusedPrivateParameter
Returns
Type Description
Object
Overrides

toBuilder()

public EvaluationJobConfig.Builder toBuilder()
Returns
Type Description
EvaluationJobConfig.Builder

writeTo(CodedOutputStream output)

public void writeTo(CodedOutputStream output)
Parameter
Name Description
output CodedOutputStream
Overrides
Exceptions
Type Description
IOException