Package com.google.cloud.datalabeling.v1beta1

Class EvaluationJobConfig.Builder

java.lang.Object

com.google.protobuf.AbstractMessageLite.Builder

com.google.protobuf.AbstractMessage.Builder<BuilderT>

com.google.protobuf.GeneratedMessage.Builder<EvaluationJobConfig.Builder>

com.google.cloud.datalabeling.v1beta1.EvaluationJobConfig.Builder

All Implemented Interfaces:

EvaluationJobConfigOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable

Enclosing class:

EvaluationJobConfig

public static final class EvaluationJobConfig.Builder
extends com.google.protobuf.GeneratedMessage.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

Method Summary

Modifier and Type	Method	Description
EvaluationJobConfig	build()
EvaluationJobConfig	buildPartial()
EvaluationJobConfig.Builder	clear()
EvaluationJobConfig.Builder	clearBigqueryImportKeys()
EvaluationJobConfig.Builder	clearBoundingPolyConfig()	Specify this field if your model version performs image object detection (bounding box detection).
EvaluationJobConfig.Builder	clearEvaluationConfig()	Required.
EvaluationJobConfig.Builder	clearEvaluationJobAlertConfig()	Optional.
EvaluationJobConfig.Builder	clearExampleCount()	Required.
EvaluationJobConfig.Builder	clearExampleSamplePercentage()	Required.
EvaluationJobConfig.Builder	clearHumanAnnotationConfig()	Optional.
EvaluationJobConfig.Builder	clearHumanAnnotationRequestConfig()
EvaluationJobConfig.Builder	clearImageClassificationConfig()	Specify this field if your model version performs image classification or general classification.
EvaluationJobConfig.Builder	clearInputConfig()	Rquired.
EvaluationJobConfig.Builder	clearTextClassificationConfig()	Specify this field if your model version performs text classification.
boolean	containsBigqueryImportKeys(String key)	Required.
Map<String,String>	getBigqueryImportKeys()	Deprecated.
int	getBigqueryImportKeysCount()	Required.
Map<String,String>	getBigqueryImportKeysMap()	Required.
String	getBigqueryImportKeysOrDefault(String key, String defaultValue)	Required.
String	getBigqueryImportKeysOrThrow(String key)	Required.
BoundingPolyConfig	getBoundingPolyConfig()	Specify this field if your model version performs image object detection (bounding box detection).
BoundingPolyConfig.Builder	getBoundingPolyConfigBuilder()	Specify this field if your model version performs image object detection (bounding box detection).
BoundingPolyConfigOrBuilder	getBoundingPolyConfigOrBuilder()	Specify this field if your model version performs image object detection (bounding box detection).
EvaluationJobConfig	getDefaultInstanceForType()
static final com.google.protobuf.Descriptors.Descriptor	getDescriptor()
com.google.protobuf.Descriptors.Descriptor	getDescriptorForType()
EvaluationConfig	getEvaluationConfig()	Required.
EvaluationConfig.Builder	getEvaluationConfigBuilder()	Required.
EvaluationConfigOrBuilder	getEvaluationConfigOrBuilder()	Required.
EvaluationJobAlertConfig	getEvaluationJobAlertConfig()	Optional.
EvaluationJobAlertConfig.Builder	getEvaluationJobAlertConfigBuilder()	Optional.
EvaluationJobAlertConfigOrBuilder	getEvaluationJobAlertConfigOrBuilder()	Optional.
int	getExampleCount()	Required.
double	getExampleSamplePercentage()	Required.
HumanAnnotationConfig	getHumanAnnotationConfig()	Optional.
HumanAnnotationConfig.Builder	getHumanAnnotationConfigBuilder()	Optional.
HumanAnnotationConfigOrBuilder	getHumanAnnotationConfigOrBuilder()	Optional.
EvaluationJobConfig.HumanAnnotationRequestConfigCase	getHumanAnnotationRequestConfigCase()
ImageClassificationConfig	getImageClassificationConfig()	Specify this field if your model version performs image classification or general classification.
ImageClassificationConfig.Builder	getImageClassificationConfigBuilder()	Specify this field if your model version performs image classification or general classification.
ImageClassificationConfigOrBuilder	getImageClassificationConfigOrBuilder()	Specify this field if your model version performs image classification or general classification.
InputConfig	getInputConfig()	Rquired.
InputConfig.Builder	getInputConfigBuilder()	Rquired.
InputConfigOrBuilder	getInputConfigOrBuilder()	Rquired.
Map<String,String>	getMutableBigqueryImportKeys()	Deprecated.
TextClassificationConfig	getTextClassificationConfig()	Specify this field if your model version performs text classification.
TextClassificationConfig.Builder	getTextClassificationConfigBuilder()	Specify this field if your model version performs text classification.
TextClassificationConfigOrBuilder	getTextClassificationConfigOrBuilder()	Specify this field if your model version performs text classification.
boolean	hasBoundingPolyConfig()	Specify this field if your model version performs image object detection (bounding box detection).
boolean	hasEvaluationConfig()	Required.
boolean	hasEvaluationJobAlertConfig()	Optional.
boolean	hasHumanAnnotationConfig()	Optional.
boolean	hasImageClassificationConfig()	Specify this field if your model version performs image classification or general classification.
boolean	hasInputConfig()	Rquired.
boolean	hasTextClassificationConfig()	Specify this field if your model version performs text classification.
protected com.google.protobuf.GeneratedMessage.FieldAccessorTable	internalGetFieldAccessorTable()
protected com.google.protobuf.MapFieldReflectionAccessor	internalGetMapFieldReflection(int number)
protected com.google.protobuf.MapFieldReflectionAccessor	internalGetMutableMapFieldReflection(int number)
final boolean	isInitialized()
EvaluationJobConfig.Builder	mergeBoundingPolyConfig(BoundingPolyConfig value)	Specify this field if your model version performs image object detection (bounding box detection).
EvaluationJobConfig.Builder	mergeEvaluationConfig(EvaluationConfig value)	Required.
EvaluationJobConfig.Builder	mergeEvaluationJobAlertConfig(EvaluationJobAlertConfig value)	Optional.
EvaluationJobConfig.Builder	mergeFrom(EvaluationJobConfig other)
EvaluationJobConfig.Builder	mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
EvaluationJobConfig.Builder	mergeFrom(com.google.protobuf.Message other)
EvaluationJobConfig.Builder	mergeHumanAnnotationConfig(HumanAnnotationConfig value)	Optional.
EvaluationJobConfig.Builder	mergeImageClassificationConfig(ImageClassificationConfig value)	Specify this field if your model version performs image classification or general classification.
EvaluationJobConfig.Builder	mergeInputConfig(InputConfig value)	Rquired.
EvaluationJobConfig.Builder	mergeTextClassificationConfig(TextClassificationConfig value)	Specify this field if your model version performs text classification.
EvaluationJobConfig.Builder	putAllBigqueryImportKeys(Map<String,String> values)	Required.
EvaluationJobConfig.Builder	putBigqueryImportKeys(String key, String value)	Required.
EvaluationJobConfig.Builder	removeBigqueryImportKeys(String key)	Required.
EvaluationJobConfig.Builder	setBoundingPolyConfig(BoundingPolyConfig value)	Specify this field if your model version performs image object detection (bounding box detection).
EvaluationJobConfig.Builder	setBoundingPolyConfig(BoundingPolyConfig.Builder builderForValue)	Specify this field if your model version performs image object detection (bounding box detection).
EvaluationJobConfig.Builder	setEvaluationConfig(EvaluationConfig value)	Required.
EvaluationJobConfig.Builder	setEvaluationConfig(EvaluationConfig.Builder builderForValue)	Required.
EvaluationJobConfig.Builder	setEvaluationJobAlertConfig(EvaluationJobAlertConfig value)	Optional.
EvaluationJobConfig.Builder	setEvaluationJobAlertConfig(EvaluationJobAlertConfig.Builder builderForValue)	Optional.
EvaluationJobConfig.Builder	setExampleCount(int value)	Required.
EvaluationJobConfig.Builder	setExampleSamplePercentage(double value)	Required.
EvaluationJobConfig.Builder	setHumanAnnotationConfig(HumanAnnotationConfig value)	Optional.
EvaluationJobConfig.Builder	setHumanAnnotationConfig(HumanAnnotationConfig.Builder builderForValue)	Optional.
EvaluationJobConfig.Builder	setImageClassificationConfig(ImageClassificationConfig value)	Specify this field if your model version performs image classification or general classification.
EvaluationJobConfig.Builder	setImageClassificationConfig(ImageClassificationConfig.Builder builderForValue)	Specify this field if your model version performs image classification or general classification.
EvaluationJobConfig.Builder	setInputConfig(InputConfig value)	Rquired.
EvaluationJobConfig.Builder	setInputConfig(InputConfig.Builder builderForValue)	Rquired.
EvaluationJobConfig.Builder	setTextClassificationConfig(TextClassificationConfig value)	Specify this field if your model version performs text classification.
EvaluationJobConfig.Builder	setTextClassificationConfig(TextClassificationConfig.Builder builderForValue)	Specify this field if your model version performs text classification.

Methods inherited from class com.google.protobuf.GeneratedMessage.Builder

addRepeatedField, clearField, clearOneof, clone, getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMutableMapField, isClean, markClean, mergeUnknownFields, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setField, setRepeatedField, setUnknownFields, setUnknownFieldSetBuilder, setUnknownFieldsProto3

Methods inherited from class com.google.protobuf.AbstractMessage.Builder

findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toString

Methods inherited from class com.google.protobuf.AbstractMessageLite.Builder

addAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, newUninitializedMessageException

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface com.google.protobuf.Message.Builder

mergeDelimitedFrom, mergeDelimitedFrom

Methods inherited from interface com.google.protobuf.MessageLite.Builder

mergeFrom

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Method Details

getDescriptor

public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

internalGetMapFieldReflection

protected com.google.protobuf.MapFieldReflectionAccessor internalGetMapFieldReflection(int number)

Overrides:

internalGetMapFieldReflection in class com.google.protobuf.GeneratedMessage.Builder<EvaluationJobConfig.Builder>

internalGetMutableMapFieldReflection

protected com.google.protobuf.MapFieldReflectionAccessor internalGetMutableMapFieldReflection(int number)

Overrides:

internalGetMutableMapFieldReflection in class com.google.protobuf.GeneratedMessage.Builder<EvaluationJobConfig.Builder>

internalGetFieldAccessorTable

protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()

Specified by:

internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<EvaluationJobConfig.Builder>

clear

public EvaluationJobConfig.Builder clear()

Specified by:

clear in interface com.google.protobuf.Message.Builder

Specified by:

clear in interface com.google.protobuf.MessageLite.Builder

Overrides:

clear in class com.google.protobuf.GeneratedMessage.Builder<EvaluationJobConfig.Builder>

getDescriptorForType

public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()

Specified by:

getDescriptorForType in interface com.google.protobuf.Message.Builder

Specified by:

getDescriptorForType in interface com.google.protobuf.MessageOrBuilder

Overrides:

getDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<EvaluationJobConfig.Builder>

getDefaultInstanceForType

public EvaluationJobConfig getDefaultInstanceForType()

Specified by:

getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder

Specified by:

getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

build

public EvaluationJobConfig build()

Specified by:

build in interface com.google.protobuf.Message.Builder

Specified by:

build in interface com.google.protobuf.MessageLite.Builder

buildPartial

public EvaluationJobConfig buildPartial()

Specified by:

buildPartial in interface com.google.protobuf.Message.Builder

Specified by:

buildPartial in interface com.google.protobuf.MessageLite.Builder

mergeFrom

public EvaluationJobConfig.Builder mergeFrom(com.google.protobuf.Message other)

Specified by:

mergeFrom in interface com.google.protobuf.Message.Builder

Overrides:

mergeFrom in class com.google.protobuf.AbstractMessage.Builder<EvaluationJobConfig.Builder>

mergeFrom

public EvaluationJobConfig.Builder mergeFrom(EvaluationJobConfig other)

isInitialized

public final boolean isInitialized()

Specified by:

isInitialized in interface com.google.protobuf.MessageLiteOrBuilder

Overrides:

isInitialized in class com.google.protobuf.GeneratedMessage.Builder<EvaluationJobConfig.Builder>

mergeFrom

public EvaluationJobConfig.Builder mergeFrom(com.google.protobuf.CodedInputStream input,
 com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                      throws IOException

Specified by:

mergeFrom in interface com.google.protobuf.Message.Builder

Specified by:

mergeFrom in interface com.google.protobuf.MessageLite.Builder

Overrides:

mergeFrom in class com.google.protobuf.AbstractMessage.Builder<EvaluationJobConfig.Builder>

Throws:

IOException

getHumanAnnotationRequestConfigCase

public EvaluationJobConfig.HumanAnnotationRequestConfigCase getHumanAnnotationRequestConfigCase()

Specified by:

getHumanAnnotationRequestConfigCase in interface EvaluationJobConfigOrBuilder

clearHumanAnnotationRequestConfig

public EvaluationJobConfig.Builder clearHumanAnnotationRequestConfig()

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][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

Specified by:

hasImageClassificationConfig in interface EvaluationJobConfigOrBuilder

Returns:

Whether the imageClassificationConfig field is set.

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][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

Specified by:

getImageClassificationConfig in interface EvaluationJobConfigOrBuilder

Returns:

The imageClassificationConfig.

setImageClassificationConfig

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][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

setImageClassificationConfig

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][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

mergeImageClassificationConfig

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][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

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][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

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][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

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][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

Specified by:

getImageClassificationConfigOrBuilder in interface EvaluationJobConfigOrBuilder

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.EvaluationJob.annotation_spec_set].
 

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

Specified by:

hasBoundingPolyConfig in interface EvaluationJobConfigOrBuilder

Returns:

Whether the boundingPolyConfig field is set.

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.EvaluationJob.annotation_spec_set].
 

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

Specified by:

getBoundingPolyConfig in interface EvaluationJobConfigOrBuilder

Returns:

The boundingPolyConfig.

setBoundingPolyConfig

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.EvaluationJob.annotation_spec_set].
 

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

setBoundingPolyConfig

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.EvaluationJob.annotation_spec_set].
 

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

mergeBoundingPolyConfig

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.EvaluationJob.annotation_spec_set].
 

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

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.EvaluationJob.annotation_spec_set].
 

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

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.EvaluationJob.annotation_spec_set].
 

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

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.EvaluationJob.annotation_spec_set].
 

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

Specified by:

getBoundingPolyConfigOrBuilder in interface EvaluationJobConfigOrBuilder

hasTextClassificationConfig

public boolean hasTextClassificationConfig()

 Specify this field if your model version performs text classification.

 `annotationSpecSet` in this configuration must match
 [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

Specified by:

hasTextClassificationConfig in interface EvaluationJobConfigOrBuilder

Returns:

Whether the textClassificationConfig field is set.

getTextClassificationConfig

public TextClassificationConfig getTextClassificationConfig()

 Specify this field if your model version performs text classification.

 `annotationSpecSet` in this configuration must match
 [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

Specified by:

getTextClassificationConfig in interface EvaluationJobConfigOrBuilder

Returns:

The textClassificationConfig.

setTextClassificationConfig

public EvaluationJobConfig.Builder setTextClassificationConfig(TextClassificationConfig value)

 Specify this field if your model version performs text classification.

 `annotationSpecSet` in this configuration must match
 [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

setTextClassificationConfig

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][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

mergeTextClassificationConfig

public EvaluationJobConfig.Builder mergeTextClassificationConfig(TextClassificationConfig value)

 Specify this field if your model version performs text classification.

 `annotationSpecSet` in this configuration must match
 [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

clearTextClassificationConfig

public EvaluationJobConfig.Builder clearTextClassificationConfig()

 Specify this field if your model version performs text classification.

 `annotationSpecSet` in this configuration must match
 [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

getTextClassificationConfigBuilder

public TextClassificationConfig.Builder getTextClassificationConfigBuilder()

 Specify this field if your model version performs text classification.

 `annotationSpecSet` in this configuration must match
 [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

getTextClassificationConfigOrBuilder

public TextClassificationConfigOrBuilder getTextClassificationConfigOrBuilder()

 Specify this field if your model version performs text classification.

 `annotationSpecSet` in this configuration must match
 [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
 `allowMultiLabel` in this configuration must match
 `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
 

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

Specified by:

getTextClassificationConfigOrBuilder in interface EvaluationJobConfigOrBuilder

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;

Specified by:

hasInputConfig in interface EvaluationJobConfigOrBuilder

Returns:

Whether the inputConfig field is set.

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;

Specified by:

getInputConfig in interface EvaluationJobConfigOrBuilder

Returns:

The inputConfig.

setInputConfig

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;

setInputConfig

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;

mergeInputConfig

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;

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;

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;

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;

Specified by:

getInputConfigOrBuilder in interface EvaluationJobConfigOrBuilder

hasEvaluationConfig

public boolean hasEvaluationConfig()

 Required. Details for calculating evaluation metrics and creating
 [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. 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;

Specified by:

hasEvaluationConfig in interface EvaluationJobConfigOrBuilder

Returns:

Whether the evaluationConfig field is set.

getEvaluationConfig

public EvaluationConfig getEvaluationConfig()

 Required. Details for calculating evaluation metrics and creating
 [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. 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;

Specified by:

getEvaluationConfig in interface EvaluationJobConfigOrBuilder

Returns:

The evaluationConfig.

setEvaluationConfig

public EvaluationJobConfig.Builder setEvaluationConfig(EvaluationConfig value)

 Required. Details for calculating evaluation metrics and creating
 [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. 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;

setEvaluationConfig

public EvaluationJobConfig.Builder setEvaluationConfig(EvaluationConfig.Builder builderForValue)

 Required. Details for calculating evaluation metrics and creating
 [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. 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;

mergeEvaluationConfig

public EvaluationJobConfig.Builder mergeEvaluationConfig(EvaluationConfig value)

 Required. Details for calculating evaluation metrics and creating
 [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. 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;

clearEvaluationConfig

public EvaluationJobConfig.Builder clearEvaluationConfig()

 Required. Details for calculating evaluation metrics and creating
 [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. 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;

getEvaluationConfigBuilder

public EvaluationConfig.Builder getEvaluationConfigBuilder()

 Required. Details for calculating evaluation metrics and creating
 [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. 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;

getEvaluationConfigOrBuilder

public EvaluationConfigOrBuilder getEvaluationConfigOrBuilder()

 Required. Details for calculating evaluation metrics and creating
 [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. 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;

Specified by:

getEvaluationConfigOrBuilder in interface EvaluationJobConfigOrBuilder

hasHumanAnnotationConfig

public boolean hasHumanAnnotationConfig()

 Optional. Details for human annotation of your data. If you set
 [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] 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][google.cloud.datalabeling.v1beta1.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;

Specified by:

hasHumanAnnotationConfig in interface EvaluationJobConfigOrBuilder

Returns:

Whether the humanAnnotationConfig field is set.

getHumanAnnotationConfig

public HumanAnnotationConfig getHumanAnnotationConfig()

 Optional. Details for human annotation of your data. If you set
 [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] 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][google.cloud.datalabeling.v1beta1.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;

Specified by:

getHumanAnnotationConfig in interface EvaluationJobConfigOrBuilder

Returns:

The humanAnnotationConfig.

setHumanAnnotationConfig

public EvaluationJobConfig.Builder setHumanAnnotationConfig(HumanAnnotationConfig value)

 Optional. Details for human annotation of your data. If you set
 [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] 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][google.cloud.datalabeling.v1beta1.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;

setHumanAnnotationConfig

public EvaluationJobConfig.Builder setHumanAnnotationConfig(HumanAnnotationConfig.Builder builderForValue)

 Optional. Details for human annotation of your data. If you set
 [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] 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][google.cloud.datalabeling.v1beta1.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;

mergeHumanAnnotationConfig

public EvaluationJobConfig.Builder mergeHumanAnnotationConfig(HumanAnnotationConfig value)

 Optional. Details for human annotation of your data. If you set
 [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] 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][google.cloud.datalabeling.v1beta1.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;

clearHumanAnnotationConfig

public EvaluationJobConfig.Builder clearHumanAnnotationConfig()

 Optional. Details for human annotation of your data. If you set
 [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] 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][google.cloud.datalabeling.v1beta1.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;

getHumanAnnotationConfigBuilder

public HumanAnnotationConfig.Builder getHumanAnnotationConfigBuilder()

 Optional. Details for human annotation of your data. If you set
 [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] 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][google.cloud.datalabeling.v1beta1.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;

getHumanAnnotationConfigOrBuilder

public HumanAnnotationConfigOrBuilder getHumanAnnotationConfigOrBuilder()

 Optional. Details for human annotation of your data. If you set
 [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] 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][google.cloud.datalabeling.v1beta1.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;

Specified by:

getHumanAnnotationConfigOrBuilder in interface EvaluationJobConfigOrBuilder

getBigqueryImportKeysCount

public int getBigqueryImportKeysCount()

Description copied from interface: EvaluationJobConfigOrBuilder

 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](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
 

map<string, string> bigquery_import_keys = 9;

Specified by:

getBigqueryImportKeysCount in interface EvaluationJobConfigOrBuilder

containsBigqueryImportKeys

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](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
 

map<string, string> bigquery_import_keys = 9;

Specified by:

containsBigqueryImportKeys in interface EvaluationJobConfigOrBuilder

getBigqueryImportKeys

@Deprecated
public Map<String,String> getBigqueryImportKeys()

Deprecated.

Use getBigqueryImportKeysMap() instead.

Specified by:

getBigqueryImportKeys in interface EvaluationJobConfigOrBuilder

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](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
 

map<string, string> bigquery_import_keys = 9;

Specified by:

getBigqueryImportKeysMap in interface EvaluationJobConfigOrBuilder

getBigqueryImportKeysOrDefault

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](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
 

map<string, string> bigquery_import_keys = 9;

Specified by:

getBigqueryImportKeysOrDefault in interface EvaluationJobConfigOrBuilder

getBigqueryImportKeysOrThrow

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](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
 

map<string, string> bigquery_import_keys = 9;

Specified by:

getBigqueryImportKeysOrThrow in interface EvaluationJobConfigOrBuilder

clearBigqueryImportKeys

public EvaluationJobConfig.Builder clearBigqueryImportKeys()

removeBigqueryImportKeys

public EvaluationJobConfig.Builder removeBigqueryImportKeys(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](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
 

map<string, string> bigquery_import_keys = 9;

getMutableBigqueryImportKeys

@Deprecated
public Map<String,String> getMutableBigqueryImportKeys()

Deprecated.

Use alternate mutation accessors instead.

putBigqueryImportKeys

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

 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](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
 

map<string, string> bigquery_import_keys = 9;

putAllBigqueryImportKeys

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

 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](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys).
 

map<string, string> bigquery_import_keys = 9;

getExampleCount

public int getExampleCount()

 Required. The maximum number of predictions to sample and save to BigQuery
 during each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. 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;

Specified by:

getExampleCount in interface EvaluationJobConfigOrBuilder

Returns:

The exampleCount.

setExampleCount

public EvaluationJobConfig.Builder setExampleCount(int value)

 Required. The maximum number of predictions to sample and save to BigQuery
 during each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. 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;

Parameters:

value - The exampleCount to set.

Returns:

This builder for chaining.

clearExampleCount

public EvaluationJobConfig.Builder clearExampleCount()

 Required. The maximum number of predictions to sample and save to BigQuery
 during each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. 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:

This builder for chaining.

getExampleSamplePercentage

public double getExampleSamplePercentage()

 Required. Fraction of predictions to sample and save to BigQuery during
 each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. For example, 0.1 means
 10% of predictions served by your model version get saved to BigQuery.
 

double example_sample_percentage = 11;

Specified by:

getExampleSamplePercentage in interface EvaluationJobConfigOrBuilder

Returns:

The exampleSamplePercentage.

setExampleSamplePercentage

public EvaluationJobConfig.Builder setExampleSamplePercentage(double value)

 Required. Fraction of predictions to sample and save to BigQuery during
 each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. For example, 0.1 means
 10% of predictions served by your model version get saved to BigQuery.
 

double example_sample_percentage = 11;

Parameters:

value - The exampleSamplePercentage to set.

Returns:

This builder for chaining.

clearExampleSamplePercentage

public EvaluationJobConfig.Builder clearExampleSamplePercentage()

 Required. Fraction of predictions to sample and save to BigQuery during
 each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. For example, 0.1 means
 10% of predictions served by your model version get saved to BigQuery.
 

double example_sample_percentage = 11;

Returns:

This builder for chaining.

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;

Specified by:

hasEvaluationJobAlertConfig in interface EvaluationJobConfigOrBuilder

Returns:

Whether the evaluationJobAlertConfig field is set.

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;

Specified by:

getEvaluationJobAlertConfig in interface EvaluationJobConfigOrBuilder

Returns:

The evaluationJobAlertConfig.

setEvaluationJobAlertConfig

public EvaluationJobConfig.Builder setEvaluationJobAlertConfig(EvaluationJobAlertConfig value)

 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;

setEvaluationJobAlertConfig

public EvaluationJobConfig.Builder setEvaluationJobAlertConfig(EvaluationJobAlertConfig.Builder builderForValue)

 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;

mergeEvaluationJobAlertConfig

public EvaluationJobConfig.Builder mergeEvaluationJobAlertConfig(EvaluationJobAlertConfig value)

 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;

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;

getEvaluationJobAlertConfigBuilder

public EvaluationJobAlertConfig.Builder getEvaluationJobAlertConfigBuilder()

 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;

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;

Specified by:

getEvaluationJobAlertConfigOrBuilder in interface EvaluationJobConfigOrBuilder