Package com.google.cloud.datalabeling.v1beta1

Class 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.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

    • Method Detail

      • getDescriptor

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

      • internalGetMapField

        protected com.google.protobuf.MapField internalGetMapField​(int number)
        Overrides:
        internalGetMapField in class com.google.protobuf.GeneratedMessageV3.Builder<EvaluationJobConfig.Builder>

      • internalGetMutableMapField

        protected com.google.protobuf.MapField internalGetMutableMapField​(int number)
        Overrides:
        internalGetMutableMapField in class com.google.protobuf.GeneratedMessageV3.Builder<EvaluationJobConfig.Builder>

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.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.GeneratedMessageV3.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.GeneratedMessageV3.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

      • clone

        public EvaluationJobConfig.Builder clone()
        Specified by:
        clone in interface com.google.protobuf.Message.Builder
        Specified by:
        clone in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        clone in class com.google.protobuf.GeneratedMessageV3.Builder<EvaluationJobConfig.Builder>

      • setField

        public EvaluationJobConfig.Builder setField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                            Object value)
        Specified by:
        setField in interface com.google.protobuf.Message.Builder
        Overrides:
        setField in class com.google.protobuf.GeneratedMessageV3.Builder<EvaluationJobConfig.Builder>

      • clearField

        public EvaluationJobConfig.Builder clearField​(com.google.protobuf.Descriptors.FieldDescriptor field)
        Specified by:
        clearField in interface com.google.protobuf.Message.Builder
        Overrides:
        clearField in class com.google.protobuf.GeneratedMessageV3.Builder<EvaluationJobConfig.Builder>

      • clearOneof

        public EvaluationJobConfig.Builder clearOneof​(com.google.protobuf.Descriptors.OneofDescriptor oneof)
        Specified by:
        clearOneof in interface com.google.protobuf.Message.Builder
        Overrides:
        clearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<EvaluationJobConfig.Builder>

      • setRepeatedField

        public EvaluationJobConfig.Builder setRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                    int index,
                                                    Object value)
        Specified by:
        setRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        setRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<EvaluationJobConfig.Builder>

      • addRepeatedField

        public EvaluationJobConfig.Builder addRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                    Object value)
        Specified by:
        addRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        addRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<EvaluationJobConfig.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>

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessageV3.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

      • 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

      • 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

      • 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

      • setUnknownFields

        public final EvaluationJobConfig.Builder setUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        setUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        setUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<EvaluationJobConfig.Builder>

      • mergeUnknownFields

        public final EvaluationJobConfig.Builder mergeUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        mergeUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        mergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<EvaluationJobConfig.Builder>