Package org.tensorflow.metadata.v0

Interface SchemaOrBuilder

  • All Superinterfaces:
    com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
    All Known Implementing Classes:
    Schema, Schema.Builder
    public interface SchemaOrBuilder
extends com.google.protobuf.MessageOrBuilder

    • Method Detail

      • getFeatureList

        List<Feature> getFeatureList()
         Features described in this schema.
        repeated .tensorflow.metadata.v0.Feature feature = 1;

      • getFeature

        Feature getFeature​(int index)
         Features described in this schema.
        repeated .tensorflow.metadata.v0.Feature feature = 1;

      • getFeatureCount

        int getFeatureCount()
         Features described in this schema.
        repeated .tensorflow.metadata.v0.Feature feature = 1;

      • getFeatureOrBuilderList

        List<? extends FeatureOrBuilder> getFeatureOrBuilderList()
         Features described in this schema.
        repeated .tensorflow.metadata.v0.Feature feature = 1;

      • getFeatureOrBuilder

        FeatureOrBuilder getFeatureOrBuilder​(int index)
         Features described in this schema.
        repeated .tensorflow.metadata.v0.Feature feature = 1;

      • getSparseFeatureList

        List<SparseFeature> getSparseFeatureList()
         Sparse features described in this schema.
        repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;

      • getSparseFeature

        SparseFeature getSparseFeature​(int index)
         Sparse features described in this schema.
        repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;

      • getSparseFeatureCount

        int getSparseFeatureCount()
         Sparse features described in this schema.
        repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;

      • getSparseFeatureOrBuilderList

        List<? extends SparseFeatureOrBuilder> getSparseFeatureOrBuilderList()
         Sparse features described in this schema.
        repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;

      • getSparseFeatureOrBuilder

        SparseFeatureOrBuilder getSparseFeatureOrBuilder​(int index)
         Sparse features described in this schema.
        repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;

      • getWeightedFeatureList

        List<WeightedFeature> getWeightedFeatureList()
         Weighted features described in this schema.
        repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;

      • getWeightedFeature

        WeightedFeature getWeightedFeature​(int index)
         Weighted features described in this schema.
        repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;

      • getWeightedFeatureCount

        int getWeightedFeatureCount()
         Weighted features described in this schema.
        repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;

      • getWeightedFeatureOrBuilderList

        List<? extends WeightedFeatureOrBuilder> getWeightedFeatureOrBuilderList()
         Weighted features described in this schema.
        repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;

      • getWeightedFeatureOrBuilder

        WeightedFeatureOrBuilder getWeightedFeatureOrBuilder​(int index)
         Weighted features described in this schema.
        repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;

      • getStringDomainList

        List<StringDomain> getStringDomainList()
         declared as top-level features in <feature>.
 String domains referenced in the features.
        repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;

      • getStringDomain

        StringDomain getStringDomain​(int index)
         declared as top-level features in <feature>.
 String domains referenced in the features.
        repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;

      • getStringDomainCount

        int getStringDomainCount()
         declared as top-level features in <feature>.
 String domains referenced in the features.
        repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;

      • getStringDomainOrBuilderList

        List<? extends StringDomainOrBuilder> getStringDomainOrBuilderList()
         declared as top-level features in <feature>.
 String domains referenced in the features.
        repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;

      • getStringDomainOrBuilder

        StringDomainOrBuilder getStringDomainOrBuilder​(int index)
         declared as top-level features in <feature>.
 String domains referenced in the features.
        repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;

      • getFloatDomainList

        List<FloatDomain> getFloatDomainList()
         top level float domains that can be reused by features
        repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;

      • getFloatDomain

        FloatDomain getFloatDomain​(int index)
         top level float domains that can be reused by features
        repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;

      • getFloatDomainCount

        int getFloatDomainCount()
         top level float domains that can be reused by features
        repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;

      • getFloatDomainOrBuilderList

        List<? extends FloatDomainOrBuilder> getFloatDomainOrBuilderList()
         top level float domains that can be reused by features
        repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;

      • getFloatDomainOrBuilder

        FloatDomainOrBuilder getFloatDomainOrBuilder​(int index)
         top level float domains that can be reused by features
        repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;

      • getIntDomainList

        List<IntDomain> getIntDomainList()
         top level int domains that can be reused by features
        repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;

      • getIntDomain

        IntDomain getIntDomain​(int index)
         top level int domains that can be reused by features
        repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;

      • getIntDomainCount

        int getIntDomainCount()
         top level int domains that can be reused by features
        repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;

      • getIntDomainOrBuilderList

        List<? extends IntDomainOrBuilder> getIntDomainOrBuilderList()
         top level int domains that can be reused by features
        repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;

      • getIntDomainOrBuilder

        IntDomainOrBuilder getIntDomainOrBuilder​(int index)
         top level int domains that can be reused by features
        repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;

      • getDefaultEnvironmentList

        List<String> getDefaultEnvironmentList()
         Default environments for each feature.
 An environment represents both a type of location (e.g. a server or phone)
 and a time (e.g. right before model X is run). In the standard scenario,
 99% of the features should be in the default environments TRAINING,
 SERVING, and the LABEL (or labels) AND WEIGHT is only available at TRAINING
 (not at serving).
 Other possible variations:
 1. There may be TRAINING_MOBILE, SERVING_MOBILE, TRAINING_SERVICE,
    and SERVING_SERVICE.
 2. If one is ensembling three models, where the predictions of the first
    three models are available for the ensemble model, there may be
    TRAINING, SERVING_INITIAL, SERVING_ENSEMBLE.
 See FeatureProto::not_in_environment and FeatureProto::in_environment.
        repeated string default_environment = 5;
        Returns:
        A list containing the defaultEnvironment.

      • getDefaultEnvironmentCount

        int getDefaultEnvironmentCount()
         Default environments for each feature.
 An environment represents both a type of location (e.g. a server or phone)
 and a time (e.g. right before model X is run). In the standard scenario,
 99% of the features should be in the default environments TRAINING,
 SERVING, and the LABEL (or labels) AND WEIGHT is only available at TRAINING
 (not at serving).
 Other possible variations:
 1. There may be TRAINING_MOBILE, SERVING_MOBILE, TRAINING_SERVICE,
    and SERVING_SERVICE.
 2. If one is ensembling three models, where the predictions of the first
    three models are available for the ensemble model, there may be
    TRAINING, SERVING_INITIAL, SERVING_ENSEMBLE.
 See FeatureProto::not_in_environment and FeatureProto::in_environment.
        repeated string default_environment = 5;
        Returns:
        The count of defaultEnvironment.

      • getDefaultEnvironment

        String getDefaultEnvironment​(int index)
         Default environments for each feature.
 An environment represents both a type of location (e.g. a server or phone)
 and a time (e.g. right before model X is run). In the standard scenario,
 99% of the features should be in the default environments TRAINING,
 SERVING, and the LABEL (or labels) AND WEIGHT is only available at TRAINING
 (not at serving).
 Other possible variations:
 1. There may be TRAINING_MOBILE, SERVING_MOBILE, TRAINING_SERVICE,
    and SERVING_SERVICE.
 2. If one is ensembling three models, where the predictions of the first
    three models are available for the ensemble model, there may be
    TRAINING, SERVING_INITIAL, SERVING_ENSEMBLE.
 See FeatureProto::not_in_environment and FeatureProto::in_environment.
        repeated string default_environment = 5;
        Parameters:
        index - The index of the element to return.
        Returns:
        The defaultEnvironment at the given index.

      • getDefaultEnvironmentBytes

        com.google.protobuf.ByteString getDefaultEnvironmentBytes​(int index)
         Default environments for each feature.
 An environment represents both a type of location (e.g. a server or phone)
 and a time (e.g. right before model X is run). In the standard scenario,
 99% of the features should be in the default environments TRAINING,
 SERVING, and the LABEL (or labels) AND WEIGHT is only available at TRAINING
 (not at serving).
 Other possible variations:
 1. There may be TRAINING_MOBILE, SERVING_MOBILE, TRAINING_SERVICE,
    and SERVING_SERVICE.
 2. If one is ensembling three models, where the predictions of the first
    three models are available for the ensemble model, there may be
    TRAINING, SERVING_INITIAL, SERVING_ENSEMBLE.
 See FeatureProto::not_in_environment and FeatureProto::in_environment.
        repeated string default_environment = 5;
        Parameters:
        index - The index of the value to return.
        Returns:
        The bytes of the defaultEnvironment at the given index.

      • hasAnnotation

        boolean hasAnnotation()
         Additional information about the schema as a whole. Features may also
 be annotated individually.
        optional .tensorflow.metadata.v0.Annotation annotation = 8;
        Returns:
        Whether the annotation field is set.

      • getAnnotation

        Annotation getAnnotation()
         Additional information about the schema as a whole. Features may also
 be annotated individually.
        optional .tensorflow.metadata.v0.Annotation annotation = 8;
        Returns:
        The annotation.

      • getAnnotationOrBuilder

        AnnotationOrBuilder getAnnotationOrBuilder()
         Additional information about the schema as a whole. Features may also
 be annotated individually.
        optional .tensorflow.metadata.v0.Annotation annotation = 8;

      • hasDatasetConstraints

        boolean hasDatasetConstraints()
         Dataset-level constraints. This is currently used for specifying
 information about changes in num_examples.
        optional .tensorflow.metadata.v0.DatasetConstraints dataset_constraints = 11;
        Returns:
        Whether the datasetConstraints field is set.

      • getDatasetConstraints

        DatasetConstraints getDatasetConstraints()
         Dataset-level constraints. This is currently used for specifying
 information about changes in num_examples.
        optional .tensorflow.metadata.v0.DatasetConstraints dataset_constraints = 11;
        Returns:
        The datasetConstraints.

      • getDatasetConstraintsOrBuilder

        DatasetConstraintsOrBuilder getDatasetConstraintsOrBuilder()
         Dataset-level constraints. This is currently used for specifying
 information about changes in num_examples.
        optional .tensorflow.metadata.v0.DatasetConstraints dataset_constraints = 11;

      • getTensorRepresentationGroupCount

        int getTensorRepresentationGroupCount()
         TensorRepresentation groups. The keys are the names of the groups.
 Key "" (empty string) denotes the "default" group, which is what should
 be used when a group name is not provided.
 See the documentation at TensorRepresentationGroup for more info.
 Under development. DO NOT USE.
        map<string, .tensorflow.metadata.v0.TensorRepresentationGroup> tensor_representation_group = 13;

      • containsTensorRepresentationGroup

        boolean containsTensorRepresentationGroup​(String key)
         TensorRepresentation groups. The keys are the names of the groups.
 Key "" (empty string) denotes the "default" group, which is what should
 be used when a group name is not provided.
 See the documentation at TensorRepresentationGroup for more info.
 Under development. DO NOT USE.
        map<string, .tensorflow.metadata.v0.TensorRepresentationGroup> tensor_representation_group = 13;

      • getTensorRepresentationGroupMap

        Map<String,​TensorRepresentationGroup> getTensorRepresentationGroupMap()
         TensorRepresentation groups. The keys are the names of the groups.
 Key "" (empty string) denotes the "default" group, which is what should
 be used when a group name is not provided.
 See the documentation at TensorRepresentationGroup for more info.
 Under development. DO NOT USE.
        map<string, .tensorflow.metadata.v0.TensorRepresentationGroup> tensor_representation_group = 13;

      • getTensorRepresentationGroupOrDefault

        TensorRepresentationGroup getTensorRepresentationGroupOrDefault​(String key,
                                                                TensorRepresentationGroup defaultValue)
         TensorRepresentation groups. The keys are the names of the groups.
 Key "" (empty string) denotes the "default" group, which is what should
 be used when a group name is not provided.
 See the documentation at TensorRepresentationGroup for more info.
 Under development. DO NOT USE.
        map<string, .tensorflow.metadata.v0.TensorRepresentationGroup> tensor_representation_group = 13;

      • getTensorRepresentationGroupOrThrow

        TensorRepresentationGroup getTensorRepresentationGroupOrThrow​(String key)
         TensorRepresentation groups. The keys are the names of the groups.
 Key "" (empty string) denotes the "default" group, which is what should
 be used when a group name is not provided.
 See the documentation at TensorRepresentationGroup for more info.
 Under development. DO NOT USE.
        map<string, .tensorflow.metadata.v0.TensorRepresentationGroup> tensor_representation_group = 13;