org.tensorflow.metadata.v0.SchemaOrBuilder Maven / Gradle / Ivy
The newest version!
// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: tensorflow_metadata/proto/v0/schema.proto
// Protobuf Java Version: 3.25.4
package org.tensorflow.metadata.v0;
public interface SchemaOrBuilder extends
// @@protoc_insertion_point(interface_extends:tensorflow.metadata.v0.Schema)
com.google.protobuf.MessageOrBuilder {
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
java.util.List
getFeatureList();
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
org.tensorflow.metadata.v0.Feature getFeature(int index);
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
int getFeatureCount();
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
java.util.List
getFeatureOrBuilderList();
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
org.tensorflow.metadata.v0.FeatureOrBuilder getFeatureOrBuilder(
int index);
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
java.util.List
getSparseFeatureList();
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
org.tensorflow.metadata.v0.SparseFeature getSparseFeature(int index);
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
int getSparseFeatureCount();
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
java.util.List
getSparseFeatureOrBuilderList();
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
org.tensorflow.metadata.v0.SparseFeatureOrBuilder getSparseFeatureOrBuilder(
int index);
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
java.util.List
getWeightedFeatureList();
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
org.tensorflow.metadata.v0.WeightedFeature getWeightedFeature(int index);
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
int getWeightedFeatureCount();
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
java.util.List
getWeightedFeatureOrBuilderList();
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
org.tensorflow.metadata.v0.WeightedFeatureOrBuilder getWeightedFeatureOrBuilder(
int index);
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
java.util.List
getStringDomainList();
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
org.tensorflow.metadata.v0.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;
*/
int getStringDomainCount();
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
java.util.List
getStringDomainOrBuilderList();
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
org.tensorflow.metadata.v0.StringDomainOrBuilder getStringDomainOrBuilder(
int index);
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
java.util.List
getFloatDomainList();
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
org.tensorflow.metadata.v0.FloatDomain getFloatDomain(int index);
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
int getFloatDomainCount();
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
java.util.List
getFloatDomainOrBuilderList();
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
org.tensorflow.metadata.v0.FloatDomainOrBuilder getFloatDomainOrBuilder(
int index);
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
java.util.List
getIntDomainList();
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
org.tensorflow.metadata.v0.IntDomain getIntDomain(int index);
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
int getIntDomainCount();
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
java.util.List
getIntDomainOrBuilderList();
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
org.tensorflow.metadata.v0.IntDomainOrBuilder getIntDomainOrBuilder(
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;
* @return A list containing the defaultEnvironment.
*/
java.util.List
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;
* @return The count of defaultEnvironment.
*/
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;
* @param index The index of the element to return.
* @return The defaultEnvironment at the given index.
*/
java.lang.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;
* @param index The index of the value to return.
* @return The bytes of the defaultEnvironment at the given index.
*/
com.google.protobuf.ByteString
getDefaultEnvironmentBytes(int index);
/**
*
* Whether to represent variable length features as RaggedTensors. By default
* they are represented as ragged left-alighned SparseTensors. RaggedTensor
* representation is more memory efficient. Therefore, turning this on will
* likely yield data processing performance improvement.
* Experimental and may be subject to change.
*
*
* optional bool represent_variable_length_as_ragged = 14;
* @return Whether the representVariableLengthAsRagged field is set.
*/
boolean hasRepresentVariableLengthAsRagged();
/**
*
* Whether to represent variable length features as RaggedTensors. By default
* they are represented as ragged left-alighned SparseTensors. RaggedTensor
* representation is more memory efficient. Therefore, turning this on will
* likely yield data processing performance improvement.
* Experimental and may be subject to change.
*
*
* optional bool represent_variable_length_as_ragged = 14;
* @return The representVariableLengthAsRagged.
*/
boolean getRepresentVariableLengthAsRagged();
/**
*
* Additional information about the schema as a whole. Features may also
* be annotated individually.
*
*
* optional .tensorflow.metadata.v0.Annotation annotation = 8;
* @return Whether the annotation field is set.
*/
boolean hasAnnotation();
/**
*
* Additional information about the schema as a whole. Features may also
* be annotated individually.
*
*
* optional .tensorflow.metadata.v0.Annotation annotation = 8;
* @return The annotation.
*/
org.tensorflow.metadata.v0.Annotation getAnnotation();
/**
*
* Additional information about the schema as a whole. Features may also
* be annotated individually.
*
*
* optional .tensorflow.metadata.v0.Annotation annotation = 8;
*/
org.tensorflow.metadata.v0.AnnotationOrBuilder getAnnotationOrBuilder();
/**
*
* Dataset-level constraints. This is currently used for specifying
* information about changes in num_examples.
*
*
* optional .tensorflow.metadata.v0.DatasetConstraints dataset_constraints = 11;
* @return Whether the datasetConstraints field is set.
*/
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;
* @return The datasetConstraints.
*/
org.tensorflow.metadata.v0.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;
*/
org.tensorflow.metadata.v0.DatasetConstraintsOrBuilder getDatasetConstraintsOrBuilder();
/**
*
* 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.
*
*
* map<string, .tensorflow.metadata.v0.TensorRepresentationGroup> tensor_representation_group = 13;
*/
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.
*
*
* map<string, .tensorflow.metadata.v0.TensorRepresentationGroup> tensor_representation_group = 13;
*/
boolean containsTensorRepresentationGroup(
java.lang.String key);
/**
* Use {@link #getTensorRepresentationGroupMap()} instead.
*/
@java.lang.Deprecated
java.util.Map
getTensorRepresentationGroup();
/**
*
* 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.
*
*
* map<string, .tensorflow.metadata.v0.TensorRepresentationGroup> tensor_representation_group = 13;
*/
java.util.Map
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.
*
*
* map<string, .tensorflow.metadata.v0.TensorRepresentationGroup> tensor_representation_group = 13;
*/
/* nullable */
org.tensorflow.metadata.v0.TensorRepresentationGroup getTensorRepresentationGroupOrDefault(
java.lang.String key,
/* nullable */
org.tensorflow.metadata.v0.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.
*
*
* map<string, .tensorflow.metadata.v0.TensorRepresentationGroup> tensor_representation_group = 13;
*/
org.tensorflow.metadata.v0.TensorRepresentationGroup getTensorRepresentationGroupOrThrow(
java.lang.String key);
}
© 2015 - 2025 Weber Informatics LLC | Privacy Policy