org.tensorflow.metadata.v0.Schema Maven / Gradle / Ivy
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// 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;
/**
*
*
* Message to represent schema information.
* NextID: 15
*
*
* Protobuf type {@code tensorflow.metadata.v0.Schema}
*/
public final class Schema extends
com.google.protobuf.GeneratedMessageV3 implements
// @@protoc_insertion_point(message_implements:tensorflow.metadata.v0.Schema)
SchemaOrBuilder {
private static final long serialVersionUID = 0L;
// Use Schema.newBuilder() to construct.
private Schema(com.google.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
}
private Schema() {
feature_ = java.util.Collections.emptyList();
sparseFeature_ = java.util.Collections.emptyList();
weightedFeature_ = java.util.Collections.emptyList();
stringDomain_ = java.util.Collections.emptyList();
floatDomain_ = java.util.Collections.emptyList();
intDomain_ = java.util.Collections.emptyList();
defaultEnvironment_ =
com.google.protobuf.LazyStringArrayList.emptyList();
}
@java.lang.Override
@SuppressWarnings({"unused"})
protected java.lang.Object newInstance(
UnusedPrivateParameter unused) {
return new Schema();
}
public static final com.google.protobuf.Descriptors.Descriptor
getDescriptor() {
return org.tensorflow.metadata.v0.SchemaOuterClass.internal_static_tensorflow_metadata_v0_Schema_descriptor;
}
@SuppressWarnings({"rawtypes"})
@java.lang.Override
protected com.google.protobuf.MapFieldReflectionAccessor internalGetMapFieldReflection(
int number) {
switch (number) {
case 13:
return internalGetTensorRepresentationGroup();
default:
throw new RuntimeException(
"Invalid map field number: " + number);
}
}
@java.lang.Override
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return org.tensorflow.metadata.v0.SchemaOuterClass.internal_static_tensorflow_metadata_v0_Schema_fieldAccessorTable
.ensureFieldAccessorsInitialized(
org.tensorflow.metadata.v0.Schema.class, org.tensorflow.metadata.v0.Schema.Builder.class);
}
private int bitField0_;
public static final int FEATURE_FIELD_NUMBER = 1;
@SuppressWarnings("serial")
private java.util.List feature_;
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
@java.lang.Override
public java.util.List getFeatureList() {
return feature_;
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
@java.lang.Override
public java.util.List
getFeatureOrBuilderList() {
return feature_;
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
@java.lang.Override
public int getFeatureCount() {
return feature_.size();
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.Feature getFeature(int index) {
return feature_.get(index);
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.FeatureOrBuilder getFeatureOrBuilder(
int index) {
return feature_.get(index);
}
public static final int SPARSE_FEATURE_FIELD_NUMBER = 6;
@SuppressWarnings("serial")
private java.util.List sparseFeature_;
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
@java.lang.Override
public java.util.List getSparseFeatureList() {
return sparseFeature_;
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
@java.lang.Override
public java.util.List
getSparseFeatureOrBuilderList() {
return sparseFeature_;
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
@java.lang.Override
public int getSparseFeatureCount() {
return sparseFeature_.size();
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.SparseFeature getSparseFeature(int index) {
return sparseFeature_.get(index);
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.SparseFeatureOrBuilder getSparseFeatureOrBuilder(
int index) {
return sparseFeature_.get(index);
}
public static final int WEIGHTED_FEATURE_FIELD_NUMBER = 12;
@SuppressWarnings("serial")
private java.util.List weightedFeature_;
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
@java.lang.Override
public java.util.List getWeightedFeatureList() {
return weightedFeature_;
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
@java.lang.Override
public java.util.List
getWeightedFeatureOrBuilderList() {
return weightedFeature_;
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
@java.lang.Override
public int getWeightedFeatureCount() {
return weightedFeature_.size();
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.WeightedFeature getWeightedFeature(int index) {
return weightedFeature_.get(index);
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.WeightedFeatureOrBuilder getWeightedFeatureOrBuilder(
int index) {
return weightedFeature_.get(index);
}
public static final int STRING_DOMAIN_FIELD_NUMBER = 4;
@SuppressWarnings("serial")
private java.util.List stringDomain_;
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
@java.lang.Override
public java.util.List getStringDomainList() {
return stringDomain_;
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
@java.lang.Override
public java.util.List
getStringDomainOrBuilderList() {
return stringDomain_;
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
@java.lang.Override
public int getStringDomainCount() {
return stringDomain_.size();
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.StringDomain getStringDomain(int index) {
return stringDomain_.get(index);
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.StringDomainOrBuilder getStringDomainOrBuilder(
int index) {
return stringDomain_.get(index);
}
public static final int FLOAT_DOMAIN_FIELD_NUMBER = 9;
@SuppressWarnings("serial")
private java.util.List floatDomain_;
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
@java.lang.Override
public java.util.List getFloatDomainList() {
return floatDomain_;
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
@java.lang.Override
public java.util.List
getFloatDomainOrBuilderList() {
return floatDomain_;
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
@java.lang.Override
public int getFloatDomainCount() {
return floatDomain_.size();
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.FloatDomain getFloatDomain(int index) {
return floatDomain_.get(index);
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.FloatDomainOrBuilder getFloatDomainOrBuilder(
int index) {
return floatDomain_.get(index);
}
public static final int INT_DOMAIN_FIELD_NUMBER = 10;
@SuppressWarnings("serial")
private java.util.List intDomain_;
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
@java.lang.Override
public java.util.List getIntDomainList() {
return intDomain_;
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
@java.lang.Override
public java.util.List
getIntDomainOrBuilderList() {
return intDomain_;
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
@java.lang.Override
public int getIntDomainCount() {
return intDomain_.size();
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.IntDomain getIntDomain(int index) {
return intDomain_.get(index);
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.IntDomainOrBuilder getIntDomainOrBuilder(
int index) {
return intDomain_.get(index);
}
public static final int DEFAULT_ENVIRONMENT_FIELD_NUMBER = 5;
@SuppressWarnings("serial")
private com.google.protobuf.LazyStringArrayList defaultEnvironment_ =
com.google.protobuf.LazyStringArrayList.emptyList();
/**
*
* 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.
*/
public com.google.protobuf.ProtocolStringList
getDefaultEnvironmentList() {
return defaultEnvironment_;
}
/**
*
* 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.
*/
public int getDefaultEnvironmentCount() {
return defaultEnvironment_.size();
}
/**
*
* 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.
*/
public java.lang.String getDefaultEnvironment(int index) {
return defaultEnvironment_.get(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.
*/
public com.google.protobuf.ByteString
getDefaultEnvironmentBytes(int index) {
return defaultEnvironment_.getByteString(index);
}
public static final int REPRESENT_VARIABLE_LENGTH_AS_RAGGED_FIELD_NUMBER = 14;
private boolean representVariableLengthAsRagged_ = false;
/**
*
* 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.
*/
@java.lang.Override
public boolean hasRepresentVariableLengthAsRagged() {
return ((bitField0_ & 0x00000001) != 0);
}
/**
*
* 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.
*/
@java.lang.Override
public boolean getRepresentVariableLengthAsRagged() {
return representVariableLengthAsRagged_;
}
public static final int ANNOTATION_FIELD_NUMBER = 8;
private org.tensorflow.metadata.v0.Annotation annotation_;
/**
*
* 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.
*/
@java.lang.Override
public boolean hasAnnotation() {
return ((bitField0_ & 0x00000002) != 0);
}
/**
*
* Additional information about the schema as a whole. Features may also
* be annotated individually.
*
*
* optional .tensorflow.metadata.v0.Annotation annotation = 8;
* @return The annotation.
*/
@java.lang.Override
public org.tensorflow.metadata.v0.Annotation getAnnotation() {
return annotation_ == null ? org.tensorflow.metadata.v0.Annotation.getDefaultInstance() : annotation_;
}
/**
*
* Additional information about the schema as a whole. Features may also
* be annotated individually.
*
*
* optional .tensorflow.metadata.v0.Annotation annotation = 8;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.AnnotationOrBuilder getAnnotationOrBuilder() {
return annotation_ == null ? org.tensorflow.metadata.v0.Annotation.getDefaultInstance() : annotation_;
}
public static final int DATASET_CONSTRAINTS_FIELD_NUMBER = 11;
private org.tensorflow.metadata.v0.DatasetConstraints datasetConstraints_;
/**
*
* 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.
*/
@java.lang.Override
public boolean hasDatasetConstraints() {
return ((bitField0_ & 0x00000004) != 0);
}
/**
*
* 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.
*/
@java.lang.Override
public org.tensorflow.metadata.v0.DatasetConstraints getDatasetConstraints() {
return datasetConstraints_ == null ? org.tensorflow.metadata.v0.DatasetConstraints.getDefaultInstance() : datasetConstraints_;
}
/**
*
* Dataset-level constraints. This is currently used for specifying
* information about changes in num_examples.
*
*
* optional .tensorflow.metadata.v0.DatasetConstraints dataset_constraints = 11;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.DatasetConstraintsOrBuilder getDatasetConstraintsOrBuilder() {
return datasetConstraints_ == null ? org.tensorflow.metadata.v0.DatasetConstraints.getDefaultInstance() : datasetConstraints_;
}
public static final int TENSOR_REPRESENTATION_GROUP_FIELD_NUMBER = 13;
private static final class TensorRepresentationGroupDefaultEntryHolder {
static final com.google.protobuf.MapEntry<
java.lang.String, org.tensorflow.metadata.v0.TensorRepresentationGroup> defaultEntry =
com.google.protobuf.MapEntry
.newDefaultInstance(
org.tensorflow.metadata.v0.SchemaOuterClass.internal_static_tensorflow_metadata_v0_Schema_TensorRepresentationGroupEntry_descriptor,
com.google.protobuf.WireFormat.FieldType.STRING,
"",
com.google.protobuf.WireFormat.FieldType.MESSAGE,
org.tensorflow.metadata.v0.TensorRepresentationGroup.getDefaultInstance());
}
@SuppressWarnings("serial")
private com.google.protobuf.MapField<
java.lang.String, org.tensorflow.metadata.v0.TensorRepresentationGroup> tensorRepresentationGroup_;
private com.google.protobuf.MapField
internalGetTensorRepresentationGroup() {
if (tensorRepresentationGroup_ == null) {
return com.google.protobuf.MapField.emptyMapField(
TensorRepresentationGroupDefaultEntryHolder.defaultEntry);
}
return tensorRepresentationGroup_;
}
public int getTensorRepresentationGroupCount() {
return internalGetTensorRepresentationGroup().getMap().size();
}
/**
*
* 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.lang.Override
public boolean containsTensorRepresentationGroup(
java.lang.String key) {
if (key == null) { throw new NullPointerException("map key"); }
return internalGetTensorRepresentationGroup().getMap().containsKey(key);
}
/**
* Use {@link #getTensorRepresentationGroupMap()} instead.
*/
@java.lang.Override
@java.lang.Deprecated
public java.util.Map getTensorRepresentationGroup() {
return 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;
*/
@java.lang.Override
public java.util.Map getTensorRepresentationGroupMap() {
return internalGetTensorRepresentationGroup().getMap();
}
/**
*
* 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.lang.Override
public /* nullable */
org.tensorflow.metadata.v0.TensorRepresentationGroup getTensorRepresentationGroupOrDefault(
java.lang.String key,
/* nullable */
org.tensorflow.metadata.v0.TensorRepresentationGroup defaultValue) {
if (key == null) { throw new NullPointerException("map key"); }
java.util.Map map =
internalGetTensorRepresentationGroup().getMap();
return map.containsKey(key) ? map.get(key) : 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;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.TensorRepresentationGroup getTensorRepresentationGroupOrThrow(
java.lang.String key) {
if (key == null) { throw new NullPointerException("map key"); }
java.util.Map map =
internalGetTensorRepresentationGroup().getMap();
if (!map.containsKey(key)) {
throw new java.lang.IllegalArgumentException();
}
return map.get(key);
}
private byte memoizedIsInitialized = -1;
@java.lang.Override
public final boolean isInitialized() {
byte isInitialized = memoizedIsInitialized;
if (isInitialized == 1) return true;
if (isInitialized == 0) return false;
memoizedIsInitialized = 1;
return true;
}
@java.lang.Override
public void writeTo(com.google.protobuf.CodedOutputStream output)
throws java.io.IOException {
for (int i = 0; i < feature_.size(); i++) {
output.writeMessage(1, feature_.get(i));
}
for (int i = 0; i < stringDomain_.size(); i++) {
output.writeMessage(4, stringDomain_.get(i));
}
for (int i = 0; i < defaultEnvironment_.size(); i++) {
com.google.protobuf.GeneratedMessageV3.writeString(output, 5, defaultEnvironment_.getRaw(i));
}
for (int i = 0; i < sparseFeature_.size(); i++) {
output.writeMessage(6, sparseFeature_.get(i));
}
if (((bitField0_ & 0x00000002) != 0)) {
output.writeMessage(8, getAnnotation());
}
for (int i = 0; i < floatDomain_.size(); i++) {
output.writeMessage(9, floatDomain_.get(i));
}
for (int i = 0; i < intDomain_.size(); i++) {
output.writeMessage(10, intDomain_.get(i));
}
if (((bitField0_ & 0x00000004) != 0)) {
output.writeMessage(11, getDatasetConstraints());
}
for (int i = 0; i < weightedFeature_.size(); i++) {
output.writeMessage(12, weightedFeature_.get(i));
}
com.google.protobuf.GeneratedMessageV3
.serializeStringMapTo(
output,
internalGetTensorRepresentationGroup(),
TensorRepresentationGroupDefaultEntryHolder.defaultEntry,
13);
if (((bitField0_ & 0x00000001) != 0)) {
output.writeBool(14, representVariableLengthAsRagged_);
}
getUnknownFields().writeTo(output);
}
@java.lang.Override
public int getSerializedSize() {
int size = memoizedSize;
if (size != -1) return size;
size = 0;
for (int i = 0; i < feature_.size(); i++) {
size += com.google.protobuf.CodedOutputStream
.computeMessageSize(1, feature_.get(i));
}
for (int i = 0; i < stringDomain_.size(); i++) {
size += com.google.protobuf.CodedOutputStream
.computeMessageSize(4, stringDomain_.get(i));
}
{
int dataSize = 0;
for (int i = 0; i < defaultEnvironment_.size(); i++) {
dataSize += computeStringSizeNoTag(defaultEnvironment_.getRaw(i));
}
size += dataSize;
size += 1 * getDefaultEnvironmentList().size();
}
for (int i = 0; i < sparseFeature_.size(); i++) {
size += com.google.protobuf.CodedOutputStream
.computeMessageSize(6, sparseFeature_.get(i));
}
if (((bitField0_ & 0x00000002) != 0)) {
size += com.google.protobuf.CodedOutputStream
.computeMessageSize(8, getAnnotation());
}
for (int i = 0; i < floatDomain_.size(); i++) {
size += com.google.protobuf.CodedOutputStream
.computeMessageSize(9, floatDomain_.get(i));
}
for (int i = 0; i < intDomain_.size(); i++) {
size += com.google.protobuf.CodedOutputStream
.computeMessageSize(10, intDomain_.get(i));
}
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public static Builder newBuilder(org.tensorflow.metadata.v0.Schema prototype) {
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protected Builder newBuilderForType(
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/**
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getWeightedFeatureFieldBuilder();
getStringDomainFieldBuilder();
getFloatDomainFieldBuilder();
getIntDomainFieldBuilder();
getAnnotationFieldBuilder();
getDatasetConstraintsFieldBuilder();
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featureBuilder_.clear();
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}
break;
} // case 98
case 106: {
com.google.protobuf.MapEntry
tensorRepresentationGroup__ = input.readMessage(
TensorRepresentationGroupDefaultEntryHolder.defaultEntry.getParserForType(), extensionRegistry);
internalGetMutableTensorRepresentationGroup().ensureBuilderMap().put(
tensorRepresentationGroup__.getKey(), tensorRepresentationGroup__.getValue());
bitField0_ |= 0x00000400;
break;
} // case 106
case 112: {
representVariableLengthAsRagged_ = input.readBool();
bitField0_ |= 0x00000080;
break;
} // case 112
default: {
if (!super.parseUnknownField(input, extensionRegistry, tag)) {
done = true; // was an endgroup tag
}
break;
} // default:
} // switch (tag)
} // while (!done)
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
throw e.unwrapIOException();
} finally {
onChanged();
} // finally
return this;
}
private int bitField0_;
private java.util.List feature_ =
java.util.Collections.emptyList();
private void ensureFeatureIsMutable() {
if (!((bitField0_ & 0x00000001) != 0)) {
feature_ = new java.util.ArrayList(feature_);
bitField0_ |= 0x00000001;
}
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.Feature, org.tensorflow.metadata.v0.Feature.Builder, org.tensorflow.metadata.v0.FeatureOrBuilder> featureBuilder_;
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public java.util.List getFeatureList() {
if (featureBuilder_ == null) {
return java.util.Collections.unmodifiableList(feature_);
} else {
return featureBuilder_.getMessageList();
}
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public int getFeatureCount() {
if (featureBuilder_ == null) {
return feature_.size();
} else {
return featureBuilder_.getCount();
}
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public org.tensorflow.metadata.v0.Feature getFeature(int index) {
if (featureBuilder_ == null) {
return feature_.get(index);
} else {
return featureBuilder_.getMessage(index);
}
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public Builder setFeature(
int index, org.tensorflow.metadata.v0.Feature value) {
if (featureBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureFeatureIsMutable();
feature_.set(index, value);
onChanged();
} else {
featureBuilder_.setMessage(index, value);
}
return this;
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public Builder setFeature(
int index, org.tensorflow.metadata.v0.Feature.Builder builderForValue) {
if (featureBuilder_ == null) {
ensureFeatureIsMutable();
feature_.set(index, builderForValue.build());
onChanged();
} else {
featureBuilder_.setMessage(index, builderForValue.build());
}
return this;
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public Builder addFeature(org.tensorflow.metadata.v0.Feature value) {
if (featureBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureFeatureIsMutable();
feature_.add(value);
onChanged();
} else {
featureBuilder_.addMessage(value);
}
return this;
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public Builder addFeature(
int index, org.tensorflow.metadata.v0.Feature value) {
if (featureBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureFeatureIsMutable();
feature_.add(index, value);
onChanged();
} else {
featureBuilder_.addMessage(index, value);
}
return this;
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public Builder addFeature(
org.tensorflow.metadata.v0.Feature.Builder builderForValue) {
if (featureBuilder_ == null) {
ensureFeatureIsMutable();
feature_.add(builderForValue.build());
onChanged();
} else {
featureBuilder_.addMessage(builderForValue.build());
}
return this;
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public Builder addFeature(
int index, org.tensorflow.metadata.v0.Feature.Builder builderForValue) {
if (featureBuilder_ == null) {
ensureFeatureIsMutable();
feature_.add(index, builderForValue.build());
onChanged();
} else {
featureBuilder_.addMessage(index, builderForValue.build());
}
return this;
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public Builder addAllFeature(
java.lang.Iterable values) {
if (featureBuilder_ == null) {
ensureFeatureIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(
values, feature_);
onChanged();
} else {
featureBuilder_.addAllMessages(values);
}
return this;
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public Builder clearFeature() {
if (featureBuilder_ == null) {
feature_ = java.util.Collections.emptyList();
bitField0_ = (bitField0_ & ~0x00000001);
onChanged();
} else {
featureBuilder_.clear();
}
return this;
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public Builder removeFeature(int index) {
if (featureBuilder_ == null) {
ensureFeatureIsMutable();
feature_.remove(index);
onChanged();
} else {
featureBuilder_.remove(index);
}
return this;
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public org.tensorflow.metadata.v0.Feature.Builder getFeatureBuilder(
int index) {
return getFeatureFieldBuilder().getBuilder(index);
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public org.tensorflow.metadata.v0.FeatureOrBuilder getFeatureOrBuilder(
int index) {
if (featureBuilder_ == null) {
return feature_.get(index); } else {
return featureBuilder_.getMessageOrBuilder(index);
}
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public java.util.List
getFeatureOrBuilderList() {
if (featureBuilder_ != null) {
return featureBuilder_.getMessageOrBuilderList();
} else {
return java.util.Collections.unmodifiableList(feature_);
}
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public org.tensorflow.metadata.v0.Feature.Builder addFeatureBuilder() {
return getFeatureFieldBuilder().addBuilder(
org.tensorflow.metadata.v0.Feature.getDefaultInstance());
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public org.tensorflow.metadata.v0.Feature.Builder addFeatureBuilder(
int index) {
return getFeatureFieldBuilder().addBuilder(
index, org.tensorflow.metadata.v0.Feature.getDefaultInstance());
}
/**
*
* Features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.Feature feature = 1;
*/
public java.util.List
getFeatureBuilderList() {
return getFeatureFieldBuilder().getBuilderList();
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.Feature, org.tensorflow.metadata.v0.Feature.Builder, org.tensorflow.metadata.v0.FeatureOrBuilder>
getFeatureFieldBuilder() {
if (featureBuilder_ == null) {
featureBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.Feature, org.tensorflow.metadata.v0.Feature.Builder, org.tensorflow.metadata.v0.FeatureOrBuilder>(
feature_,
((bitField0_ & 0x00000001) != 0),
getParentForChildren(),
isClean());
feature_ = null;
}
return featureBuilder_;
}
private java.util.List sparseFeature_ =
java.util.Collections.emptyList();
private void ensureSparseFeatureIsMutable() {
if (!((bitField0_ & 0x00000002) != 0)) {
sparseFeature_ = new java.util.ArrayList(sparseFeature_);
bitField0_ |= 0x00000002;
}
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.SparseFeature, org.tensorflow.metadata.v0.SparseFeature.Builder, org.tensorflow.metadata.v0.SparseFeatureOrBuilder> sparseFeatureBuilder_;
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public java.util.List getSparseFeatureList() {
if (sparseFeatureBuilder_ == null) {
return java.util.Collections.unmodifiableList(sparseFeature_);
} else {
return sparseFeatureBuilder_.getMessageList();
}
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public int getSparseFeatureCount() {
if (sparseFeatureBuilder_ == null) {
return sparseFeature_.size();
} else {
return sparseFeatureBuilder_.getCount();
}
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public org.tensorflow.metadata.v0.SparseFeature getSparseFeature(int index) {
if (sparseFeatureBuilder_ == null) {
return sparseFeature_.get(index);
} else {
return sparseFeatureBuilder_.getMessage(index);
}
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public Builder setSparseFeature(
int index, org.tensorflow.metadata.v0.SparseFeature value) {
if (sparseFeatureBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureSparseFeatureIsMutable();
sparseFeature_.set(index, value);
onChanged();
} else {
sparseFeatureBuilder_.setMessage(index, value);
}
return this;
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public Builder setSparseFeature(
int index, org.tensorflow.metadata.v0.SparseFeature.Builder builderForValue) {
if (sparseFeatureBuilder_ == null) {
ensureSparseFeatureIsMutable();
sparseFeature_.set(index, builderForValue.build());
onChanged();
} else {
sparseFeatureBuilder_.setMessage(index, builderForValue.build());
}
return this;
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public Builder addSparseFeature(org.tensorflow.metadata.v0.SparseFeature value) {
if (sparseFeatureBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureSparseFeatureIsMutable();
sparseFeature_.add(value);
onChanged();
} else {
sparseFeatureBuilder_.addMessage(value);
}
return this;
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public Builder addSparseFeature(
int index, org.tensorflow.metadata.v0.SparseFeature value) {
if (sparseFeatureBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureSparseFeatureIsMutable();
sparseFeature_.add(index, value);
onChanged();
} else {
sparseFeatureBuilder_.addMessage(index, value);
}
return this;
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public Builder addSparseFeature(
org.tensorflow.metadata.v0.SparseFeature.Builder builderForValue) {
if (sparseFeatureBuilder_ == null) {
ensureSparseFeatureIsMutable();
sparseFeature_.add(builderForValue.build());
onChanged();
} else {
sparseFeatureBuilder_.addMessage(builderForValue.build());
}
return this;
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public Builder addSparseFeature(
int index, org.tensorflow.metadata.v0.SparseFeature.Builder builderForValue) {
if (sparseFeatureBuilder_ == null) {
ensureSparseFeatureIsMutable();
sparseFeature_.add(index, builderForValue.build());
onChanged();
} else {
sparseFeatureBuilder_.addMessage(index, builderForValue.build());
}
return this;
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public Builder addAllSparseFeature(
java.lang.Iterable values) {
if (sparseFeatureBuilder_ == null) {
ensureSparseFeatureIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(
values, sparseFeature_);
onChanged();
} else {
sparseFeatureBuilder_.addAllMessages(values);
}
return this;
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public Builder clearSparseFeature() {
if (sparseFeatureBuilder_ == null) {
sparseFeature_ = java.util.Collections.emptyList();
bitField0_ = (bitField0_ & ~0x00000002);
onChanged();
} else {
sparseFeatureBuilder_.clear();
}
return this;
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public Builder removeSparseFeature(int index) {
if (sparseFeatureBuilder_ == null) {
ensureSparseFeatureIsMutable();
sparseFeature_.remove(index);
onChanged();
} else {
sparseFeatureBuilder_.remove(index);
}
return this;
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public org.tensorflow.metadata.v0.SparseFeature.Builder getSparseFeatureBuilder(
int index) {
return getSparseFeatureFieldBuilder().getBuilder(index);
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public org.tensorflow.metadata.v0.SparseFeatureOrBuilder getSparseFeatureOrBuilder(
int index) {
if (sparseFeatureBuilder_ == null) {
return sparseFeature_.get(index); } else {
return sparseFeatureBuilder_.getMessageOrBuilder(index);
}
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public java.util.List
getSparseFeatureOrBuilderList() {
if (sparseFeatureBuilder_ != null) {
return sparseFeatureBuilder_.getMessageOrBuilderList();
} else {
return java.util.Collections.unmodifiableList(sparseFeature_);
}
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public org.tensorflow.metadata.v0.SparseFeature.Builder addSparseFeatureBuilder() {
return getSparseFeatureFieldBuilder().addBuilder(
org.tensorflow.metadata.v0.SparseFeature.getDefaultInstance());
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public org.tensorflow.metadata.v0.SparseFeature.Builder addSparseFeatureBuilder(
int index) {
return getSparseFeatureFieldBuilder().addBuilder(
index, org.tensorflow.metadata.v0.SparseFeature.getDefaultInstance());
}
/**
*
* Sparse features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.SparseFeature sparse_feature = 6;
*/
public java.util.List
getSparseFeatureBuilderList() {
return getSparseFeatureFieldBuilder().getBuilderList();
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.SparseFeature, org.tensorflow.metadata.v0.SparseFeature.Builder, org.tensorflow.metadata.v0.SparseFeatureOrBuilder>
getSparseFeatureFieldBuilder() {
if (sparseFeatureBuilder_ == null) {
sparseFeatureBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.SparseFeature, org.tensorflow.metadata.v0.SparseFeature.Builder, org.tensorflow.metadata.v0.SparseFeatureOrBuilder>(
sparseFeature_,
((bitField0_ & 0x00000002) != 0),
getParentForChildren(),
isClean());
sparseFeature_ = null;
}
return sparseFeatureBuilder_;
}
private java.util.List weightedFeature_ =
java.util.Collections.emptyList();
private void ensureWeightedFeatureIsMutable() {
if (!((bitField0_ & 0x00000004) != 0)) {
weightedFeature_ = new java.util.ArrayList(weightedFeature_);
bitField0_ |= 0x00000004;
}
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.WeightedFeature, org.tensorflow.metadata.v0.WeightedFeature.Builder, org.tensorflow.metadata.v0.WeightedFeatureOrBuilder> weightedFeatureBuilder_;
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public java.util.List getWeightedFeatureList() {
if (weightedFeatureBuilder_ == null) {
return java.util.Collections.unmodifiableList(weightedFeature_);
} else {
return weightedFeatureBuilder_.getMessageList();
}
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public int getWeightedFeatureCount() {
if (weightedFeatureBuilder_ == null) {
return weightedFeature_.size();
} else {
return weightedFeatureBuilder_.getCount();
}
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public org.tensorflow.metadata.v0.WeightedFeature getWeightedFeature(int index) {
if (weightedFeatureBuilder_ == null) {
return weightedFeature_.get(index);
} else {
return weightedFeatureBuilder_.getMessage(index);
}
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public Builder setWeightedFeature(
int index, org.tensorflow.metadata.v0.WeightedFeature value) {
if (weightedFeatureBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureWeightedFeatureIsMutable();
weightedFeature_.set(index, value);
onChanged();
} else {
weightedFeatureBuilder_.setMessage(index, value);
}
return this;
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public Builder setWeightedFeature(
int index, org.tensorflow.metadata.v0.WeightedFeature.Builder builderForValue) {
if (weightedFeatureBuilder_ == null) {
ensureWeightedFeatureIsMutable();
weightedFeature_.set(index, builderForValue.build());
onChanged();
} else {
weightedFeatureBuilder_.setMessage(index, builderForValue.build());
}
return this;
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public Builder addWeightedFeature(org.tensorflow.metadata.v0.WeightedFeature value) {
if (weightedFeatureBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureWeightedFeatureIsMutable();
weightedFeature_.add(value);
onChanged();
} else {
weightedFeatureBuilder_.addMessage(value);
}
return this;
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public Builder addWeightedFeature(
int index, org.tensorflow.metadata.v0.WeightedFeature value) {
if (weightedFeatureBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureWeightedFeatureIsMutable();
weightedFeature_.add(index, value);
onChanged();
} else {
weightedFeatureBuilder_.addMessage(index, value);
}
return this;
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public Builder addWeightedFeature(
org.tensorflow.metadata.v0.WeightedFeature.Builder builderForValue) {
if (weightedFeatureBuilder_ == null) {
ensureWeightedFeatureIsMutable();
weightedFeature_.add(builderForValue.build());
onChanged();
} else {
weightedFeatureBuilder_.addMessage(builderForValue.build());
}
return this;
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public Builder addWeightedFeature(
int index, org.tensorflow.metadata.v0.WeightedFeature.Builder builderForValue) {
if (weightedFeatureBuilder_ == null) {
ensureWeightedFeatureIsMutable();
weightedFeature_.add(index, builderForValue.build());
onChanged();
} else {
weightedFeatureBuilder_.addMessage(index, builderForValue.build());
}
return this;
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public Builder addAllWeightedFeature(
java.lang.Iterable values) {
if (weightedFeatureBuilder_ == null) {
ensureWeightedFeatureIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(
values, weightedFeature_);
onChanged();
} else {
weightedFeatureBuilder_.addAllMessages(values);
}
return this;
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public Builder clearWeightedFeature() {
if (weightedFeatureBuilder_ == null) {
weightedFeature_ = java.util.Collections.emptyList();
bitField0_ = (bitField0_ & ~0x00000004);
onChanged();
} else {
weightedFeatureBuilder_.clear();
}
return this;
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public Builder removeWeightedFeature(int index) {
if (weightedFeatureBuilder_ == null) {
ensureWeightedFeatureIsMutable();
weightedFeature_.remove(index);
onChanged();
} else {
weightedFeatureBuilder_.remove(index);
}
return this;
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public org.tensorflow.metadata.v0.WeightedFeature.Builder getWeightedFeatureBuilder(
int index) {
return getWeightedFeatureFieldBuilder().getBuilder(index);
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public org.tensorflow.metadata.v0.WeightedFeatureOrBuilder getWeightedFeatureOrBuilder(
int index) {
if (weightedFeatureBuilder_ == null) {
return weightedFeature_.get(index); } else {
return weightedFeatureBuilder_.getMessageOrBuilder(index);
}
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public java.util.List
getWeightedFeatureOrBuilderList() {
if (weightedFeatureBuilder_ != null) {
return weightedFeatureBuilder_.getMessageOrBuilderList();
} else {
return java.util.Collections.unmodifiableList(weightedFeature_);
}
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public org.tensorflow.metadata.v0.WeightedFeature.Builder addWeightedFeatureBuilder() {
return getWeightedFeatureFieldBuilder().addBuilder(
org.tensorflow.metadata.v0.WeightedFeature.getDefaultInstance());
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public org.tensorflow.metadata.v0.WeightedFeature.Builder addWeightedFeatureBuilder(
int index) {
return getWeightedFeatureFieldBuilder().addBuilder(
index, org.tensorflow.metadata.v0.WeightedFeature.getDefaultInstance());
}
/**
*
* Weighted features described in this schema.
*
*
* repeated .tensorflow.metadata.v0.WeightedFeature weighted_feature = 12;
*/
public java.util.List
getWeightedFeatureBuilderList() {
return getWeightedFeatureFieldBuilder().getBuilderList();
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.WeightedFeature, org.tensorflow.metadata.v0.WeightedFeature.Builder, org.tensorflow.metadata.v0.WeightedFeatureOrBuilder>
getWeightedFeatureFieldBuilder() {
if (weightedFeatureBuilder_ == null) {
weightedFeatureBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.WeightedFeature, org.tensorflow.metadata.v0.WeightedFeature.Builder, org.tensorflow.metadata.v0.WeightedFeatureOrBuilder>(
weightedFeature_,
((bitField0_ & 0x00000004) != 0),
getParentForChildren(),
isClean());
weightedFeature_ = null;
}
return weightedFeatureBuilder_;
}
private java.util.List stringDomain_ =
java.util.Collections.emptyList();
private void ensureStringDomainIsMutable() {
if (!((bitField0_ & 0x00000008) != 0)) {
stringDomain_ = new java.util.ArrayList(stringDomain_);
bitField0_ |= 0x00000008;
}
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.StringDomain, org.tensorflow.metadata.v0.StringDomain.Builder, org.tensorflow.metadata.v0.StringDomainOrBuilder> stringDomainBuilder_;
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public java.util.List getStringDomainList() {
if (stringDomainBuilder_ == null) {
return java.util.Collections.unmodifiableList(stringDomain_);
} else {
return stringDomainBuilder_.getMessageList();
}
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public int getStringDomainCount() {
if (stringDomainBuilder_ == null) {
return stringDomain_.size();
} else {
return stringDomainBuilder_.getCount();
}
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public org.tensorflow.metadata.v0.StringDomain getStringDomain(int index) {
if (stringDomainBuilder_ == null) {
return stringDomain_.get(index);
} else {
return stringDomainBuilder_.getMessage(index);
}
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public Builder setStringDomain(
int index, org.tensorflow.metadata.v0.StringDomain value) {
if (stringDomainBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureStringDomainIsMutable();
stringDomain_.set(index, value);
onChanged();
} else {
stringDomainBuilder_.setMessage(index, value);
}
return this;
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public Builder setStringDomain(
int index, org.tensorflow.metadata.v0.StringDomain.Builder builderForValue) {
if (stringDomainBuilder_ == null) {
ensureStringDomainIsMutable();
stringDomain_.set(index, builderForValue.build());
onChanged();
} else {
stringDomainBuilder_.setMessage(index, builderForValue.build());
}
return this;
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public Builder addStringDomain(org.tensorflow.metadata.v0.StringDomain value) {
if (stringDomainBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureStringDomainIsMutable();
stringDomain_.add(value);
onChanged();
} else {
stringDomainBuilder_.addMessage(value);
}
return this;
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public Builder addStringDomain(
int index, org.tensorflow.metadata.v0.StringDomain value) {
if (stringDomainBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureStringDomainIsMutable();
stringDomain_.add(index, value);
onChanged();
} else {
stringDomainBuilder_.addMessage(index, value);
}
return this;
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public Builder addStringDomain(
org.tensorflow.metadata.v0.StringDomain.Builder builderForValue) {
if (stringDomainBuilder_ == null) {
ensureStringDomainIsMutable();
stringDomain_.add(builderForValue.build());
onChanged();
} else {
stringDomainBuilder_.addMessage(builderForValue.build());
}
return this;
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public Builder addStringDomain(
int index, org.tensorflow.metadata.v0.StringDomain.Builder builderForValue) {
if (stringDomainBuilder_ == null) {
ensureStringDomainIsMutable();
stringDomain_.add(index, builderForValue.build());
onChanged();
} else {
stringDomainBuilder_.addMessage(index, builderForValue.build());
}
return this;
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public Builder addAllStringDomain(
java.lang.Iterable values) {
if (stringDomainBuilder_ == null) {
ensureStringDomainIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(
values, stringDomain_);
onChanged();
} else {
stringDomainBuilder_.addAllMessages(values);
}
return this;
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public Builder clearStringDomain() {
if (stringDomainBuilder_ == null) {
stringDomain_ = java.util.Collections.emptyList();
bitField0_ = (bitField0_ & ~0x00000008);
onChanged();
} else {
stringDomainBuilder_.clear();
}
return this;
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public Builder removeStringDomain(int index) {
if (stringDomainBuilder_ == null) {
ensureStringDomainIsMutable();
stringDomain_.remove(index);
onChanged();
} else {
stringDomainBuilder_.remove(index);
}
return this;
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public org.tensorflow.metadata.v0.StringDomain.Builder getStringDomainBuilder(
int index) {
return getStringDomainFieldBuilder().getBuilder(index);
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public org.tensorflow.metadata.v0.StringDomainOrBuilder getStringDomainOrBuilder(
int index) {
if (stringDomainBuilder_ == null) {
return stringDomain_.get(index); } else {
return stringDomainBuilder_.getMessageOrBuilder(index);
}
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public java.util.List
getStringDomainOrBuilderList() {
if (stringDomainBuilder_ != null) {
return stringDomainBuilder_.getMessageOrBuilderList();
} else {
return java.util.Collections.unmodifiableList(stringDomain_);
}
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public org.tensorflow.metadata.v0.StringDomain.Builder addStringDomainBuilder() {
return getStringDomainFieldBuilder().addBuilder(
org.tensorflow.metadata.v0.StringDomain.getDefaultInstance());
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public org.tensorflow.metadata.v0.StringDomain.Builder addStringDomainBuilder(
int index) {
return getStringDomainFieldBuilder().addBuilder(
index, org.tensorflow.metadata.v0.StringDomain.getDefaultInstance());
}
/**
*
* declared as top-level features in <feature>.
* String domains referenced in the features.
*
*
* repeated .tensorflow.metadata.v0.StringDomain string_domain = 4;
*/
public java.util.List
getStringDomainBuilderList() {
return getStringDomainFieldBuilder().getBuilderList();
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.StringDomain, org.tensorflow.metadata.v0.StringDomain.Builder, org.tensorflow.metadata.v0.StringDomainOrBuilder>
getStringDomainFieldBuilder() {
if (stringDomainBuilder_ == null) {
stringDomainBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.StringDomain, org.tensorflow.metadata.v0.StringDomain.Builder, org.tensorflow.metadata.v0.StringDomainOrBuilder>(
stringDomain_,
((bitField0_ & 0x00000008) != 0),
getParentForChildren(),
isClean());
stringDomain_ = null;
}
return stringDomainBuilder_;
}
private java.util.List floatDomain_ =
java.util.Collections.emptyList();
private void ensureFloatDomainIsMutable() {
if (!((bitField0_ & 0x00000010) != 0)) {
floatDomain_ = new java.util.ArrayList(floatDomain_);
bitField0_ |= 0x00000010;
}
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.FloatDomain, org.tensorflow.metadata.v0.FloatDomain.Builder, org.tensorflow.metadata.v0.FloatDomainOrBuilder> floatDomainBuilder_;
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public java.util.List getFloatDomainList() {
if (floatDomainBuilder_ == null) {
return java.util.Collections.unmodifiableList(floatDomain_);
} else {
return floatDomainBuilder_.getMessageList();
}
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public int getFloatDomainCount() {
if (floatDomainBuilder_ == null) {
return floatDomain_.size();
} else {
return floatDomainBuilder_.getCount();
}
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public org.tensorflow.metadata.v0.FloatDomain getFloatDomain(int index) {
if (floatDomainBuilder_ == null) {
return floatDomain_.get(index);
} else {
return floatDomainBuilder_.getMessage(index);
}
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public Builder setFloatDomain(
int index, org.tensorflow.metadata.v0.FloatDomain value) {
if (floatDomainBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureFloatDomainIsMutable();
floatDomain_.set(index, value);
onChanged();
} else {
floatDomainBuilder_.setMessage(index, value);
}
return this;
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public Builder setFloatDomain(
int index, org.tensorflow.metadata.v0.FloatDomain.Builder builderForValue) {
if (floatDomainBuilder_ == null) {
ensureFloatDomainIsMutable();
floatDomain_.set(index, builderForValue.build());
onChanged();
} else {
floatDomainBuilder_.setMessage(index, builderForValue.build());
}
return this;
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public Builder addFloatDomain(org.tensorflow.metadata.v0.FloatDomain value) {
if (floatDomainBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureFloatDomainIsMutable();
floatDomain_.add(value);
onChanged();
} else {
floatDomainBuilder_.addMessage(value);
}
return this;
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public Builder addFloatDomain(
int index, org.tensorflow.metadata.v0.FloatDomain value) {
if (floatDomainBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureFloatDomainIsMutable();
floatDomain_.add(index, value);
onChanged();
} else {
floatDomainBuilder_.addMessage(index, value);
}
return this;
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public Builder addFloatDomain(
org.tensorflow.metadata.v0.FloatDomain.Builder builderForValue) {
if (floatDomainBuilder_ == null) {
ensureFloatDomainIsMutable();
floatDomain_.add(builderForValue.build());
onChanged();
} else {
floatDomainBuilder_.addMessage(builderForValue.build());
}
return this;
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public Builder addFloatDomain(
int index, org.tensorflow.metadata.v0.FloatDomain.Builder builderForValue) {
if (floatDomainBuilder_ == null) {
ensureFloatDomainIsMutable();
floatDomain_.add(index, builderForValue.build());
onChanged();
} else {
floatDomainBuilder_.addMessage(index, builderForValue.build());
}
return this;
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public Builder addAllFloatDomain(
java.lang.Iterable values) {
if (floatDomainBuilder_ == null) {
ensureFloatDomainIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(
values, floatDomain_);
onChanged();
} else {
floatDomainBuilder_.addAllMessages(values);
}
return this;
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public Builder clearFloatDomain() {
if (floatDomainBuilder_ == null) {
floatDomain_ = java.util.Collections.emptyList();
bitField0_ = (bitField0_ & ~0x00000010);
onChanged();
} else {
floatDomainBuilder_.clear();
}
return this;
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public Builder removeFloatDomain(int index) {
if (floatDomainBuilder_ == null) {
ensureFloatDomainIsMutable();
floatDomain_.remove(index);
onChanged();
} else {
floatDomainBuilder_.remove(index);
}
return this;
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public org.tensorflow.metadata.v0.FloatDomain.Builder getFloatDomainBuilder(
int index) {
return getFloatDomainFieldBuilder().getBuilder(index);
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public org.tensorflow.metadata.v0.FloatDomainOrBuilder getFloatDomainOrBuilder(
int index) {
if (floatDomainBuilder_ == null) {
return floatDomain_.get(index); } else {
return floatDomainBuilder_.getMessageOrBuilder(index);
}
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public java.util.List
getFloatDomainOrBuilderList() {
if (floatDomainBuilder_ != null) {
return floatDomainBuilder_.getMessageOrBuilderList();
} else {
return java.util.Collections.unmodifiableList(floatDomain_);
}
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public org.tensorflow.metadata.v0.FloatDomain.Builder addFloatDomainBuilder() {
return getFloatDomainFieldBuilder().addBuilder(
org.tensorflow.metadata.v0.FloatDomain.getDefaultInstance());
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public org.tensorflow.metadata.v0.FloatDomain.Builder addFloatDomainBuilder(
int index) {
return getFloatDomainFieldBuilder().addBuilder(
index, org.tensorflow.metadata.v0.FloatDomain.getDefaultInstance());
}
/**
*
* top level float domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.FloatDomain float_domain = 9;
*/
public java.util.List
getFloatDomainBuilderList() {
return getFloatDomainFieldBuilder().getBuilderList();
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.FloatDomain, org.tensorflow.metadata.v0.FloatDomain.Builder, org.tensorflow.metadata.v0.FloatDomainOrBuilder>
getFloatDomainFieldBuilder() {
if (floatDomainBuilder_ == null) {
floatDomainBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.FloatDomain, org.tensorflow.metadata.v0.FloatDomain.Builder, org.tensorflow.metadata.v0.FloatDomainOrBuilder>(
floatDomain_,
((bitField0_ & 0x00000010) != 0),
getParentForChildren(),
isClean());
floatDomain_ = null;
}
return floatDomainBuilder_;
}
private java.util.List intDomain_ =
java.util.Collections.emptyList();
private void ensureIntDomainIsMutable() {
if (!((bitField0_ & 0x00000020) != 0)) {
intDomain_ = new java.util.ArrayList(intDomain_);
bitField0_ |= 0x00000020;
}
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.IntDomain, org.tensorflow.metadata.v0.IntDomain.Builder, org.tensorflow.metadata.v0.IntDomainOrBuilder> intDomainBuilder_;
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public java.util.List getIntDomainList() {
if (intDomainBuilder_ == null) {
return java.util.Collections.unmodifiableList(intDomain_);
} else {
return intDomainBuilder_.getMessageList();
}
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public int getIntDomainCount() {
if (intDomainBuilder_ == null) {
return intDomain_.size();
} else {
return intDomainBuilder_.getCount();
}
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public org.tensorflow.metadata.v0.IntDomain getIntDomain(int index) {
if (intDomainBuilder_ == null) {
return intDomain_.get(index);
} else {
return intDomainBuilder_.getMessage(index);
}
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public Builder setIntDomain(
int index, org.tensorflow.metadata.v0.IntDomain value) {
if (intDomainBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureIntDomainIsMutable();
intDomain_.set(index, value);
onChanged();
} else {
intDomainBuilder_.setMessage(index, value);
}
return this;
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public Builder setIntDomain(
int index, org.tensorflow.metadata.v0.IntDomain.Builder builderForValue) {
if (intDomainBuilder_ == null) {
ensureIntDomainIsMutable();
intDomain_.set(index, builderForValue.build());
onChanged();
} else {
intDomainBuilder_.setMessage(index, builderForValue.build());
}
return this;
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public Builder addIntDomain(org.tensorflow.metadata.v0.IntDomain value) {
if (intDomainBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureIntDomainIsMutable();
intDomain_.add(value);
onChanged();
} else {
intDomainBuilder_.addMessage(value);
}
return this;
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public Builder addIntDomain(
int index, org.tensorflow.metadata.v0.IntDomain value) {
if (intDomainBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureIntDomainIsMutable();
intDomain_.add(index, value);
onChanged();
} else {
intDomainBuilder_.addMessage(index, value);
}
return this;
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public Builder addIntDomain(
org.tensorflow.metadata.v0.IntDomain.Builder builderForValue) {
if (intDomainBuilder_ == null) {
ensureIntDomainIsMutable();
intDomain_.add(builderForValue.build());
onChanged();
} else {
intDomainBuilder_.addMessage(builderForValue.build());
}
return this;
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public Builder addIntDomain(
int index, org.tensorflow.metadata.v0.IntDomain.Builder builderForValue) {
if (intDomainBuilder_ == null) {
ensureIntDomainIsMutable();
intDomain_.add(index, builderForValue.build());
onChanged();
} else {
intDomainBuilder_.addMessage(index, builderForValue.build());
}
return this;
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public Builder addAllIntDomain(
java.lang.Iterable values) {
if (intDomainBuilder_ == null) {
ensureIntDomainIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(
values, intDomain_);
onChanged();
} else {
intDomainBuilder_.addAllMessages(values);
}
return this;
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public Builder clearIntDomain() {
if (intDomainBuilder_ == null) {
intDomain_ = java.util.Collections.emptyList();
bitField0_ = (bitField0_ & ~0x00000020);
onChanged();
} else {
intDomainBuilder_.clear();
}
return this;
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public Builder removeIntDomain(int index) {
if (intDomainBuilder_ == null) {
ensureIntDomainIsMutable();
intDomain_.remove(index);
onChanged();
} else {
intDomainBuilder_.remove(index);
}
return this;
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public org.tensorflow.metadata.v0.IntDomain.Builder getIntDomainBuilder(
int index) {
return getIntDomainFieldBuilder().getBuilder(index);
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public org.tensorflow.metadata.v0.IntDomainOrBuilder getIntDomainOrBuilder(
int index) {
if (intDomainBuilder_ == null) {
return intDomain_.get(index); } else {
return intDomainBuilder_.getMessageOrBuilder(index);
}
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public java.util.List
getIntDomainOrBuilderList() {
if (intDomainBuilder_ != null) {
return intDomainBuilder_.getMessageOrBuilderList();
} else {
return java.util.Collections.unmodifiableList(intDomain_);
}
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public org.tensorflow.metadata.v0.IntDomain.Builder addIntDomainBuilder() {
return getIntDomainFieldBuilder().addBuilder(
org.tensorflow.metadata.v0.IntDomain.getDefaultInstance());
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public org.tensorflow.metadata.v0.IntDomain.Builder addIntDomainBuilder(
int index) {
return getIntDomainFieldBuilder().addBuilder(
index, org.tensorflow.metadata.v0.IntDomain.getDefaultInstance());
}
/**
*
* top level int domains that can be reused by features
*
*
* repeated .tensorflow.metadata.v0.IntDomain int_domain = 10;
*/
public java.util.List
getIntDomainBuilderList() {
return getIntDomainFieldBuilder().getBuilderList();
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.IntDomain, org.tensorflow.metadata.v0.IntDomain.Builder, org.tensorflow.metadata.v0.IntDomainOrBuilder>
getIntDomainFieldBuilder() {
if (intDomainBuilder_ == null) {
intDomainBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.metadata.v0.IntDomain, org.tensorflow.metadata.v0.IntDomain.Builder, org.tensorflow.metadata.v0.IntDomainOrBuilder>(
intDomain_,
((bitField0_ & 0x00000020) != 0),
getParentForChildren(),
isClean());
intDomain_ = null;
}
return intDomainBuilder_;
}
private com.google.protobuf.LazyStringArrayList defaultEnvironment_ =
com.google.protobuf.LazyStringArrayList.emptyList();
private void ensureDefaultEnvironmentIsMutable() {
if (!defaultEnvironment_.isModifiable()) {
defaultEnvironment_ = new com.google.protobuf.LazyStringArrayList(defaultEnvironment_);
}
bitField0_ |= 0x00000040;
}
/**
*
* 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.
*/
public com.google.protobuf.ProtocolStringList
getDefaultEnvironmentList() {
defaultEnvironment_.makeImmutable();
return defaultEnvironment_;
}
/**
*
* 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.
*/
public int getDefaultEnvironmentCount() {
return defaultEnvironment_.size();
}
/**
*
* 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.
*/
public java.lang.String getDefaultEnvironment(int index) {
return defaultEnvironment_.get(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.
*/
public com.google.protobuf.ByteString
getDefaultEnvironmentBytes(int index) {
return defaultEnvironment_.getByteString(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 to set the value at.
* @param value The defaultEnvironment to set.
* @return This builder for chaining.
*/
public Builder setDefaultEnvironment(
int index, java.lang.String value) {
if (value == null) { throw new NullPointerException(); }
ensureDefaultEnvironmentIsMutable();
defaultEnvironment_.set(index, value);
bitField0_ |= 0x00000040;
onChanged();
return this;
}
/**
*
* 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 value The defaultEnvironment to add.
* @return This builder for chaining.
*/
public Builder addDefaultEnvironment(
java.lang.String value) {
if (value == null) { throw new NullPointerException(); }
ensureDefaultEnvironmentIsMutable();
defaultEnvironment_.add(value);
bitField0_ |= 0x00000040;
onChanged();
return this;
}
/**
*
* 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 values The defaultEnvironment to add.
* @return This builder for chaining.
*/
public Builder addAllDefaultEnvironment(
java.lang.Iterable values) {
ensureDefaultEnvironmentIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(
values, defaultEnvironment_);
bitField0_ |= 0x00000040;
onChanged();
return this;
}
/**
*
* 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 This builder for chaining.
*/
public Builder clearDefaultEnvironment() {
defaultEnvironment_ =
com.google.protobuf.LazyStringArrayList.emptyList();
bitField0_ = (bitField0_ & ~0x00000040);;
onChanged();
return this;
}
/**
*
* 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 value The bytes of the defaultEnvironment to add.
* @return This builder for chaining.
*/
public Builder addDefaultEnvironmentBytes(
com.google.protobuf.ByteString value) {
if (value == null) { throw new NullPointerException(); }
ensureDefaultEnvironmentIsMutable();
defaultEnvironment_.add(value);
bitField0_ |= 0x00000040;
onChanged();
return this;
}
private boolean representVariableLengthAsRagged_ ;
/**
*
* 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.
*/
@java.lang.Override
public boolean hasRepresentVariableLengthAsRagged() {
return ((bitField0_ & 0x00000080) != 0);
}
/**
*
* 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.
*/
@java.lang.Override
public boolean getRepresentVariableLengthAsRagged() {
return representVariableLengthAsRagged_;
}
/**
*
* 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;
* @param value The representVariableLengthAsRagged to set.
* @return This builder for chaining.
*/
public Builder setRepresentVariableLengthAsRagged(boolean value) {
representVariableLengthAsRagged_ = value;
bitField0_ |= 0x00000080;
onChanged();
return this;
}
/**
*
* 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 This builder for chaining.
*/
public Builder clearRepresentVariableLengthAsRagged() {
bitField0_ = (bitField0_ & ~0x00000080);
representVariableLengthAsRagged_ = false;
onChanged();
return this;
}
private org.tensorflow.metadata.v0.Annotation annotation_;
private com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.metadata.v0.Annotation, org.tensorflow.metadata.v0.Annotation.Builder, org.tensorflow.metadata.v0.AnnotationOrBuilder> annotationBuilder_;
/**
*
* 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.
*/
public boolean hasAnnotation() {
return ((bitField0_ & 0x00000100) != 0);
}
/**
*
* Additional information about the schema as a whole. Features may also
* be annotated individually.
*
*
* optional .tensorflow.metadata.v0.Annotation annotation = 8;
* @return The annotation.
*/
public org.tensorflow.metadata.v0.Annotation getAnnotation() {
if (annotationBuilder_ == null) {
return annotation_ == null ? org.tensorflow.metadata.v0.Annotation.getDefaultInstance() : annotation_;
} else {
return annotationBuilder_.getMessage();
}
}
/**
*
* Additional information about the schema as a whole. Features may also
* be annotated individually.
*
*
* optional .tensorflow.metadata.v0.Annotation annotation = 8;
*/
public Builder setAnnotation(org.tensorflow.metadata.v0.Annotation value) {
if (annotationBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
annotation_ = value;
} else {
annotationBuilder_.setMessage(value);
}
bitField0_ |= 0x00000100;
onChanged();
return this;
}
/**
*
* Additional information about the schema as a whole. Features may also
* be annotated individually.
*
*
* optional .tensorflow.metadata.v0.Annotation annotation = 8;
*/
public Builder setAnnotation(
org.tensorflow.metadata.v0.Annotation.Builder builderForValue) {
if (annotationBuilder_ == null) {
annotation_ = builderForValue.build();
} else {
annotationBuilder_.setMessage(builderForValue.build());
}
bitField0_ |= 0x00000100;
onChanged();
return this;
}
/**
*
* Additional information about the schema as a whole. Features may also
* be annotated individually.
*
*
* optional .tensorflow.metadata.v0.Annotation annotation = 8;
*/
public Builder mergeAnnotation(org.tensorflow.metadata.v0.Annotation value) {
if (annotationBuilder_ == null) {
if (((bitField0_ & 0x00000100) != 0) &&
annotation_ != null &&
annotation_ != org.tensorflow.metadata.v0.Annotation.getDefaultInstance()) {
getAnnotationBuilder().mergeFrom(value);
} else {
annotation_ = value;
}
} else {
annotationBuilder_.mergeFrom(value);
}
if (annotation_ != null) {
bitField0_ |= 0x00000100;
onChanged();
}
return this;
}
/**
*
* Additional information about the schema as a whole. Features may also
* be annotated individually.
*
*
* optional .tensorflow.metadata.v0.Annotation annotation = 8;
*/
public Builder clearAnnotation() {
bitField0_ = (bitField0_ & ~0x00000100);
annotation_ = null;
if (annotationBuilder_ != null) {
annotationBuilder_.dispose();
annotationBuilder_ = null;
}
onChanged();
return this;
}
/**
*
* Additional information about the schema as a whole. Features may also
* be annotated individually.
*
*
* optional .tensorflow.metadata.v0.Annotation annotation = 8;
*/
public org.tensorflow.metadata.v0.Annotation.Builder getAnnotationBuilder() {
bitField0_ |= 0x00000100;
onChanged();
return getAnnotationFieldBuilder().getBuilder();
}
/**
*
* Additional information about the schema as a whole. Features may also
* be annotated individually.
*
*
* optional .tensorflow.metadata.v0.Annotation annotation = 8;
*/
public org.tensorflow.metadata.v0.AnnotationOrBuilder getAnnotationOrBuilder() {
if (annotationBuilder_ != null) {
return annotationBuilder_.getMessageOrBuilder();
} else {
return annotation_ == null ?
org.tensorflow.metadata.v0.Annotation.getDefaultInstance() : annotation_;
}
}
/**
*
* Additional information about the schema as a whole. Features may also
* be annotated individually.
*
*
* optional .tensorflow.metadata.v0.Annotation annotation = 8;
*/
private com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.metadata.v0.Annotation, org.tensorflow.metadata.v0.Annotation.Builder, org.tensorflow.metadata.v0.AnnotationOrBuilder>
getAnnotationFieldBuilder() {
if (annotationBuilder_ == null) {
annotationBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.metadata.v0.Annotation, org.tensorflow.metadata.v0.Annotation.Builder, org.tensorflow.metadata.v0.AnnotationOrBuilder>(
getAnnotation(),
getParentForChildren(),
isClean());
annotation_ = null;
}
return annotationBuilder_;
}
private org.tensorflow.metadata.v0.DatasetConstraints datasetConstraints_;
private com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.metadata.v0.DatasetConstraints, org.tensorflow.metadata.v0.DatasetConstraints.Builder, org.tensorflow.metadata.v0.DatasetConstraintsOrBuilder> datasetConstraintsBuilder_;
/**
*
* 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.
*/
public boolean hasDatasetConstraints() {
return ((bitField0_ & 0x00000200) != 0);
}
/**
*
* 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.
*/
public org.tensorflow.metadata.v0.DatasetConstraints getDatasetConstraints() {
if (datasetConstraintsBuilder_ == null) {
return datasetConstraints_ == null ? org.tensorflow.metadata.v0.DatasetConstraints.getDefaultInstance() : datasetConstraints_;
} else {
return datasetConstraintsBuilder_.getMessage();
}
}
/**
*
* Dataset-level constraints. This is currently used for specifying
* information about changes in num_examples.
*
*
* optional .tensorflow.metadata.v0.DatasetConstraints dataset_constraints = 11;
*/
public Builder setDatasetConstraints(org.tensorflow.metadata.v0.DatasetConstraints value) {
if (datasetConstraintsBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
datasetConstraints_ = value;
} else {
datasetConstraintsBuilder_.setMessage(value);
}
bitField0_ |= 0x00000200;
onChanged();
return this;
}
/**
*
* Dataset-level constraints. This is currently used for specifying
* information about changes in num_examples.
*
*
* optional .tensorflow.metadata.v0.DatasetConstraints dataset_constraints = 11;
*/
public Builder setDatasetConstraints(
org.tensorflow.metadata.v0.DatasetConstraints.Builder builderForValue) {
if (datasetConstraintsBuilder_ == null) {
datasetConstraints_ = builderForValue.build();
} else {
datasetConstraintsBuilder_.setMessage(builderForValue.build());
}
bitField0_ |= 0x00000200;
onChanged();
return this;
}
/**
*
* Dataset-level constraints. This is currently used for specifying
* information about changes in num_examples.
*
*
* optional .tensorflow.metadata.v0.DatasetConstraints dataset_constraints = 11;
*/
public Builder mergeDatasetConstraints(org.tensorflow.metadata.v0.DatasetConstraints value) {
if (datasetConstraintsBuilder_ == null) {
if (((bitField0_ & 0x00000200) != 0) &&
datasetConstraints_ != null &&
datasetConstraints_ != org.tensorflow.metadata.v0.DatasetConstraints.getDefaultInstance()) {
getDatasetConstraintsBuilder().mergeFrom(value);
} else {
datasetConstraints_ = value;
}
} else {
datasetConstraintsBuilder_.mergeFrom(value);
}
if (datasetConstraints_ != null) {
bitField0_ |= 0x00000200;
onChanged();
}
return this;
}
/**
*
* Dataset-level constraints. This is currently used for specifying
* information about changes in num_examples.
*
*
* optional .tensorflow.metadata.v0.DatasetConstraints dataset_constraints = 11;
*/
public Builder clearDatasetConstraints() {
bitField0_ = (bitField0_ & ~0x00000200);
datasetConstraints_ = null;
if (datasetConstraintsBuilder_ != null) {
datasetConstraintsBuilder_.dispose();
datasetConstraintsBuilder_ = null;
}
onChanged();
return this;
}
/**
*
* Dataset-level constraints. This is currently used for specifying
* information about changes in num_examples.
*
*
* optional .tensorflow.metadata.v0.DatasetConstraints dataset_constraints = 11;
*/
public org.tensorflow.metadata.v0.DatasetConstraints.Builder getDatasetConstraintsBuilder() {
bitField0_ |= 0x00000200;
onChanged();
return getDatasetConstraintsFieldBuilder().getBuilder();
}
/**
*
* Dataset-level constraints. This is currently used for specifying
* information about changes in num_examples.
*
*
* optional .tensorflow.metadata.v0.DatasetConstraints dataset_constraints = 11;
*/
public org.tensorflow.metadata.v0.DatasetConstraintsOrBuilder getDatasetConstraintsOrBuilder() {
if (datasetConstraintsBuilder_ != null) {
return datasetConstraintsBuilder_.getMessageOrBuilder();
} else {
return datasetConstraints_ == null ?
org.tensorflow.metadata.v0.DatasetConstraints.getDefaultInstance() : datasetConstraints_;
}
}
/**
*
* Dataset-level constraints. This is currently used for specifying
* information about changes in num_examples.
*
*
* optional .tensorflow.metadata.v0.DatasetConstraints dataset_constraints = 11;
*/
private com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.metadata.v0.DatasetConstraints, org.tensorflow.metadata.v0.DatasetConstraints.Builder, org.tensorflow.metadata.v0.DatasetConstraintsOrBuilder>
getDatasetConstraintsFieldBuilder() {
if (datasetConstraintsBuilder_ == null) {
datasetConstraintsBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.metadata.v0.DatasetConstraints, org.tensorflow.metadata.v0.DatasetConstraints.Builder, org.tensorflow.metadata.v0.DatasetConstraintsOrBuilder>(
getDatasetConstraints(),
getParentForChildren(),
isClean());
datasetConstraints_ = null;
}
return datasetConstraintsBuilder_;
}
private static final class TensorRepresentationGroupConverter implements com.google.protobuf.MapFieldBuilder.Converter {
@java.lang.Override
public org.tensorflow.metadata.v0.TensorRepresentationGroup build(org.tensorflow.metadata.v0.TensorRepresentationGroupOrBuilder val) {
if (val instanceof org.tensorflow.metadata.v0.TensorRepresentationGroup) { return (org.tensorflow.metadata.v0.TensorRepresentationGroup) val; }
return ((org.tensorflow.metadata.v0.TensorRepresentationGroup.Builder) val).build();
}
@java.lang.Override
public com.google.protobuf.MapEntry defaultEntry() {
return TensorRepresentationGroupDefaultEntryHolder.defaultEntry;
}
};
private static final TensorRepresentationGroupConverter tensorRepresentationGroupConverter = new TensorRepresentationGroupConverter();
private com.google.protobuf.MapFieldBuilder<
java.lang.String, org.tensorflow.metadata.v0.TensorRepresentationGroupOrBuilder, org.tensorflow.metadata.v0.TensorRepresentationGroup, org.tensorflow.metadata.v0.TensorRepresentationGroup.Builder> tensorRepresentationGroup_;
private com.google.protobuf.MapFieldBuilder
internalGetTensorRepresentationGroup() {
if (tensorRepresentationGroup_ == null) {
return new com.google.protobuf.MapFieldBuilder<>(tensorRepresentationGroupConverter);
}
return tensorRepresentationGroup_;
}
private com.google.protobuf.MapFieldBuilder
internalGetMutableTensorRepresentationGroup() {
if (tensorRepresentationGroup_ == null) {
tensorRepresentationGroup_ = new com.google.protobuf.MapFieldBuilder<>(tensorRepresentationGroupConverter);
}
bitField0_ |= 0x00000400;
onChanged();
return tensorRepresentationGroup_;
}
public int getTensorRepresentationGroupCount() {
return internalGetTensorRepresentationGroup().ensureBuilderMap().size();
}
/**
*
* 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.lang.Override
public boolean containsTensorRepresentationGroup(
java.lang.String key) {
if (key == null) { throw new NullPointerException("map key"); }
return internalGetTensorRepresentationGroup().ensureBuilderMap().containsKey(key);
}
/**
* Use {@link #getTensorRepresentationGroupMap()} instead.
*/
@java.lang.Override
@java.lang.Deprecated
public java.util.Map getTensorRepresentationGroup() {
return 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;
*/
@java.lang.Override
public java.util.Map getTensorRepresentationGroupMap() {
return internalGetTensorRepresentationGroup().getImmutableMap();
}
/**
*
* 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.lang.Override
public /* nullable */
org.tensorflow.metadata.v0.TensorRepresentationGroup getTensorRepresentationGroupOrDefault(
java.lang.String key,
/* nullable */
org.tensorflow.metadata.v0.TensorRepresentationGroup defaultValue) {
if (key == null) { throw new NullPointerException("map key"); }
java.util.Map map = internalGetMutableTensorRepresentationGroup().ensureBuilderMap();
return map.containsKey(key) ? tensorRepresentationGroupConverter.build(map.get(key)) : 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;
*/
@java.lang.Override
public org.tensorflow.metadata.v0.TensorRepresentationGroup getTensorRepresentationGroupOrThrow(
java.lang.String key) {
if (key == null) { throw new NullPointerException("map key"); }
java.util.Map map = internalGetMutableTensorRepresentationGroup().ensureBuilderMap();
if (!map.containsKey(key)) {
throw new java.lang.IllegalArgumentException();
}
return tensorRepresentationGroupConverter.build(map.get(key));
}
public Builder clearTensorRepresentationGroup() {
bitField0_ = (bitField0_ & ~0x00000400);
internalGetMutableTensorRepresentationGroup().clear();
return this;
}
/**
*
* 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;
*/
public Builder removeTensorRepresentationGroup(
java.lang.String key) {
if (key == null) { throw new NullPointerException("map key"); }
internalGetMutableTensorRepresentationGroup().ensureBuilderMap()
.remove(key);
return this;
}
/**
* Use alternate mutation accessors instead.
*/
@java.lang.Deprecated
public java.util.Map
getMutableTensorRepresentationGroup() {
bitField0_ |= 0x00000400;
return internalGetMutableTensorRepresentationGroup().ensureMessageMap();
}
/**
*
* 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;
*/
public Builder putTensorRepresentationGroup(
java.lang.String key,
org.tensorflow.metadata.v0.TensorRepresentationGroup value) {
if (key == null) { throw new NullPointerException("map key"); }
if (value == null) { throw new NullPointerException("map value"); }
internalGetMutableTensorRepresentationGroup().ensureBuilderMap()
.put(key, value);
bitField0_ |= 0x00000400;
return this;
}
/**
*
* 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;
*/
public Builder putAllTensorRepresentationGroup(
java.util.Map values) {
for (java.util.Map.Entry e : values.entrySet()) {
if (e.getKey() == null || e.getValue() == null) {
throw new NullPointerException();
}
}
internalGetMutableTensorRepresentationGroup().ensureBuilderMap()
.putAll(values);
bitField0_ |= 0x00000400;
return this;
}
/**
*
* 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;
*/
public org.tensorflow.metadata.v0.TensorRepresentationGroup.Builder putTensorRepresentationGroupBuilderIfAbsent(
java.lang.String key) {
java.util.Map builderMap = internalGetMutableTensorRepresentationGroup().ensureBuilderMap();
org.tensorflow.metadata.v0.TensorRepresentationGroupOrBuilder entry = builderMap.get(key);
if (entry == null) {
entry = org.tensorflow.metadata.v0.TensorRepresentationGroup.newBuilder();
builderMap.put(key, entry);
}
if (entry instanceof org.tensorflow.metadata.v0.TensorRepresentationGroup) {
entry = ((org.tensorflow.metadata.v0.TensorRepresentationGroup) entry).toBuilder();
builderMap.put(key, entry);
}
return (org.tensorflow.metadata.v0.TensorRepresentationGroup.Builder) entry;
}
@java.lang.Override
public final Builder setUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFields(unknownFields);
}
@java.lang.Override
public final Builder mergeUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:tensorflow.metadata.v0.Schema)
}
// @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.Schema)
private static final org.tensorflow.metadata.v0.Schema DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new org.tensorflow.metadata.v0.Schema();
}
public static org.tensorflow.metadata.v0.Schema getDefaultInstance() {
return DEFAULT_INSTANCE;
}
@java.lang.Deprecated public static final com.google.protobuf.Parser
PARSER = new com.google.protobuf.AbstractParser() {
@java.lang.Override
public Schema parsePartialFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
Builder builder = newBuilder();
try {
builder.mergeFrom(input, extensionRegistry);
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
throw e.setUnfinishedMessage(builder.buildPartial());
} catch (com.google.protobuf.UninitializedMessageException e) {
throw e.asInvalidProtocolBufferException().setUnfinishedMessage(builder.buildPartial());
} catch (java.io.IOException e) {
throw new com.google.protobuf.InvalidProtocolBufferException(e)
.setUnfinishedMessage(builder.buildPartial());
}
return builder.buildPartial();
}
};
public static com.google.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public com.google.protobuf.Parser getParserForType() {
return PARSER;
}
@java.lang.Override
public org.tensorflow.metadata.v0.Schema getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
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