trait AnomaliesOrBuilder extends MessageOrBuilder
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-   abstract  def containsAnomalyInfo(key: String): Boolean
Information about feature-level anomalies.
Information about feature-level anomalies.
map<string, .tensorflow.metadata.v0.AnomalyInfo> anomaly_info = 2; -   abstract  def findInitializationErrors(): List[String]
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 - MessageOrBuilder
 
 -   abstract  def getAllFields(): Map[FieldDescriptor, AnyRef]
- Definition Classes
 - MessageOrBuilder
 
 -   abstract  def getAnomalyInfoCount(): Int
Information about feature-level anomalies.
Information about feature-level anomalies.
map<string, .tensorflow.metadata.v0.AnomalyInfo> anomaly_info = 2; -   abstract  def getAnomalyInfoMap(): Map[String, AnomalyInfo]
Information about feature-level anomalies.
Information about feature-level anomalies.
map<string, .tensorflow.metadata.v0.AnomalyInfo> anomaly_info = 2; -   abstract  def getAnomalyInfoOrDefault(key: String, defaultValue: AnomalyInfo): AnomalyInfo
Information about feature-level anomalies.
Information about feature-level anomalies.
map<string, .tensorflow.metadata.v0.AnomalyInfo> anomaly_info = 2; -   abstract  def getAnomalyInfoOrThrow(key: String): AnomalyInfo
Information about feature-level anomalies.
Information about feature-level anomalies.
map<string, .tensorflow.metadata.v0.AnomalyInfo> anomaly_info = 2; -   abstract  def getAnomalyNameFormat(): AnomalyNameFormat
The format of the keys in anomaly_info. If absent, default is DEFAULT.
The format of the keys in anomaly_info. If absent, default is DEFAULT.
optional .tensorflow.metadata.v0.Anomalies.AnomalyNameFormat anomaly_name_format = 7;- returns
 The anomalyNameFormat.
 -   abstract  def getBaseline(): Schema
.tensorflow.metadata.v0.Schema baseline = 1;.tensorflow.metadata.v0.Schema baseline = 1;- returns
 The baseline.
 -   abstract  def getBaselineOrBuilder(): SchemaOrBuilder
.tensorflow.metadata.v0.Schema baseline = 1; -  abstract def getBaselineSchemaCase(): BaselineSchemaCase
 -   abstract  def getDataMissing(): Boolean
True if numExamples == 0.
True if numExamples == 0.
optional bool data_missing = 3;- returns
 The dataMissing.
 -   abstract  def getDatasetAnomalyInfo(): AnomalyInfo
Information about dataset-level anomalies.
Information about dataset-level anomalies.
optional .tensorflow.metadata.v0.AnomalyInfo dataset_anomaly_info = 8;- returns
 The datasetAnomalyInfo.
 -   abstract  def getDatasetAnomalyInfoOrBuilder(): AnomalyInfoOrBuilder
Information about dataset-level anomalies.
Information about dataset-level anomalies.
optional .tensorflow.metadata.v0.AnomalyInfo dataset_anomaly_info = 8; -   abstract  def getDefaultInstanceForType(): Message
- Definition Classes
 - MessageOrBuilder → MessageLiteOrBuilder
 
 -   abstract  def getDescriptorForType(): Descriptor
- Definition Classes
 - MessageOrBuilder
 
 -   abstract  def getDriftSkewInfo(index: Int): DriftSkewInfo
If drift / skew detection was conducted, this field will hold the comparison results for all the features compared, regardless whether a related anomaly was reported.
If drift / skew detection was conducted, this field will hold the comparison results for all the features compared, regardless whether a related anomaly was reported.
repeated .tensorflow.metadata.v0.DriftSkewInfo drift_skew_info = 9; -   abstract  def getDriftSkewInfoCount(): Int
If drift / skew detection was conducted, this field will hold the comparison results for all the features compared, regardless whether a related anomaly was reported.
If drift / skew detection was conducted, this field will hold the comparison results for all the features compared, regardless whether a related anomaly was reported.
repeated .tensorflow.metadata.v0.DriftSkewInfo drift_skew_info = 9; -   abstract  def getDriftSkewInfoList(): List[DriftSkewInfo]
If drift / skew detection was conducted, this field will hold the comparison results for all the features compared, regardless whether a related anomaly was reported.
If drift / skew detection was conducted, this field will hold the comparison results for all the features compared, regardless whether a related anomaly was reported.
repeated .tensorflow.metadata.v0.DriftSkewInfo drift_skew_info = 9; -   abstract  def getDriftSkewInfoOrBuilder(index: Int): DriftSkewInfoOrBuilder
If drift / skew detection was conducted, this field will hold the comparison results for all the features compared, regardless whether a related anomaly was reported.
If drift / skew detection was conducted, this field will hold the comparison results for all the features compared, regardless whether a related anomaly was reported.
repeated .tensorflow.metadata.v0.DriftSkewInfo drift_skew_info = 9; -   abstract  def getDriftSkewInfoOrBuilderList(): List[_ <: DriftSkewInfoOrBuilder]
If drift / skew detection was conducted, this field will hold the comparison results for all the features compared, regardless whether a related anomaly was reported.
If drift / skew detection was conducted, this field will hold the comparison results for all the features compared, regardless whether a related anomaly was reported.
repeated .tensorflow.metadata.v0.DriftSkewInfo drift_skew_info = 9; -   abstract  def getField(field: FieldDescriptor): AnyRef
- Definition Classes
 - MessageOrBuilder
 
 -   abstract  def getInitializationErrorString(): String
- Definition Classes
 - MessageOrBuilder
 
 -   abstract  def getOneofFieldDescriptor(oneof: OneofDescriptor): FieldDescriptor
- Definition Classes
 - MessageOrBuilder
 
 -   abstract  def getRepeatedField(field: FieldDescriptor, index: Int): AnyRef
- Definition Classes
 - MessageOrBuilder
 
 -   abstract  def getRepeatedFieldCount(field: FieldDescriptor): Int
- Definition Classes
 - MessageOrBuilder
 
 -   abstract  def getUnknownFields(): UnknownFieldSet
- Definition Classes
 - MessageOrBuilder
 
 -   abstract  def hasAnomalyNameFormat(): Boolean
The format of the keys in anomaly_info. If absent, default is DEFAULT.
The format of the keys in anomaly_info. If absent, default is DEFAULT.
optional .tensorflow.metadata.v0.Anomalies.AnomalyNameFormat anomaly_name_format = 7;- returns
 Whether the anomalyNameFormat field is set.
 -   abstract  def hasBaseline(): Boolean
.tensorflow.metadata.v0.Schema baseline = 1;.tensorflow.metadata.v0.Schema baseline = 1;- returns
 Whether the baseline field is set.
 -   abstract  def hasDataMissing(): Boolean
True if numExamples == 0.
True if numExamples == 0.
optional bool data_missing = 3;- returns
 Whether the dataMissing field is set.
 -   abstract  def hasDatasetAnomalyInfo(): Boolean
Information about dataset-level anomalies.
Information about dataset-level anomalies.
optional .tensorflow.metadata.v0.AnomalyInfo dataset_anomaly_info = 8;- returns
 Whether the datasetAnomalyInfo field is set.
 -   abstract  def hasField(field: FieldDescriptor): Boolean
- Definition Classes
 - MessageOrBuilder
 
 -   abstract  def hasOneof(oneof: OneofDescriptor): Boolean
- Definition Classes
 - MessageOrBuilder
 
 -   abstract  def isInitialized(): Boolean
- Definition Classes
 - MessageLiteOrBuilder
 
 -   abstract  def getAnomalyInfo(): Map[String, AnomalyInfo]
Use
#getAnomalyInfoMap()instead.Use
#getAnomalyInfoMap()instead.- Annotations
 - @Deprecated
 - Deprecated
 
 -   abstract  def getBaselineV1(): Schema
.tensorflow.metadata.v0.Schema baseline_v1 = 6 [deprecated = true];.tensorflow.metadata.v0.Schema baseline_v1 = 6 [deprecated = true];- returns
 The baselineV1.
- Annotations
 - @Deprecated
 - Deprecated
 
 -   abstract  def getBaselineV1OrBuilder(): SchemaOrBuilder
.tensorflow.metadata.v0.Schema baseline_v1 = 6 [deprecated = true];.tensorflow.metadata.v0.Schema baseline_v1 = 6 [deprecated = true];- Annotations
 - @Deprecated
 - Deprecated
 
 -   abstract  def hasBaselineV1(): Boolean
.tensorflow.metadata.v0.Schema baseline_v1 = 6 [deprecated = true];.tensorflow.metadata.v0.Schema baseline_v1 = 6 [deprecated = true];- returns
 Whether the baselineV1 field is set.
- Annotations
 - @Deprecated
 - Deprecated
 
 
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