Class ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder (3.44.0)

public static final class ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder extends GeneratedMessageV3.Builder<ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder> implements ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValueOrBuilder

Summary statistics for a population of values.

Protobuf type google.cloud.aiplatform.v1beta1.ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
Type Description
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
Name Description
field FieldDescriptor
value Object
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder
Overrides

build()

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue build()
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue

buildPartial()

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue buildPartial()
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue

clear()

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clear()
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder
Overrides

clearDistribution()

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clearDistribution()

tensorflow.metadata.v0.DatasetFeatureStatistics format.

.google.protobuf.Value distribution = 1;

Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder

clearDistributionDeviation()

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clearDistributionDeviation()

Distribution distance deviation from the current dataset's statistics to baseline dataset's statistics.

  • For categorical feature, the distribution distance is calculated by L-inifinity norm or Jensen–Shannon divergence.
  • For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.

double distribution_deviation = 2;

Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder

This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
Name Description
field FieldDescriptor
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder
Overrides

clearOneof(Descriptors.OneofDescriptor oneof)

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
Name Description
oneof OneofDescriptor
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder
Overrides

clone()

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder clone()
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder
Overrides

getDefaultInstanceForType()

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue getDefaultInstanceForType()
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
Type Description
Descriptor
Overrides

getDistribution()

public Value getDistribution()

tensorflow.metadata.v0.DatasetFeatureStatistics format.

.google.protobuf.Value distribution = 1;

Returns
Type Description
Value

The distribution.

getDistributionBuilder()

public Value.Builder getDistributionBuilder()

tensorflow.metadata.v0.DatasetFeatureStatistics format.

.google.protobuf.Value distribution = 1;

Returns
Type Description
Builder

getDistributionDeviation()

public double getDistributionDeviation()

Distribution distance deviation from the current dataset's statistics to baseline dataset's statistics.

  • For categorical feature, the distribution distance is calculated by L-inifinity norm or Jensen–Shannon divergence.
  • For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.

double distribution_deviation = 2;

Returns
Type Description
double

The distributionDeviation.

getDistributionOrBuilder()

public ValueOrBuilder getDistributionOrBuilder()

tensorflow.metadata.v0.DatasetFeatureStatistics format.

.google.protobuf.Value distribution = 1;

Returns
Type Description
ValueOrBuilder

hasDistribution()

public boolean hasDistribution()

tensorflow.metadata.v0.DatasetFeatureStatistics format.

.google.protobuf.Value distribution = 1;

Returns
Type Description
boolean

Whether the distribution field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Type Description
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

mergeDistribution(Value value)

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder mergeDistribution(Value value)

tensorflow.metadata.v0.DatasetFeatureStatistics format.

.google.protobuf.Value distribution = 1;

Parameter
Name Description
value Value
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder

mergeFrom(ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue other)

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder mergeFrom(ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue other)
Parameter
Name Description
other ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input CodedInputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder
Overrides
Exceptions
Type Description
IOException

mergeFrom(Message other)

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder mergeFrom(Message other)
Parameter
Name Description
other Message
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder
Overrides

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
Name Description
unknownFields UnknownFieldSet
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder
Overrides

setDistribution(Value value)

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setDistribution(Value value)

tensorflow.metadata.v0.DatasetFeatureStatistics format.

.google.protobuf.Value distribution = 1;

Parameter
Name Description
value Value
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder

setDistribution(Value.Builder builderForValue)

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setDistribution(Value.Builder builderForValue)

tensorflow.metadata.v0.DatasetFeatureStatistics format.

.google.protobuf.Value distribution = 1;

Parameter
Name Description
builderForValue Builder
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder

setDistributionDeviation(double value)

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setDistributionDeviation(double value)

Distribution distance deviation from the current dataset's statistics to baseline dataset's statistics.

  • For categorical feature, the distribution distance is calculated by L-inifinity norm or Jensen–Shannon divergence.
  • For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.

double distribution_deviation = 2;

Parameter
Name Description
value double

The distributionDeviation to set.

Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder

This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
Name Description
field FieldDescriptor
value Object
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder
Overrides

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
Name Description
field FieldDescriptor
index int
value Object
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder
Overrides

setUnknownFields(UnknownFieldSet unknownFields)

public final ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
Name Description
unknownFields UnknownFieldSet
Returns
Type Description
ModelMonitoringStatsDataPoint.TypedValue.DistributionDataValue.Builder
Overrides