public final class ActiveLearningConfig extends GeneratedMessageV3 implements ActiveLearningConfigOrBuilder
Parameters that configure the active learning pipeline. Active learning will
label the data incrementally by several iterations. For every iteration, it
will select a batch of data based on the sampling strategy.
Protobuf type google.cloud.aiplatform.v1beta1.ActiveLearningConfig
Inherited Members
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT)
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT,int)
com.google.protobuf.GeneratedMessageV3.<T>emptyList(java.lang.Class<T>)
com.google.protobuf.GeneratedMessageV3.internalGetMapFieldReflection(int)
Static Fields
public static final int MAX_DATA_ITEM_COUNT_FIELD_NUMBER
| Field Value |
| Type |
Description |
int |
|
public static final int MAX_DATA_ITEM_PERCENTAGE_FIELD_NUMBER
| Field Value |
| Type |
Description |
int |
|
public static final int SAMPLE_CONFIG_FIELD_NUMBER
| Field Value |
| Type |
Description |
int |
|
public static final int TRAINING_CONFIG_FIELD_NUMBER
| Field Value |
| Type |
Description |
int |
|
Static Methods
public static ActiveLearningConfig getDefaultInstance()
public static final Descriptors.Descriptor getDescriptor()
public static ActiveLearningConfig.Builder newBuilder()
public static ActiveLearningConfig.Builder newBuilder(ActiveLearningConfig prototype)
public static ActiveLearningConfig parseDelimitedFrom(InputStream input)
public static ActiveLearningConfig parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ActiveLearningConfig parseFrom(byte[] data)
| Parameter |
| Name |
Description |
data |
byte[]
|
public static ActiveLearningConfig parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static ActiveLearningConfig parseFrom(ByteString data)
public static ActiveLearningConfig parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static ActiveLearningConfig parseFrom(CodedInputStream input)
public static ActiveLearningConfig parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static ActiveLearningConfig parseFrom(InputStream input)
public static ActiveLearningConfig parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ActiveLearningConfig parseFrom(ByteBuffer data)
public static ActiveLearningConfig parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static Parser<ActiveLearningConfig> parser()
Methods
public boolean equals(Object obj)
| Parameter |
| Name |
Description |
obj |
Object
|
Overrides
public ActiveLearningConfig getDefaultInstanceForType()
public ActiveLearningConfig.HumanLabelingBudgetCase getHumanLabelingBudgetCase()
public long getMaxDataItemCount()
Max number of human labeled DataItems.
int64 max_data_item_count = 1;
| Returns |
| Type |
Description |
long |
The maxDataItemCount.
|
public int getMaxDataItemPercentage()
Max percent of total DataItems for human labeling.
int32 max_data_item_percentage = 2;
| Returns |
| Type |
Description |
int |
The maxDataItemPercentage.
|
public Parser<ActiveLearningConfig> getParserForType()
Overrides
public SampleConfig getSampleConfig()
Active learning data sampling config. For every active learning labeling
iteration, it will select a batch of data based on the sampling strategy.
.google.cloud.aiplatform.v1beta1.SampleConfig sample_config = 3;
public SampleConfigOrBuilder getSampleConfigOrBuilder()
Active learning data sampling config. For every active learning labeling
iteration, it will select a batch of data based on the sampling strategy.
.google.cloud.aiplatform.v1beta1.SampleConfig sample_config = 3;
public int getSerializedSize()
| Returns |
| Type |
Description |
int |
|
Overrides
public TrainingConfig getTrainingConfig()
CMLE training config. For every active learning labeling iteration, system
will train a machine learning model on CMLE. The trained model will be used
by data sampling algorithm to select DataItems.
.google.cloud.aiplatform.v1beta1.TrainingConfig training_config = 4;
public TrainingConfigOrBuilder getTrainingConfigOrBuilder()
CMLE training config. For every active learning labeling iteration, system
will train a machine learning model on CMLE. The trained model will be used
by data sampling algorithm to select DataItems.
.google.cloud.aiplatform.v1beta1.TrainingConfig training_config = 4;
public boolean hasMaxDataItemCount()
Max number of human labeled DataItems.
int64 max_data_item_count = 1;
| Returns |
| Type |
Description |
boolean |
Whether the maxDataItemCount field is set.
|
public boolean hasMaxDataItemPercentage()
Max percent of total DataItems for human labeling.
int32 max_data_item_percentage = 2;
| Returns |
| Type |
Description |
boolean |
Whether the maxDataItemPercentage field is set.
|
public boolean hasSampleConfig()
Active learning data sampling config. For every active learning labeling
iteration, it will select a batch of data based on the sampling strategy.
.google.cloud.aiplatform.v1beta1.SampleConfig sample_config = 3;
| Returns |
| Type |
Description |
boolean |
Whether the sampleConfig field is set.
|
public boolean hasTrainingConfig()
CMLE training config. For every active learning labeling iteration, system
will train a machine learning model on CMLE. The trained model will be used
by data sampling algorithm to select DataItems.
.google.cloud.aiplatform.v1beta1.TrainingConfig training_config = 4;
| Returns |
| Type |
Description |
boolean |
Whether the trainingConfig field is set.
|
| Returns |
| Type |
Description |
int |
|
Overrides
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Overrides
public final boolean isInitialized()
Overrides
public ActiveLearningConfig.Builder newBuilderForType()
protected ActiveLearningConfig.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Overrides
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
| Returns |
| Type |
Description |
Object |
|
Overrides
public ActiveLearningConfig.Builder toBuilder()
public void writeTo(CodedOutputStream output)
Overrides
