Class AutoMlImageClassificationInputs.Builder (2.5.3)

Version 2.5.3

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public static final class AutoMlImageClassificationInputs.Builder extends GeneratedMessageV3.Builder<AutoMlImageClassificationInputs.Builder> implements AutoMlImageClassificationInputsOrBuilder

Protobuf type google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageClassificationInputs

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > AutoMlImageClassificationInputs.Builder

Implements

AutoMlImageClassificationInputsOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeDelimitedFrom(InputStream)

AbstractMessage.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public AutoMlImageClassificationInputs.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
AutoMlImageClassificationInputs.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

build()

public AutoMlImageClassificationInputs build()

Returns

Type	Description
AutoMlImageClassificationInputs

buildPartial()

public AutoMlImageClassificationInputs buildPartial()

Returns

Type	Description
AutoMlImageClassificationInputs

clear()

public AutoMlImageClassificationInputs.Builder clear()

Returns

Type	Description
AutoMlImageClassificationInputs.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearBaseModelId()

public AutoMlImageClassificationInputs.Builder clearBaseModelId()

The ID of the base model. If it is specified, the new model will be trained based on the base model. Otherwise, the new model will be trained from scratch. The base model must be in the same Project and Location as the new Model to train, and have the same modelType.

string base_model_id = 2;

Returns

Type	Description
AutoMlImageClassificationInputs.Builder	This builder for chaining.

clearBudgetMilliNodeHours()

public AutoMlImageClassificationInputs.Builder clearBudgetMilliNodeHours()

The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be model-converged. Note, node_hour = actual_hour * number_of_nodes_involved. For modelType cloud(default), the budget must be between 8,000 and 800,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time, considering 8 nodes are used. For model types mobile-tf-low-latency-1, mobile-tf-versatile-1, mobile-tf-high-accuracy-1, the training budget must be between 1,000 and 100,000 milli node hours, inclusive. The default value is 24,000 which represents one day in wall time on a single node that is used.

int64 budget_milli_node_hours = 3;

Returns

Type	Description
AutoMlImageClassificationInputs.Builder	This builder for chaining.

clearDisableEarlyStopping()

public AutoMlImageClassificationInputs.Builder clearDisableEarlyStopping()

Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Classification might stop training before the entire training budget has been used.

bool disable_early_stopping = 4;

Returns

Type	Description
AutoMlImageClassificationInputs.Builder	This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public AutoMlImageClassificationInputs.Builder clearField(Descriptors.FieldDescriptor field)

Parameter

Name	Description
field	FieldDescriptor

Returns

Type	Description
AutoMlImageClassificationInputs.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

clearModelType()

public AutoMlImageClassificationInputs.Builder clearModelType()

.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageClassificationInputs.ModelType model_type = 1;

Returns

Type	Description
AutoMlImageClassificationInputs.Builder	This builder for chaining.

clearMultiLabel()

public AutoMlImageClassificationInputs.Builder clearMultiLabel()

If false, a single-label (multi-class) Model will be trained (i.e. assuming that for each image just up to one annotation may be applicable). If true, a multi-label Model will be trained (i.e. assuming that for each image multiple annotations may be applicable).

bool multi_label = 5;

Returns

Type	Description
AutoMlImageClassificationInputs.Builder	This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public AutoMlImageClassificationInputs.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter

Name	Description
oneof	OneofDescriptor

Returns

Type	Description
AutoMlImageClassificationInputs.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

clone()

public AutoMlImageClassificationInputs.Builder clone()

Returns

Type	Description
AutoMlImageClassificationInputs.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

getBaseModelId()

public String getBaseModelId()

The ID of the base model. If it is specified, the new model will be trained based on the base model. Otherwise, the new model will be trained from scratch. The base model must be in the same Project and Location as the new Model to train, and have the same modelType.

string base_model_id = 2;

Returns

Type	Description
String	The baseModelId.

getBaseModelIdBytes()

public ByteString getBaseModelIdBytes()

The ID of the base model. If it is specified, the new model will be trained based on the base model. Otherwise, the new model will be trained from scratch. The base model must be in the same Project and Location as the new Model to train, and have the same modelType.

string base_model_id = 2;

Returns

Type	Description
ByteString	The bytes for baseModelId.

getBudgetMilliNodeHours()

public long getBudgetMilliNodeHours()

The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be model-converged. Note, node_hour = actual_hour * number_of_nodes_involved. For modelType cloud(default), the budget must be between 8,000 and 800,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time, considering 8 nodes are used. For model types mobile-tf-low-latency-1, mobile-tf-versatile-1, mobile-tf-high-accuracy-1, the training budget must be between 1,000 and 100,000 milli node hours, inclusive. The default value is 24,000 which represents one day in wall time on a single node that is used.

int64 budget_milli_node_hours = 3;

Returns

Type	Description
long	The budgetMilliNodeHours.

getDefaultInstanceForType()

public AutoMlImageClassificationInputs getDefaultInstanceForType()

Returns

Type	Description
AutoMlImageClassificationInputs

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns

Type	Description
Descriptor

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns

Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getDisableEarlyStopping()

public boolean getDisableEarlyStopping()

Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Classification might stop training before the entire training budget has been used.

bool disable_early_stopping = 4;

Returns

Type	Description
boolean	The disableEarlyStopping.

getModelType()

public AutoMlImageClassificationInputs.ModelType getModelType()

.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageClassificationInputs.ModelType model_type = 1;

Returns

Type	Description
AutoMlImageClassificationInputs.ModelType	The modelType.

getModelTypeValue()

public int getModelTypeValue()

.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageClassificationInputs.ModelType model_type = 1;

Returns

Type	Description
int	The enum numeric value on the wire for modelType.

getMultiLabel()

public boolean getMultiLabel()

If false, a single-label (multi-class) Model will be trained (i.e. assuming that for each image just up to one annotation may be applicable). If true, a multi-label Model will be trained (i.e. assuming that for each image multiple annotations may be applicable).

bool multi_label = 5;

Returns

Type	Description
boolean	The multiLabel.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns

Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

isInitialized()

public final boolean isInitialized()

Returns

Type	Description
boolean

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeFrom(AutoMlImageClassificationInputs other)

public AutoMlImageClassificationInputs.Builder mergeFrom(AutoMlImageClassificationInputs other)

Parameter

Name	Description
other	AutoMlImageClassificationInputs

Returns

Type	Description
AutoMlImageClassificationInputs.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public AutoMlImageClassificationInputs.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
AutoMlImageClassificationInputs.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions

Type	Description
IOException

mergeFrom(Message other)

public AutoMlImageClassificationInputs.Builder mergeFrom(Message other)

Parameter

Name	Description
other	Message

Returns

Type	Description
AutoMlImageClassificationInputs.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

mergeUnknownFields(UnknownFieldSet unknownFields)

public final AutoMlImageClassificationInputs.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
AutoMlImageClassificationInputs.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

setBaseModelId(String value)

public AutoMlImageClassificationInputs.Builder setBaseModelId(String value)

The ID of the base model. If it is specified, the new model will be trained based on the base model. Otherwise, the new model will be trained from scratch. The base model must be in the same Project and Location as the new Model to train, and have the same modelType.

string base_model_id = 2;

Parameter

Name	Description
value	String The baseModelId to set.

Returns

Type	Description
AutoMlImageClassificationInputs.Builder	This builder for chaining.

setBaseModelIdBytes(ByteString value)

public AutoMlImageClassificationInputs.Builder setBaseModelIdBytes(ByteString value)

The ID of the base model. If it is specified, the new model will be trained based on the base model. Otherwise, the new model will be trained from scratch. The base model must be in the same Project and Location as the new Model to train, and have the same modelType.

string base_model_id = 2;

Parameter

Name	Description
value	ByteString The bytes for baseModelId to set.

Returns

Type	Description
AutoMlImageClassificationInputs.Builder	This builder for chaining.

setBudgetMilliNodeHours(long value)

public AutoMlImageClassificationInputs.Builder setBudgetMilliNodeHours(long value)

The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be model-converged. Note, node_hour = actual_hour * number_of_nodes_involved. For modelType cloud(default), the budget must be between 8,000 and 800,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time, considering 8 nodes are used. For model types mobile-tf-low-latency-1, mobile-tf-versatile-1, mobile-tf-high-accuracy-1, the training budget must be between 1,000 and 100,000 milli node hours, inclusive. The default value is 24,000 which represents one day in wall time on a single node that is used.

int64 budget_milli_node_hours = 3;

Parameter

Name	Description
value	long The budgetMilliNodeHours to set.

Returns

Type	Description
AutoMlImageClassificationInputs.Builder	This builder for chaining.

setDisableEarlyStopping(boolean value)

public AutoMlImageClassificationInputs.Builder setDisableEarlyStopping(boolean value)

Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Classification might stop training before the entire training budget has been used.

bool disable_early_stopping = 4;

Parameter

Name	Description
value	boolean The disableEarlyStopping to set.

Returns

Type	Description
AutoMlImageClassificationInputs.Builder	This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public AutoMlImageClassificationInputs.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
AutoMlImageClassificationInputs.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

setModelType(AutoMlImageClassificationInputs.ModelType value)

public AutoMlImageClassificationInputs.Builder setModelType(AutoMlImageClassificationInputs.ModelType value)

.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageClassificationInputs.ModelType model_type = 1;

Parameter

Name	Description
value	AutoMlImageClassificationInputs.ModelType The modelType to set.

Returns

Type	Description
AutoMlImageClassificationInputs.Builder	This builder for chaining.

setModelTypeValue(int value)

public AutoMlImageClassificationInputs.Builder setModelTypeValue(int value)

.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageClassificationInputs.ModelType model_type = 1;

Parameter

Name	Description
value	int The enum numeric value on the wire for modelType to set.

Returns

Type	Description
AutoMlImageClassificationInputs.Builder	This builder for chaining.

setMultiLabel(boolean value)

public AutoMlImageClassificationInputs.Builder setMultiLabel(boolean value)

If false, a single-label (multi-class) Model will be trained (i.e. assuming that for each image just up to one annotation may be applicable). If true, a multi-label Model will be trained (i.e. assuming that for each image multiple annotations may be applicable).

bool multi_label = 5;

Parameter

Name	Description
value	boolean The multiLabel to set.

Returns

Type	Description
AutoMlImageClassificationInputs.Builder	This builder for chaining.

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

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

Parameters

Name	Description
field	FieldDescriptor
index	int
value	Object

Returns

Type	Description
AutoMlImageClassificationInputs.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

setUnknownFields(UnknownFieldSet unknownFields)

public final AutoMlImageClassificationInputs.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
AutoMlImageClassificationInputs.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)