Class AutoMlImageSegmentationInputs.Builder (3.49.0)

public static final class AutoMlImageSegmentationInputs.Builder extends GeneratedMessageV3.Builder<AutoMlImageSegmentationInputs.Builder> implements AutoMlImageSegmentationInputsOrBuilder

Protobuf type google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageSegmentationInputs

Static Methods

getDescriptor()

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

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

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

build()

public AutoMlImageSegmentationInputs build()
Returns
Type Description
AutoMlImageSegmentationInputs

buildPartial()

public AutoMlImageSegmentationInputs buildPartial()
Returns
Type Description
AutoMlImageSegmentationInputs

clear()

public AutoMlImageSegmentationInputs.Builder clear()
Returns
Type Description
AutoMlImageSegmentationInputs.Builder
Overrides

clearBaseModelId()

public AutoMlImageSegmentationInputs.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 = 3;

Returns
Type Description
AutoMlImageSegmentationInputs.Builder

This builder for chaining.

clearBudgetMilliNodeHours()

public AutoMlImageSegmentationInputs.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. Or actaul_wall_clock_hours = train_budget_milli_node_hours / (number_of_nodes_involved * 1000) For modelType cloud-high-accuracy-1(default), the budget must be between 20,000 and 2,000,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time (1000 milli * 24 hours * 8 nodes).

int64 budget_milli_node_hours = 2;

Returns
Type Description
AutoMlImageSegmentationInputs.Builder

This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public AutoMlImageSegmentationInputs.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
Name Description
field FieldDescriptor
Returns
Type Description
AutoMlImageSegmentationInputs.Builder
Overrides

clearModelType()

public AutoMlImageSegmentationInputs.Builder clearModelType()

.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;

Returns
Type Description
AutoMlImageSegmentationInputs.Builder

This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public AutoMlImageSegmentationInputs.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
Name Description
oneof OneofDescriptor
Returns
Type Description
AutoMlImageSegmentationInputs.Builder
Overrides

clone()

public AutoMlImageSegmentationInputs.Builder clone()
Returns
Type Description
AutoMlImageSegmentationInputs.Builder
Overrides

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 = 3;

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 = 3;

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. Or actaul_wall_clock_hours = train_budget_milli_node_hours / (number_of_nodes_involved * 1000) For modelType cloud-high-accuracy-1(default), the budget must be between 20,000 and 2,000,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time (1000 milli * 24 hours * 8 nodes).

int64 budget_milli_node_hours = 2;

Returns
Type Description
long

The budgetMilliNodeHours.

getDefaultInstanceForType()

public AutoMlImageSegmentationInputs getDefaultInstanceForType()
Returns
Type Description
AutoMlImageSegmentationInputs

getDescriptorForType()

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

getModelType()

public AutoMlImageSegmentationInputs.ModelType getModelType()

.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;

Returns
Type Description
AutoMlImageSegmentationInputs.ModelType

The modelType.

getModelTypeValue()

public int getModelTypeValue()

.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;

Returns
Type Description
int

The enum numeric value on the wire for modelType.

internalGetFieldAccessorTable()

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

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

mergeFrom(AutoMlImageSegmentationInputs other)

public AutoMlImageSegmentationInputs.Builder mergeFrom(AutoMlImageSegmentationInputs other)
Parameter
Name Description
other AutoMlImageSegmentationInputs
Returns
Type Description
AutoMlImageSegmentationInputs.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

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

mergeFrom(Message other)

public AutoMlImageSegmentationInputs.Builder mergeFrom(Message other)
Parameter
Name Description
other Message
Returns
Type Description
AutoMlImageSegmentationInputs.Builder
Overrides

mergeUnknownFields(UnknownFieldSet unknownFields)

public final AutoMlImageSegmentationInputs.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
Name Description
unknownFields UnknownFieldSet
Returns
Type Description
AutoMlImageSegmentationInputs.Builder
Overrides

setBaseModelId(String value)

public AutoMlImageSegmentationInputs.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 = 3;

Parameter
Name Description
value String

The baseModelId to set.

Returns
Type Description
AutoMlImageSegmentationInputs.Builder

This builder for chaining.

setBaseModelIdBytes(ByteString value)

public AutoMlImageSegmentationInputs.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 = 3;

Parameter
Name Description
value ByteString

The bytes for baseModelId to set.

Returns
Type Description
AutoMlImageSegmentationInputs.Builder

This builder for chaining.

setBudgetMilliNodeHours(long value)

public AutoMlImageSegmentationInputs.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. Or actaul_wall_clock_hours = train_budget_milli_node_hours / (number_of_nodes_involved * 1000) For modelType cloud-high-accuracy-1(default), the budget must be between 20,000 and 2,000,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time (1000 milli * 24 hours * 8 nodes).

int64 budget_milli_node_hours = 2;

Parameter
Name Description
value long

The budgetMilliNodeHours to set.

Returns
Type Description
AutoMlImageSegmentationInputs.Builder

This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

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

setModelType(AutoMlImageSegmentationInputs.ModelType value)

public AutoMlImageSegmentationInputs.Builder setModelType(AutoMlImageSegmentationInputs.ModelType value)

.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;

Parameter
Name Description
value AutoMlImageSegmentationInputs.ModelType

The modelType to set.

Returns
Type Description
AutoMlImageSegmentationInputs.Builder

This builder for chaining.

setModelTypeValue(int value)

public AutoMlImageSegmentationInputs.Builder setModelTypeValue(int value)

.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;

Parameter
Name Description
value int

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

Returns
Type Description
AutoMlImageSegmentationInputs.Builder

This builder for chaining.

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

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

setUnknownFields(UnknownFieldSet unknownFields)

public final AutoMlImageSegmentationInputs.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
Name Description
unknownFields UnknownFieldSet
Returns
Type Description
AutoMlImageSegmentationInputs.Builder
Overrides