Class AutoMlImageClassificationInputs.Builder (3.52.0) 

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

Static Methods

getDescriptor()

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

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

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

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

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

clone()

public AutoMlImageClassificationInputs.Builder clone()
Returns
Type Description
AutoMlImageClassificationInputs.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 = 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

getDescriptorForType()

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

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

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

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
Exceptions
Type Description
IOException

mergeFrom(Message other)

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

mergeUnknownFields(UnknownFieldSet unknownFields)

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

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

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

setUnknownFields(UnknownFieldSet unknownFields)

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