public static final class AutoMlImageSegmentationInputs.Builder extends GeneratedMessageV3.Builder<AutoMlImageSegmentationInputs.Builder> implements AutoMlImageSegmentationInputsOrBuilder
Protobuf type
google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageSegmentationInputs
Static Methods
public static final Descriptors.Descriptor getDescriptor()
Returns
Methods
public AutoMlImageSegmentationInputs.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
Returns
Overrides
public AutoMlImageSegmentationInputs build()
Returns
public AutoMlImageSegmentationInputs buildPartial()
Returns
public AutoMlImageSegmentationInputs.Builder clear()
Returns
Overrides
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;
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;
public AutoMlImageSegmentationInputs.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
Returns
Overrides
public AutoMlImageSegmentationInputs.Builder clearModelType()
.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;
public AutoMlImageSegmentationInputs.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
Returns
Overrides
public AutoMlImageSegmentationInputs.Builder clone()
Returns
Overrides
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;
| Type | Description |
| String | The baseModelId.
|
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;
| Type | Description |
| ByteString | The bytes for baseModelId.
|
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;
| Type | Description |
| long | The budgetMilliNodeHours.
|
public AutoMlImageSegmentationInputs getDefaultInstanceForType()
Returns
public Descriptors.Descriptor getDescriptorForType()
Returns
Overrides
public AutoMlImageSegmentationInputs.ModelType getModelType()
.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;
public int getModelTypeValue()
.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;
| Type | Description |
| int | The enum numeric value on the wire for modelType.
|
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Overrides
public final boolean isInitialized()
Returns
Overrides
public AutoMlImageSegmentationInputs.Builder mergeFrom(AutoMlImageSegmentationInputs other)
Parameter
Returns
public AutoMlImageSegmentationInputs.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Returns
Overrides
Exceptions
public AutoMlImageSegmentationInputs.Builder mergeFrom(Message other)
Parameter
Returns
Overrides
public final AutoMlImageSegmentationInputs.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
Returns
Overrides
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;
| Name | Description |
| value | String
The baseModelId to set.
|
Returns
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;
| Name | Description |
| value | ByteString
The bytes for baseModelId to set.
|
Returns
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;
| Name | Description |
| value | long
The budgetMilliNodeHours to set.
|
Returns
public AutoMlImageSegmentationInputs.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
Returns
Overrides
public AutoMlImageSegmentationInputs.Builder setModelType(AutoMlImageSegmentationInputs.ModelType value)
.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;
public AutoMlImageSegmentationInputs.Builder setModelTypeValue(int value)
.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;
| Name | Description |
| value | int
The enum numeric value on the wire for modelType to set.
|
Returns
public AutoMlImageSegmentationInputs.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
Returns
Overrides
public final AutoMlImageSegmentationInputs.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
Returns
Overrides
