Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::Schema::TrainingJob::Definition::AutoMlImageSegmentationInputs (v0.6.0)

Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::Schema::TrainingJob::Definition::AutoMlImageSegmentationInputs.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#base_model_id

def base_model_id() -> ::String
Returns
  • (::String) — 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.

#base_model_id=

def base_model_id=(value) -> ::String
Parameter
  • value (::String) — 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.
Returns
  • (::String) — 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.

#budget_milli_node_hours

def budget_milli_node_hours() -> ::Integer
Returns
  • (::Integer) — 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).

#budget_milli_node_hours=

def budget_milli_node_hours=(value) -> ::Integer
Parameter
  • value (::Integer) — 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).
Returns
  • (::Integer) — 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).

#model_type

def model_type() -> ::Google::Cloud::AIPlatform::V1::Schema::TrainingJob::Definition::AutoMlImageSegmentationInputs::ModelType
Returns

#model_type=

def model_type=(value) -> ::Google::Cloud::AIPlatform::V1::Schema::TrainingJob::Definition::AutoMlImageSegmentationInputs::ModelType
Parameter
Returns