public sealed class AutoMlImageSegmentationInputs : IMessage<AutoMlImageSegmentationInputs>, IEquatable<AutoMlImageSegmentationInputs>, IDeepCloneable<AutoMlImageSegmentationInputs>, IBufferMessage, IMessage
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.
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).
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-20 UTC."],[[["\u003cp\u003eThis document outlines the different versions of \u003ccode\u003eAutoMlImageSegmentationInputs\u003c/code\u003e, a class used in Google Cloud AI Platform for defining inputs for automated machine learning image segmentation tasks, with versions ranging from 1.0.0 to 3.22.0.\u003c/p\u003e\n"],["\u003cp\u003e\u003ccode\u003eAutoMlImageSegmentationInputs\u003c/code\u003e implements several interfaces, including \u003ccode\u003eIMessage\u003c/code\u003e, \u003ccode\u003eIEquatable\u003c/code\u003e, \u003ccode\u003eIDeepCloneable\u003c/code\u003e, and \u003ccode\u003eIBufferMessage\u003c/code\u003e, to support its functionality within the .NET ecosystem, and inherits from the base \u003ccode\u003eobject\u003c/code\u003e class.\u003c/p\u003e\n"],["\u003cp\u003eThe class provides constructors for creating new instances and copying existing ones, enabling flexible object creation and management.\u003c/p\u003e\n"],["\u003cp\u003e\u003ccode\u003eAutoMlImageSegmentationInputs\u003c/code\u003e includes properties such as \u003ccode\u003eBaseModelId\u003c/code\u003e, \u003ccode\u003eBudgetMilliNodeHours\u003c/code\u003e, and \u003ccode\u003eModelType\u003c/code\u003e, to configure training parameters like using a base model, setting a training budget, and defining the model type, which are crucial for customizing the image segmentation model creation.\u003c/p\u003e\n"],["\u003cp\u003eThe latest version of the class is \u003ccode\u003e3.22.0\u003c/code\u003e and the class falls under the \u003ccode\u003eGoogle.Cloud.AIPlatform.V1.Schema.TrainingJob.Definition\u003c/code\u003e namespace, within the \u003ccode\u003eGoogle.Cloud.AIPlatform.V1.dll\u003c/code\u003e assembly, to manage the structure of training jobs in the Google Cloud AI Platform.\u003c/p\u003e\n"]]],[],null,[]]
