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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-20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 webpage provides documentation for the \u003ccode\u003eAutoMlImageSegmentationInputs\u003c/code\u003e class within the \u003ccode\u003eGoogle.Cloud.AIPlatform.V1\u003c/code\u003e namespace, specifically for the .NET library.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eAutoMlImageSegmentationInputs\u003c/code\u003e class is used for defining inputs for AutoML image segmentation training jobs, and it 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.\u003c/p\u003e\n"],["\u003cp\u003eThe class features two constructors, one being a default constructor, and the other a copy constructor that takes an \u003ccode\u003eAutoMlImageSegmentationInputs\u003c/code\u003e object.\u003c/p\u003e\n"],["\u003cp\u003eKey properties of the \u003ccode\u003eAutoMlImageSegmentationInputs\u003c/code\u003e class include \u003ccode\u003eBaseModelId\u003c/code\u003e for specifying a base model for training and \u003ccode\u003eBudgetMilliNodeHours\u003c/code\u003e for setting the training budget, along with the \u003ccode\u003eModelType\u003c/code\u003e property for picking the model type.\u003c/p\u003e\n"],["\u003cp\u003eThe documentation is available across many versions, ranging from 1.0.0 all the way to 3.22.0, allowing developers to access information specific to their used version.\u003c/p\u003e\n"]]],[],null,[]]
