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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-20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 Google Cloud AI Platform, specifically for version 3.13.0 and other versions of the .NET library.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eAutoMlImageSegmentationInputs\u003c/code\u003e class is used to define inputs for training AutoML image segmentation models, implementing interfaces such as \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\u003eKey properties of the class include \u003ccode\u003eBaseModelId\u003c/code\u003e for training based on an existing model, \u003ccode\u003eBudgetMilliNodeHours\u003c/code\u003e for specifying the training budget, and \u003ccode\u003eModelType\u003c/code\u003e to define the type of model to be trained.\u003c/p\u003e\n"],["\u003cp\u003eThe documentation includes links to all available versions of this class, ranging from the latest 3.22.0 down to version 1.0.0, allowing users to browse the API for various versions.\u003c/p\u003e\n"],["\u003cp\u003eThere is information about the contructors \u003ccode\u003eAutoMlImageSegmentationInputs()\u003c/code\u003e, \u003ccode\u003eAutoMlImageSegmentationInputs(AutoMlImageSegmentationInputs other)\u003c/code\u003e and a description of the properties such as \u003ccode\u003eBaseModelId\u003c/code\u003e, \u003ccode\u003eBudgetMilliNodeHours\u003c/code\u003e, and \u003ccode\u003eModelType\u003c/code\u003e.\u003c/p\u003e\n"]]],[],null,[]]
