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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-20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 .NET library, specifically for version 2.14.0 and later.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eAutoMlImageSegmentationInputs\u003c/code\u003e class is used for configuring inputs for training AutoML image segmentation models, and it implements interfaces for message handling, equality checks, deep cloning, and buffer messaging.\u003c/p\u003e\n"],["\u003cp\u003eThe page lists historical versions of the documentation for \u003ccode\u003eAutoMlImageSegmentationInputs\u003c/code\u003e, ranging from version 1.0.0 to the latest 3.22.0, with links to each version's specific documentation.\u003c/p\u003e\n"],["\u003cp\u003eThe class has properties such as \u003ccode\u003eBaseModelId\u003c/code\u003e, \u003ccode\u003eBudgetMilliNodeHours\u003c/code\u003e and \u003ccode\u003eModelType\u003c/code\u003e that are important for model training and specifying training parameters, along with two constructors for its creation.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eBudgetMilliNodeHours\u003c/code\u003e property specifies the training budget, which is measured in milli node hours, and has a default value and limitations based on the type of model.\u003c/p\u003e\n"]]],[],null,[]]
